diff --git a/challenge1/analysis/shino/.ipynb_checkpoints/Challenge1-checkpoint.ipynb b/challenge1/analysis/shino/.ipynb_checkpoints/Challenge1-checkpoint.ipynb
new file mode 100644
index 000000000..32fed455e
--- /dev/null
+++ b/challenge1/analysis/shino/.ipynb_checkpoints/Challenge1-checkpoint.ipynb
@@ -0,0 +1,1524 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "import seaborn as sns"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from sklearn.linear_model import LinearRegression\n",
+    "from sklearn.linear_model import LogisticRegression\n",
+    "from sklearn.ensemble import RandomForestClassifier"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "train_df = pd.read_csv('../../data/training_dataset_500.csv')\n",
+    "test_df = pd.read_csv('../../data/test_dataset_500.csv')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>ID</th>\n",
+       "      <th>Label</th>\n",
+       "      <th>House</th>\n",
+       "      <th>Year</th>\n",
+       "      <th>Month</th>\n",
+       "      <th>Temperature</th>\n",
+       "      <th>Daylight</th>\n",
+       "      <th>EnergyProduction</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>7</td>\n",
+       "      <td>26.2</td>\n",
+       "      <td>178.9</td>\n",
+       "      <td>740</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>8</td>\n",
+       "      <td>25.8</td>\n",
+       "      <td>169.7</td>\n",
+       "      <td>731</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>9</td>\n",
+       "      <td>22.8</td>\n",
+       "      <td>170.2</td>\n",
+       "      <td>694</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>3</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>10</td>\n",
+       "      <td>16.4</td>\n",
+       "      <td>169.1</td>\n",
+       "      <td>688</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>4</td>\n",
+       "      <td>4</td>\n",
+       "      <td>4</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>11</td>\n",
+       "      <td>11.4</td>\n",
+       "      <td>169.1</td>\n",
+       "      <td>650</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>5</td>\n",
+       "      <td>5</td>\n",
+       "      <td>5</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>12</td>\n",
+       "      <td>4.2</td>\n",
+       "      <td>199.5</td>\n",
+       "      <td>763</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>6</td>\n",
+       "      <td>6</td>\n",
+       "      <td>6</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1.8</td>\n",
+       "      <td>203.1</td>\n",
+       "      <td>765</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>7</td>\n",
+       "      <td>7</td>\n",
+       "      <td>7</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2.8</td>\n",
+       "      <td>178.2</td>\n",
+       "      <td>706</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>8</td>\n",
+       "      <td>8</td>\n",
+       "      <td>8</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>6.7</td>\n",
+       "      <td>172.7</td>\n",
+       "      <td>788</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>9</td>\n",
+       "      <td>9</td>\n",
+       "      <td>9</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>4</td>\n",
+       "      <td>12.6</td>\n",
+       "      <td>182.2</td>\n",
+       "      <td>831</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>10</td>\n",
+       "      <td>10</td>\n",
+       "      <td>10</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>5</td>\n",
+       "      <td>17.6</td>\n",
+       "      <td>214.2</td>\n",
+       "      <td>955</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>11</td>\n",
+       "      <td>11</td>\n",
+       "      <td>11</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>6</td>\n",
+       "      <td>20.8</td>\n",
+       "      <td>143.0</td>\n",
+       "      <td>837</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    ID  Label  House  Year  Month  Temperature  Daylight  EnergyProduction\n",
+       "0    0      0      1  2011      7         26.2     178.9               740\n",
+       "1    1      1      1  2011      8         25.8     169.7               731\n",
+       "2    2      2      1  2011      9         22.8     170.2               694\n",
+       "3    3      3      1  2011     10         16.4     169.1               688\n",
+       "4    4      4      1  2011     11         11.4     169.1               650\n",
+       "5    5      5      1  2011     12          4.2     199.5               763\n",
+       "6    6      6      1  2012      1          1.8     203.1               765\n",
+       "7    7      7      1  2012      2          2.8     178.2               706\n",
+       "8    8      8      1  2012      3          6.7     172.7               788\n",
+       "9    9      9      1  2012      4         12.6     182.2               831\n",
+       "10  10     10      1  2012      5         17.6     214.2               955\n",
+       "11  11     11      1  2012      6         20.8     143.0               837"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_df.head(12)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
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+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>ID</th>\n",
+       "      <th>Label</th>\n",
+       "      <th>House</th>\n",
+       "      <th>Year</th>\n",
+       "      <th>Month</th>\n",
+       "      <th>Temperature</th>\n",
+       "      <th>Daylight</th>\n",
+       "      <th>EnergyProduction</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>11488</td>\n",
+       "      <td>11987</td>\n",
+       "      <td>11</td>\n",
+       "      <td>500</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>6</td>\n",
+       "      <td>21.8</td>\n",
+       "      <td>152.1</td>\n",
+       "      <td>645</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>11489</td>\n",
+       "      <td>11988</td>\n",
+       "      <td>12</td>\n",
+       "      <td>500</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>7</td>\n",
+       "      <td>26.2</td>\n",
+       "      <td>169.8</td>\n",
+       "      <td>661</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>11490</td>\n",
+       "      <td>11989</td>\n",
+       "      <td>13</td>\n",
+       "      <td>500</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>8</td>\n",
+       "      <td>27.8</td>\n",
+       "      <td>257.9</td>\n",
+       "      <td>822</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>11491</td>\n",
+       "      <td>11990</td>\n",
+       "      <td>14</td>\n",
+       "      <td>500</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>9</td>\n",
+       "      <td>24.7</td>\n",
+       "      <td>183.2</td>\n",
+       "      <td>665</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>11492</td>\n",
+       "      <td>11991</td>\n",
+       "      <td>15</td>\n",
+       "      <td>500</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>10</td>\n",
+       "      <td>17.4</td>\n",
+       "      <td>201.2</td>\n",
+       "      <td>655</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>11493</td>\n",
+       "      <td>11992</td>\n",
+       "      <td>16</td>\n",
+       "      <td>500</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>11</td>\n",
+       "      <td>9.7</td>\n",
+       "      <td>203.5</td>\n",
+       "      <td>582</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>11494</td>\n",
+       "      <td>11993</td>\n",
+       "      <td>17</td>\n",
+       "      <td>500</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>12</td>\n",
+       "      <td>3.8</td>\n",
+       "      <td>194.2</td>\n",
+       "      <td>534</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>11495</td>\n",
+       "      <td>11994</td>\n",
+       "      <td>18</td>\n",
+       "      <td>500</td>\n",
+       "      <td>2013</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>234.6</td>\n",
+       "      <td>640</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>11496</td>\n",
+       "      <td>11995</td>\n",
+       "      <td>19</td>\n",
+       "      <td>500</td>\n",
+       "      <td>2013</td>\n",
+       "      <td>2</td>\n",
+       "      <td>4.2</td>\n",
+       "      <td>201.8</td>\n",
+       "      <td>638</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>11497</td>\n",
+       "      <td>11996</td>\n",
+       "      <td>20</td>\n",
+       "      <td>500</td>\n",
+       "      <td>2013</td>\n",
+       "      <td>3</td>\n",
+       "      <td>11.2</td>\n",
+       "      <td>234.0</td>\n",
+       "      <td>778</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>11498</td>\n",
+       "      <td>11997</td>\n",
+       "      <td>21</td>\n",
+       "      <td>500</td>\n",
+       "      <td>2013</td>\n",
+       "      <td>4</td>\n",
+       "      <td>13.6</td>\n",
+       "      <td>237.1</td>\n",
+       "      <td>758</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>11499</td>\n",
+       "      <td>11998</td>\n",
+       "      <td>22</td>\n",
+       "      <td>500</td>\n",
+       "      <td>2013</td>\n",
+       "      <td>5</td>\n",
+       "      <td>19.2</td>\n",
+       "      <td>258.4</td>\n",
+       "      <td>838</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "          ID  Label  House  Year  Month  Temperature  Daylight  \\\n",
+       "11488  11987     11    500  2012      6         21.8     152.1   \n",
+       "11489  11988     12    500  2012      7         26.2     169.8   \n",
+       "11490  11989     13    500  2012      8         27.8     257.9   \n",
+       "11491  11990     14    500  2012      9         24.7     183.2   \n",
+       "11492  11991     15    500  2012     10         17.4     201.2   \n",
+       "11493  11992     16    500  2012     11          9.7     203.5   \n",
+       "11494  11993     17    500  2012     12          3.8     194.2   \n",
+       "11495  11994     18    500  2013      1          2.0     234.6   \n",
+       "11496  11995     19    500  2013      2          4.2     201.8   \n",
+       "11497  11996     20    500  2013      3         11.2     234.0   \n",
+       "11498  11997     21    500  2013      4         13.6     237.1   \n",
+       "11499  11998     22    500  2013      5         19.2     258.4   \n",
+       "\n",
+       "       EnergyProduction  \n",
+       "11488               645  \n",
+       "11489               661  \n",
+       "11490               822  \n",
+       "11491               665  \n",
+       "11492               655  \n",
+       "11493               582  \n",
+       "11494               534  \n",
+       "11495               640  \n",
+       "11496               638  \n",
+       "11497               778  \n",
+       "11498               758  \n",
+       "11499               838  "
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_df.tail(12)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "((11500, 8), (500, 8))"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_df.shape, test_df.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "train_df_hde = train_df.drop(['Label','Year','Month','Temperature'], axis=1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
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+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>ID</th>\n",
+       "      <th>House</th>\n",
+       "      <th>Daylight</th>\n",
+       "      <th>EnergyProduction</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>11495</td>\n",
+       "      <td>11994</td>\n",
+       "      <td>500</td>\n",
+       "      <td>234.6</td>\n",
+       "      <td>640</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>11496</td>\n",
+       "      <td>11995</td>\n",
+       "      <td>500</td>\n",
+       "      <td>201.8</td>\n",
+       "      <td>638</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>11497</td>\n",
+       "      <td>11996</td>\n",
+       "      <td>500</td>\n",
+       "      <td>234.0</td>\n",
+       "      <td>778</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>11498</td>\n",
+       "      <td>11997</td>\n",
+       "      <td>500</td>\n",
+       "      <td>237.1</td>\n",
+       "      <td>758</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>11499</td>\n",
+       "      <td>11998</td>\n",
+       "      <td>500</td>\n",
+       "      <td>258.4</td>\n",
+       "      <td>838</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "          ID  House  Daylight  EnergyProduction\n",
+       "11495  11994    500     234.6               640\n",
+       "11496  11995    500     201.8               638\n",
+       "11497  11996    500     234.0               778\n",
+       "11498  11997    500     237.1               758\n",
+       "11499  11998    500     258.4               838"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_df_hde.tail()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
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+       "    .dataframe tbody tr th:only-of-type {\n",
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+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>House</th>\n",
+       "      <th>Daylight</th>\n",
+       "      <th>EnergyProduction</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>House</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.001583</td>\n",
+       "      <td>-0.008303</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>Daylight</td>\n",
+       "      <td>0.001583</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.531577</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>EnergyProduction</td>\n",
+       "      <td>-0.008303</td>\n",
+       "      <td>0.531577</td>\n",
+       "      <td>1.000000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                     House  Daylight  EnergyProduction\n",
+       "House             1.000000  0.001583         -0.008303\n",
+       "Daylight          0.001583  1.000000          0.531577\n",
+       "EnergyProduction -0.008303  0.531577          1.000000"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_df_hde[['House','Daylight','EnergyProduction']].corr()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "LinearRegression(copy_X=True, fit_intercept=True, n_jobs=None, normalize=False)"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "lr = LinearRegression()\n",
+    "X = train_df_hde[['Daylight']].values\n",
+    "Y = train_df_hde[['EnergyProduction']].values\n",
+    "lr.fit(X,Y)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "coefficient =  [2.56478737]\n",
+      "intercept =  [127.69148663]\n"
+     ]
+    }
+   ],
+   "source": [
+    "print('coefficient = ', lr.coef_[0]) # 説明変数の係数を出力\n",
+    "print('intercept = ', lr.intercept_) # 切片を出力"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.scatter(X, Y, color = 'blue')         # 説明変数と目的変数のデータ点の散布図をプロット\n",
+    "plt.plot(X, lr.predict(X), color = 'red') # 回帰直線をプロット\n",
+    "\n",
+    "plt.title('Regression Line')            # 図のタイトル\n",
+    "plt.xlabel('Daylight')                     # x軸のラベル\n",
+    "plt.ylabel('EnergyProduction')    # y軸のラベル\n",
+    "plt.grid()                                 # グリッド線を表示\n",
+    "\n",
+    "plt.show()                                 # 図の表示"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# DaylightとEnergyProductionに相関はあるが、ばらつきが大きい。\n",
+    "# Houseごとに、発電能力に差があるためでは？\n",
+    "MeanEnergy = np.mean(train_df_hde['EnergyProduction'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "612.7488695652174\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(MeanEnergy)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "pivot_House = pd.pivot_table(train_df_hde, index='House')\n",
+    "# 各Houseごとの発電量の平均を求める"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "23.0\n"
+     ]
+    }
+   ],
+   "source": [
+    "cases_House = train_df.shape[0]/pivot_House.shape[0]\n",
+    "print(cases_House)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "eachHouse_perMeanEnergy = pivot_House/MeanEnergy\n",
+    "# 各Houseごとの平均を、全体の平均から求める係数を算出する"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "k_Energy_House_Mean = eachHouse_perMeanEnergy[['EnergyProduction']]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "k_Energy_House_Mean_array = k_Energy_House_Mean.values"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(500, 1)"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "k_Energy_House_Mean_array.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "test_X = test_df[['Daylight']].values\n",
+    "test_Y = test_df[['EnergyProduction']].values"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.PathCollection at 0x7fa7cbd2c750>"
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.scatter(test_X, test_Y, color='blue')\n",
+    "plt.scatter(test_X, lr.predict(test_X), color='black')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    " sim_Y = k_Energy_House_Mean_array * lr.predict(test_X)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.PathCollection at 0x7fa7cbfc9a50>"
+      ]
+     },
+     "execution_count": 24,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.scatter(test_X, lr.predict(test_X), color = 'black') \n",
+    "plt.scatter(test_X, sim_Y, color = 'red') \n",
+    "plt.scatter(test_X, test_Y, color='blue')\n",
+    "# ばらつき具合は、Houseごとの係数を考慮することで表現できている。\n",
+    "# 全体的に、発電量が小さい。北半球6月なら、太陽の角度が大きいことを考慮できていないため？"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>ID</th>\n",
+       "      <th>Label</th>\n",
+       "      <th>House</th>\n",
+       "      <th>Year</th>\n",
+       "      <th>Month</th>\n",
+       "      <th>Temperature</th>\n",
+       "      <th>Daylight</th>\n",
+       "      <th>EnergyProduction</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>495</td>\n",
+       "      <td>11903</td>\n",
+       "      <td>23</td>\n",
+       "      <td>496</td>\n",
+       "      <td>2013</td>\n",
+       "      <td>6</td>\n",
+       "      <td>19.3</td>\n",
+       "      <td>125.9</td>\n",
+       "      <td>483</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>496</td>\n",
+       "      <td>11927</td>\n",
+       "      <td>23</td>\n",
+       "      <td>497</td>\n",
+       "      <td>2013</td>\n",
+       "      <td>6</td>\n",
+       "      <td>21.9</td>\n",
+       "      <td>122.4</td>\n",
+       "      <td>628</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>497</td>\n",
+       "      <td>11951</td>\n",
+       "      <td>23</td>\n",
+       "      <td>498</td>\n",
+       "      <td>2013</td>\n",
+       "      <td>6</td>\n",
+       "      <td>22.8</td>\n",
+       "      <td>127.2</td>\n",
+       "      <td>673</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>498</td>\n",
+       "      <td>11975</td>\n",
+       "      <td>23</td>\n",
+       "      <td>499</td>\n",
+       "      <td>2013</td>\n",
+       "      <td>6</td>\n",
+       "      <td>21.9</td>\n",
+       "      <td>126.8</td>\n",
+       "      <td>735</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>499</td>\n",
+       "      <td>11999</td>\n",
+       "      <td>23</td>\n",
+       "      <td>500</td>\n",
+       "      <td>2013</td>\n",
+       "      <td>6</td>\n",
+       "      <td>22.7</td>\n",
+       "      <td>122.9</td>\n",
+       "      <td>586</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        ID  Label  House  Year  Month  Temperature  Daylight  EnergyProduction\n",
+       "495  11903     23    496  2013      6         19.3     125.9               483\n",
+       "496  11927     23    497  2013      6         21.9     122.4               628\n",
+       "497  11951     23    498  2013      6         22.8     127.2               673\n",
+       "498  11975     23    499  2013      6         21.9     126.8               735\n",
+       "499  11999     23    500  2013      6         22.7     122.9               586"
+      ]
+     },
+     "execution_count": 25,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "test_df.tail()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# RandomForestを使い、Month, Daylight, House, TemperatureからEnergyProductionを推測してみる。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from sklearn.ensemble import RandomForestClassifier\n",
+    "model = RandomForestClassifier(max_depth=1000)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "X = train_df.drop(['ID', 'Label', 'Year'], axis=1)\n",
+    "test_X = test_df.drop(['ID', 'Label', 'Year'], axis=1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/saber/opt/anaconda3/lib/python3.7/site-packages/sklearn/ensemble/forest.py:245: FutureWarning: The default value of n_estimators will change from 10 in version 0.20 to 100 in 0.22.\n",
+      "  \"10 in version 0.20 to 100 in 0.22.\", FutureWarning)\n",
+      "/Users/saber/opt/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:1: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().\n",
+      "  \"\"\"Entry point for launching an IPython kernel.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "0.08"
+      ]
+     },
+     "execution_count": 29,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "model.fit(X,Y)\n",
+    "predicted = model.predict(test_X)\n",
+    "model.score(test_X, test_Y)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "1.0"
+      ]
+     },
+     "execution_count": 47,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "model.score(test_X, predicted)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.PathCollection at 0x7fa7c7b66150>"
+      ]
+     },
+     "execution_count": 30,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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8svj/tcz8NQAo/l5b3H8dgPOVOs8W96ZARMeI6AwRnbl48aInGwKBQCAwwdm5E9EagJ8B8Ke2oop7M7EfZv4YMx9m5sPXXHONKxsCgUAgcIDPyP2dAP6Wmb9efP56GW4p/l4o7j8L4PWVetcDeC6WUWe4LDv2Wf6sa7e+fNn1vq5N35OjY9v34dMHTSzz96XZ5mnTbbfV1CncMfzUt0JQbU0Q2l51mb7qvXV9f030muqHeZ8urptprV8A/hjAz1U+/yaAO4v/7wTwG8X/PwXgL5CP4G8G8EVb20myZZjdUqBMaXE+G0rHbmrtmyJoS/Xybd9n8+2U+k+xibWNZmoaqemkTK3ztdnYsvV6rumgMe2trdnTFkP6o8l+aMkuEbv9AIB1AM8D+O7KvQGAB5CnQj4A4GBxnwDcBeApAI8AOGxrP5lzd1x2nOEID/E0E3Z5iKc5w5G955rl7so6/b72vpJ2zNLqan0dP4b2vfgPXRKt48ukh1i46GLR6IS25bMM3rNsKD9lPWCX+3iVUdQf4VSwfDZbrdOyvr8O/IfK7fr+NWL7nMC5N30lc+4OxyhlOMLreHH6CxUv7hmI4tTbDEeVdUY4ZW6rflXbjjj5WsdPhqPK9nUy6/k/yiHQ83VEr4dIOOliwegEt+VzUrNH2VB+VPX2rnGQfD626vr++vAfKrfp/WvK9pmXybk7jIbzb/7ZR0M8zbpv1mH/vLJOPnpQtXVWTT/RyF3Hz7B/Xtm+TmYt/9V2fNSv46vUrUoPkXDSxYLRCW6roZF7KD+6elrzdZDP11Zd3l9f/kPl1r1/Tdk+M/PyOHeHmC9hV/mIsKuNiVFtFLJ3qe8Txo3G3HX8EMbK9nUyG/kPgJ6vXb0eIuGkiwWjE9xWQ3H0UH7074X6cpHP11Zd3l9f/kPl1r1/Tdk+My+Rc2e2LjseDi4rO2bYP69VvO5L2Bhad1mu7LIsX1HfeVBQtK8dDTlMDfhAy1f/fGOHXbY0QEpKJ6otn2XwjmWb3NHWVz7d+2nbndf0/vryn2zqI2ZLFEcsl3Nn+7Yjqn2lVKee67aFKL+EUyeb+MjnQ1dVvpRHJ1foNhop9GH6zqtvEzMYzCY/6fozBq4JEi56i9GT75Y6LvVTJo3ortLOVP1pa5PIvB9aPZHM57uv6aSler3Uvn6pnPtoNOuwys9156BybibHXW+HWd9hDQ7co9pXyVyVK/YLy3W/JlN9k8NQZbJWnbnK2af6wvUdNNi+cH1fdFWm4Oqq3kHXv+RMfRvqeLJsdg8zn0v1Banap6w66ADU+/iF2G6M3L7vXxN2uTTOPcvsSSiuu/TqfgYOBuZRZclH6pC76ovFpgsVD7oXsfxJafvJmXJkpGorZJ7Zh39fGVyRQm+2Mrq+K20y1MG6hEuqfWNzqKH0be9EvQ9d6bqGzmLtwubMY3jTYWmcu6uBD4dxL4PuKh2Xi4OJoe/yje/bfpmhZcrg8h2dmvSgaytUJy78M6cLHdURqzeXMjb5Y3Wng8mRxtCt07fZbJVPH/t2yT6MtQvfwZoPbyYsjXN3NTQie9mYYy5dUlxjXwrbN75v+y4jX98JKJMedG3F6N3Gv8vzUMTqzaWMTf6mbKmJgZCKvs1mq3z62LdL38baRewvzlAsjXNPOXIP/blpclypRu4lnRBdDAb2UInuue+6DJMeTC+nb8zdZ2eGptaWxOrNpYwpLBM6cnQZnaYYnbvQt70TVT5d3x/X0XesXYToSGLuHnAx8GrMXdchg8Fee9UYnMvEkSnkEBNzV9Hx1YXr5Jnuue/oxsSDLWRjmtcI5T9EBh/E6M11rqD+xVY/0bCqN53t9Pt+cWWXcEn1c3Ui1/RLTDUpbXsnXcr6yueq/xgd1fWSaq5naZw7s1+2hiqzxjelUFc3VbaM6uVJkTYXgpC4pI6HpmLfTcjQBk1Xvnz61Ne+ffivtmd6x3z17cNzKvlC+HSp34Qzr2OpnLsvfB2gbVS5CDw2iZS8zEuuedBNkS3TFF2fdsqRsWrknYoHn/KLZI/zsCuTc6f8+XwhZ6gKBAKBP1KeoSoQCASCfQBx7gKBQNBBiHMXCASCDqKbzt337EjbmY2q81dN55LOU54U7Zmet3GOqE3HMfynlsG13VRnbvrSSHWmrc+5w3Wab3/7Xp1eD3jNa+wy6t5JG62YM3tj7WJedqeDbqa1zSv5lr8+e177nNloOn+1qZy61Ll7tvZsCfKpeNG1ZVs9FruKqalcyFi9xZbR5eLZNjgJ3QbRh0cf+qZ3UpUX6rqwJab/XDAnu8NSpUL6rEYwrTyIXQc/D3lStJdy/4EQPmT/gbAyMUuebbLb2o5deu1av86nz5L0mP5zwZzszuTcu5cK2evlaquDCBiP3crGQEUnBj7ypGjP9BxIx0tq3bvw7/I8FLF6c+ErhIYLbLLb+sqFR1f6pvp1Pl1pufRtrF3Mye6WKxXy0CH3+7qyANDvp6UfCh95UrRnep6SF12dWL3HyBeDWL3Flonh31bX53msLZjq15+50nIpF2sX87I7E3RD+jYvibknkidFexJzT69Xibm705eYuxewVDF3Zv/1y9Vdlsot9nTtdGH/AVt7pudtrPe26TiG/9QyuLbrQjO2jM1ebZstucgG2PcfqNPc3t6rQ8R84IBdRt07aaMVKp+qLV+7mIPdLZ9znzNC+7Apn+ODReBhmeHq3+u7PvZ6uV8zteHaty7fEaHfTb5o611q2u6ban8pnLvrl6Zu4JHKiLa33XaqU9Vz+SWaQhe6Mr6/HJt48Zp8yeb1xeXjVG07C45G6qhF9VLZn49dukR36rtB+p4Rmo0e5GH/PAO73MerDOwyYYeBMQNjHtAlHm0/FhTJcLXjKg+E3Vn5th/jYf88E3Z52D/P2ehBe18XbVbrNBSRYeYlcO4h4a66kaYyIt1VzXjyqVffxzpWF6YytvNVfen48tfkS9Bk26noumT2pT44IzS70JUXpe2MHuR1vOhAY+zcposMU++gAw8zDh8vGh28qs11vMiDA98JksMFnXfuoSmm5aVLrQ41It2LEFIPSKuLEPqq02hC03ZN9ULbTKWXJuBDt8kTj1z7NjUPStvpn0/eposMU+9gIA/D/nl9X2vbVH9JxZ7+xcxscu6dyHMPTTG1ITb9t4rhEDh71r8e4Fc2Jl1ahyrvPnR8+QPC2nRBU+ntKelubQHPPNMcLyrU+zY1D0rboTE4Igtb1WYVOhmm3sFAHghjjFldT98mAyAjP6HofJ57aIppCV1qdWz6bwki4ORJ/3oAMBi4lzW17ZJKPBgA6+vT99bXp3n3oePLX5OpwPNIM/ale/LkrP5TgGb9yuR+vW9VPKyuAmtrbm1WobWd/nP2yiUdTH8D6tqsQiVDvZ6Nhzpdl3q6ZwP6hvN7lRS6IX2bV5dj7kR7WQw+9YA8XBSSjRWbLh06+Scx93i6Vf3rJilHI/t5vmVoopyErfOgsksVD6aMStvkr2ky1SXmvoaX80nNYdpJex0PeYx9nMu3/Zgyfh4Scy8nVSVbJhCLki3jmmarquea2uvLU1Npa5It0zzdmPTFVDzE8qas65At45KdEgNVZovP85A2U8Pk3DsRcxcIBIJlROdj7gKBQCCYRnecu8tG+dUDAFwO5gihazssQHfowfHj7gcU2GQOPQTDF6HttXUYiA/d/V439KCImMMuFu1wClea8+BrHrR18Zo2r+iYu8uMqm5Zn26TsFQzqq4zuzrefGc0dbLYNuTynV20yWLarG2/zaguet2QjAIXmwjtx1i5QxGbTdA0GqCN2AlVAFcB+DMAjwN4DMBbARwEcD+AJ4q/VxdlCcBHATwJ4GEAb7a1H+3cF30VkysfPjzo2tLJ4nIIhs+KHhdZVO3tx1VMi1431P5dD0bx7cdYuUMRs4Kv6dVsDdE2OXenCVUiuhfAg8z8B0S0BmAdwH8C8A1m/jUiurNw7r9IRLcAOAHgFgBvAfDbzPwWU/vRE6qLvoophg8dD/M+aMSFvs8BKYu8imnR6zZl/yZe53UoigmxB540uZqtIdpRE6pE9M8A/CiAewCAmV9h5m8BuBXAvUWxewG8q/j/VgCfKL5YvgDgKiK6LohzVyz6KiZXPnxo+B524XIIhg9/oQcg7MdVTIteN9T+XQ9G8e1Hl+dNINWhKE2hbdq6IX15AXgTgC8C+DiAvwPwBwA2AHyrVu6bxd/PAPiRyv0HABw20ZCYu+aSmLvE3CXm7g6JuU/7bt2DSQHgMIAdAG8pPv82gP9icO7/XeHcb1K0ewzAGQBnDh06FCzcBC6rOOrL+nQHcwwGzBsb6nImui71dHy4rGJyXTGl00Wddq+X/62u6vI57KAuu+vBJXU+6v2QajWXid8YWZtYiaST27Vu1e6qm7vbeKjT3djY+1zdgctmj66HqpT36nank6te1mZnpj4u69ZlK2UOsQPVe2t6l2PsSIFY5/49AM5WPv/LwoF/FcB1xb3rAHy1+P/3ARyplJ+U010LdViHbpRv21w91Sgrtn3fNmxXE6OaeY3eXXloG6E2F1u3rK/aR0A12aprM8b2fUbYvvYZYu+mNkPb8+kPT0Q597w+HgTw/cX/vwLgN4vrzuLenQB+o/j/pwD8BfKsmZsBfNHW/kI5d1MWiGlWO1VmQ2z7obKZrtSZBPPKmHHloW2E2lxsXVt91zZjbV9V3ocv34yy1HLO6z1i5hTO/U1FCOVhAH8O4GoAgyLk8kTx92BRlgDcBeApAI/Y4u3M7Tl3p19Epg2tTRswE3GGIzzE0/m+EniaMxyZqZPhKA9wgSd7aOCCspwLXxN6rkeJKWiPcGqK5/pnJ97Y89emSVeOeoyGy6bfofIF8KKU2WZzlbpBNsW5Taj6f2avF1ObGv4zHJ3WGY6anV+17Uqb1f1nBrjAA1zQ2sZUP1X1WHlfqu152bzmHbS9U9W+TG1H0c696asN5+78K3w41L8shm/ebHBCvSPc4MQUD6t4ecam1/DyVDklCr5KoxngAq/V2rL9QlXRnj1IYGyUIUq3Drpy0WMS1PQ5eQkVfdx0BEclM2GXRzhlHe1lgxO8itmTflxsKsuY1+kliz3Y21Txv4rv8Br+aVpn9NLUl0fVwdZ1r2pTdVVtQxlhwneKd3n2KD1vm1e8g328Ym2v7MtscCK5HYlzZ/dfjtnoQf3LYtjhbTi4rG5/cNnKQ72cCq7bpDbyC9XCm2+Ew6QrFz2mgGl71lj5fKGTmbBr3VVQVzem33xtwcSDSiatk67I6tNmyVNs1MQmp/vxgGq5mzhuz+Tcl2ZXSNf1A6aTaEwnp8SegGRbx+B6Qk4Ta55iTlfy4aXpdUxVuJzWU6LpdS+mvrGd1hNjU6nW1KVaTxd6WlmqtVqqNqto6qSsGDuSXSHhvn7g3Dl9G6ZnMesnbM9stG3tnD6dG34oDh4072mm4/3gQfUeSSHrmA4eDOVeDZ0+y/vV/Z10uqvyGrO/l6nvn3nG3KarTfnSdWnThQcfVPskZD1dyrVAKt01dQRiY+undEP6Nq9FirmHJh+4rp8IzVpz+cnpm33mcrlkxemy6VSnCGVZngasojUaxWf2ucIUanHRWch6HV250cjtYGpdmzZ9xdK19YFr/9toVd8vnVy+coZcMesOTddgkH7uBhJzz+G6HiQm5Th0rYoL76oXyLb2IiYO2e+bj3Orv4xV2XX1XLIdTXVTweSQdfz1+2pdp8iCdXW0Kh3YbMqXbvnZtoapzoNuvZLpaD6Tk7MdJVjypeNDdUyhKUmq1ImL7nRXr8e8vT1Lp7qMQ7Jl5ohQB9wGX76G4TMyUxl8RGaod5tle55ZisHQ6dOXvmt5W7kqPyE618GHbvI0zxpUi051NF1s16YPnWyuMvu+P23rVJz7EsM0CrUZqmmUXT73pesycp/3+iLv7B/H8j7tptTBvPUZCpdRc9MypFjj1SRMzr3zE6qnj/81tlaeRY/G2Fp5FqeP/3Wj9UztbNLz2Ow979xmCh5OngTW13am7q2v7eDYsdn79TK3vPFxvHjueQA883xtZRe3vPFxLX+3vPFxEKZTANbXdnDypJ6nkyfNPJfPm4YvfVV5gHHpmctT/X3LGx9XtqvSo67N55+5bE5lHvUAABq0SURBVLQDlc3MU5+uNuzKdxVtyKCyY9X70BY/XtB5/TavpkbuPrnMKeq5tOPaZioeOMs4W/3A9GKd1Q8wj0acrX6gslhrjw5hl7fxWQXv1VV4v6PlT8U7YZdHdPck8KjkqfKb2fi8afjSL8qrdFnXz4jurq0IvUutx+17eIS7GIq8cN2aC63NbN8zF3262rAr3zOrUxuWQWfH2/hL9UKsNm20AJYtLJONHuRh/7z2RRv2z0/KEHYnn0vkddX1fKBrx6XNUB5m5Nq4Y1K5vrrO5Ixyo1Xfp4lRq/nT8o6no+Iyo/7vFXTH3MerPLrx8+568PhSzDbuUL+8G3eo2y34zetY+htPT93Q1clXP6p1XPZDXSa93s+a9d0Q9PY/nuoTb74VMpj6OzT+bbRjxYMMRyZ1bPMJqbBUzt1tFdmucUShW0VH2PXiRb/c2d5mCA/aERCOcIYjnqvr9CNQmzyq0Wap99AZ1RFOKXgaKx18zK8ek/3kS+pfnm232DvEub8rN1yXxKuuukxGmzHpuyHY9FHy7813TQZTf8dsHeHDl+n9anKz0aVy7i6jZdOo09TGoo/cTSMNl1Gli45c5DGN+kNH7sY2E+jOp89m9XuWGWlH7j76tvf/WbO+G4Kr/ceO3E39HTOZ7DNyt/VjU6peKufuMlrQjSzLUfF+jbmbRhouo8oqHVVM3aVeNnpQq19gdy/Z1/MUH/1IduylBxt89DTV7vq6w6+jMWf9903dzHrv1cxteNC22cz2PXPZu97lV3S5f44z3woZjHYfkVZr+iVcb9BmN039SFoq5+4S53MZ2cXEbKuotjPAJR7QJec2fXnQytU7x0OcdXAW40lsmbNsir4tBu8UQ+2dqwhnCYTWni/0yL1/fsJvhiNaXge4pJS73s8DuuRH28Vm2kxmV/Bjmv9y5ltzClNTI/cJX71ze5O4G3fsne4ETILrNruRkXsssoyztQ9YR7zJMlEU9J1eoOpKDtsywNFob3am38+Xv2loZNv3aEYaR62jysmIRDMTpG27+CKYEs80EjOtDjPob/S9n1I4iFrMveJgtfQtK1pU9lNe2pi7a/ZH3b408qrqu9IOssEWZv+cdKJz5Jaj9YxzTYMTvL5S09vaq9NNuC6vNdhuluXtGt+tBvS7HM69sm/AzD7d2/fMFk80Mp+iH3vUGDC9z4FuExYVjaJd7aEPqGfLVH5F1Mp5t62Qc0a/2/eY93Uw6a94NsKp6WyZ7/2UVq9TvJb0HQ+JVh7qUNiIq91Yy1nsRVU/tk0nG2wwXGPk3/ZeWHicattg96q0W6eNcWzvaiV9VrlXfUP6XQ7nHrqUMhVilymq6rgsIy3L+yyl6/fd+XFt26ZjW//ELGl10X/sUt3UaGLZaCobnMfS1VRLQV3bsdmFLx8+7STUr8m5d2c/95iNrVPAddNvl02nyzrlBuc2mDZC16Esa+PHte2YzcNtG7mbntk2y0+x2XcT9tPEJvGpbLCN96UO3/6JPbgg1SbwIe0k1O9y7Oces1l6k/Tr9114Kcv0++60fWSstmur59q2SzshNGzPbO3bNvt20XET9uNqL020GdNXTcGXZqz+Um0CH9JOW/rVDenbvFLH3Keu1BuBm+gvQMx96lmvp64zGrnxY2rbJqdKP5ExdyPNgPRKXczdW7YQxKyuiW1zTjF3b95D+sSlHZtdBMbcnfiXmHsgsmy+e/XOOVtGSb9ev+rYVfzoMiccUtKc9BOYLeOkW8/0SlW2TLBsIWgiPXFBs2WcEJgtY2ynzHTxtQvPbJmpdurvdTnIajlbpjthGQCncRs2cQkEBoGxiUs4jdtapb+Fs+hhjC2c1dIuyxEYPYyN/B7H3VjBDgiMFezg7fgfWhoq+vX6x3G3kZ+yrKntTVzCJi5Z5VTRMfWPSX8uurWV0T1PIVsIXO2liTZd+rxt6PrBt09mdPC2u/PDWcfj/O9tdruo3zuOu+2+5bbb8vaZcfqPxtga5mVXaHc++tV5/TavFCN3icpIVEaiMhKV8dVrqqiMqyyp9YtlCMtIJqRbWUAyIeu6iJUtBJIJ6ceTK4++ek2VCenTZkr9mpx7Z1IhJRPS3m4VZVnJhLRDMiGbR9OZkLGZkz58tKnfpUiFlExIt7L1diUTUs+Xre0YSCZkHE1f/TWhb139hdGvbkjf5rUoMfds9CAPcIknJw7RpZll3wO6xIMD31EmXNTjbPlOceOppf4b+Dabdv1rPuY+5gN0ebL02xQfnPBPl3htZUfLg+7keJf+6ff3khBMJ8bb4qjb27Ntr66WbY+ZsKPQ+5ivwD8aZcvr7M7YhLNdKjaOA3aV/BCpk5mcaSn7csyD3vMzh1foZF7t7/Cg93zwthy6LQZsiUqq/tfaW9EfZfuj0d69vWv2nVIl4/jQVV26pBmJuXM6585cz7QrjBpH9elNFS1nowd5Fd+ZdT54ZWbDpqnOWnt1chpPhqOTHfDct44dGw1lJhPyxme1u9RlODr9bHCCR9uPVQy/wndlM6Ns9GAtK26W/1V8hwe4yITx9IuhanfjDmXqWj0TcmNj1slMXtyyWlFpan+QweUpPY22H1M67h659UEfrxSnUpkOGqk4C7zM2RU/Z03Nczs4RmFPupffIWUzy5gHV8wOIKqbdKltfcwbK46bk1V52TMazjbuUG7gNdp+bGZTrfW1V/P7eKnW/+PJu1DPhFTZZQ//pOj76Wu1v5NPnGs29qrSrdszCnufzoSs6/almU33Zt+pZjJNl8a5T5ApzsDsvZez/vu0GwiFbPU6ccq4MNVu7ijc6w8Hl93l6r23cjxeeZ7pKeM5k8PeOQ3tsfLsR50uetjJ9yMvdTa4rHlRdpzOutTVH+DC5MtYJW+VB84y7sE08na9Zkd8pquHHbt8gTaltIeaTWvPE80yrf3ZDqOxHWKj4qW6SZZpW2adDn3eh5h3tE92G9GVqfKjs9lyM7u2z1NdOueeDU64b5k6OMHMYYc0TDsG02fz5Xp8XzY4ofx1YTuU2TYarerBpos1vOyts3r7djpjzgYntPJWecgGJ7z1nfryl8/fHlQ2reLBpI+yXd+j/er82Hhxt083erH6NPPgx0+szafG0jl3n6PLhng6rxMxKoi9Sh5SylW9XI7Mq/JgPXig1FmAnl3lsR0NGMJD230YPHL31JWzzhKN3Js+slH3PkSN3B140MpffTcibT41TM69M9kyVZyD+3R0WfbksbNYxcsB1Njz/jTW8RJODj7sVNZHrip20cM6XnJu++SxszDxP9HZ4MPWdlXtT+gMPqylcw6HjPKWz/Rl3PSfCkr5jp111k8JnT249L1ZZ1z0q5qvdbyEYzf+tfJ+Wc+Hl6l21z6u0IP+vdG9Dyq+e3jF0FaFB/y+sS90Zer9EWvzrULn9du8ko/ctXExxbdrJZ5Wz5bRxQSr8dYBLirLDK74tjHWaIvXxspVl9F63Fktzjm4Uk9rUraIvTr9MtDEkXX6Gw4uG+Ut29PH/XXnau54TnbPTkY7y8ds1Xvs/ISrzgZXfFvJ10xWi8NhJDZeZo5eVMyBad+bcr5Fgxn+bjzJI5zS6rePV3Odjkb2OYtaGWV/TM03mO3CeS4tAli2sEyWzc6Mr/Z3ZjIzjJkJmnbWV4p4b5GlkI0eVGYCTFL4LPV9Jl2yLJdD7YTUBlaXUcmTQg86WmsrO9Nls8weDzboOc8oeUmrPxsPSnnwIo9u/Pzs8WorL2v7ZYbnMmaaZdbyNjsy6r3ItLJm3jjy4Nq/MTDxoqVVy1RTvjd4KexEtNGIM7pNfdRe0YczPOg2IzNk1NVlyXB0xnab0rkOS+fcmdV95NJvLu34lAmhaeOnvjldddM7lw30XHlS0TKVDd1Y0aY/1834fN7TaibfzIhLwXOMfC5y+tY38ZDa5ky8AOGpfk28G03LraMZo4cYmJx7Z7YfEAgEgmVD9PYDRHSWiB4hoi8R0Zni3kEiup+Inij+Xl3cJyL6KBE9SUQPE9Gb04kiEAgEAhf4ZMv8ODO/qfItcSeAB5j5BgAPFJ8B4J0AbiiuYwB+NxWzAoFAIHBDTCrkrQDuLf6/F8C7Kvc/UYSEvgDgKiK6LoKOQCAQCDzh6twZwF8R0UNEdKy491pm/hoAFH+vLe6/DsD5St1ni3tTIKJjRHSGiM5cvHgxjHuBQCAQKLHiWO5tzPwcEV0L4H4ietxQVrUL+cysLTN/DMDHgHxC1ZEPgUAgEDjAaeTOzM8Vfy8A+BSAHwbw9TLcUvy9UBR/FsDrK9WvB/BcKoYFAoFAYIfVuRPRBhG9pvwfwE8CeBTAfQBuL4rdDuDTxf/3AXh/kTVzM4AXyvDNwuD0aWBrKz8yZWsr/9wGzc3N/BgWovz/06f9eNGVbUKeapubm/lVbV9FMyUfIfRVOH4cWFnJdb6ykn92oRnaFzHPQvhwQYjd1O2139+z23pfzAs2PR0/nj8rZXjNa8L4je2PefgbwL6ICcAbAHy5uL4C4JeL+wPkWTJPFH8PFvcJwF0AngLwCIDDNhpNLGLSQrWTftOnAmeGkyrqJ/HqeNHxrTrhuYmTlqvX6urs9sm997rL0gR91bL90Wh6H3g8ne+7rToRw8cuVFtKV7bcDXoWwkeoLm12o9tqGUcUSzEX6ETtKi+jEY9wqnIoypgP4AXO6L3eK62sfdZkfQuwjCtUtWjiZOJQmrrL59Rd3QnPTZy0XFwZjqiXeqte/hA+QunXtljVLkmn29xpKvhXbbdQ3XI35FkIH1G6NNiNcavlVH0cC4ueRvgdVm3LsYJXvLbideqzBuvbIM69Ct2ZWkTt09RdKl5StJGIX922p0M8nYaPGPoVuJYz0lTwb2o39FkIHyl0qaJj3Wq5zXfHV66CF9Nmdj5b8XrZUAP1bTA5905u+WuE7nRaZnM8LCYGnOL0X98Tng8e9I/zlTIwG4vptjJV3i/59ok7WvTlSj+IT4f7pnZDn030cvCgMx9O8LWbXs9pq2UrjabjzJb+2oX+5HPrVrwV3o195jB/4WWDqaHz+m1ercfcVfHv8lLFEB1iwMZ4c9sxdxs/Or2YZHQaOZ9V0/SNI1v6aIizevqVNocHLqnLHbjkrl8Fj7otb01b7hqfVUfDIX1ngo/dWPp3hlef9yV1bN5Cw3SsnnEr3lq71l+plvkLkz2kACQsU0N1m0Gl5ofT5X1j5qp2dNsb+mxl57r9oU4+U2zUJGN1C8J+XxPzfkm/fW1IHFknQ7+v3ia4cuB3VV26bX+99Kso5rXNs+mZaq5iMGhnu8Tq/UoMPsMRfcxdc/j5FNqa1zL012jErIy593bN6qzx7jS/ZJq/MNhDCohzr4NokkVRPeB3kk1RjyFWyis3+scRdVbGPGKRCn6d+HGtU5SbzaQ42io/GY6qszlqbTa1DWzoNs9Tz/D01OHmc7UbhY1v4IWJgzRt92xra15yjUbTofkDBxxkUPBuPIC+cPJGW21wK2Jx7jWYDpdQZl1YDqOwHb7dNkJm6F3rNNm2T52msxDawCLJkJKXRZLLFyHZTiP8ztzkXV7nPhrN/mQaDo1HyAGz8bDg4+0OXJp8ZWeDEzzY2Pupa4zKaIYcU2UHlycnOmWDEzwcXN6LymjkU8aarTKOp6MyPfURddWj/PLRy9l89DIY6GPkhrjj4MBsWABg7mOHM7pNHwtdeXavz/t9zrbvyXWGcX4sG45qh9P56Ovs3hFu2/fMnsRQVcZgwLyxMcvExobTaR7aI/FwkYe9c9N86E4sMZ1mMpHraNEvY31UxtSv9UNCrry8N0Kl2/bWDRQFtX2j6++QoW2WnwA2GS0XfJrKu5x0oo2R0zPaORztwdqV4yibGrovp3PPg24zV4YjbDv7UBGJCHLuhN0JTVUMUzmfuqLOJc7overj5HBK8atCd17nrtawQmWs0tTFJrXnmWp+pWeZmVZOR3dG6u5UX2vjpbXJXq/cfd9LM5mo1/nYzsfaWm7jqonn8plOLvN8qpJ9U19kOMK8vT0p6NXfIZOvxcKgGblMR/wZhdijp82wxK7h7F3N+0aB8nlgOZ27ZpLDlAlQXsnmU4sZdReaqnoufLscTj3VrmZSK1RGGx/G/G41K068mOjZdDYpMxxOiHnl7gcZw6ywPjpX8qGbyKs809qNoapvuTpvXv0dMvlq+nXgQ0NRUcuOwY61tjgMlM8Dy+ncNZ2o//bNr6BMSF3MvRht2WjWr+ro08637leIZvSnGS57ZEIqdWbiQ/XrYh0vagcvbr8ixjM6IezyCKesOpvol2hCzKRf68S5U6fO6l2tc70edTRNPPna3my/uly7M/yofi0o+ztk0RaR368DF4OqTH6qfgkPcEFrx8r7pbwNL5pcTuceMHK3HRadx24dsmWG+cSMC00lHx4jdye/UnV6hhFDKaNLm/3+dAhx0Hte7ySKF2DKARkmm/x+RehDGD4j9zzzxkzL9iVu7lS13rOMK/MUTzvxMaGpTUsttlgw6EA3Iq/3q0tfEHbNXziG92rRRu7M+bu7l4lVs+ONj0/8gDZbpiqvjNybibmPcKr4yTTmasrczAvqEwJTbKo0ScXrv29qtqrcMCiPD8+ONHQx92385YTvPl7lEU4pY+4+1xBPOwvqEaKcoDpZrHQaeHXvhajqKYC+/cr7hLDDK3hF7Rirm2StfoB70C96caVXXht4YfrL37ZRVM1WXEbbQ5xlHo30k9UHLnG2+gG1k/LYb861L4ZX/kPYBllZwMZaWcaj3u/N6ClFzL0sP8BFtZzVSVJHBcrGYYmhW8QAMK/2d1ySGZTIsry+qt21lZ2pTIRZZ7zHjy5bZntbxfeYR9uPeY2s65dpMlUnp0NywQQ+E7IuizhU9EMd74ED+mwZdT+lvWzyqnigyYBANzk+zvVuSA5Q2Z8imcb6HlTL2eQM6Wffemp9jZWbfSqFsBh0PqFvmCRVtalRoCxiasC52yaCUm+yV2839NeYju+qUZna1j3r99MunqjD90snRP+uk4A62X0Wz6a+QhcH62QeDPK6hoW8Se0+tA9s9AKjMt51fAYrpv6o0nD5cmx6se5SOneb0TW1yV7Zbug8iqntqV8F+q24tb9Am9x62zeUEqL/GOeq01d8Cmi8vCE82DIhU9t9aB/Y6AXOp3rV8Y3KmPrD5R2Mlc8HS+ncuzZyr9c1jRqyrLmRmwnVsFET+jf9KglxkLZfOqo1cKFX6MjddJlG9U2NGE36CqHXxsjdcz5VW778teTDg4zcG4u5q6/YTfZ0Gxaurfl/s/vw7fNt3/SIIYYHIEz/Np2adKfTha1N3XPdqDnE3uInkP3lCoVJHyH0AtcwedXxyIR0bt/1/Wp4DdNyOndm7e4DSQy8HutUbazkOmFVx4EDasPx+bZvesQQw0N1BOQLm06rfV6Ovm26sLWpe66yA8B59wElDR8nbhsth9qfK6+2zUld6YXU86njO3J3ad/n/WqqH5iX2LnvV6T4tm96xLBfeFgkPlyg4lW3xXsTx+d2Eb4x99A256F7ce77ECm+7ZscMewnHhaJDxeoeE09Wl42+Kb2+rY5L92bnDvlz+eLw4cP85kzZ+bNhkAgEOwrENFDzHxY9Wz5zlAVCASCJYA4d4FAIOggxLkLBAJBByHOXSAQCDoIce4CgUDQQYhzFwgEgg5CnLtAIBB0EAuR505EFwE8k6CpTQCXErSzH7BMsgIib9ch8oZhyMzXqB4shHNPBSI6o0vo7xqWSVZA5O06RN70kLCMQCAQdBDi3AUCgaCD6Jpz/9i8GWgRyyQrIPJ2HSJvYnQq5i4QCASCHF0buQsEAoEA4twFAoGgk+iEcyeidxDRV4noSSK6c978pAAR/SERXSCiRyv3DhLR/UT0RPH36uI+EdFHC/kfJqI3z4/zMBDR64no80T0GBF9hYg+VNzvnMxEdCURfZGIvlzI+qvF/e8jor8pZP0TIlor7l9RfH6yeL41T/5DQUR9Ivo7IvpM8bmz8hLRWSJ6hIi+RERninut2vK+d+5E1AdwF4B3ArgRwBEiunG+XCXBxwG8o3bvTgAPMPMNAB4oPgO57DcU1zEAv9sSjymxA+A/MPMPALgZwM8X/dhFmf8JwE8w8w8BeBOAdxDRzQB+HcBHClm/CeCDRfkPAvgmM78RwEeKcvsRHwLwWOVz1+X9cWZ+UyWfvV1b1h3RtF8uAG8F8NnK518C8Evz5iuRbFsAHq18/iqA64r/rwPw1eL/3wdwRFVuv14APg3gX3VdZgDrAP4WwFuQr1hcKe5P7BrAZwG8tfh/pShH8+bdU87rkTu0nwDwGQDUcXnPAtis3WvVlvf9yB3A6wCcr3x+trjXRbyWmb8GAMXfa4v7ndJB8TP8XwD4G3RU5iJE8SUAFwDcD+ApAN9i5p2iSFWeiazF8xcADNrlOBq/BeA/AhgXnwfotrwM4K+I6CEiOlbca9WWV2IbWACQ4t6y5Xd2RgdEdADAfwXwC8z8bSKVaHlRxb19IzMz7wJ4ExFdBeBTAH5AVaz4u69lJaKfBnCBmR8ioh8rbyuKdkLeAm9j5ueI6FoA9xPR44ayjcjbhZH7swBeX/l8PYDn5sRL0/g6EV0HAMXfC8X9TuiAiFaRO/bTzPzfitudlpmZvwXgfyKfZ7iKiMoBV1WeiazF8+8G8I12OY3C2wD8DBGdBfDHyEMzv4Xuygtmfq74ewH5l/cPo2Vb7oJz/z8Abihm3tcAvAfAfXPmqSncB+D24v/bkcely/vvL2bdbwbwQvnzb7+A8iH6PQAeY+YPVx51TmYiuqYYsYOIvgvA25FPNH4ewLuLYnVZSx28G8DnuAjO7gcw8y8x8/XMvIX8/fwcM9+GjspLRBtE9JryfwA/CeBRtG3L8554SDR5cQuA/4s8bvnL8+YnkUyfBPA1AK8i/2b/IPK44wMAnij+HizKEvKMoacAPALg8Lz5D5D3R5D/FH0YwJeK65YuygzgnwP4u0LWRwH85+L+GwB8EcCTAP4UwBXF/SuLz08Wz98wbxkiZP8xAJ/psryFXF8urq+UPqltW5btBwQCgaCD6EJYRiAQCAQ1iHMXCASCDkKcu0AgEHQQ4twFAoGggxDnLhAIBB2EOHeBQCDoIMS5CwQCQQfx/wGMbEjeF0fExQAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.scatter(test_X[['House']].values, predicted, color='red')\n",
+    "plt.scatter(test_X[['House']].values, test_Y, color='blue')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.PathCollection at 0x7fa7cbce7750>"
+      ]
+     },
+     "execution_count": 31,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.scatter(test_X[['Daylight']].values, predicted, color='red')\n",
+    "plt.scatter(test_X[['Daylight']].values, test_Y, color='blue')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# RandomForestを使い、Month, Daylight, HouseからEnergyProductionを推測してみる。（Temperatureを除いた場合）\n",
+    "X_hdm = train_df.drop(['ID', 'Label', 'Year', 'Temperature'], axis=1)\n",
+    "test_X_hdm = test_df.drop(['ID', 'Label', 'Year', 'Temperature'], axis=1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/saber/opt/anaconda3/lib/python3.7/site-packages/sklearn/ensemble/forest.py:245: FutureWarning: The default value of n_estimators will change from 10 in version 0.20 to 100 in 0.22.\n",
+      "  \"10 in version 0.20 to 100 in 0.22.\", FutureWarning)\n",
+      "/Users/saber/opt/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:2: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().\n",
+      "  \n"
+     ]
+    }
+   ],
+   "source": [
+    "model_hdm = RandomForestClassifier(max_depth=1000)\n",
+    "model_hdm.fit(X_hdm,Y)\n",
+    "predicted_hdm = model_hdm.predict(test_X_hdm)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.PathCollection at 0x7fa7cc179450>"
+      ]
+     },
+     "execution_count": 34,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.scatter(test_X_hdm[['House']].values, predicted, color='red')\n",
+    "plt.scatter(test_X_hdm[['House']].values, test_Y, color='blue')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.PathCollection at 0x7fa7b5172450>"
+      ]
+     },
+     "execution_count": 35,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.scatter(test_X_hdm[['Daylight']].values, predicted, color='red')\n",
+    "plt.scatter(test_X_hdm[['Daylight']].values, test_Y, color='blue')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.146"
+      ]
+     },
+     "execution_count": 36,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Temperatureの影響があるかは、はっきりしない。\n",
+    "model_hdm.score(test_X_hdm, test_Y)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/saber/opt/anaconda3/lib/python3.7/site-packages/sklearn/utils/validation.py:724: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().\n",
+      "  y = column_or_1d(y, warn=True)\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0,\n",
+       "    decision_function_shape='ovr', degree=3, gamma='scale', kernel='rbf',\n",
+       "    max_iter=-1, probability=False, random_state=None, shrinking=True,\n",
+       "    tol=0.001, verbose=False)"
+      ]
+     },
+     "execution_count": 39,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# SVCも試してみる。\n",
+    "from sklearn.svm import SVC\n",
+    "model_svc = SVC(gamma='scale')\n",
+    "model_svc.fit(X, Y)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "test_Y_svc = model_svc.predict(test_X)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.PathCollection at 0x7fa7b53d8d90>"
+      ]
+     },
+     "execution_count": 41,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.scatter(test_X[['House']].values, test_Y_svc, color='red')\n",
+    "plt.scatter(test_X[['House']].values, test_Y, color='blue')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.0"
+      ]
+     },
+     "execution_count": 42,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "model_svc.score(test_X, test_Y)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/saber/opt/anaconda3/lib/python3.7/site-packages/sklearn/utils/validation.py:724: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().\n",
+      "  y = column_or_1d(y, warn=True)\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0,\n",
+       "    decision_function_shape='ovr', degree=3, gamma='scale', kernel='rbf',\n",
+       "    max_iter=-1, probability=False, random_state=None, shrinking=True,\n",
+       "    tol=0.001, verbose=False)"
+      ]
+     },
+     "execution_count": 43,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "model_svc_hdm = SVC(gamma='scale')\n",
+    "model_svc_hdm.fit(X_hdm, Y)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.PathCollection at 0x7fa7cbfc9610>"
+      ]
+     },
+     "execution_count": 48,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# RandomForestを使い、Month, Daylight, HouseからEnergyProductionを推測したものが、この中では一番よかった。\n",
+    "plt.scatter(test_X[['House']].values, predicted, color='red')\n",
+    "plt.scatter(test_X[['House']].values, test_Y, color='blue')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "solution = pd.DataFrame({'House': test_df['House'], 'EnergyProduction': predicted})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<bound method DataFrame.info of      House  EnergyProduction\n",
+       "0        1               794\n",
+       "1        2               605\n",
+       "2        3               714\n",
+       "3        4               549\n",
+       "4        5               549\n",
+       "..     ...               ...\n",
+       "495    496               486\n",
+       "496    497               714\n",
+       "497    498               645\n",
+       "498    499               714\n",
+       "499    500               605\n",
+       "\n",
+       "[500 rows x 2 columns]>"
+      ]
+     },
+     "execution_count": 55,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "solution.info"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "solution.to_csv(\"predicted_energy_production.csv\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
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+   "pygments_lexer": "ipython3",
+   "version": "3.7.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/challenge1/analysis/shino/Challenge1.html b/challenge1/analysis/shino/Challenge1.html
new file mode 100644
index 000000000..f46ab9562
--- /dev/null
+++ b/challenge1/analysis/shino/Challenge1.html
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+}
+.glyphicon-queen:before {
+  content: "\e212";
+}
+.glyphicon-pawn:before {
+  content: "\e213";
+}
+.glyphicon-bishop:before {
+  content: "\e214";
+}
+.glyphicon-knight:before {
+  content: "\e215";
+}
+.glyphicon-baby-formula:before {
+  content: "\e216";
+}
+.glyphicon-tent:before {
+  content: "\26fa";
+}
+.glyphicon-blackboard:before {
+  content: "\e218";
+}
+.glyphicon-bed:before {
+  content: "\e219";
+}
+.glyphicon-apple:before {
+  content: "\f8ff";
+}
+.glyphicon-erase:before {
+  content: "\e221";
+}
+.glyphicon-hourglass:before {
+  content: "\231b";
+}
+.glyphicon-lamp:before {
+  content: "\e223";
+}
+.glyphicon-duplicate:before {
+  content: "\e224";
+}
+.glyphicon-piggy-bank:before {
+  content: "\e225";
+}
+.glyphicon-scissors:before {
+  content: "\e226";
+}
+.glyphicon-bitcoin:before {
+  content: "\e227";
+}
+.glyphicon-btc:before {
+  content: "\e227";
+}
+.glyphicon-xbt:before {
+  content: "\e227";
+}
+.glyphicon-yen:before {
+  content: "\00a5";
+}
+.glyphicon-jpy:before {
+  content: "\00a5";
+}
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+  content: "\20bd";
+}
+.glyphicon-rub:before {
+  content: "\20bd";
+}
+.glyphicon-scale:before {
+  content: "\e230";
+}
+.glyphicon-ice-lolly:before {
+  content: "\e231";
+}
+.glyphicon-ice-lolly-tasted:before {
+  content: "\e232";
+}
+.glyphicon-education:before {
+  content: "\e233";
+}
+.glyphicon-option-horizontal:before {
+  content: "\e234";
+}
+.glyphicon-option-vertical:before {
+  content: "\e235";
+}
+.glyphicon-menu-hamburger:before {
+  content: "\e236";
+}
+.glyphicon-modal-window:before {
+  content: "\e237";
+}
+.glyphicon-oil:before {
+  content: "\e238";
+}
+.glyphicon-grain:before {
+  content: "\e239";
+}
+.glyphicon-sunglasses:before {
+  content: "\e240";
+}
+.glyphicon-text-size:before {
+  content: "\e241";
+}
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+  content: "\e242";
+}
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+  content: "\e243";
+}
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+  content: "\e244";
+}
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+  content: "\e245";
+}
+.glyphicon-object-align-horizontal:before {
+  content: "\e246";
+}
+.glyphicon-object-align-left:before {
+  content: "\e247";
+}
+.glyphicon-object-align-vertical:before {
+  content: "\e248";
+}
+.glyphicon-object-align-right:before {
+  content: "\e249";
+}
+.glyphicon-triangle-right:before {
+  content: "\e250";
+}
+.glyphicon-triangle-left:before {
+  content: "\e251";
+}
+.glyphicon-triangle-bottom:before {
+  content: "\e252";
+}
+.glyphicon-triangle-top:before {
+  content: "\e253";
+}
+.glyphicon-console:before {
+  content: "\e254";
+}
+.glyphicon-superscript:before {
+  content: "\e255";
+}
+.glyphicon-subscript:before {
+  content: "\e256";
+}
+.glyphicon-menu-left:before {
+  content: "\e257";
+}
+.glyphicon-menu-right:before {
+  content: "\e258";
+}
+.glyphicon-menu-down:before {
+  content: "\e259";
+}
+.glyphicon-menu-up:before {
+  content: "\e260";
+}
+* {
+  -webkit-box-sizing: border-box;
+  -moz-box-sizing: border-box;
+  box-sizing: border-box;
+}
+*:before,
+*:after {
+  -webkit-box-sizing: border-box;
+  -moz-box-sizing: border-box;
+  box-sizing: border-box;
+}
+html {
+  font-size: 10px;
+  -webkit-tap-highlight-color: rgba(0, 0, 0, 0);
+}
+body {
+  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
+  font-size: 13px;
+  line-height: 1.42857143;
+  color: #000;
+  background-color: #fff;
+}
+input,
+button,
+select,
+textarea {
+  font-family: inherit;
+  font-size: inherit;
+  line-height: inherit;
+}
+a {
+  color: #337ab7;
+  text-decoration: none;
+}
+a:hover,
+a:focus {
+  color: #23527c;
+  text-decoration: underline;
+}
+a:focus {
+  outline: 5px auto -webkit-focus-ring-color;
+  outline-offset: -2px;
+}
+figure {
+  margin: 0;
+}
+img {
+  vertical-align: middle;
+}
+.img-responsive,
+.thumbnail > img,
+.thumbnail a > img,
+.carousel-inner > .item > img,
+.carousel-inner > .item > a > img {
+  display: block;
+  max-width: 100%;
+  height: auto;
+}
+.img-rounded {
+  border-radius: 3px;
+}
+.img-thumbnail {
+  padding: 4px;
+  line-height: 1.42857143;
+  background-color: #fff;
+  border: 1px solid #ddd;
+  border-radius: 2px;
+  -webkit-transition: all 0.2s ease-in-out;
+  -o-transition: all 0.2s ease-in-out;
+  transition: all 0.2s ease-in-out;
+  display: inline-block;
+  max-width: 100%;
+  height: auto;
+}
+.img-circle {
+  border-radius: 50%;
+}
+hr {
+  margin-top: 18px;
+  margin-bottom: 18px;
+  border: 0;
+  border-top: 1px solid #eeeeee;
+}
+.sr-only {
+  position: absolute;
+  width: 1px;
+  height: 1px;
+  margin: -1px;
+  padding: 0;
+  overflow: hidden;
+  clip: rect(0, 0, 0, 0);
+  border: 0;
+}
+.sr-only-focusable:active,
+.sr-only-focusable:focus {
+  position: static;
+  width: auto;
+  height: auto;
+  margin: 0;
+  overflow: visible;
+  clip: auto;
+}
+[role="button"] {
+  cursor: pointer;
+}
+h1,
+h2,
+h3,
+h4,
+h5,
+h6,
+.h1,
+.h2,
+.h3,
+.h4,
+.h5,
+.h6 {
+  font-family: inherit;
+  font-weight: 500;
+  line-height: 1.1;
+  color: inherit;
+}
+h1 small,
+h2 small,
+h3 small,
+h4 small,
+h5 small,
+h6 small,
+.h1 small,
+.h2 small,
+.h3 small,
+.h4 small,
+.h5 small,
+.h6 small,
+h1 .small,
+h2 .small,
+h3 .small,
+h4 .small,
+h5 .small,
+h6 .small,
+.h1 .small,
+.h2 .small,
+.h3 .small,
+.h4 .small,
+.h5 .small,
+.h6 .small {
+  font-weight: normal;
+  line-height: 1;
+  color: #777777;
+}
+h1,
+.h1,
+h2,
+.h2,
+h3,
+.h3 {
+  margin-top: 18px;
+  margin-bottom: 9px;
+}
+h1 small,
+.h1 small,
+h2 small,
+.h2 small,
+h3 small,
+.h3 small,
+h1 .small,
+.h1 .small,
+h2 .small,
+.h2 .small,
+h3 .small,
+.h3 .small {
+  font-size: 65%;
+}
+h4,
+.h4,
+h5,
+.h5,
+h6,
+.h6 {
+  margin-top: 9px;
+  margin-bottom: 9px;
+}
+h4 small,
+.h4 small,
+h5 small,
+.h5 small,
+h6 small,
+.h6 small,
+h4 .small,
+.h4 .small,
+h5 .small,
+.h5 .small,
+h6 .small,
+.h6 .small {
+  font-size: 75%;
+}
+h1,
+.h1 {
+  font-size: 33px;
+}
+h2,
+.h2 {
+  font-size: 27px;
+}
+h3,
+.h3 {
+  font-size: 23px;
+}
+h4,
+.h4 {
+  font-size: 17px;
+}
+h5,
+.h5 {
+  font-size: 13px;
+}
+h6,
+.h6 {
+  font-size: 12px;
+}
+p {
+  margin: 0 0 9px;
+}
+.lead {
+  margin-bottom: 18px;
+  font-size: 14px;
+  font-weight: 300;
+  line-height: 1.4;
+}
+@media (min-width: 768px) {
+  .lead {
+    font-size: 19.5px;
+  }
+}
+small,
+.small {
+  font-size: 92%;
+}
+mark,
+.mark {
+  background-color: #fcf8e3;
+  padding: .2em;
+}
+.text-left {
+  text-align: left;
+}
+.text-right {
+  text-align: right;
+}
+.text-center {
+  text-align: center;
+}
+.text-justify {
+  text-align: justify;
+}
+.text-nowrap {
+  white-space: nowrap;
+}
+.text-lowercase {
+  text-transform: lowercase;
+}
+.text-uppercase {
+  text-transform: uppercase;
+}
+.text-capitalize {
+  text-transform: capitalize;
+}
+.text-muted {
+  color: #777777;
+}
+.text-primary {
+  color: #337ab7;
+}
+a.text-primary:hover,
+a.text-primary:focus {
+  color: #286090;
+}
+.text-success {
+  color: #3c763d;
+}
+a.text-success:hover,
+a.text-success:focus {
+  color: #2b542c;
+}
+.text-info {
+  color: #31708f;
+}
+a.text-info:hover,
+a.text-info:focus {
+  color: #245269;
+}
+.text-warning {
+  color: #8a6d3b;
+}
+a.text-warning:hover,
+a.text-warning:focus {
+  color: #66512c;
+}
+.text-danger {
+  color: #a94442;
+}
+a.text-danger:hover,
+a.text-danger:focus {
+  color: #843534;
+}
+.bg-primary {
+  color: #fff;
+  background-color: #337ab7;
+}
+a.bg-primary:hover,
+a.bg-primary:focus {
+  background-color: #286090;
+}
+.bg-success {
+  background-color: #dff0d8;
+}
+a.bg-success:hover,
+a.bg-success:focus {
+  background-color: #c1e2b3;
+}
+.bg-info {
+  background-color: #d9edf7;
+}
+a.bg-info:hover,
+a.bg-info:focus {
+  background-color: #afd9ee;
+}
+.bg-warning {
+  background-color: #fcf8e3;
+}
+a.bg-warning:hover,
+a.bg-warning:focus {
+  background-color: #f7ecb5;
+}
+.bg-danger {
+  background-color: #f2dede;
+}
+a.bg-danger:hover,
+a.bg-danger:focus {
+  background-color: #e4b9b9;
+}
+.page-header {
+  padding-bottom: 8px;
+  margin: 36px 0 18px;
+  border-bottom: 1px solid #eeeeee;
+}
+ul,
+ol {
+  margin-top: 0;
+  margin-bottom: 9px;
+}
+ul ul,
+ol ul,
+ul ol,
+ol ol {
+  margin-bottom: 0;
+}
+.list-unstyled {
+  padding-left: 0;
+  list-style: none;
+}
+.list-inline {
+  padding-left: 0;
+  list-style: none;
+  margin-left: -5px;
+}
+.list-inline > li {
+  display: inline-block;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+dl {
+  margin-top: 0;
+  margin-bottom: 18px;
+}
+dt,
+dd {
+  line-height: 1.42857143;
+}
+dt {
+  font-weight: bold;
+}
+dd {
+  margin-left: 0;
+}
+@media (min-width: 541px) {
+  .dl-horizontal dt {
+    float: left;
+    width: 160px;
+    clear: left;
+    text-align: right;
+    overflow: hidden;
+    text-overflow: ellipsis;
+    white-space: nowrap;
+  }
+  .dl-horizontal dd {
+    margin-left: 180px;
+  }
+}
+abbr[title],
+abbr[data-original-title] {
+  cursor: help;
+  border-bottom: 1px dotted #777777;
+}
+.initialism {
+  font-size: 90%;
+  text-transform: uppercase;
+}
+blockquote {
+  padding: 9px 18px;
+  margin: 0 0 18px;
+  font-size: inherit;
+  border-left: 5px solid #eeeeee;
+}
+blockquote p:last-child,
+blockquote ul:last-child,
+blockquote ol:last-child {
+  margin-bottom: 0;
+}
+blockquote footer,
+blockquote small,
+blockquote .small {
+  display: block;
+  font-size: 80%;
+  line-height: 1.42857143;
+  color: #777777;
+}
+blockquote footer:before,
+blockquote small:before,
+blockquote .small:before {
+  content: '\2014 \00A0';
+}
+.blockquote-reverse,
+blockquote.pull-right {
+  padding-right: 15px;
+  padding-left: 0;
+  border-right: 5px solid #eeeeee;
+  border-left: 0;
+  text-align: right;
+}
+.blockquote-reverse footer:before,
+blockquote.pull-right footer:before,
+.blockquote-reverse small:before,
+blockquote.pull-right small:before,
+.blockquote-reverse .small:before,
+blockquote.pull-right .small:before {
+  content: '';
+}
+.blockquote-reverse footer:after,
+blockquote.pull-right footer:after,
+.blockquote-reverse small:after,
+blockquote.pull-right small:after,
+.blockquote-reverse .small:after,
+blockquote.pull-right .small:after {
+  content: '\00A0 \2014';
+}
+address {
+  margin-bottom: 18px;
+  font-style: normal;
+  line-height: 1.42857143;
+}
+code,
+kbd,
+pre,
+samp {
+  font-family: monospace;
+}
+code {
+  padding: 2px 4px;
+  font-size: 90%;
+  color: #c7254e;
+  background-color: #f9f2f4;
+  border-radius: 2px;
+}
+kbd {
+  padding: 2px 4px;
+  font-size: 90%;
+  color: #888;
+  background-color: transparent;
+  border-radius: 1px;
+  box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.25);
+}
+kbd kbd {
+  padding: 0;
+  font-size: 100%;
+  font-weight: bold;
+  box-shadow: none;
+}
+pre {
+  display: block;
+  padding: 8.5px;
+  margin: 0 0 9px;
+  font-size: 12px;
+  line-height: 1.42857143;
+  word-break: break-all;
+  word-wrap: break-word;
+  color: #333333;
+  background-color: #f5f5f5;
+  border: 1px solid #ccc;
+  border-radius: 2px;
+}
+pre code {
+  padding: 0;
+  font-size: inherit;
+  color: inherit;
+  white-space: pre-wrap;
+  background-color: transparent;
+  border-radius: 0;
+}
+.pre-scrollable {
+  max-height: 340px;
+  overflow-y: scroll;
+}
+.container {
+  margin-right: auto;
+  margin-left: auto;
+  padding-left: 0px;
+  padding-right: 0px;
+}
+@media (min-width: 768px) {
+  .container {
+    width: 768px;
+  }
+}
+@media (min-width: 992px) {
+  .container {
+    width: 940px;
+  }
+}
+@media (min-width: 1200px) {
+  .container {
+    width: 1140px;
+  }
+}
+.container-fluid {
+  margin-right: auto;
+  margin-left: auto;
+  padding-left: 0px;
+  padding-right: 0px;
+}
+.row {
+  margin-left: 0px;
+  margin-right: 0px;
+}
+.col-xs-1, .col-sm-1, .col-md-1, .col-lg-1, .col-xs-2, .col-sm-2, .col-md-2, .col-lg-2, .col-xs-3, .col-sm-3, .col-md-3, .col-lg-3, .col-xs-4, .col-sm-4, .col-md-4, .col-lg-4, .col-xs-5, .col-sm-5, .col-md-5, .col-lg-5, .col-xs-6, .col-sm-6, .col-md-6, .col-lg-6, .col-xs-7, .col-sm-7, .col-md-7, .col-lg-7, .col-xs-8, .col-sm-8, .col-md-8, .col-lg-8, .col-xs-9, .col-sm-9, .col-md-9, .col-lg-9, .col-xs-10, .col-sm-10, .col-md-10, .col-lg-10, .col-xs-11, .col-sm-11, .col-md-11, .col-lg-11, .col-xs-12, .col-sm-12, .col-md-12, .col-lg-12 {
+  position: relative;
+  min-height: 1px;
+  padding-left: 0px;
+  padding-right: 0px;
+}
+.col-xs-1, .col-xs-2, .col-xs-3, .col-xs-4, .col-xs-5, .col-xs-6, .col-xs-7, .col-xs-8, .col-xs-9, .col-xs-10, .col-xs-11, .col-xs-12 {
+  float: left;
+}
+.col-xs-12 {
+  width: 100%;
+}
+.col-xs-11 {
+  width: 91.66666667%;
+}
+.col-xs-10 {
+  width: 83.33333333%;
+}
+.col-xs-9 {
+  width: 75%;
+}
+.col-xs-8 {
+  width: 66.66666667%;
+}
+.col-xs-7 {
+  width: 58.33333333%;
+}
+.col-xs-6 {
+  width: 50%;
+}
+.col-xs-5 {
+  width: 41.66666667%;
+}
+.col-xs-4 {
+  width: 33.33333333%;
+}
+.col-xs-3 {
+  width: 25%;
+}
+.col-xs-2 {
+  width: 16.66666667%;
+}
+.col-xs-1 {
+  width: 8.33333333%;
+}
+.col-xs-pull-12 {
+  right: 100%;
+}
+.col-xs-pull-11 {
+  right: 91.66666667%;
+}
+.col-xs-pull-10 {
+  right: 83.33333333%;
+}
+.col-xs-pull-9 {
+  right: 75%;
+}
+.col-xs-pull-8 {
+  right: 66.66666667%;
+}
+.col-xs-pull-7 {
+  right: 58.33333333%;
+}
+.col-xs-pull-6 {
+  right: 50%;
+}
+.col-xs-pull-5 {
+  right: 41.66666667%;
+}
+.col-xs-pull-4 {
+  right: 33.33333333%;
+}
+.col-xs-pull-3 {
+  right: 25%;
+}
+.col-xs-pull-2 {
+  right: 16.66666667%;
+}
+.col-xs-pull-1 {
+  right: 8.33333333%;
+}
+.col-xs-pull-0 {
+  right: auto;
+}
+.col-xs-push-12 {
+  left: 100%;
+}
+.col-xs-push-11 {
+  left: 91.66666667%;
+}
+.col-xs-push-10 {
+  left: 83.33333333%;
+}
+.col-xs-push-9 {
+  left: 75%;
+}
+.col-xs-push-8 {
+  left: 66.66666667%;
+}
+.col-xs-push-7 {
+  left: 58.33333333%;
+}
+.col-xs-push-6 {
+  left: 50%;
+}
+.col-xs-push-5 {
+  left: 41.66666667%;
+}
+.col-xs-push-4 {
+  left: 33.33333333%;
+}
+.col-xs-push-3 {
+  left: 25%;
+}
+.col-xs-push-2 {
+  left: 16.66666667%;
+}
+.col-xs-push-1 {
+  left: 8.33333333%;
+}
+.col-xs-push-0 {
+  left: auto;
+}
+.col-xs-offset-12 {
+  margin-left: 100%;
+}
+.col-xs-offset-11 {
+  margin-left: 91.66666667%;
+}
+.col-xs-offset-10 {
+  margin-left: 83.33333333%;
+}
+.col-xs-offset-9 {
+  margin-left: 75%;
+}
+.col-xs-offset-8 {
+  margin-left: 66.66666667%;
+}
+.col-xs-offset-7 {
+  margin-left: 58.33333333%;
+}
+.col-xs-offset-6 {
+  margin-left: 50%;
+}
+.col-xs-offset-5 {
+  margin-left: 41.66666667%;
+}
+.col-xs-offset-4 {
+  margin-left: 33.33333333%;
+}
+.col-xs-offset-3 {
+  margin-left: 25%;
+}
+.col-xs-offset-2 {
+  margin-left: 16.66666667%;
+}
+.col-xs-offset-1 {
+  margin-left: 8.33333333%;
+}
+.col-xs-offset-0 {
+  margin-left: 0%;
+}
+@media (min-width: 768px) {
+  .col-sm-1, .col-sm-2, .col-sm-3, .col-sm-4, .col-sm-5, .col-sm-6, .col-sm-7, .col-sm-8, .col-sm-9, .col-sm-10, .col-sm-11, .col-sm-12 {
+    float: left;
+  }
+  .col-sm-12 {
+    width: 100%;
+  }
+  .col-sm-11 {
+    width: 91.66666667%;
+  }
+  .col-sm-10 {
+    width: 83.33333333%;
+  }
+  .col-sm-9 {
+    width: 75%;
+  }
+  .col-sm-8 {
+    width: 66.66666667%;
+  }
+  .col-sm-7 {
+    width: 58.33333333%;
+  }
+  .col-sm-6 {
+    width: 50%;
+  }
+  .col-sm-5 {
+    width: 41.66666667%;
+  }
+  .col-sm-4 {
+    width: 33.33333333%;
+  }
+  .col-sm-3 {
+    width: 25%;
+  }
+  .col-sm-2 {
+    width: 16.66666667%;
+  }
+  .col-sm-1 {
+    width: 8.33333333%;
+  }
+  .col-sm-pull-12 {
+    right: 100%;
+  }
+  .col-sm-pull-11 {
+    right: 91.66666667%;
+  }
+  .col-sm-pull-10 {
+    right: 83.33333333%;
+  }
+  .col-sm-pull-9 {
+    right: 75%;
+  }
+  .col-sm-pull-8 {
+    right: 66.66666667%;
+  }
+  .col-sm-pull-7 {
+    right: 58.33333333%;
+  }
+  .col-sm-pull-6 {
+    right: 50%;
+  }
+  .col-sm-pull-5 {
+    right: 41.66666667%;
+  }
+  .col-sm-pull-4 {
+    right: 33.33333333%;
+  }
+  .col-sm-pull-3 {
+    right: 25%;
+  }
+  .col-sm-pull-2 {
+    right: 16.66666667%;
+  }
+  .col-sm-pull-1 {
+    right: 8.33333333%;
+  }
+  .col-sm-pull-0 {
+    right: auto;
+  }
+  .col-sm-push-12 {
+    left: 100%;
+  }
+  .col-sm-push-11 {
+    left: 91.66666667%;
+  }
+  .col-sm-push-10 {
+    left: 83.33333333%;
+  }
+  .col-sm-push-9 {
+    left: 75%;
+  }
+  .col-sm-push-8 {
+    left: 66.66666667%;
+  }
+  .col-sm-push-7 {
+    left: 58.33333333%;
+  }
+  .col-sm-push-6 {
+    left: 50%;
+  }
+  .col-sm-push-5 {
+    left: 41.66666667%;
+  }
+  .col-sm-push-4 {
+    left: 33.33333333%;
+  }
+  .col-sm-push-3 {
+    left: 25%;
+  }
+  .col-sm-push-2 {
+    left: 16.66666667%;
+  }
+  .col-sm-push-1 {
+    left: 8.33333333%;
+  }
+  .col-sm-push-0 {
+    left: auto;
+  }
+  .col-sm-offset-12 {
+    margin-left: 100%;
+  }
+  .col-sm-offset-11 {
+    margin-left: 91.66666667%;
+  }
+  .col-sm-offset-10 {
+    margin-left: 83.33333333%;
+  }
+  .col-sm-offset-9 {
+    margin-left: 75%;
+  }
+  .col-sm-offset-8 {
+    margin-left: 66.66666667%;
+  }
+  .col-sm-offset-7 {
+    margin-left: 58.33333333%;
+  }
+  .col-sm-offset-6 {
+    margin-left: 50%;
+  }
+  .col-sm-offset-5 {
+    margin-left: 41.66666667%;
+  }
+  .col-sm-offset-4 {
+    margin-left: 33.33333333%;
+  }
+  .col-sm-offset-3 {
+    margin-left: 25%;
+  }
+  .col-sm-offset-2 {
+    margin-left: 16.66666667%;
+  }
+  .col-sm-offset-1 {
+    margin-left: 8.33333333%;
+  }
+  .col-sm-offset-0 {
+    margin-left: 0%;
+  }
+}
+@media (min-width: 992px) {
+  .col-md-1, .col-md-2, .col-md-3, .col-md-4, .col-md-5, .col-md-6, .col-md-7, .col-md-8, .col-md-9, .col-md-10, .col-md-11, .col-md-12 {
+    float: left;
+  }
+  .col-md-12 {
+    width: 100%;
+  }
+  .col-md-11 {
+    width: 91.66666667%;
+  }
+  .col-md-10 {
+    width: 83.33333333%;
+  }
+  .col-md-9 {
+    width: 75%;
+  }
+  .col-md-8 {
+    width: 66.66666667%;
+  }
+  .col-md-7 {
+    width: 58.33333333%;
+  }
+  .col-md-6 {
+    width: 50%;
+  }
+  .col-md-5 {
+    width: 41.66666667%;
+  }
+  .col-md-4 {
+    width: 33.33333333%;
+  }
+  .col-md-3 {
+    width: 25%;
+  }
+  .col-md-2 {
+    width: 16.66666667%;
+  }
+  .col-md-1 {
+    width: 8.33333333%;
+  }
+  .col-md-pull-12 {
+    right: 100%;
+  }
+  .col-md-pull-11 {
+    right: 91.66666667%;
+  }
+  .col-md-pull-10 {
+    right: 83.33333333%;
+  }
+  .col-md-pull-9 {
+    right: 75%;
+  }
+  .col-md-pull-8 {
+    right: 66.66666667%;
+  }
+  .col-md-pull-7 {
+    right: 58.33333333%;
+  }
+  .col-md-pull-6 {
+    right: 50%;
+  }
+  .col-md-pull-5 {
+    right: 41.66666667%;
+  }
+  .col-md-pull-4 {
+    right: 33.33333333%;
+  }
+  .col-md-pull-3 {
+    right: 25%;
+  }
+  .col-md-pull-2 {
+    right: 16.66666667%;
+  }
+  .col-md-pull-1 {
+    right: 8.33333333%;
+  }
+  .col-md-pull-0 {
+    right: auto;
+  }
+  .col-md-push-12 {
+    left: 100%;
+  }
+  .col-md-push-11 {
+    left: 91.66666667%;
+  }
+  .col-md-push-10 {
+    left: 83.33333333%;
+  }
+  .col-md-push-9 {
+    left: 75%;
+  }
+  .col-md-push-8 {
+    left: 66.66666667%;
+  }
+  .col-md-push-7 {
+    left: 58.33333333%;
+  }
+  .col-md-push-6 {
+    left: 50%;
+  }
+  .col-md-push-5 {
+    left: 41.66666667%;
+  }
+  .col-md-push-4 {
+    left: 33.33333333%;
+  }
+  .col-md-push-3 {
+    left: 25%;
+  }
+  .col-md-push-2 {
+    left: 16.66666667%;
+  }
+  .col-md-push-1 {
+    left: 8.33333333%;
+  }
+  .col-md-push-0 {
+    left: auto;
+  }
+  .col-md-offset-12 {
+    margin-left: 100%;
+  }
+  .col-md-offset-11 {
+    margin-left: 91.66666667%;
+  }
+  .col-md-offset-10 {
+    margin-left: 83.33333333%;
+  }
+  .col-md-offset-9 {
+    margin-left: 75%;
+  }
+  .col-md-offset-8 {
+    margin-left: 66.66666667%;
+  }
+  .col-md-offset-7 {
+    margin-left: 58.33333333%;
+  }
+  .col-md-offset-6 {
+    margin-left: 50%;
+  }
+  .col-md-offset-5 {
+    margin-left: 41.66666667%;
+  }
+  .col-md-offset-4 {
+    margin-left: 33.33333333%;
+  }
+  .col-md-offset-3 {
+    margin-left: 25%;
+  }
+  .col-md-offset-2 {
+    margin-left: 16.66666667%;
+  }
+  .col-md-offset-1 {
+    margin-left: 8.33333333%;
+  }
+  .col-md-offset-0 {
+    margin-left: 0%;
+  }
+}
+@media (min-width: 1200px) {
+  .col-lg-1, .col-lg-2, .col-lg-3, .col-lg-4, .col-lg-5, .col-lg-6, .col-lg-7, .col-lg-8, .col-lg-9, .col-lg-10, .col-lg-11, .col-lg-12 {
+    float: left;
+  }
+  .col-lg-12 {
+    width: 100%;
+  }
+  .col-lg-11 {
+    width: 91.66666667%;
+  }
+  .col-lg-10 {
+    width: 83.33333333%;
+  }
+  .col-lg-9 {
+    width: 75%;
+  }
+  .col-lg-8 {
+    width: 66.66666667%;
+  }
+  .col-lg-7 {
+    width: 58.33333333%;
+  }
+  .col-lg-6 {
+    width: 50%;
+  }
+  .col-lg-5 {
+    width: 41.66666667%;
+  }
+  .col-lg-4 {
+    width: 33.33333333%;
+  }
+  .col-lg-3 {
+    width: 25%;
+  }
+  .col-lg-2 {
+    width: 16.66666667%;
+  }
+  .col-lg-1 {
+    width: 8.33333333%;
+  }
+  .col-lg-pull-12 {
+    right: 100%;
+  }
+  .col-lg-pull-11 {
+    right: 91.66666667%;
+  }
+  .col-lg-pull-10 {
+    right: 83.33333333%;
+  }
+  .col-lg-pull-9 {
+    right: 75%;
+  }
+  .col-lg-pull-8 {
+    right: 66.66666667%;
+  }
+  .col-lg-pull-7 {
+    right: 58.33333333%;
+  }
+  .col-lg-pull-6 {
+    right: 50%;
+  }
+  .col-lg-pull-5 {
+    right: 41.66666667%;
+  }
+  .col-lg-pull-4 {
+    right: 33.33333333%;
+  }
+  .col-lg-pull-3 {
+    right: 25%;
+  }
+  .col-lg-pull-2 {
+    right: 16.66666667%;
+  }
+  .col-lg-pull-1 {
+    right: 8.33333333%;
+  }
+  .col-lg-pull-0 {
+    right: auto;
+  }
+  .col-lg-push-12 {
+    left: 100%;
+  }
+  .col-lg-push-11 {
+    left: 91.66666667%;
+  }
+  .col-lg-push-10 {
+    left: 83.33333333%;
+  }
+  .col-lg-push-9 {
+    left: 75%;
+  }
+  .col-lg-push-8 {
+    left: 66.66666667%;
+  }
+  .col-lg-push-7 {
+    left: 58.33333333%;
+  }
+  .col-lg-push-6 {
+    left: 50%;
+  }
+  .col-lg-push-5 {
+    left: 41.66666667%;
+  }
+  .col-lg-push-4 {
+    left: 33.33333333%;
+  }
+  .col-lg-push-3 {
+    left: 25%;
+  }
+  .col-lg-push-2 {
+    left: 16.66666667%;
+  }
+  .col-lg-push-1 {
+    left: 8.33333333%;
+  }
+  .col-lg-push-0 {
+    left: auto;
+  }
+  .col-lg-offset-12 {
+    margin-left: 100%;
+  }
+  .col-lg-offset-11 {
+    margin-left: 91.66666667%;
+  }
+  .col-lg-offset-10 {
+    margin-left: 83.33333333%;
+  }
+  .col-lg-offset-9 {
+    margin-left: 75%;
+  }
+  .col-lg-offset-8 {
+    margin-left: 66.66666667%;
+  }
+  .col-lg-offset-7 {
+    margin-left: 58.33333333%;
+  }
+  .col-lg-offset-6 {
+    margin-left: 50%;
+  }
+  .col-lg-offset-5 {
+    margin-left: 41.66666667%;
+  }
+  .col-lg-offset-4 {
+    margin-left: 33.33333333%;
+  }
+  .col-lg-offset-3 {
+    margin-left: 25%;
+  }
+  .col-lg-offset-2 {
+    margin-left: 16.66666667%;
+  }
+  .col-lg-offset-1 {
+    margin-left: 8.33333333%;
+  }
+  .col-lg-offset-0 {
+    margin-left: 0%;
+  }
+}
+table {
+  background-color: transparent;
+}
+caption {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  color: #777777;
+  text-align: left;
+}
+th {
+  text-align: left;
+}
+.table {
+  width: 100%;
+  max-width: 100%;
+  margin-bottom: 18px;
+}
+.table > thead > tr > th,
+.table > tbody > tr > th,
+.table > tfoot > tr > th,
+.table > thead > tr > td,
+.table > tbody > tr > td,
+.table > tfoot > tr > td {
+  padding: 8px;
+  line-height: 1.42857143;
+  vertical-align: top;
+  border-top: 1px solid #ddd;
+}
+.table > thead > tr > th {
+  vertical-align: bottom;
+  border-bottom: 2px solid #ddd;
+}
+.table > caption + thead > tr:first-child > th,
+.table > colgroup + thead > tr:first-child > th,
+.table > thead:first-child > tr:first-child > th,
+.table > caption + thead > tr:first-child > td,
+.table > colgroup + thead > tr:first-child > td,
+.table > thead:first-child > tr:first-child > td {
+  border-top: 0;
+}
+.table > tbody + tbody {
+  border-top: 2px solid #ddd;
+}
+.table .table {
+  background-color: #fff;
+}
+.table-condensed > thead > tr > th,
+.table-condensed > tbody > tr > th,
+.table-condensed > tfoot > tr > th,
+.table-condensed > thead > tr > td,
+.table-condensed > tbody > tr > td,
+.table-condensed > tfoot > tr > td {
+  padding: 5px;
+}
+.table-bordered {
+  border: 1px solid #ddd;
+}
+.table-bordered > thead > tr > th,
+.table-bordered > tbody > tr > th,
+.table-bordered > tfoot > tr > th,
+.table-bordered > thead > tr > td,
+.table-bordered > tbody > tr > td,
+.table-bordered > tfoot > tr > td {
+  border: 1px solid #ddd;
+}
+.table-bordered > thead > tr > th,
+.table-bordered > thead > tr > td {
+  border-bottom-width: 2px;
+}
+.table-striped > tbody > tr:nth-of-type(odd) {
+  background-color: #f9f9f9;
+}
+.table-hover > tbody > tr:hover {
+  background-color: #f5f5f5;
+}
+table col[class*="col-"] {
+  position: static;
+  float: none;
+  display: table-column;
+}
+table td[class*="col-"],
+table th[class*="col-"] {
+  position: static;
+  float: none;
+  display: table-cell;
+}
+.table > thead > tr > td.active,
+.table > tbody > tr > td.active,
+.table > tfoot > tr > td.active,
+.table > thead > tr > th.active,
+.table > tbody > tr > th.active,
+.table > tfoot > tr > th.active,
+.table > thead > tr.active > td,
+.table > tbody > tr.active > td,
+.table > tfoot > tr.active > td,
+.table > thead > tr.active > th,
+.table > tbody > tr.active > th,
+.table > tfoot > tr.active > th {
+  background-color: #f5f5f5;
+}
+.table-hover > tbody > tr > td.active:hover,
+.table-hover > tbody > tr > th.active:hover,
+.table-hover > tbody > tr.active:hover > td,
+.table-hover > tbody > tr:hover > .active,
+.table-hover > tbody > tr.active:hover > th {
+  background-color: #e8e8e8;
+}
+.table > thead > tr > td.success,
+.table > tbody > tr > td.success,
+.table > tfoot > tr > td.success,
+.table > thead > tr > th.success,
+.table > tbody > tr > th.success,
+.table > tfoot > tr > th.success,
+.table > thead > tr.success > td,
+.table > tbody > tr.success > td,
+.table > tfoot > tr.success > td,
+.table > thead > tr.success > th,
+.table > tbody > tr.success > th,
+.table > tfoot > tr.success > th {
+  background-color: #dff0d8;
+}
+.table-hover > tbody > tr > td.success:hover,
+.table-hover > tbody > tr > th.success:hover,
+.table-hover > tbody > tr.success:hover > td,
+.table-hover > tbody > tr:hover > .success,
+.table-hover > tbody > tr.success:hover > th {
+  background-color: #d0e9c6;
+}
+.table > thead > tr > td.info,
+.table > tbody > tr > td.info,
+.table > tfoot > tr > td.info,
+.table > thead > tr > th.info,
+.table > tbody > tr > th.info,
+.table > tfoot > tr > th.info,
+.table > thead > tr.info > td,
+.table > tbody > tr.info > td,
+.table > tfoot > tr.info > td,
+.table > thead > tr.info > th,
+.table > tbody > tr.info > th,
+.table > tfoot > tr.info > th {
+  background-color: #d9edf7;
+}
+.table-hover > tbody > tr > td.info:hover,
+.table-hover > tbody > tr > th.info:hover,
+.table-hover > tbody > tr.info:hover > td,
+.table-hover > tbody > tr:hover > .info,
+.table-hover > tbody > tr.info:hover > th {
+  background-color: #c4e3f3;
+}
+.table > thead > tr > td.warning,
+.table > tbody > tr > td.warning,
+.table > tfoot > tr > td.warning,
+.table > thead > tr > th.warning,
+.table > tbody > tr > th.warning,
+.table > tfoot > tr > th.warning,
+.table > thead > tr.warning > td,
+.table > tbody > tr.warning > td,
+.table > tfoot > tr.warning > td,
+.table > thead > tr.warning > th,
+.table > tbody > tr.warning > th,
+.table > tfoot > tr.warning > th {
+  background-color: #fcf8e3;
+}
+.table-hover > tbody > tr > td.warning:hover,
+.table-hover > tbody > tr > th.warning:hover,
+.table-hover > tbody > tr.warning:hover > td,
+.table-hover > tbody > tr:hover > .warning,
+.table-hover > tbody > tr.warning:hover > th {
+  background-color: #faf2cc;
+}
+.table > thead > tr > td.danger,
+.table > tbody > tr > td.danger,
+.table > tfoot > tr > td.danger,
+.table > thead > tr > th.danger,
+.table > tbody > tr > th.danger,
+.table > tfoot > tr > th.danger,
+.table > thead > tr.danger > td,
+.table > tbody > tr.danger > td,
+.table > tfoot > tr.danger > td,
+.table > thead > tr.danger > th,
+.table > tbody > tr.danger > th,
+.table > tfoot > tr.danger > th {
+  background-color: #f2dede;
+}
+.table-hover > tbody > tr > td.danger:hover,
+.table-hover > tbody > tr > th.danger:hover,
+.table-hover > tbody > tr.danger:hover > td,
+.table-hover > tbody > tr:hover > .danger,
+.table-hover > tbody > tr.danger:hover > th {
+  background-color: #ebcccc;
+}
+.table-responsive {
+  overflow-x: auto;
+  min-height: 0.01%;
+}
+@media screen and (max-width: 767px) {
+  .table-responsive {
+    width: 100%;
+    margin-bottom: 13.5px;
+    overflow-y: hidden;
+    -ms-overflow-style: -ms-autohiding-scrollbar;
+    border: 1px solid #ddd;
+  }
+  .table-responsive > .table {
+    margin-bottom: 0;
+  }
+  .table-responsive > .table > thead > tr > th,
+  .table-responsive > .table > tbody > tr > th,
+  .table-responsive > .table > tfoot > tr > th,
+  .table-responsive > .table > thead > tr > td,
+  .table-responsive > .table > tbody > tr > td,
+  .table-responsive > .table > tfoot > tr > td {
+    white-space: nowrap;
+  }
+  .table-responsive > .table-bordered {
+    border: 0;
+  }
+  .table-responsive > .table-bordered > thead > tr > th:first-child,
+  .table-responsive > .table-bordered > tbody > tr > th:first-child,
+  .table-responsive > .table-bordered > tfoot > tr > th:first-child,
+  .table-responsive > .table-bordered > thead > tr > td:first-child,
+  .table-responsive > .table-bordered > tbody > tr > td:first-child,
+  .table-responsive > .table-bordered > tfoot > tr > td:first-child {
+    border-left: 0;
+  }
+  .table-responsive > .table-bordered > thead > tr > th:last-child,
+  .table-responsive > .table-bordered > tbody > tr > th:last-child,
+  .table-responsive > .table-bordered > tfoot > tr > th:last-child,
+  .table-responsive > .table-bordered > thead > tr > td:last-child,
+  .table-responsive > .table-bordered > tbody > tr > td:last-child,
+  .table-responsive > .table-bordered > tfoot > tr > td:last-child {
+    border-right: 0;
+  }
+  .table-responsive > .table-bordered > tbody > tr:last-child > th,
+  .table-responsive > .table-bordered > tfoot > tr:last-child > th,
+  .table-responsive > .table-bordered > tbody > tr:last-child > td,
+  .table-responsive > .table-bordered > tfoot > tr:last-child > td {
+    border-bottom: 0;
+  }
+}
+fieldset {
+  padding: 0;
+  margin: 0;
+  border: 0;
+  min-width: 0;
+}
+legend {
+  display: block;
+  width: 100%;
+  padding: 0;
+  margin-bottom: 18px;
+  font-size: 19.5px;
+  line-height: inherit;
+  color: #333333;
+  border: 0;
+  border-bottom: 1px solid #e5e5e5;
+}
+label {
+  display: inline-block;
+  max-width: 100%;
+  margin-bottom: 5px;
+  font-weight: bold;
+}
+input[type="search"] {
+  -webkit-box-sizing: border-box;
+  -moz-box-sizing: border-box;
+  box-sizing: border-box;
+}
+input[type="radio"],
+input[type="checkbox"] {
+  margin: 4px 0 0;
+  margin-top: 1px \9;
+  line-height: normal;
+}
+input[type="file"] {
+  display: block;
+}
+input[type="range"] {
+  display: block;
+  width: 100%;
+}
+select[multiple],
+select[size] {
+  height: auto;
+}
+input[type="file"]:focus,
+input[type="radio"]:focus,
+input[type="checkbox"]:focus {
+  outline: 5px auto -webkit-focus-ring-color;
+  outline-offset: -2px;
+}
+output {
+  display: block;
+  padding-top: 7px;
+  font-size: 13px;
+  line-height: 1.42857143;
+  color: #555555;
+}
+.form-control {
+  display: block;
+  width: 100%;
+  height: 32px;
+  padding: 6px 12px;
+  font-size: 13px;
+  line-height: 1.42857143;
+  color: #555555;
+  background-color: #fff;
+  background-image: none;
+  border: 1px solid #ccc;
+  border-radius: 2px;
+  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
+  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
+  -webkit-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
+  -o-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
+  transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
+}
+.form-control:focus {
+  border-color: #66afe9;
+  outline: 0;
+  -webkit-box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
+  box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
+}
+.form-control::-moz-placeholder {
+  color: #999;
+  opacity: 1;
+}
+.form-control:-ms-input-placeholder {
+  color: #999;
+}
+.form-control::-webkit-input-placeholder {
+  color: #999;
+}
+.form-control::-ms-expand {
+  border: 0;
+  background-color: transparent;
+}
+.form-control[disabled],
+.form-control[readonly],
+fieldset[disabled] .form-control {
+  background-color: #eeeeee;
+  opacity: 1;
+}
+.form-control[disabled],
+fieldset[disabled] .form-control {
+  cursor: not-allowed;
+}
+textarea.form-control {
+  height: auto;
+}
+input[type="search"] {
+  -webkit-appearance: none;
+}
+@media screen and (-webkit-min-device-pixel-ratio: 0) {
+  input[type="date"].form-control,
+  input[type="time"].form-control,
+  input[type="datetime-local"].form-control,
+  input[type="month"].form-control {
+    line-height: 32px;
+  }
+  input[type="date"].input-sm,
+  input[type="time"].input-sm,
+  input[type="datetime-local"].input-sm,
+  input[type="month"].input-sm,
+  .input-group-sm input[type="date"],
+  .input-group-sm input[type="time"],
+  .input-group-sm input[type="datetime-local"],
+  .input-group-sm input[type="month"] {
+    line-height: 30px;
+  }
+  input[type="date"].input-lg,
+  input[type="time"].input-lg,
+  input[type="datetime-local"].input-lg,
+  input[type="month"].input-lg,
+  .input-group-lg input[type="date"],
+  .input-group-lg input[type="time"],
+  .input-group-lg input[type="datetime-local"],
+  .input-group-lg input[type="month"] {
+    line-height: 45px;
+  }
+}
+.form-group {
+  margin-bottom: 15px;
+}
+.radio,
+.checkbox {
+  position: relative;
+  display: block;
+  margin-top: 10px;
+  margin-bottom: 10px;
+}
+.radio label,
+.checkbox label {
+  min-height: 18px;
+  padding-left: 20px;
+  margin-bottom: 0;
+  font-weight: normal;
+  cursor: pointer;
+}
+.radio input[type="radio"],
+.radio-inline input[type="radio"],
+.checkbox input[type="checkbox"],
+.checkbox-inline input[type="checkbox"] {
+  position: absolute;
+  margin-left: -20px;
+  margin-top: 4px \9;
+}
+.radio + .radio,
+.checkbox + .checkbox {
+  margin-top: -5px;
+}
+.radio-inline,
+.checkbox-inline {
+  position: relative;
+  display: inline-block;
+  padding-left: 20px;
+  margin-bottom: 0;
+  vertical-align: middle;
+  font-weight: normal;
+  cursor: pointer;
+}
+.radio-inline + .radio-inline,
+.checkbox-inline + .checkbox-inline {
+  margin-top: 0;
+  margin-left: 10px;
+}
+input[type="radio"][disabled],
+input[type="checkbox"][disabled],
+input[type="radio"].disabled,
+input[type="checkbox"].disabled,
+fieldset[disabled] input[type="radio"],
+fieldset[disabled] input[type="checkbox"] {
+  cursor: not-allowed;
+}
+.radio-inline.disabled,
+.checkbox-inline.disabled,
+fieldset[disabled] .radio-inline,
+fieldset[disabled] .checkbox-inline {
+  cursor: not-allowed;
+}
+.radio.disabled label,
+.checkbox.disabled label,
+fieldset[disabled] .radio label,
+fieldset[disabled] .checkbox label {
+  cursor: not-allowed;
+}
+.form-control-static {
+  padding-top: 7px;
+  padding-bottom: 7px;
+  margin-bottom: 0;
+  min-height: 31px;
+}
+.form-control-static.input-lg,
+.form-control-static.input-sm {
+  padding-left: 0;
+  padding-right: 0;
+}
+.input-sm {
+  height: 30px;
+  padding: 5px 10px;
+  font-size: 12px;
+  line-height: 1.5;
+  border-radius: 1px;
+}
+select.input-sm {
+  height: 30px;
+  line-height: 30px;
+}
+textarea.input-sm,
+select[multiple].input-sm {
+  height: auto;
+}
+.form-group-sm .form-control {
+  height: 30px;
+  padding: 5px 10px;
+  font-size: 12px;
+  line-height: 1.5;
+  border-radius: 1px;
+}
+.form-group-sm select.form-control {
+  height: 30px;
+  line-height: 30px;
+}
+.form-group-sm textarea.form-control,
+.form-group-sm select[multiple].form-control {
+  height: auto;
+}
+.form-group-sm .form-control-static {
+  height: 30px;
+  min-height: 30px;
+  padding: 6px 10px;
+  font-size: 12px;
+  line-height: 1.5;
+}
+.input-lg {
+  height: 45px;
+  padding: 10px 16px;
+  font-size: 17px;
+  line-height: 1.3333333;
+  border-radius: 3px;
+}
+select.input-lg {
+  height: 45px;
+  line-height: 45px;
+}
+textarea.input-lg,
+select[multiple].input-lg {
+  height: auto;
+}
+.form-group-lg .form-control {
+  height: 45px;
+  padding: 10px 16px;
+  font-size: 17px;
+  line-height: 1.3333333;
+  border-radius: 3px;
+}
+.form-group-lg select.form-control {
+  height: 45px;
+  line-height: 45px;
+}
+.form-group-lg textarea.form-control,
+.form-group-lg select[multiple].form-control {
+  height: auto;
+}
+.form-group-lg .form-control-static {
+  height: 45px;
+  min-height: 35px;
+  padding: 11px 16px;
+  font-size: 17px;
+  line-height: 1.3333333;
+}
+.has-feedback {
+  position: relative;
+}
+.has-feedback .form-control {
+  padding-right: 40px;
+}
+.form-control-feedback {
+  position: absolute;
+  top: 0;
+  right: 0;
+  z-index: 2;
+  display: block;
+  width: 32px;
+  height: 32px;
+  line-height: 32px;
+  text-align: center;
+  pointer-events: none;
+}
+.input-lg + .form-control-feedback,
+.input-group-lg + .form-control-feedback,
+.form-group-lg .form-control + .form-control-feedback {
+  width: 45px;
+  height: 45px;
+  line-height: 45px;
+}
+.input-sm + .form-control-feedback,
+.input-group-sm + .form-control-feedback,
+.form-group-sm .form-control + .form-control-feedback {
+  width: 30px;
+  height: 30px;
+  line-height: 30px;
+}
+.has-success .help-block,
+.has-success .control-label,
+.has-success .radio,
+.has-success .checkbox,
+.has-success .radio-inline,
+.has-success .checkbox-inline,
+.has-success.radio label,
+.has-success.checkbox label,
+.has-success.radio-inline label,
+.has-success.checkbox-inline label {
+  color: #3c763d;
+}
+.has-success .form-control {
+  border-color: #3c763d;
+  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
+  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
+}
+.has-success .form-control:focus {
+  border-color: #2b542c;
+  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #67b168;
+  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #67b168;
+}
+.has-success .input-group-addon {
+  color: #3c763d;
+  border-color: #3c763d;
+  background-color: #dff0d8;
+}
+.has-success .form-control-feedback {
+  color: #3c763d;
+}
+.has-warning .help-block,
+.has-warning .control-label,
+.has-warning .radio,
+.has-warning .checkbox,
+.has-warning .radio-inline,
+.has-warning .checkbox-inline,
+.has-warning.radio label,
+.has-warning.checkbox label,
+.has-warning.radio-inline label,
+.has-warning.checkbox-inline label {
+  color: #8a6d3b;
+}
+.has-warning .form-control {
+  border-color: #8a6d3b;
+  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
+  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
+}
+.has-warning .form-control:focus {
+  border-color: #66512c;
+  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #c0a16b;
+  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #c0a16b;
+}
+.has-warning .input-group-addon {
+  color: #8a6d3b;
+  border-color: #8a6d3b;
+  background-color: #fcf8e3;
+}
+.has-warning .form-control-feedback {
+  color: #8a6d3b;
+}
+.has-error .help-block,
+.has-error .control-label,
+.has-error .radio,
+.has-error .checkbox,
+.has-error .radio-inline,
+.has-error .checkbox-inline,
+.has-error.radio label,
+.has-error.checkbox label,
+.has-error.radio-inline label,
+.has-error.checkbox-inline label {
+  color: #a94442;
+}
+.has-error .form-control {
+  border-color: #a94442;
+  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
+  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
+}
+.has-error .form-control:focus {
+  border-color: #843534;
+  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #ce8483;
+  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #ce8483;
+}
+.has-error .input-group-addon {
+  color: #a94442;
+  border-color: #a94442;
+  background-color: #f2dede;
+}
+.has-error .form-control-feedback {
+  color: #a94442;
+}
+.has-feedback label ~ .form-control-feedback {
+  top: 23px;
+}
+.has-feedback label.sr-only ~ .form-control-feedback {
+  top: 0;
+}
+.help-block {
+  display: block;
+  margin-top: 5px;
+  margin-bottom: 10px;
+  color: #404040;
+}
+@media (min-width: 768px) {
+  .form-inline .form-group {
+    display: inline-block;
+    margin-bottom: 0;
+    vertical-align: middle;
+  }
+  .form-inline .form-control {
+    display: inline-block;
+    width: auto;
+    vertical-align: middle;
+  }
+  .form-inline .form-control-static {
+    display: inline-block;
+  }
+  .form-inline .input-group {
+    display: inline-table;
+    vertical-align: middle;
+  }
+  .form-inline .input-group .input-group-addon,
+  .form-inline .input-group .input-group-btn,
+  .form-inline .input-group .form-control {
+    width: auto;
+  }
+  .form-inline .input-group > .form-control {
+    width: 100%;
+  }
+  .form-inline .control-label {
+    margin-bottom: 0;
+    vertical-align: middle;
+  }
+  .form-inline .radio,
+  .form-inline .checkbox {
+    display: inline-block;
+    margin-top: 0;
+    margin-bottom: 0;
+    vertical-align: middle;
+  }
+  .form-inline .radio label,
+  .form-inline .checkbox label {
+    padding-left: 0;
+  }
+  .form-inline .radio input[type="radio"],
+  .form-inline .checkbox input[type="checkbox"] {
+    position: relative;
+    margin-left: 0;
+  }
+  .form-inline .has-feedback .form-control-feedback {
+    top: 0;
+  }
+}
+.form-horizontal .radio,
+.form-horizontal .checkbox,
+.form-horizontal .radio-inline,
+.form-horizontal .checkbox-inline {
+  margin-top: 0;
+  margin-bottom: 0;
+  padding-top: 7px;
+}
+.form-horizontal .radio,
+.form-horizontal .checkbox {
+  min-height: 25px;
+}
+.form-horizontal .form-group {
+  margin-left: 0px;
+  margin-right: 0px;
+}
+@media (min-width: 768px) {
+  .form-horizontal .control-label {
+    text-align: right;
+    margin-bottom: 0;
+    padding-top: 7px;
+  }
+}
+.form-horizontal .has-feedback .form-control-feedback {
+  right: 0px;
+}
+@media (min-width: 768px) {
+  .form-horizontal .form-group-lg .control-label {
+    padding-top: 11px;
+    font-size: 17px;
+  }
+}
+@media (min-width: 768px) {
+  .form-horizontal .form-group-sm .control-label {
+    padding-top: 6px;
+    font-size: 12px;
+  }
+}
+.btn {
+  display: inline-block;
+  margin-bottom: 0;
+  font-weight: normal;
+  text-align: center;
+  vertical-align: middle;
+  touch-action: manipulation;
+  cursor: pointer;
+  background-image: none;
+  border: 1px solid transparent;
+  white-space: nowrap;
+  padding: 6px 12px;
+  font-size: 13px;
+  line-height: 1.42857143;
+  border-radius: 2px;
+  -webkit-user-select: none;
+  -moz-user-select: none;
+  -ms-user-select: none;
+  user-select: none;
+}
+.btn:focus,
+.btn:active:focus,
+.btn.active:focus,
+.btn.focus,
+.btn:active.focus,
+.btn.active.focus {
+  outline: 5px auto -webkit-focus-ring-color;
+  outline-offset: -2px;
+}
+.btn:hover,
+.btn:focus,
+.btn.focus {
+  color: #333;
+  text-decoration: none;
+}
+.btn:active,
+.btn.active {
+  outline: 0;
+  background-image: none;
+  -webkit-box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
+  box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
+}
+.btn.disabled,
+.btn[disabled],
+fieldset[disabled] .btn {
+  cursor: not-allowed;
+  opacity: 0.65;
+  filter: alpha(opacity=65);
+  -webkit-box-shadow: none;
+  box-shadow: none;
+}
+a.btn.disabled,
+fieldset[disabled] a.btn {
+  pointer-events: none;
+}
+.btn-default {
+  color: #333;
+  background-color: #fff;
+  border-color: #ccc;
+}
+.btn-default:focus,
+.btn-default.focus {
+  color: #333;
+  background-color: #e6e6e6;
+  border-color: #8c8c8c;
+}
+.btn-default:hover {
+  color: #333;
+  background-color: #e6e6e6;
+  border-color: #adadad;
+}
+.btn-default:active,
+.btn-default.active,
+.open > .dropdown-toggle.btn-default {
+  color: #333;
+  background-color: #e6e6e6;
+  border-color: #adadad;
+}
+.btn-default:active:hover,
+.btn-default.active:hover,
+.open > .dropdown-toggle.btn-default:hover,
+.btn-default:active:focus,
+.btn-default.active:focus,
+.open > .dropdown-toggle.btn-default:focus,
+.btn-default:active.focus,
+.btn-default.active.focus,
+.open > .dropdown-toggle.btn-default.focus {
+  color: #333;
+  background-color: #d4d4d4;
+  border-color: #8c8c8c;
+}
+.btn-default:active,
+.btn-default.active,
+.open > .dropdown-toggle.btn-default {
+  background-image: none;
+}
+.btn-default.disabled:hover,
+.btn-default[disabled]:hover,
+fieldset[disabled] .btn-default:hover,
+.btn-default.disabled:focus,
+.btn-default[disabled]:focus,
+fieldset[disabled] .btn-default:focus,
+.btn-default.disabled.focus,
+.btn-default[disabled].focus,
+fieldset[disabled] .btn-default.focus {
+  background-color: #fff;
+  border-color: #ccc;
+}
+.btn-default .badge {
+  color: #fff;
+  background-color: #333;
+}
+.btn-primary {
+  color: #fff;
+  background-color: #337ab7;
+  border-color: #2e6da4;
+}
+.btn-primary:focus,
+.btn-primary.focus {
+  color: #fff;
+  background-color: #286090;
+  border-color: #122b40;
+}
+.btn-primary:hover {
+  color: #fff;
+  background-color: #286090;
+  border-color: #204d74;
+}
+.btn-primary:active,
+.btn-primary.active,
+.open > .dropdown-toggle.btn-primary {
+  color: #fff;
+  background-color: #286090;
+  border-color: #204d74;
+}
+.btn-primary:active:hover,
+.btn-primary.active:hover,
+.open > .dropdown-toggle.btn-primary:hover,
+.btn-primary:active:focus,
+.btn-primary.active:focus,
+.open > .dropdown-toggle.btn-primary:focus,
+.btn-primary:active.focus,
+.btn-primary.active.focus,
+.open > .dropdown-toggle.btn-primary.focus {
+  color: #fff;
+  background-color: #204d74;
+  border-color: #122b40;
+}
+.btn-primary:active,
+.btn-primary.active,
+.open > .dropdown-toggle.btn-primary {
+  background-image: none;
+}
+.btn-primary.disabled:hover,
+.btn-primary[disabled]:hover,
+fieldset[disabled] .btn-primary:hover,
+.btn-primary.disabled:focus,
+.btn-primary[disabled]:focus,
+fieldset[disabled] .btn-primary:focus,
+.btn-primary.disabled.focus,
+.btn-primary[disabled].focus,
+fieldset[disabled] .btn-primary.focus {
+  background-color: #337ab7;
+  border-color: #2e6da4;
+}
+.btn-primary .badge {
+  color: #337ab7;
+  background-color: #fff;
+}
+.btn-success {
+  color: #fff;
+  background-color: #5cb85c;
+  border-color: #4cae4c;
+}
+.btn-success:focus,
+.btn-success.focus {
+  color: #fff;
+  background-color: #449d44;
+  border-color: #255625;
+}
+.btn-success:hover {
+  color: #fff;
+  background-color: #449d44;
+  border-color: #398439;
+}
+.btn-success:active,
+.btn-success.active,
+.open > .dropdown-toggle.btn-success {
+  color: #fff;
+  background-color: #449d44;
+  border-color: #398439;
+}
+.btn-success:active:hover,
+.btn-success.active:hover,
+.open > .dropdown-toggle.btn-success:hover,
+.btn-success:active:focus,
+.btn-success.active:focus,
+.open > .dropdown-toggle.btn-success:focus,
+.btn-success:active.focus,
+.btn-success.active.focus,
+.open > .dropdown-toggle.btn-success.focus {
+  color: #fff;
+  background-color: #398439;
+  border-color: #255625;
+}
+.btn-success:active,
+.btn-success.active,
+.open > .dropdown-toggle.btn-success {
+  background-image: none;
+}
+.btn-success.disabled:hover,
+.btn-success[disabled]:hover,
+fieldset[disabled] .btn-success:hover,
+.btn-success.disabled:focus,
+.btn-success[disabled]:focus,
+fieldset[disabled] .btn-success:focus,
+.btn-success.disabled.focus,
+.btn-success[disabled].focus,
+fieldset[disabled] .btn-success.focus {
+  background-color: #5cb85c;
+  border-color: #4cae4c;
+}
+.btn-success .badge {
+  color: #5cb85c;
+  background-color: #fff;
+}
+.btn-info {
+  color: #fff;
+  background-color: #5bc0de;
+  border-color: #46b8da;
+}
+.btn-info:focus,
+.btn-info.focus {
+  color: #fff;
+  background-color: #31b0d5;
+  border-color: #1b6d85;
+}
+.btn-info:hover {
+  color: #fff;
+  background-color: #31b0d5;
+  border-color: #269abc;
+}
+.btn-info:active,
+.btn-info.active,
+.open > .dropdown-toggle.btn-info {
+  color: #fff;
+  background-color: #31b0d5;
+  border-color: #269abc;
+}
+.btn-info:active:hover,
+.btn-info.active:hover,
+.open > .dropdown-toggle.btn-info:hover,
+.btn-info:active:focus,
+.btn-info.active:focus,
+.open > .dropdown-toggle.btn-info:focus,
+.btn-info:active.focus,
+.btn-info.active.focus,
+.open > .dropdown-toggle.btn-info.focus {
+  color: #fff;
+  background-color: #269abc;
+  border-color: #1b6d85;
+}
+.btn-info:active,
+.btn-info.active,
+.open > .dropdown-toggle.btn-info {
+  background-image: none;
+}
+.btn-info.disabled:hover,
+.btn-info[disabled]:hover,
+fieldset[disabled] .btn-info:hover,
+.btn-info.disabled:focus,
+.btn-info[disabled]:focus,
+fieldset[disabled] .btn-info:focus,
+.btn-info.disabled.focus,
+.btn-info[disabled].focus,
+fieldset[disabled] .btn-info.focus {
+  background-color: #5bc0de;
+  border-color: #46b8da;
+}
+.btn-info .badge {
+  color: #5bc0de;
+  background-color: #fff;
+}
+.btn-warning {
+  color: #fff;
+  background-color: #f0ad4e;
+  border-color: #eea236;
+}
+.btn-warning:focus,
+.btn-warning.focus {
+  color: #fff;
+  background-color: #ec971f;
+  border-color: #985f0d;
+}
+.btn-warning:hover {
+  color: #fff;
+  background-color: #ec971f;
+  border-color: #d58512;
+}
+.btn-warning:active,
+.btn-warning.active,
+.open > .dropdown-toggle.btn-warning {
+  color: #fff;
+  background-color: #ec971f;
+  border-color: #d58512;
+}
+.btn-warning:active:hover,
+.btn-warning.active:hover,
+.open > .dropdown-toggle.btn-warning:hover,
+.btn-warning:active:focus,
+.btn-warning.active:focus,
+.open > .dropdown-toggle.btn-warning:focus,
+.btn-warning:active.focus,
+.btn-warning.active.focus,
+.open > .dropdown-toggle.btn-warning.focus {
+  color: #fff;
+  background-color: #d58512;
+  border-color: #985f0d;
+}
+.btn-warning:active,
+.btn-warning.active,
+.open > .dropdown-toggle.btn-warning {
+  background-image: none;
+}
+.btn-warning.disabled:hover,
+.btn-warning[disabled]:hover,
+fieldset[disabled] .btn-warning:hover,
+.btn-warning.disabled:focus,
+.btn-warning[disabled]:focus,
+fieldset[disabled] .btn-warning:focus,
+.btn-warning.disabled.focus,
+.btn-warning[disabled].focus,
+fieldset[disabled] .btn-warning.focus {
+  background-color: #f0ad4e;
+  border-color: #eea236;
+}
+.btn-warning .badge {
+  color: #f0ad4e;
+  background-color: #fff;
+}
+.btn-danger {
+  color: #fff;
+  background-color: #d9534f;
+  border-color: #d43f3a;
+}
+.btn-danger:focus,
+.btn-danger.focus {
+  color: #fff;
+  background-color: #c9302c;
+  border-color: #761c19;
+}
+.btn-danger:hover {
+  color: #fff;
+  background-color: #c9302c;
+  border-color: #ac2925;
+}
+.btn-danger:active,
+.btn-danger.active,
+.open > .dropdown-toggle.btn-danger {
+  color: #fff;
+  background-color: #c9302c;
+  border-color: #ac2925;
+}
+.btn-danger:active:hover,
+.btn-danger.active:hover,
+.open > .dropdown-toggle.btn-danger:hover,
+.btn-danger:active:focus,
+.btn-danger.active:focus,
+.open > .dropdown-toggle.btn-danger:focus,
+.btn-danger:active.focus,
+.btn-danger.active.focus,
+.open > .dropdown-toggle.btn-danger.focus {
+  color: #fff;
+  background-color: #ac2925;
+  border-color: #761c19;
+}
+.btn-danger:active,
+.btn-danger.active,
+.open > .dropdown-toggle.btn-danger {
+  background-image: none;
+}
+.btn-danger.disabled:hover,
+.btn-danger[disabled]:hover,
+fieldset[disabled] .btn-danger:hover,
+.btn-danger.disabled:focus,
+.btn-danger[disabled]:focus,
+fieldset[disabled] .btn-danger:focus,
+.btn-danger.disabled.focus,
+.btn-danger[disabled].focus,
+fieldset[disabled] .btn-danger.focus {
+  background-color: #d9534f;
+  border-color: #d43f3a;
+}
+.btn-danger .badge {
+  color: #d9534f;
+  background-color: #fff;
+}
+.btn-link {
+  color: #337ab7;
+  font-weight: normal;
+  border-radius: 0;
+}
+.btn-link,
+.btn-link:active,
+.btn-link.active,
+.btn-link[disabled],
+fieldset[disabled] .btn-link {
+  background-color: transparent;
+  -webkit-box-shadow: none;
+  box-shadow: none;
+}
+.btn-link,
+.btn-link:hover,
+.btn-link:focus,
+.btn-link:active {
+  border-color: transparent;
+}
+.btn-link:hover,
+.btn-link:focus {
+  color: #23527c;
+  text-decoration: underline;
+  background-color: transparent;
+}
+.btn-link[disabled]:hover,
+fieldset[disabled] .btn-link:hover,
+.btn-link[disabled]:focus,
+fieldset[disabled] .btn-link:focus {
+  color: #777777;
+  text-decoration: none;
+}
+.btn-lg,
+.btn-group-lg > .btn {
+  padding: 10px 16px;
+  font-size: 17px;
+  line-height: 1.3333333;
+  border-radius: 3px;
+}
+.btn-sm,
+.btn-group-sm > .btn {
+  padding: 5px 10px;
+  font-size: 12px;
+  line-height: 1.5;
+  border-radius: 1px;
+}
+.btn-xs,
+.btn-group-xs > .btn {
+  padding: 1px 5px;
+  font-size: 12px;
+  line-height: 1.5;
+  border-radius: 1px;
+}
+.btn-block {
+  display: block;
+  width: 100%;
+}
+.btn-block + .btn-block {
+  margin-top: 5px;
+}
+input[type="submit"].btn-block,
+input[type="reset"].btn-block,
+input[type="button"].btn-block {
+  width: 100%;
+}
+.fade {
+  opacity: 0;
+  -webkit-transition: opacity 0.15s linear;
+  -o-transition: opacity 0.15s linear;
+  transition: opacity 0.15s linear;
+}
+.fade.in {
+  opacity: 1;
+}
+.collapse {
+  display: none;
+}
+.collapse.in {
+  display: block;
+}
+tr.collapse.in {
+  display: table-row;
+}
+tbody.collapse.in {
+  display: table-row-group;
+}
+.collapsing {
+  position: relative;
+  height: 0;
+  overflow: hidden;
+  -webkit-transition-property: height, visibility;
+  transition-property: height, visibility;
+  -webkit-transition-duration: 0.35s;
+  transition-duration: 0.35s;
+  -webkit-transition-timing-function: ease;
+  transition-timing-function: ease;
+}
+.caret {
+  display: inline-block;
+  width: 0;
+  height: 0;
+  margin-left: 2px;
+  vertical-align: middle;
+  border-top: 4px dashed;
+  border-top: 4px solid \9;
+  border-right: 4px solid transparent;
+  border-left: 4px solid transparent;
+}
+.dropup,
+.dropdown {
+  position: relative;
+}
+.dropdown-toggle:focus {
+  outline: 0;
+}
+.dropdown-menu {
+  position: absolute;
+  top: 100%;
+  left: 0;
+  z-index: 1000;
+  display: none;
+  float: left;
+  min-width: 160px;
+  padding: 5px 0;
+  margin: 2px 0 0;
+  list-style: none;
+  font-size: 13px;
+  text-align: left;
+  background-color: #fff;
+  border: 1px solid #ccc;
+  border: 1px solid rgba(0, 0, 0, 0.15);
+  border-radius: 2px;
+  -webkit-box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175);
+  box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175);
+  background-clip: padding-box;
+}
+.dropdown-menu.pull-right {
+  right: 0;
+  left: auto;
+}
+.dropdown-menu .divider {
+  height: 1px;
+  margin: 8px 0;
+  overflow: hidden;
+  background-color: #e5e5e5;
+}
+.dropdown-menu > li > a {
+  display: block;
+  padding: 3px 20px;
+  clear: both;
+  font-weight: normal;
+  line-height: 1.42857143;
+  color: #333333;
+  white-space: nowrap;
+}
+.dropdown-menu > li > a:hover,
+.dropdown-menu > li > a:focus {
+  text-decoration: none;
+  color: #262626;
+  background-color: #f5f5f5;
+}
+.dropdown-menu > .active > a,
+.dropdown-menu > .active > a:hover,
+.dropdown-menu > .active > a:focus {
+  color: #fff;
+  text-decoration: none;
+  outline: 0;
+  background-color: #337ab7;
+}
+.dropdown-menu > .disabled > a,
+.dropdown-menu > .disabled > a:hover,
+.dropdown-menu > .disabled > a:focus {
+  color: #777777;
+}
+.dropdown-menu > .disabled > a:hover,
+.dropdown-menu > .disabled > a:focus {
+  text-decoration: none;
+  background-color: transparent;
+  background-image: none;
+  filter: progid:DXImageTransform.Microsoft.gradient(enabled = false);
+  cursor: not-allowed;
+}
+.open > .dropdown-menu {
+  display: block;
+}
+.open > a {
+  outline: 0;
+}
+.dropdown-menu-right {
+  left: auto;
+  right: 0;
+}
+.dropdown-menu-left {
+  left: 0;
+  right: auto;
+}
+.dropdown-header {
+  display: block;
+  padding: 3px 20px;
+  font-size: 12px;
+  line-height: 1.42857143;
+  color: #777777;
+  white-space: nowrap;
+}
+.dropdown-backdrop {
+  position: fixed;
+  left: 0;
+  right: 0;
+  bottom: 0;
+  top: 0;
+  z-index: 990;
+}
+.pull-right > .dropdown-menu {
+  right: 0;
+  left: auto;
+}
+.dropup .caret,
+.navbar-fixed-bottom .dropdown .caret {
+  border-top: 0;
+  border-bottom: 4px dashed;
+  border-bottom: 4px solid \9;
+  content: "";
+}
+.dropup .dropdown-menu,
+.navbar-fixed-bottom .dropdown .dropdown-menu {
+  top: auto;
+  bottom: 100%;
+  margin-bottom: 2px;
+}
+@media (min-width: 541px) {
+  .navbar-right .dropdown-menu {
+    left: auto;
+    right: 0;
+  }
+  .navbar-right .dropdown-menu-left {
+    left: 0;
+    right: auto;
+  }
+}
+.btn-group,
+.btn-group-vertical {
+  position: relative;
+  display: inline-block;
+  vertical-align: middle;
+}
+.btn-group > .btn,
+.btn-group-vertical > .btn {
+  position: relative;
+  float: left;
+}
+.btn-group > .btn:hover,
+.btn-group-vertical > .btn:hover,
+.btn-group > .btn:focus,
+.btn-group-vertical > .btn:focus,
+.btn-group > .btn:active,
+.btn-group-vertical > .btn:active,
+.btn-group > .btn.active,
+.btn-group-vertical > .btn.active {
+  z-index: 2;
+}
+.btn-group .btn + .btn,
+.btn-group .btn + .btn-group,
+.btn-group .btn-group + .btn,
+.btn-group .btn-group + .btn-group {
+  margin-left: -1px;
+}
+.btn-toolbar {
+  margin-left: -5px;
+}
+.btn-toolbar .btn,
+.btn-toolbar .btn-group,
+.btn-toolbar .input-group {
+  float: left;
+}
+.btn-toolbar > .btn,
+.btn-toolbar > .btn-group,
+.btn-toolbar > .input-group {
+  margin-left: 5px;
+}
+.btn-group > .btn:not(:first-child):not(:last-child):not(.dropdown-toggle) {
+  border-radius: 0;
+}
+.btn-group > .btn:first-child {
+  margin-left: 0;
+}
+.btn-group > .btn:first-child:not(:last-child):not(.dropdown-toggle) {
+  border-bottom-right-radius: 0;
+  border-top-right-radius: 0;
+}
+.btn-group > .btn:last-child:not(:first-child),
+.btn-group > .dropdown-toggle:not(:first-child) {
+  border-bottom-left-radius: 0;
+  border-top-left-radius: 0;
+}
+.btn-group > .btn-group {
+  float: left;
+}
+.btn-group > .btn-group:not(:first-child):not(:last-child) > .btn {
+  border-radius: 0;
+}
+.btn-group > .btn-group:first-child:not(:last-child) > .btn:last-child,
+.btn-group > .btn-group:first-child:not(:last-child) > .dropdown-toggle {
+  border-bottom-right-radius: 0;
+  border-top-right-radius: 0;
+}
+.btn-group > .btn-group:last-child:not(:first-child) > .btn:first-child {
+  border-bottom-left-radius: 0;
+  border-top-left-radius: 0;
+}
+.btn-group .dropdown-toggle:active,
+.btn-group.open .dropdown-toggle {
+  outline: 0;
+}
+.btn-group > .btn + .dropdown-toggle {
+  padding-left: 8px;
+  padding-right: 8px;
+}
+.btn-group > .btn-lg + .dropdown-toggle {
+  padding-left: 12px;
+  padding-right: 12px;
+}
+.btn-group.open .dropdown-toggle {
+  -webkit-box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
+  box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
+}
+.btn-group.open .dropdown-toggle.btn-link {
+  -webkit-box-shadow: none;
+  box-shadow: none;
+}
+.btn .caret {
+  margin-left: 0;
+}
+.btn-lg .caret {
+  border-width: 5px 5px 0;
+  border-bottom-width: 0;
+}
+.dropup .btn-lg .caret {
+  border-width: 0 5px 5px;
+}
+.btn-group-vertical > .btn,
+.btn-group-vertical > .btn-group,
+.btn-group-vertical > .btn-group > .btn {
+  display: block;
+  float: none;
+  width: 100%;
+  max-width: 100%;
+}
+.btn-group-vertical > .btn-group > .btn {
+  float: none;
+}
+.btn-group-vertical > .btn + .btn,
+.btn-group-vertical > .btn + .btn-group,
+.btn-group-vertical > .btn-group + .btn,
+.btn-group-vertical > .btn-group + .btn-group {
+  margin-top: -1px;
+  margin-left: 0;
+}
+.btn-group-vertical > .btn:not(:first-child):not(:last-child) {
+  border-radius: 0;
+}
+.btn-group-vertical > .btn:first-child:not(:last-child) {
+  border-top-right-radius: 2px;
+  border-top-left-radius: 2px;
+  border-bottom-right-radius: 0;
+  border-bottom-left-radius: 0;
+}
+.btn-group-vertical > .btn:last-child:not(:first-child) {
+  border-top-right-radius: 0;
+  border-top-left-radius: 0;
+  border-bottom-right-radius: 2px;
+  border-bottom-left-radius: 2px;
+}
+.btn-group-vertical > .btn-group:not(:first-child):not(:last-child) > .btn {
+  border-radius: 0;
+}
+.btn-group-vertical > .btn-group:first-child:not(:last-child) > .btn:last-child,
+.btn-group-vertical > .btn-group:first-child:not(:last-child) > .dropdown-toggle {
+  border-bottom-right-radius: 0;
+  border-bottom-left-radius: 0;
+}
+.btn-group-vertical > .btn-group:last-child:not(:first-child) > .btn:first-child {
+  border-top-right-radius: 0;
+  border-top-left-radius: 0;
+}
+.btn-group-justified {
+  display: table;
+  width: 100%;
+  table-layout: fixed;
+  border-collapse: separate;
+}
+.btn-group-justified > .btn,
+.btn-group-justified > .btn-group {
+  float: none;
+  display: table-cell;
+  width: 1%;
+}
+.btn-group-justified > .btn-group .btn {
+  width: 100%;
+}
+.btn-group-justified > .btn-group .dropdown-menu {
+  left: auto;
+}
+[data-toggle="buttons"] > .btn input[type="radio"],
+[data-toggle="buttons"] > .btn-group > .btn input[type="radio"],
+[data-toggle="buttons"] > .btn input[type="checkbox"],
+[data-toggle="buttons"] > .btn-group > .btn input[type="checkbox"] {
+  position: absolute;
+  clip: rect(0, 0, 0, 0);
+  pointer-events: none;
+}
+.input-group {
+  position: relative;
+  display: table;
+  border-collapse: separate;
+}
+.input-group[class*="col-"] {
+  float: none;
+  padding-left: 0;
+  padding-right: 0;
+}
+.input-group .form-control {
+  position: relative;
+  z-index: 2;
+  float: left;
+  width: 100%;
+  margin-bottom: 0;
+}
+.input-group .form-control:focus {
+  z-index: 3;
+}
+.input-group-lg > .form-control,
+.input-group-lg > .input-group-addon,
+.input-group-lg > .input-group-btn > .btn {
+  height: 45px;
+  padding: 10px 16px;
+  font-size: 17px;
+  line-height: 1.3333333;
+  border-radius: 3px;
+}
+select.input-group-lg > .form-control,
+select.input-group-lg > .input-group-addon,
+select.input-group-lg > .input-group-btn > .btn {
+  height: 45px;
+  line-height: 45px;
+}
+textarea.input-group-lg > .form-control,
+textarea.input-group-lg > .input-group-addon,
+textarea.input-group-lg > .input-group-btn > .btn,
+select[multiple].input-group-lg > .form-control,
+select[multiple].input-group-lg > .input-group-addon,
+select[multiple].input-group-lg > .input-group-btn > .btn {
+  height: auto;
+}
+.input-group-sm > .form-control,
+.input-group-sm > .input-group-addon,
+.input-group-sm > .input-group-btn > .btn {
+  height: 30px;
+  padding: 5px 10px;
+  font-size: 12px;
+  line-height: 1.5;
+  border-radius: 1px;
+}
+select.input-group-sm > .form-control,
+select.input-group-sm > .input-group-addon,
+select.input-group-sm > .input-group-btn > .btn {
+  height: 30px;
+  line-height: 30px;
+}
+textarea.input-group-sm > .form-control,
+textarea.input-group-sm > .input-group-addon,
+textarea.input-group-sm > .input-group-btn > .btn,
+select[multiple].input-group-sm > .form-control,
+select[multiple].input-group-sm > .input-group-addon,
+select[multiple].input-group-sm > .input-group-btn > .btn {
+  height: auto;
+}
+.input-group-addon,
+.input-group-btn,
+.input-group .form-control {
+  display: table-cell;
+}
+.input-group-addon:not(:first-child):not(:last-child),
+.input-group-btn:not(:first-child):not(:last-child),
+.input-group .form-control:not(:first-child):not(:last-child) {
+  border-radius: 0;
+}
+.input-group-addon,
+.input-group-btn {
+  width: 1%;
+  white-space: nowrap;
+  vertical-align: middle;
+}
+.input-group-addon {
+  padding: 6px 12px;
+  font-size: 13px;
+  font-weight: normal;
+  line-height: 1;
+  color: #555555;
+  text-align: center;
+  background-color: #eeeeee;
+  border: 1px solid #ccc;
+  border-radius: 2px;
+}
+.input-group-addon.input-sm {
+  padding: 5px 10px;
+  font-size: 12px;
+  border-radius: 1px;
+}
+.input-group-addon.input-lg {
+  padding: 10px 16px;
+  font-size: 17px;
+  border-radius: 3px;
+}
+.input-group-addon input[type="radio"],
+.input-group-addon input[type="checkbox"] {
+  margin-top: 0;
+}
+.input-group .form-control:first-child,
+.input-group-addon:first-child,
+.input-group-btn:first-child > .btn,
+.input-group-btn:first-child > .btn-group > .btn,
+.input-group-btn:first-child > .dropdown-toggle,
+.input-group-btn:last-child > .btn:not(:last-child):not(.dropdown-toggle),
+.input-group-btn:last-child > .btn-group:not(:last-child) > .btn {
+  border-bottom-right-radius: 0;
+  border-top-right-radius: 0;
+}
+.input-group-addon:first-child {
+  border-right: 0;
+}
+.input-group .form-control:last-child,
+.input-group-addon:last-child,
+.input-group-btn:last-child > .btn,
+.input-group-btn:last-child > .btn-group > .btn,
+.input-group-btn:last-child > .dropdown-toggle,
+.input-group-btn:first-child > .btn:not(:first-child),
+.input-group-btn:first-child > .btn-group:not(:first-child) > .btn {
+  border-bottom-left-radius: 0;
+  border-top-left-radius: 0;
+}
+.input-group-addon:last-child {
+  border-left: 0;
+}
+.input-group-btn {
+  position: relative;
+  font-size: 0;
+  white-space: nowrap;
+}
+.input-group-btn > .btn {
+  position: relative;
+}
+.input-group-btn > .btn + .btn {
+  margin-left: -1px;
+}
+.input-group-btn > .btn:hover,
+.input-group-btn > .btn:focus,
+.input-group-btn > .btn:active {
+  z-index: 2;
+}
+.input-group-btn:first-child > .btn,
+.input-group-btn:first-child > .btn-group {
+  margin-right: -1px;
+}
+.input-group-btn:last-child > .btn,
+.input-group-btn:last-child > .btn-group {
+  z-index: 2;
+  margin-left: -1px;
+}
+.nav {
+  margin-bottom: 0;
+  padding-left: 0;
+  list-style: none;
+}
+.nav > li {
+  position: relative;
+  display: block;
+}
+.nav > li > a {
+  position: relative;
+  display: block;
+  padding: 10px 15px;
+}
+.nav > li > a:hover,
+.nav > li > a:focus {
+  text-decoration: none;
+  background-color: #eeeeee;
+}
+.nav > li.disabled > a {
+  color: #777777;
+}
+.nav > li.disabled > a:hover,
+.nav > li.disabled > a:focus {
+  color: #777777;
+  text-decoration: none;
+  background-color: transparent;
+  cursor: not-allowed;
+}
+.nav .open > a,
+.nav .open > a:hover,
+.nav .open > a:focus {
+  background-color: #eeeeee;
+  border-color: #337ab7;
+}
+.nav .nav-divider {
+  height: 1px;
+  margin: 8px 0;
+  overflow: hidden;
+  background-color: #e5e5e5;
+}
+.nav > li > a > img {
+  max-width: none;
+}
+.nav-tabs {
+  border-bottom: 1px solid #ddd;
+}
+.nav-tabs > li {
+  float: left;
+  margin-bottom: -1px;
+}
+.nav-tabs > li > a {
+  margin-right: 2px;
+  line-height: 1.42857143;
+  border: 1px solid transparent;
+  border-radius: 2px 2px 0 0;
+}
+.nav-tabs > li > a:hover {
+  border-color: #eeeeee #eeeeee #ddd;
+}
+.nav-tabs > li.active > a,
+.nav-tabs > li.active > a:hover,
+.nav-tabs > li.active > a:focus {
+  color: #555555;
+  background-color: #fff;
+  border: 1px solid #ddd;
+  border-bottom-color: transparent;
+  cursor: default;
+}
+.nav-tabs.nav-justified {
+  width: 100%;
+  border-bottom: 0;
+}
+.nav-tabs.nav-justified > li {
+  float: none;
+}
+.nav-tabs.nav-justified > li > a {
+  text-align: center;
+  margin-bottom: 5px;
+}
+.nav-tabs.nav-justified > .dropdown .dropdown-menu {
+  top: auto;
+  left: auto;
+}
+@media (min-width: 768px) {
+  .nav-tabs.nav-justified > li {
+    display: table-cell;
+    width: 1%;
+  }
+  .nav-tabs.nav-justified > li > a {
+    margin-bottom: 0;
+  }
+}
+.nav-tabs.nav-justified > li > a {
+  margin-right: 0;
+  border-radius: 2px;
+}
+.nav-tabs.nav-justified > .active > a,
+.nav-tabs.nav-justified > .active > a:hover,
+.nav-tabs.nav-justified > .active > a:focus {
+  border: 1px solid #ddd;
+}
+@media (min-width: 768px) {
+  .nav-tabs.nav-justified > li > a {
+    border-bottom: 1px solid #ddd;
+    border-radius: 2px 2px 0 0;
+  }
+  .nav-tabs.nav-justified > .active > a,
+  .nav-tabs.nav-justified > .active > a:hover,
+  .nav-tabs.nav-justified > .active > a:focus {
+    border-bottom-color: #fff;
+  }
+}
+.nav-pills > li {
+  float: left;
+}
+.nav-pills > li > a {
+  border-radius: 2px;
+}
+.nav-pills > li + li {
+  margin-left: 2px;
+}
+.nav-pills > li.active > a,
+.nav-pills > li.active > a:hover,
+.nav-pills > li.active > a:focus {
+  color: #fff;
+  background-color: #337ab7;
+}
+.nav-stacked > li {
+  float: none;
+}
+.nav-stacked > li + li {
+  margin-top: 2px;
+  margin-left: 0;
+}
+.nav-justified {
+  width: 100%;
+}
+.nav-justified > li {
+  float: none;
+}
+.nav-justified > li > a {
+  text-align: center;
+  margin-bottom: 5px;
+}
+.nav-justified > .dropdown .dropdown-menu {
+  top: auto;
+  left: auto;
+}
+@media (min-width: 768px) {
+  .nav-justified > li {
+    display: table-cell;
+    width: 1%;
+  }
+  .nav-justified > li > a {
+    margin-bottom: 0;
+  }
+}
+.nav-tabs-justified {
+  border-bottom: 0;
+}
+.nav-tabs-justified > li > a {
+  margin-right: 0;
+  border-radius: 2px;
+}
+.nav-tabs-justified > .active > a,
+.nav-tabs-justified > .active > a:hover,
+.nav-tabs-justified > .active > a:focus {
+  border: 1px solid #ddd;
+}
+@media (min-width: 768px) {
+  .nav-tabs-justified > li > a {
+    border-bottom: 1px solid #ddd;
+    border-radius: 2px 2px 0 0;
+  }
+  .nav-tabs-justified > .active > a,
+  .nav-tabs-justified > .active > a:hover,
+  .nav-tabs-justified > .active > a:focus {
+    border-bottom-color: #fff;
+  }
+}
+.tab-content > .tab-pane {
+  display: none;
+}
+.tab-content > .active {
+  display: block;
+}
+.nav-tabs .dropdown-menu {
+  margin-top: -1px;
+  border-top-right-radius: 0;
+  border-top-left-radius: 0;
+}
+.navbar {
+  position: relative;
+  min-height: 30px;
+  margin-bottom: 18px;
+  border: 1px solid transparent;
+}
+@media (min-width: 541px) {
+  .navbar {
+    border-radius: 2px;
+  }
+}
+@media (min-width: 541px) {
+  .navbar-header {
+    float: left;
+  }
+}
+.navbar-collapse {
+  overflow-x: visible;
+  padding-right: 0px;
+  padding-left: 0px;
+  border-top: 1px solid transparent;
+  box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1);
+  -webkit-overflow-scrolling: touch;
+}
+.navbar-collapse.in {
+  overflow-y: auto;
+}
+@media (min-width: 541px) {
+  .navbar-collapse {
+    width: auto;
+    border-top: 0;
+    box-shadow: none;
+  }
+  .navbar-collapse.collapse {
+    display: block !important;
+    height: auto !important;
+    padding-bottom: 0;
+    overflow: visible !important;
+  }
+  .navbar-collapse.in {
+    overflow-y: visible;
+  }
+  .navbar-fixed-top .navbar-collapse,
+  .navbar-static-top .navbar-collapse,
+  .navbar-fixed-bottom .navbar-collapse {
+    padding-left: 0;
+    padding-right: 0;
+  }
+}
+.navbar-fixed-top .navbar-collapse,
+.navbar-fixed-bottom .navbar-collapse {
+  max-height: 340px;
+}
+@media (max-device-width: 540px) and (orientation: landscape) {
+  .navbar-fixed-top .navbar-collapse,
+  .navbar-fixed-bottom .navbar-collapse {
+    max-height: 200px;
+  }
+}
+.container > .navbar-header,
+.container-fluid > .navbar-header,
+.container > .navbar-collapse,
+.container-fluid > .navbar-collapse {
+  margin-right: 0px;
+  margin-left: 0px;
+}
+@media (min-width: 541px) {
+  .container > .navbar-header,
+  .container-fluid > .navbar-header,
+  .container > .navbar-collapse,
+  .container-fluid > .navbar-collapse {
+    margin-right: 0;
+    margin-left: 0;
+  }
+}
+.navbar-static-top {
+  z-index: 1000;
+  border-width: 0 0 1px;
+}
+@media (min-width: 541px) {
+  .navbar-static-top {
+    border-radius: 0;
+  }
+}
+.navbar-fixed-top,
+.navbar-fixed-bottom {
+  position: fixed;
+  right: 0;
+  left: 0;
+  z-index: 1030;
+}
+@media (min-width: 541px) {
+  .navbar-fixed-top,
+  .navbar-fixed-bottom {
+    border-radius: 0;
+  }
+}
+.navbar-fixed-top {
+  top: 0;
+  border-width: 0 0 1px;
+}
+.navbar-fixed-bottom {
+  bottom: 0;
+  margin-bottom: 0;
+  border-width: 1px 0 0;
+}
+.navbar-brand {
+  float: left;
+  padding: 6px 0px;
+  font-size: 17px;
+  line-height: 18px;
+  height: 30px;
+}
+.navbar-brand:hover,
+.navbar-brand:focus {
+  text-decoration: none;
+}
+.navbar-brand > img {
+  display: block;
+}
+@media (min-width: 541px) {
+  .navbar > .container .navbar-brand,
+  .navbar > .container-fluid .navbar-brand {
+    margin-left: 0px;
+  }
+}
+.navbar-toggle {
+  position: relative;
+  float: right;
+  margin-right: 0px;
+  padding: 9px 10px;
+  margin-top: -2px;
+  margin-bottom: -2px;
+  background-color: transparent;
+  background-image: none;
+  border: 1px solid transparent;
+  border-radius: 2px;
+}
+.navbar-toggle:focus {
+  outline: 0;
+}
+.navbar-toggle .icon-bar {
+  display: block;
+  width: 22px;
+  height: 2px;
+  border-radius: 1px;
+}
+.navbar-toggle .icon-bar + .icon-bar {
+  margin-top: 4px;
+}
+@media (min-width: 541px) {
+  .navbar-toggle {
+    display: none;
+  }
+}
+.navbar-nav {
+  margin: 3px 0px;
+}
+.navbar-nav > li > a {
+  padding-top: 10px;
+  padding-bottom: 10px;
+  line-height: 18px;
+}
+@media (max-width: 540px) {
+  .navbar-nav .open .dropdown-menu {
+    position: static;
+    float: none;
+    width: auto;
+    margin-top: 0;
+    background-color: transparent;
+    border: 0;
+    box-shadow: none;
+  }
+  .navbar-nav .open .dropdown-menu > li > a,
+  .navbar-nav .open .dropdown-menu .dropdown-header {
+    padding: 5px 15px 5px 25px;
+  }
+  .navbar-nav .open .dropdown-menu > li > a {
+    line-height: 18px;
+  }
+  .navbar-nav .open .dropdown-menu > li > a:hover,
+  .navbar-nav .open .dropdown-menu > li > a:focus {
+    background-image: none;
+  }
+}
+@media (min-width: 541px) {
+  .navbar-nav {
+    float: left;
+    margin: 0;
+  }
+  .navbar-nav > li {
+    float: left;
+  }
+  .navbar-nav > li > a {
+    padding-top: 6px;
+    padding-bottom: 6px;
+  }
+}
+.navbar-form {
+  margin-left: 0px;
+  margin-right: 0px;
+  padding: 10px 0px;
+  border-top: 1px solid transparent;
+  border-bottom: 1px solid transparent;
+  -webkit-box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1), 0 1px 0 rgba(255, 255, 255, 0.1);
+  box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1), 0 1px 0 rgba(255, 255, 255, 0.1);
+  margin-top: -1px;
+  margin-bottom: -1px;
+}
+@media (min-width: 768px) {
+  .navbar-form .form-group {
+    display: inline-block;
+    margin-bottom: 0;
+    vertical-align: middle;
+  }
+  .navbar-form .form-control {
+    display: inline-block;
+    width: auto;
+    vertical-align: middle;
+  }
+  .navbar-form .form-control-static {
+    display: inline-block;
+  }
+  .navbar-form .input-group {
+    display: inline-table;
+    vertical-align: middle;
+  }
+  .navbar-form .input-group .input-group-addon,
+  .navbar-form .input-group .input-group-btn,
+  .navbar-form .input-group .form-control {
+    width: auto;
+  }
+  .navbar-form .input-group > .form-control {
+    width: 100%;
+  }
+  .navbar-form .control-label {
+    margin-bottom: 0;
+    vertical-align: middle;
+  }
+  .navbar-form .radio,
+  .navbar-form .checkbox {
+    display: inline-block;
+    margin-top: 0;
+    margin-bottom: 0;
+    vertical-align: middle;
+  }
+  .navbar-form .radio label,
+  .navbar-form .checkbox label {
+    padding-left: 0;
+  }
+  .navbar-form .radio input[type="radio"],
+  .navbar-form .checkbox input[type="checkbox"] {
+    position: relative;
+    margin-left: 0;
+  }
+  .navbar-form .has-feedback .form-control-feedback {
+    top: 0;
+  }
+}
+@media (max-width: 540px) {
+  .navbar-form .form-group {
+    margin-bottom: 5px;
+  }
+  .navbar-form .form-group:last-child {
+    margin-bottom: 0;
+  }
+}
+@media (min-width: 541px) {
+  .navbar-form {
+    width: auto;
+    border: 0;
+    margin-left: 0;
+    margin-right: 0;
+    padding-top: 0;
+    padding-bottom: 0;
+    -webkit-box-shadow: none;
+    box-shadow: none;
+  }
+}
+.navbar-nav > li > .dropdown-menu {
+  margin-top: 0;
+  border-top-right-radius: 0;
+  border-top-left-radius: 0;
+}
+.navbar-fixed-bottom .navbar-nav > li > .dropdown-menu {
+  margin-bottom: 0;
+  border-top-right-radius: 2px;
+  border-top-left-radius: 2px;
+  border-bottom-right-radius: 0;
+  border-bottom-left-radius: 0;
+}
+.navbar-btn {
+  margin-top: -1px;
+  margin-bottom: -1px;
+}
+.navbar-btn.btn-sm {
+  margin-top: 0px;
+  margin-bottom: 0px;
+}
+.navbar-btn.btn-xs {
+  margin-top: 4px;
+  margin-bottom: 4px;
+}
+.navbar-text {
+  margin-top: 6px;
+  margin-bottom: 6px;
+}
+@media (min-width: 541px) {
+  .navbar-text {
+    float: left;
+    margin-left: 0px;
+    margin-right: 0px;
+  }
+}
+@media (min-width: 541px) {
+  .navbar-left {
+    float: left !important;
+    float: left;
+  }
+  .navbar-right {
+    float: right !important;
+    float: right;
+    margin-right: 0px;
+  }
+  .navbar-right ~ .navbar-right {
+    margin-right: 0;
+  }
+}
+.navbar-default {
+  background-color: #f8f8f8;
+  border-color: #e7e7e7;
+}
+.navbar-default .navbar-brand {
+  color: #777;
+}
+.navbar-default .navbar-brand:hover,
+.navbar-default .navbar-brand:focus {
+  color: #5e5e5e;
+  background-color: transparent;
+}
+.navbar-default .navbar-text {
+  color: #777;
+}
+.navbar-default .navbar-nav > li > a {
+  color: #777;
+}
+.navbar-default .navbar-nav > li > a:hover,
+.navbar-default .navbar-nav > li > a:focus {
+  color: #333;
+  background-color: transparent;
+}
+.navbar-default .navbar-nav > .active > a,
+.navbar-default .navbar-nav > .active > a:hover,
+.navbar-default .navbar-nav > .active > a:focus {
+  color: #555;
+  background-color: #e7e7e7;
+}
+.navbar-default .navbar-nav > .disabled > a,
+.navbar-default .navbar-nav > .disabled > a:hover,
+.navbar-default .navbar-nav > .disabled > a:focus {
+  color: #ccc;
+  background-color: transparent;
+}
+.navbar-default .navbar-toggle {
+  border-color: #ddd;
+}
+.navbar-default .navbar-toggle:hover,
+.navbar-default .navbar-toggle:focus {
+  background-color: #ddd;
+}
+.navbar-default .navbar-toggle .icon-bar {
+  background-color: #888;
+}
+.navbar-default .navbar-collapse,
+.navbar-default .navbar-form {
+  border-color: #e7e7e7;
+}
+.navbar-default .navbar-nav > .open > a,
+.navbar-default .navbar-nav > .open > a:hover,
+.navbar-default .navbar-nav > .open > a:focus {
+  background-color: #e7e7e7;
+  color: #555;
+}
+@media (max-width: 540px) {
+  .navbar-default .navbar-nav .open .dropdown-menu > li > a {
+    color: #777;
+  }
+  .navbar-default .navbar-nav .open .dropdown-menu > li > a:hover,
+  .navbar-default .navbar-nav .open .dropdown-menu > li > a:focus {
+    color: #333;
+    background-color: transparent;
+  }
+  .navbar-default .navbar-nav .open .dropdown-menu > .active > a,
+  .navbar-default .navbar-nav .open .dropdown-menu > .active > a:hover,
+  .navbar-default .navbar-nav .open .dropdown-menu > .active > a:focus {
+    color: #555;
+    background-color: #e7e7e7;
+  }
+  .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a,
+  .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a:hover,
+  .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a:focus {
+    color: #ccc;
+    background-color: transparent;
+  }
+}
+.navbar-default .navbar-link {
+  color: #777;
+}
+.navbar-default .navbar-link:hover {
+  color: #333;
+}
+.navbar-default .btn-link {
+  color: #777;
+}
+.navbar-default .btn-link:hover,
+.navbar-default .btn-link:focus {
+  color: #333;
+}
+.navbar-default .btn-link[disabled]:hover,
+fieldset[disabled] .navbar-default .btn-link:hover,
+.navbar-default .btn-link[disabled]:focus,
+fieldset[disabled] .navbar-default .btn-link:focus {
+  color: #ccc;
+}
+.navbar-inverse {
+  background-color: #222;
+  border-color: #080808;
+}
+.navbar-inverse .navbar-brand {
+  color: #9d9d9d;
+}
+.navbar-inverse .navbar-brand:hover,
+.navbar-inverse .navbar-brand:focus {
+  color: #fff;
+  background-color: transparent;
+}
+.navbar-inverse .navbar-text {
+  color: #9d9d9d;
+}
+.navbar-inverse .navbar-nav > li > a {
+  color: #9d9d9d;
+}
+.navbar-inverse .navbar-nav > li > a:hover,
+.navbar-inverse .navbar-nav > li > a:focus {
+  color: #fff;
+  background-color: transparent;
+}
+.navbar-inverse .navbar-nav > .active > a,
+.navbar-inverse .navbar-nav > .active > a:hover,
+.navbar-inverse .navbar-nav > .active > a:focus {
+  color: #fff;
+  background-color: #080808;
+}
+.navbar-inverse .navbar-nav > .disabled > a,
+.navbar-inverse .navbar-nav > .disabled > a:hover,
+.navbar-inverse .navbar-nav > .disabled > a:focus {
+  color: #444;
+  background-color: transparent;
+}
+.navbar-inverse .navbar-toggle {
+  border-color: #333;
+}
+.navbar-inverse .navbar-toggle:hover,
+.navbar-inverse .navbar-toggle:focus {
+  background-color: #333;
+}
+.navbar-inverse .navbar-toggle .icon-bar {
+  background-color: #fff;
+}
+.navbar-inverse .navbar-collapse,
+.navbar-inverse .navbar-form {
+  border-color: #101010;
+}
+.navbar-inverse .navbar-nav > .open > a,
+.navbar-inverse .navbar-nav > .open > a:hover,
+.navbar-inverse .navbar-nav > .open > a:focus {
+  background-color: #080808;
+  color: #fff;
+}
+@media (max-width: 540px) {
+  .navbar-inverse .navbar-nav .open .dropdown-menu > .dropdown-header {
+    border-color: #080808;
+  }
+  .navbar-inverse .navbar-nav .open .dropdown-menu .divider {
+    background-color: #080808;
+  }
+  .navbar-inverse .navbar-nav .open .dropdown-menu > li > a {
+    color: #9d9d9d;
+  }
+  .navbar-inverse .navbar-nav .open .dropdown-menu > li > a:hover,
+  .navbar-inverse .navbar-nav .open .dropdown-menu > li > a:focus {
+    color: #fff;
+    background-color: transparent;
+  }
+  .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a,
+  .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a:hover,
+  .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a:focus {
+    color: #fff;
+    background-color: #080808;
+  }
+  .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a,
+  .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a:hover,
+  .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a:focus {
+    color: #444;
+    background-color: transparent;
+  }
+}
+.navbar-inverse .navbar-link {
+  color: #9d9d9d;
+}
+.navbar-inverse .navbar-link:hover {
+  color: #fff;
+}
+.navbar-inverse .btn-link {
+  color: #9d9d9d;
+}
+.navbar-inverse .btn-link:hover,
+.navbar-inverse .btn-link:focus {
+  color: #fff;
+}
+.navbar-inverse .btn-link[disabled]:hover,
+fieldset[disabled] .navbar-inverse .btn-link:hover,
+.navbar-inverse .btn-link[disabled]:focus,
+fieldset[disabled] .navbar-inverse .btn-link:focus {
+  color: #444;
+}
+.breadcrumb {
+  padding: 8px 15px;
+  margin-bottom: 18px;
+  list-style: none;
+  background-color: #f5f5f5;
+  border-radius: 2px;
+}
+.breadcrumb > li {
+  display: inline-block;
+}
+.breadcrumb > li + li:before {
+  content: "/\00a0";
+  padding: 0 5px;
+  color: #5e5e5e;
+}
+.breadcrumb > .active {
+  color: #777777;
+}
+.pagination {
+  display: inline-block;
+  padding-left: 0;
+  margin: 18px 0;
+  border-radius: 2px;
+}
+.pagination > li {
+  display: inline;
+}
+.pagination > li > a,
+.pagination > li > span {
+  position: relative;
+  float: left;
+  padding: 6px 12px;
+  line-height: 1.42857143;
+  text-decoration: none;
+  color: #337ab7;
+  background-color: #fff;
+  border: 1px solid #ddd;
+  margin-left: -1px;
+}
+.pagination > li:first-child > a,
+.pagination > li:first-child > span {
+  margin-left: 0;
+  border-bottom-left-radius: 2px;
+  border-top-left-radius: 2px;
+}
+.pagination > li:last-child > a,
+.pagination > li:last-child > span {
+  border-bottom-right-radius: 2px;
+  border-top-right-radius: 2px;
+}
+.pagination > li > a:hover,
+.pagination > li > span:hover,
+.pagination > li > a:focus,
+.pagination > li > span:focus {
+  z-index: 2;
+  color: #23527c;
+  background-color: #eeeeee;
+  border-color: #ddd;
+}
+.pagination > .active > a,
+.pagination > .active > span,
+.pagination > .active > a:hover,
+.pagination > .active > span:hover,
+.pagination > .active > a:focus,
+.pagination > .active > span:focus {
+  z-index: 3;
+  color: #fff;
+  background-color: #337ab7;
+  border-color: #337ab7;
+  cursor: default;
+}
+.pagination > .disabled > span,
+.pagination > .disabled > span:hover,
+.pagination > .disabled > span:focus,
+.pagination > .disabled > a,
+.pagination > .disabled > a:hover,
+.pagination > .disabled > a:focus {
+  color: #777777;
+  background-color: #fff;
+  border-color: #ddd;
+  cursor: not-allowed;
+}
+.pagination-lg > li > a,
+.pagination-lg > li > span {
+  padding: 10px 16px;
+  font-size: 17px;
+  line-height: 1.3333333;
+}
+.pagination-lg > li:first-child > a,
+.pagination-lg > li:first-child > span {
+  border-bottom-left-radius: 3px;
+  border-top-left-radius: 3px;
+}
+.pagination-lg > li:last-child > a,
+.pagination-lg > li:last-child > span {
+  border-bottom-right-radius: 3px;
+  border-top-right-radius: 3px;
+}
+.pagination-sm > li > a,
+.pagination-sm > li > span {
+  padding: 5px 10px;
+  font-size: 12px;
+  line-height: 1.5;
+}
+.pagination-sm > li:first-child > a,
+.pagination-sm > li:first-child > span {
+  border-bottom-left-radius: 1px;
+  border-top-left-radius: 1px;
+}
+.pagination-sm > li:last-child > a,
+.pagination-sm > li:last-child > span {
+  border-bottom-right-radius: 1px;
+  border-top-right-radius: 1px;
+}
+.pager {
+  padding-left: 0;
+  margin: 18px 0;
+  list-style: none;
+  text-align: center;
+}
+.pager li {
+  display: inline;
+}
+.pager li > a,
+.pager li > span {
+  display: inline-block;
+  padding: 5px 14px;
+  background-color: #fff;
+  border: 1px solid #ddd;
+  border-radius: 15px;
+}
+.pager li > a:hover,
+.pager li > a:focus {
+  text-decoration: none;
+  background-color: #eeeeee;
+}
+.pager .next > a,
+.pager .next > span {
+  float: right;
+}
+.pager .previous > a,
+.pager .previous > span {
+  float: left;
+}
+.pager .disabled > a,
+.pager .disabled > a:hover,
+.pager .disabled > a:focus,
+.pager .disabled > span {
+  color: #777777;
+  background-color: #fff;
+  cursor: not-allowed;
+}
+.label {
+  display: inline;
+  padding: .2em .6em .3em;
+  font-size: 75%;
+  font-weight: bold;
+  line-height: 1;
+  color: #fff;
+  text-align: center;
+  white-space: nowrap;
+  vertical-align: baseline;
+  border-radius: .25em;
+}
+a.label:hover,
+a.label:focus {
+  color: #fff;
+  text-decoration: none;
+  cursor: pointer;
+}
+.label:empty {
+  display: none;
+}
+.btn .label {
+  position: relative;
+  top: -1px;
+}
+.label-default {
+  background-color: #777777;
+}
+.label-default[href]:hover,
+.label-default[href]:focus {
+  background-color: #5e5e5e;
+}
+.label-primary {
+  background-color: #337ab7;
+}
+.label-primary[href]:hover,
+.label-primary[href]:focus {
+  background-color: #286090;
+}
+.label-success {
+  background-color: #5cb85c;
+}
+.label-success[href]:hover,
+.label-success[href]:focus {
+  background-color: #449d44;
+}
+.label-info {
+  background-color: #5bc0de;
+}
+.label-info[href]:hover,
+.label-info[href]:focus {
+  background-color: #31b0d5;
+}
+.label-warning {
+  background-color: #f0ad4e;
+}
+.label-warning[href]:hover,
+.label-warning[href]:focus {
+  background-color: #ec971f;
+}
+.label-danger {
+  background-color: #d9534f;
+}
+.label-danger[href]:hover,
+.label-danger[href]:focus {
+  background-color: #c9302c;
+}
+.badge {
+  display: inline-block;
+  min-width: 10px;
+  padding: 3px 7px;
+  font-size: 12px;
+  font-weight: bold;
+  color: #fff;
+  line-height: 1;
+  vertical-align: middle;
+  white-space: nowrap;
+  text-align: center;
+  background-color: #777777;
+  border-radius: 10px;
+}
+.badge:empty {
+  display: none;
+}
+.btn .badge {
+  position: relative;
+  top: -1px;
+}
+.btn-xs .badge,
+.btn-group-xs > .btn .badge {
+  top: 0;
+  padding: 1px 5px;
+}
+a.badge:hover,
+a.badge:focus {
+  color: #fff;
+  text-decoration: none;
+  cursor: pointer;
+}
+.list-group-item.active > .badge,
+.nav-pills > .active > a > .badge {
+  color: #337ab7;
+  background-color: #fff;
+}
+.list-group-item > .badge {
+  float: right;
+}
+.list-group-item > .badge + .badge {
+  margin-right: 5px;
+}
+.nav-pills > li > a > .badge {
+  margin-left: 3px;
+}
+.jumbotron {
+  padding-top: 30px;
+  padding-bottom: 30px;
+  margin-bottom: 30px;
+  color: inherit;
+  background-color: #eeeeee;
+}
+.jumbotron h1,
+.jumbotron .h1 {
+  color: inherit;
+}
+.jumbotron p {
+  margin-bottom: 15px;
+  font-size: 20px;
+  font-weight: 200;
+}
+.jumbotron > hr {
+  border-top-color: #d5d5d5;
+}
+.container .jumbotron,
+.container-fluid .jumbotron {
+  border-radius: 3px;
+  padding-left: 0px;
+  padding-right: 0px;
+}
+.jumbotron .container {
+  max-width: 100%;
+}
+@media screen and (min-width: 768px) {
+  .jumbotron {
+    padding-top: 48px;
+    padding-bottom: 48px;
+  }
+  .container .jumbotron,
+  .container-fluid .jumbotron {
+    padding-left: 60px;
+    padding-right: 60px;
+  }
+  .jumbotron h1,
+  .jumbotron .h1 {
+    font-size: 59px;
+  }
+}
+.thumbnail {
+  display: block;
+  padding: 4px;
+  margin-bottom: 18px;
+  line-height: 1.42857143;
+  background-color: #fff;
+  border: 1px solid #ddd;
+  border-radius: 2px;
+  -webkit-transition: border 0.2s ease-in-out;
+  -o-transition: border 0.2s ease-in-out;
+  transition: border 0.2s ease-in-out;
+}
+.thumbnail > img,
+.thumbnail a > img {
+  margin-left: auto;
+  margin-right: auto;
+}
+a.thumbnail:hover,
+a.thumbnail:focus,
+a.thumbnail.active {
+  border-color: #337ab7;
+}
+.thumbnail .caption {
+  padding: 9px;
+  color: #000;
+}
+.alert {
+  padding: 15px;
+  margin-bottom: 18px;
+  border: 1px solid transparent;
+  border-radius: 2px;
+}
+.alert h4 {
+  margin-top: 0;
+  color: inherit;
+}
+.alert .alert-link {
+  font-weight: bold;
+}
+.alert > p,
+.alert > ul {
+  margin-bottom: 0;
+}
+.alert > p + p {
+  margin-top: 5px;
+}
+.alert-dismissable,
+.alert-dismissible {
+  padding-right: 35px;
+}
+.alert-dismissable .close,
+.alert-dismissible .close {
+  position: relative;
+  top: -2px;
+  right: -21px;
+  color: inherit;
+}
+.alert-success {
+  background-color: #dff0d8;
+  border-color: #d6e9c6;
+  color: #3c763d;
+}
+.alert-success hr {
+  border-top-color: #c9e2b3;
+}
+.alert-success .alert-link {
+  color: #2b542c;
+}
+.alert-info {
+  background-color: #d9edf7;
+  border-color: #bce8f1;
+  color: #31708f;
+}
+.alert-info hr {
+  border-top-color: #a6e1ec;
+}
+.alert-info .alert-link {
+  color: #245269;
+}
+.alert-warning {
+  background-color: #fcf8e3;
+  border-color: #faebcc;
+  color: #8a6d3b;
+}
+.alert-warning hr {
+  border-top-color: #f7e1b5;
+}
+.alert-warning .alert-link {
+  color: #66512c;
+}
+.alert-danger {
+  background-color: #f2dede;
+  border-color: #ebccd1;
+  color: #a94442;
+}
+.alert-danger hr {
+  border-top-color: #e4b9c0;
+}
+.alert-danger .alert-link {
+  color: #843534;
+}
+@-webkit-keyframes progress-bar-stripes {
+  from {
+    background-position: 40px 0;
+  }
+  to {
+    background-position: 0 0;
+  }
+}
+@keyframes progress-bar-stripes {
+  from {
+    background-position: 40px 0;
+  }
+  to {
+    background-position: 0 0;
+  }
+}
+.progress {
+  overflow: hidden;
+  height: 18px;
+  margin-bottom: 18px;
+  background-color: #f5f5f5;
+  border-radius: 2px;
+  -webkit-box-shadow: inset 0 1px 2px rgba(0, 0, 0, 0.1);
+  box-shadow: inset 0 1px 2px rgba(0, 0, 0, 0.1);
+}
+.progress-bar {
+  float: left;
+  width: 0%;
+  height: 100%;
+  font-size: 12px;
+  line-height: 18px;
+  color: #fff;
+  text-align: center;
+  background-color: #337ab7;
+  -webkit-box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.15);
+  box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.15);
+  -webkit-transition: width 0.6s ease;
+  -o-transition: width 0.6s ease;
+  transition: width 0.6s ease;
+}
+.progress-striped .progress-bar,
+.progress-bar-striped {
+  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
+  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
+  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
+  background-size: 40px 40px;
+}
+.progress.active .progress-bar,
+.progress-bar.active {
+  -webkit-animation: progress-bar-stripes 2s linear infinite;
+  -o-animation: progress-bar-stripes 2s linear infinite;
+  animation: progress-bar-stripes 2s linear infinite;
+}
+.progress-bar-success {
+  background-color: #5cb85c;
+}
+.progress-striped .progress-bar-success {
+  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
+  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
+  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
+}
+.progress-bar-info {
+  background-color: #5bc0de;
+}
+.progress-striped .progress-bar-info {
+  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
+  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
+  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
+}
+.progress-bar-warning {
+  background-color: #f0ad4e;
+}
+.progress-striped .progress-bar-warning {
+  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
+  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
+  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
+}
+.progress-bar-danger {
+  background-color: #d9534f;
+}
+.progress-striped .progress-bar-danger {
+  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
+  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
+  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
+}
+.media {
+  margin-top: 15px;
+}
+.media:first-child {
+  margin-top: 0;
+}
+.media,
+.media-body {
+  zoom: 1;
+  overflow: hidden;
+}
+.media-body {
+  width: 10000px;
+}
+.media-object {
+  display: block;
+}
+.media-object.img-thumbnail {
+  max-width: none;
+}
+.media-right,
+.media > .pull-right {
+  padding-left: 10px;
+}
+.media-left,
+.media > .pull-left {
+  padding-right: 10px;
+}
+.media-left,
+.media-right,
+.media-body {
+  display: table-cell;
+  vertical-align: top;
+}
+.media-middle {
+  vertical-align: middle;
+}
+.media-bottom {
+  vertical-align: bottom;
+}
+.media-heading {
+  margin-top: 0;
+  margin-bottom: 5px;
+}
+.media-list {
+  padding-left: 0;
+  list-style: none;
+}
+.list-group {
+  margin-bottom: 20px;
+  padding-left: 0;
+}
+.list-group-item {
+  position: relative;
+  display: block;
+  padding: 10px 15px;
+  margin-bottom: -1px;
+  background-color: #fff;
+  border: 1px solid #ddd;
+}
+.list-group-item:first-child {
+  border-top-right-radius: 2px;
+  border-top-left-radius: 2px;
+}
+.list-group-item:last-child {
+  margin-bottom: 0;
+  border-bottom-right-radius: 2px;
+  border-bottom-left-radius: 2px;
+}
+a.list-group-item,
+button.list-group-item {
+  color: #555;
+}
+a.list-group-item .list-group-item-heading,
+button.list-group-item .list-group-item-heading {
+  color: #333;
+}
+a.list-group-item:hover,
+button.list-group-item:hover,
+a.list-group-item:focus,
+button.list-group-item:focus {
+  text-decoration: none;
+  color: #555;
+  background-color: #f5f5f5;
+}
+button.list-group-item {
+  width: 100%;
+  text-align: left;
+}
+.list-group-item.disabled,
+.list-group-item.disabled:hover,
+.list-group-item.disabled:focus {
+  background-color: #eeeeee;
+  color: #777777;
+  cursor: not-allowed;
+}
+.list-group-item.disabled .list-group-item-heading,
+.list-group-item.disabled:hover .list-group-item-heading,
+.list-group-item.disabled:focus .list-group-item-heading {
+  color: inherit;
+}
+.list-group-item.disabled .list-group-item-text,
+.list-group-item.disabled:hover .list-group-item-text,
+.list-group-item.disabled:focus .list-group-item-text {
+  color: #777777;
+}
+.list-group-item.active,
+.list-group-item.active:hover,
+.list-group-item.active:focus {
+  z-index: 2;
+  color: #fff;
+  background-color: #337ab7;
+  border-color: #337ab7;
+}
+.list-group-item.active .list-group-item-heading,
+.list-group-item.active:hover .list-group-item-heading,
+.list-group-item.active:focus .list-group-item-heading,
+.list-group-item.active .list-group-item-heading > small,
+.list-group-item.active:hover .list-group-item-heading > small,
+.list-group-item.active:focus .list-group-item-heading > small,
+.list-group-item.active .list-group-item-heading > .small,
+.list-group-item.active:hover .list-group-item-heading > .small,
+.list-group-item.active:focus .list-group-item-heading > .small {
+  color: inherit;
+}
+.list-group-item.active .list-group-item-text,
+.list-group-item.active:hover .list-group-item-text,
+.list-group-item.active:focus .list-group-item-text {
+  color: #c7ddef;
+}
+.list-group-item-success {
+  color: #3c763d;
+  background-color: #dff0d8;
+}
+a.list-group-item-success,
+button.list-group-item-success {
+  color: #3c763d;
+}
+a.list-group-item-success .list-group-item-heading,
+button.list-group-item-success .list-group-item-heading {
+  color: inherit;
+}
+a.list-group-item-success:hover,
+button.list-group-item-success:hover,
+a.list-group-item-success:focus,
+button.list-group-item-success:focus {
+  color: #3c763d;
+  background-color: #d0e9c6;
+}
+a.list-group-item-success.active,
+button.list-group-item-success.active,
+a.list-group-item-success.active:hover,
+button.list-group-item-success.active:hover,
+a.list-group-item-success.active:focus,
+button.list-group-item-success.active:focus {
+  color: #fff;
+  background-color: #3c763d;
+  border-color: #3c763d;
+}
+.list-group-item-info {
+  color: #31708f;
+  background-color: #d9edf7;
+}
+a.list-group-item-info,
+button.list-group-item-info {
+  color: #31708f;
+}
+a.list-group-item-info .list-group-item-heading,
+button.list-group-item-info .list-group-item-heading {
+  color: inherit;
+}
+a.list-group-item-info:hover,
+button.list-group-item-info:hover,
+a.list-group-item-info:focus,
+button.list-group-item-info:focus {
+  color: #31708f;
+  background-color: #c4e3f3;
+}
+a.list-group-item-info.active,
+button.list-group-item-info.active,
+a.list-group-item-info.active:hover,
+button.list-group-item-info.active:hover,
+a.list-group-item-info.active:focus,
+button.list-group-item-info.active:focus {
+  color: #fff;
+  background-color: #31708f;
+  border-color: #31708f;
+}
+.list-group-item-warning {
+  color: #8a6d3b;
+  background-color: #fcf8e3;
+}
+a.list-group-item-warning,
+button.list-group-item-warning {
+  color: #8a6d3b;
+}
+a.list-group-item-warning .list-group-item-heading,
+button.list-group-item-warning .list-group-item-heading {
+  color: inherit;
+}
+a.list-group-item-warning:hover,
+button.list-group-item-warning:hover,
+a.list-group-item-warning:focus,
+button.list-group-item-warning:focus {
+  color: #8a6d3b;
+  background-color: #faf2cc;
+}
+a.list-group-item-warning.active,
+button.list-group-item-warning.active,
+a.list-group-item-warning.active:hover,
+button.list-group-item-warning.active:hover,
+a.list-group-item-warning.active:focus,
+button.list-group-item-warning.active:focus {
+  color: #fff;
+  background-color: #8a6d3b;
+  border-color: #8a6d3b;
+}
+.list-group-item-danger {
+  color: #a94442;
+  background-color: #f2dede;
+}
+a.list-group-item-danger,
+button.list-group-item-danger {
+  color: #a94442;
+}
+a.list-group-item-danger .list-group-item-heading,
+button.list-group-item-danger .list-group-item-heading {
+  color: inherit;
+}
+a.list-group-item-danger:hover,
+button.list-group-item-danger:hover,
+a.list-group-item-danger:focus,
+button.list-group-item-danger:focus {
+  color: #a94442;
+  background-color: #ebcccc;
+}
+a.list-group-item-danger.active,
+button.list-group-item-danger.active,
+a.list-group-item-danger.active:hover,
+button.list-group-item-danger.active:hover,
+a.list-group-item-danger.active:focus,
+button.list-group-item-danger.active:focus {
+  color: #fff;
+  background-color: #a94442;
+  border-color: #a94442;
+}
+.list-group-item-heading {
+  margin-top: 0;
+  margin-bottom: 5px;
+}
+.list-group-item-text {
+  margin-bottom: 0;
+  line-height: 1.3;
+}
+.panel {
+  margin-bottom: 18px;
+  background-color: #fff;
+  border: 1px solid transparent;
+  border-radius: 2px;
+  -webkit-box-shadow: 0 1px 1px rgba(0, 0, 0, 0.05);
+  box-shadow: 0 1px 1px rgba(0, 0, 0, 0.05);
+}
+.panel-body {
+  padding: 15px;
+}
+.panel-heading {
+  padding: 10px 15px;
+  border-bottom: 1px solid transparent;
+  border-top-right-radius: 1px;
+  border-top-left-radius: 1px;
+}
+.panel-heading > .dropdown .dropdown-toggle {
+  color: inherit;
+}
+.panel-title {
+  margin-top: 0;
+  margin-bottom: 0;
+  font-size: 15px;
+  color: inherit;
+}
+.panel-title > a,
+.panel-title > small,
+.panel-title > .small,
+.panel-title > small > a,
+.panel-title > .small > a {
+  color: inherit;
+}
+.panel-footer {
+  padding: 10px 15px;
+  background-color: #f5f5f5;
+  border-top: 1px solid #ddd;
+  border-bottom-right-radius: 1px;
+  border-bottom-left-radius: 1px;
+}
+.panel > .list-group,
+.panel > .panel-collapse > .list-group {
+  margin-bottom: 0;
+}
+.panel > .list-group .list-group-item,
+.panel > .panel-collapse > .list-group .list-group-item {
+  border-width: 1px 0;
+  border-radius: 0;
+}
+.panel > .list-group:first-child .list-group-item:first-child,
+.panel > .panel-collapse > .list-group:first-child .list-group-item:first-child {
+  border-top: 0;
+  border-top-right-radius: 1px;
+  border-top-left-radius: 1px;
+}
+.panel > .list-group:last-child .list-group-item:last-child,
+.panel > .panel-collapse > .list-group:last-child .list-group-item:last-child {
+  border-bottom: 0;
+  border-bottom-right-radius: 1px;
+  border-bottom-left-radius: 1px;
+}
+.panel > .panel-heading + .panel-collapse > .list-group .list-group-item:first-child {
+  border-top-right-radius: 0;
+  border-top-left-radius: 0;
+}
+.panel-heading + .list-group .list-group-item:first-child {
+  border-top-width: 0;
+}
+.list-group + .panel-footer {
+  border-top-width: 0;
+}
+.panel > .table,
+.panel > .table-responsive > .table,
+.panel > .panel-collapse > .table {
+  margin-bottom: 0;
+}
+.panel > .table caption,
+.panel > .table-responsive > .table caption,
+.panel > .panel-collapse > .table caption {
+  padding-left: 15px;
+  padding-right: 15px;
+}
+.panel > .table:first-child,
+.panel > .table-responsive:first-child > .table:first-child {
+  border-top-right-radius: 1px;
+  border-top-left-radius: 1px;
+}
+.panel > .table:first-child > thead:first-child > tr:first-child,
+.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child,
+.panel > .table:first-child > tbody:first-child > tr:first-child,
+.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child {
+  border-top-left-radius: 1px;
+  border-top-right-radius: 1px;
+}
+.panel > .table:first-child > thead:first-child > tr:first-child td:first-child,
+.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child td:first-child,
+.panel > .table:first-child > tbody:first-child > tr:first-child td:first-child,
+.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child td:first-child,
+.panel > .table:first-child > thead:first-child > tr:first-child th:first-child,
+.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child th:first-child,
+.panel > .table:first-child > tbody:first-child > tr:first-child th:first-child,
+.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child th:first-child {
+  border-top-left-radius: 1px;
+}
+.panel > .table:first-child > thead:first-child > tr:first-child td:last-child,
+.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child td:last-child,
+.panel > .table:first-child > tbody:first-child > tr:first-child td:last-child,
+.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child td:last-child,
+.panel > .table:first-child > thead:first-child > tr:first-child th:last-child,
+.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child th:last-child,
+.panel > .table:first-child > tbody:first-child > tr:first-child th:last-child,
+.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child th:last-child {
+  border-top-right-radius: 1px;
+}
+.panel > .table:last-child,
+.panel > .table-responsive:last-child > .table:last-child {
+  border-bottom-right-radius: 1px;
+  border-bottom-left-radius: 1px;
+}
+.panel > .table:last-child > tbody:last-child > tr:last-child,
+.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child,
+.panel > .table:last-child > tfoot:last-child > tr:last-child,
+.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child {
+  border-bottom-left-radius: 1px;
+  border-bottom-right-radius: 1px;
+}
+.panel > .table:last-child > tbody:last-child > tr:last-child td:first-child,
+.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child td:first-child,
+.panel > .table:last-child > tfoot:last-child > tr:last-child td:first-child,
+.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child td:first-child,
+.panel > .table:last-child > tbody:last-child > tr:last-child th:first-child,
+.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child th:first-child,
+.panel > .table:last-child > tfoot:last-child > tr:last-child th:first-child,
+.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child th:first-child {
+  border-bottom-left-radius: 1px;
+}
+.panel > .table:last-child > tbody:last-child > tr:last-child td:last-child,
+.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child td:last-child,
+.panel > .table:last-child > tfoot:last-child > tr:last-child td:last-child,
+.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child td:last-child,
+.panel > .table:last-child > tbody:last-child > tr:last-child th:last-child,
+.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child th:last-child,
+.panel > .table:last-child > tfoot:last-child > tr:last-child th:last-child,
+.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child th:last-child {
+  border-bottom-right-radius: 1px;
+}
+.panel > .panel-body + .table,
+.panel > .panel-body + .table-responsive,
+.panel > .table + .panel-body,
+.panel > .table-responsive + .panel-body {
+  border-top: 1px solid #ddd;
+}
+.panel > .table > tbody:first-child > tr:first-child th,
+.panel > .table > tbody:first-child > tr:first-child td {
+  border-top: 0;
+}
+.panel > .table-bordered,
+.panel > .table-responsive > .table-bordered {
+  border: 0;
+}
+.panel > .table-bordered > thead > tr > th:first-child,
+.panel > .table-responsive > .table-bordered > thead > tr > th:first-child,
+.panel > .table-bordered > tbody > tr > th:first-child,
+.panel > .table-responsive > .table-bordered > tbody > tr > th:first-child,
+.panel > .table-bordered > tfoot > tr > th:first-child,
+.panel > .table-responsive > .table-bordered > tfoot > tr > th:first-child,
+.panel > .table-bordered > thead > tr > td:first-child,
+.panel > .table-responsive > .table-bordered > thead > tr > td:first-child,
+.panel > .table-bordered > tbody > tr > td:first-child,
+.panel > .table-responsive > .table-bordered > tbody > tr > td:first-child,
+.panel > .table-bordered > tfoot > tr > td:first-child,
+.panel > .table-responsive > .table-bordered > tfoot > tr > td:first-child {
+  border-left: 0;
+}
+.panel > .table-bordered > thead > tr > th:last-child,
+.panel > .table-responsive > .table-bordered > thead > tr > th:last-child,
+.panel > .table-bordered > tbody > tr > th:last-child,
+.panel > .table-responsive > .table-bordered > tbody > tr > th:last-child,
+.panel > .table-bordered > tfoot > tr > th:last-child,
+.panel > .table-responsive > .table-bordered > tfoot > tr > th:last-child,
+.panel > .table-bordered > thead > tr > td:last-child,
+.panel > .table-responsive > .table-bordered > thead > tr > td:last-child,
+.panel > .table-bordered > tbody > tr > td:last-child,
+.panel > .table-responsive > .table-bordered > tbody > tr > td:last-child,
+.panel > .table-bordered > tfoot > tr > td:last-child,
+.panel > .table-responsive > .table-bordered > tfoot > tr > td:last-child {
+  border-right: 0;
+}
+.panel > .table-bordered > thead > tr:first-child > td,
+.panel > .table-responsive > .table-bordered > thead > tr:first-child > td,
+.panel > .table-bordered > tbody > tr:first-child > td,
+.panel > .table-responsive > .table-bordered > tbody > tr:first-child > td,
+.panel > .table-bordered > thead > tr:first-child > th,
+.panel > .table-responsive > .table-bordered > thead > tr:first-child > th,
+.panel > .table-bordered > tbody > tr:first-child > th,
+.panel > .table-responsive > .table-bordered > tbody > tr:first-child > th {
+  border-bottom: 0;
+}
+.panel > .table-bordered > tbody > tr:last-child > td,
+.panel > .table-responsive > .table-bordered > tbody > tr:last-child > td,
+.panel > .table-bordered > tfoot > tr:last-child > td,
+.panel > .table-responsive > .table-bordered > tfoot > tr:last-child > td,
+.panel > .table-bordered > tbody > tr:last-child > th,
+.panel > .table-responsive > .table-bordered > tbody > tr:last-child > th,
+.panel > .table-bordered > tfoot > tr:last-child > th,
+.panel > .table-responsive > .table-bordered > tfoot > tr:last-child > th {
+  border-bottom: 0;
+}
+.panel > .table-responsive {
+  border: 0;
+  margin-bottom: 0;
+}
+.panel-group {
+  margin-bottom: 18px;
+}
+.panel-group .panel {
+  margin-bottom: 0;
+  border-radius: 2px;
+}
+.panel-group .panel + .panel {
+  margin-top: 5px;
+}
+.panel-group .panel-heading {
+  border-bottom: 0;
+}
+.panel-group .panel-heading + .panel-collapse > .panel-body,
+.panel-group .panel-heading + .panel-collapse > .list-group {
+  border-top: 1px solid #ddd;
+}
+.panel-group .panel-footer {
+  border-top: 0;
+}
+.panel-group .panel-footer + .panel-collapse .panel-body {
+  border-bottom: 1px solid #ddd;
+}
+.panel-default {
+  border-color: #ddd;
+}
+.panel-default > .panel-heading {
+  color: #333333;
+  background-color: #f5f5f5;
+  border-color: #ddd;
+}
+.panel-default > .panel-heading + .panel-collapse > .panel-body {
+  border-top-color: #ddd;
+}
+.panel-default > .panel-heading .badge {
+  color: #f5f5f5;
+  background-color: #333333;
+}
+.panel-default > .panel-footer + .panel-collapse > .panel-body {
+  border-bottom-color: #ddd;
+}
+.panel-primary {
+  border-color: #337ab7;
+}
+.panel-primary > .panel-heading {
+  color: #fff;
+  background-color: #337ab7;
+  border-color: #337ab7;
+}
+.panel-primary > .panel-heading + .panel-collapse > .panel-body {
+  border-top-color: #337ab7;
+}
+.panel-primary > .panel-heading .badge {
+  color: #337ab7;
+  background-color: #fff;
+}
+.panel-primary > .panel-footer + .panel-collapse > .panel-body {
+  border-bottom-color: #337ab7;
+}
+.panel-success {
+  border-color: #d6e9c6;
+}
+.panel-success > .panel-heading {
+  color: #3c763d;
+  background-color: #dff0d8;
+  border-color: #d6e9c6;
+}
+.panel-success > .panel-heading + .panel-collapse > .panel-body {
+  border-top-color: #d6e9c6;
+}
+.panel-success > .panel-heading .badge {
+  color: #dff0d8;
+  background-color: #3c763d;
+}
+.panel-success > .panel-footer + .panel-collapse > .panel-body {
+  border-bottom-color: #d6e9c6;
+}
+.panel-info {
+  border-color: #bce8f1;
+}
+.panel-info > .panel-heading {
+  color: #31708f;
+  background-color: #d9edf7;
+  border-color: #bce8f1;
+}
+.panel-info > .panel-heading + .panel-collapse > .panel-body {
+  border-top-color: #bce8f1;
+}
+.panel-info > .panel-heading .badge {
+  color: #d9edf7;
+  background-color: #31708f;
+}
+.panel-info > .panel-footer + .panel-collapse > .panel-body {
+  border-bottom-color: #bce8f1;
+}
+.panel-warning {
+  border-color: #faebcc;
+}
+.panel-warning > .panel-heading {
+  color: #8a6d3b;
+  background-color: #fcf8e3;
+  border-color: #faebcc;
+}
+.panel-warning > .panel-heading + .panel-collapse > .panel-body {
+  border-top-color: #faebcc;
+}
+.panel-warning > .panel-heading .badge {
+  color: #fcf8e3;
+  background-color: #8a6d3b;
+}
+.panel-warning > .panel-footer + .panel-collapse > .panel-body {
+  border-bottom-color: #faebcc;
+}
+.panel-danger {
+  border-color: #ebccd1;
+}
+.panel-danger > .panel-heading {
+  color: #a94442;
+  background-color: #f2dede;
+  border-color: #ebccd1;
+}
+.panel-danger > .panel-heading + .panel-collapse > .panel-body {
+  border-top-color: #ebccd1;
+}
+.panel-danger > .panel-heading .badge {
+  color: #f2dede;
+  background-color: #a94442;
+}
+.panel-danger > .panel-footer + .panel-collapse > .panel-body {
+  border-bottom-color: #ebccd1;
+}
+.embed-responsive {
+  position: relative;
+  display: block;
+  height: 0;
+  padding: 0;
+  overflow: hidden;
+}
+.embed-responsive .embed-responsive-item,
+.embed-responsive iframe,
+.embed-responsive embed,
+.embed-responsive object,
+.embed-responsive video {
+  position: absolute;
+  top: 0;
+  left: 0;
+  bottom: 0;
+  height: 100%;
+  width: 100%;
+  border: 0;
+}
+.embed-responsive-16by9 {
+  padding-bottom: 56.25%;
+}
+.embed-responsive-4by3 {
+  padding-bottom: 75%;
+}
+.well {
+  min-height: 20px;
+  padding: 19px;
+  margin-bottom: 20px;
+  background-color: #f5f5f5;
+  border: 1px solid #e3e3e3;
+  border-radius: 2px;
+  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.05);
+  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.05);
+}
+.well blockquote {
+  border-color: #ddd;
+  border-color: rgba(0, 0, 0, 0.15);
+}
+.well-lg {
+  padding: 24px;
+  border-radius: 3px;
+}
+.well-sm {
+  padding: 9px;
+  border-radius: 1px;
+}
+.close {
+  float: right;
+  font-size: 19.5px;
+  font-weight: bold;
+  line-height: 1;
+  color: #000;
+  text-shadow: 0 1px 0 #fff;
+  opacity: 0.2;
+  filter: alpha(opacity=20);
+}
+.close:hover,
+.close:focus {
+  color: #000;
+  text-decoration: none;
+  cursor: pointer;
+  opacity: 0.5;
+  filter: alpha(opacity=50);
+}
+button.close {
+  padding: 0;
+  cursor: pointer;
+  background: transparent;
+  border: 0;
+  -webkit-appearance: none;
+}
+.modal-open {
+  overflow: hidden;
+}
+.modal {
+  display: none;
+  overflow: hidden;
+  position: fixed;
+  top: 0;
+  right: 0;
+  bottom: 0;
+  left: 0;
+  z-index: 1050;
+  -webkit-overflow-scrolling: touch;
+  outline: 0;
+}
+.modal.fade .modal-dialog {
+  -webkit-transform: translate(0, -25%);
+  -ms-transform: translate(0, -25%);
+  -o-transform: translate(0, -25%);
+  transform: translate(0, -25%);
+  -webkit-transition: -webkit-transform 0.3s ease-out;
+  -moz-transition: -moz-transform 0.3s ease-out;
+  -o-transition: -o-transform 0.3s ease-out;
+  transition: transform 0.3s ease-out;
+}
+.modal.in .modal-dialog {
+  -webkit-transform: translate(0, 0);
+  -ms-transform: translate(0, 0);
+  -o-transform: translate(0, 0);
+  transform: translate(0, 0);
+}
+.modal-open .modal {
+  overflow-x: hidden;
+  overflow-y: auto;
+}
+.modal-dialog {
+  position: relative;
+  width: auto;
+  margin: 10px;
+}
+.modal-content {
+  position: relative;
+  background-color: #fff;
+  border: 1px solid #999;
+  border: 1px solid rgba(0, 0, 0, 0.2);
+  border-radius: 3px;
+  -webkit-box-shadow: 0 3px 9px rgba(0, 0, 0, 0.5);
+  box-shadow: 0 3px 9px rgba(0, 0, 0, 0.5);
+  background-clip: padding-box;
+  outline: 0;
+}
+.modal-backdrop {
+  position: fixed;
+  top: 0;
+  right: 0;
+  bottom: 0;
+  left: 0;
+  z-index: 1040;
+  background-color: #000;
+}
+.modal-backdrop.fade {
+  opacity: 0;
+  filter: alpha(opacity=0);
+}
+.modal-backdrop.in {
+  opacity: 0.5;
+  filter: alpha(opacity=50);
+}
+.modal-header {
+  padding: 15px;
+  border-bottom: 1px solid #e5e5e5;
+}
+.modal-header .close {
+  margin-top: -2px;
+}
+.modal-title {
+  margin: 0;
+  line-height: 1.42857143;
+}
+.modal-body {
+  position: relative;
+  padding: 15px;
+}
+.modal-footer {
+  padding: 15px;
+  text-align: right;
+  border-top: 1px solid #e5e5e5;
+}
+.modal-footer .btn + .btn {
+  margin-left: 5px;
+  margin-bottom: 0;
+}
+.modal-footer .btn-group .btn + .btn {
+  margin-left: -1px;
+}
+.modal-footer .btn-block + .btn-block {
+  margin-left: 0;
+}
+.modal-scrollbar-measure {
+  position: absolute;
+  top: -9999px;
+  width: 50px;
+  height: 50px;
+  overflow: scroll;
+}
+@media (min-width: 768px) {
+  .modal-dialog {
+    width: 600px;
+    margin: 30px auto;
+  }
+  .modal-content {
+    -webkit-box-shadow: 0 5px 15px rgba(0, 0, 0, 0.5);
+    box-shadow: 0 5px 15px rgba(0, 0, 0, 0.5);
+  }
+  .modal-sm {
+    width: 300px;
+  }
+}
+@media (min-width: 992px) {
+  .modal-lg {
+    width: 900px;
+  }
+}
+.tooltip {
+  position: absolute;
+  z-index: 1070;
+  display: block;
+  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
+  font-style: normal;
+  font-weight: normal;
+  letter-spacing: normal;
+  line-break: auto;
+  line-height: 1.42857143;
+  text-align: left;
+  text-align: start;
+  text-decoration: none;
+  text-shadow: none;
+  text-transform: none;
+  white-space: normal;
+  word-break: normal;
+  word-spacing: normal;
+  word-wrap: normal;
+  font-size: 12px;
+  opacity: 0;
+  filter: alpha(opacity=0);
+}
+.tooltip.in {
+  opacity: 0.9;
+  filter: alpha(opacity=90);
+}
+.tooltip.top {
+  margin-top: -3px;
+  padding: 5px 0;
+}
+.tooltip.right {
+  margin-left: 3px;
+  padding: 0 5px;
+}
+.tooltip.bottom {
+  margin-top: 3px;
+  padding: 5px 0;
+}
+.tooltip.left {
+  margin-left: -3px;
+  padding: 0 5px;
+}
+.tooltip-inner {
+  max-width: 200px;
+  padding: 3px 8px;
+  color: #fff;
+  text-align: center;
+  background-color: #000;
+  border-radius: 2px;
+}
+.tooltip-arrow {
+  position: absolute;
+  width: 0;
+  height: 0;
+  border-color: transparent;
+  border-style: solid;
+}
+.tooltip.top .tooltip-arrow {
+  bottom: 0;
+  left: 50%;
+  margin-left: -5px;
+  border-width: 5px 5px 0;
+  border-top-color: #000;
+}
+.tooltip.top-left .tooltip-arrow {
+  bottom: 0;
+  right: 5px;
+  margin-bottom: -5px;
+  border-width: 5px 5px 0;
+  border-top-color: #000;
+}
+.tooltip.top-right .tooltip-arrow {
+  bottom: 0;
+  left: 5px;
+  margin-bottom: -5px;
+  border-width: 5px 5px 0;
+  border-top-color: #000;
+}
+.tooltip.right .tooltip-arrow {
+  top: 50%;
+  left: 0;
+  margin-top: -5px;
+  border-width: 5px 5px 5px 0;
+  border-right-color: #000;
+}
+.tooltip.left .tooltip-arrow {
+  top: 50%;
+  right: 0;
+  margin-top: -5px;
+  border-width: 5px 0 5px 5px;
+  border-left-color: #000;
+}
+.tooltip.bottom .tooltip-arrow {
+  top: 0;
+  left: 50%;
+  margin-left: -5px;
+  border-width: 0 5px 5px;
+  border-bottom-color: #000;
+}
+.tooltip.bottom-left .tooltip-arrow {
+  top: 0;
+  right: 5px;
+  margin-top: -5px;
+  border-width: 0 5px 5px;
+  border-bottom-color: #000;
+}
+.tooltip.bottom-right .tooltip-arrow {
+  top: 0;
+  left: 5px;
+  margin-top: -5px;
+  border-width: 0 5px 5px;
+  border-bottom-color: #000;
+}
+.popover {
+  position: absolute;
+  top: 0;
+  left: 0;
+  z-index: 1060;
+  display: none;
+  max-width: 276px;
+  padding: 1px;
+  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
+  font-style: normal;
+  font-weight: normal;
+  letter-spacing: normal;
+  line-break: auto;
+  line-height: 1.42857143;
+  text-align: left;
+  text-align: start;
+  text-decoration: none;
+  text-shadow: none;
+  text-transform: none;
+  white-space: normal;
+  word-break: normal;
+  word-spacing: normal;
+  word-wrap: normal;
+  font-size: 13px;
+  background-color: #fff;
+  background-clip: padding-box;
+  border: 1px solid #ccc;
+  border: 1px solid rgba(0, 0, 0, 0.2);
+  border-radius: 3px;
+  -webkit-box-shadow: 0 5px 10px rgba(0, 0, 0, 0.2);
+  box-shadow: 0 5px 10px rgba(0, 0, 0, 0.2);
+}
+.popover.top {
+  margin-top: -10px;
+}
+.popover.right {
+  margin-left: 10px;
+}
+.popover.bottom {
+  margin-top: 10px;
+}
+.popover.left {
+  margin-left: -10px;
+}
+.popover-title {
+  margin: 0;
+  padding: 8px 14px;
+  font-size: 13px;
+  background-color: #f7f7f7;
+  border-bottom: 1px solid #ebebeb;
+  border-radius: 2px 2px 0 0;
+}
+.popover-content {
+  padding: 9px 14px;
+}
+.popover > .arrow,
+.popover > .arrow:after {
+  position: absolute;
+  display: block;
+  width: 0;
+  height: 0;
+  border-color: transparent;
+  border-style: solid;
+}
+.popover > .arrow {
+  border-width: 11px;
+}
+.popover > .arrow:after {
+  border-width: 10px;
+  content: "";
+}
+.popover.top > .arrow {
+  left: 50%;
+  margin-left: -11px;
+  border-bottom-width: 0;
+  border-top-color: #999999;
+  border-top-color: rgba(0, 0, 0, 0.25);
+  bottom: -11px;
+}
+.popover.top > .arrow:after {
+  content: " ";
+  bottom: 1px;
+  margin-left: -10px;
+  border-bottom-width: 0;
+  border-top-color: #fff;
+}
+.popover.right > .arrow {
+  top: 50%;
+  left: -11px;
+  margin-top: -11px;
+  border-left-width: 0;
+  border-right-color: #999999;
+  border-right-color: rgba(0, 0, 0, 0.25);
+}
+.popover.right > .arrow:after {
+  content: " ";
+  left: 1px;
+  bottom: -10px;
+  border-left-width: 0;
+  border-right-color: #fff;
+}
+.popover.bottom > .arrow {
+  left: 50%;
+  margin-left: -11px;
+  border-top-width: 0;
+  border-bottom-color: #999999;
+  border-bottom-color: rgba(0, 0, 0, 0.25);
+  top: -11px;
+}
+.popover.bottom > .arrow:after {
+  content: " ";
+  top: 1px;
+  margin-left: -10px;
+  border-top-width: 0;
+  border-bottom-color: #fff;
+}
+.popover.left > .arrow {
+  top: 50%;
+  right: -11px;
+  margin-top: -11px;
+  border-right-width: 0;
+  border-left-color: #999999;
+  border-left-color: rgba(0, 0, 0, 0.25);
+}
+.popover.left > .arrow:after {
+  content: " ";
+  right: 1px;
+  border-right-width: 0;
+  border-left-color: #fff;
+  bottom: -10px;
+}
+.carousel {
+  position: relative;
+}
+.carousel-inner {
+  position: relative;
+  overflow: hidden;
+  width: 100%;
+}
+.carousel-inner > .item {
+  display: none;
+  position: relative;
+  -webkit-transition: 0.6s ease-in-out left;
+  -o-transition: 0.6s ease-in-out left;
+  transition: 0.6s ease-in-out left;
+}
+.carousel-inner > .item > img,
+.carousel-inner > .item > a > img {
+  line-height: 1;
+}
+@media all and (transform-3d), (-webkit-transform-3d) {
+  .carousel-inner > .item {
+    -webkit-transition: -webkit-transform 0.6s ease-in-out;
+    -moz-transition: -moz-transform 0.6s ease-in-out;
+    -o-transition: -o-transform 0.6s ease-in-out;
+    transition: transform 0.6s ease-in-out;
+    -webkit-backface-visibility: hidden;
+    -moz-backface-visibility: hidden;
+    backface-visibility: hidden;
+    -webkit-perspective: 1000px;
+    -moz-perspective: 1000px;
+    perspective: 1000px;
+  }
+  .carousel-inner > .item.next,
+  .carousel-inner > .item.active.right {
+    -webkit-transform: translate3d(100%, 0, 0);
+    transform: translate3d(100%, 0, 0);
+    left: 0;
+  }
+  .carousel-inner > .item.prev,
+  .carousel-inner > .item.active.left {
+    -webkit-transform: translate3d(-100%, 0, 0);
+    transform: translate3d(-100%, 0, 0);
+    left: 0;
+  }
+  .carousel-inner > .item.next.left,
+  .carousel-inner > .item.prev.right,
+  .carousel-inner > .item.active {
+    -webkit-transform: translate3d(0, 0, 0);
+    transform: translate3d(0, 0, 0);
+    left: 0;
+  }
+}
+.carousel-inner > .active,
+.carousel-inner > .next,
+.carousel-inner > .prev {
+  display: block;
+}
+.carousel-inner > .active {
+  left: 0;
+}
+.carousel-inner > .next,
+.carousel-inner > .prev {
+  position: absolute;
+  top: 0;
+  width: 100%;
+}
+.carousel-inner > .next {
+  left: 100%;
+}
+.carousel-inner > .prev {
+  left: -100%;
+}
+.carousel-inner > .next.left,
+.carousel-inner > .prev.right {
+  left: 0;
+}
+.carousel-inner > .active.left {
+  left: -100%;
+}
+.carousel-inner > .active.right {
+  left: 100%;
+}
+.carousel-control {
+  position: absolute;
+  top: 0;
+  left: 0;
+  bottom: 0;
+  width: 15%;
+  opacity: 0.5;
+  filter: alpha(opacity=50);
+  font-size: 20px;
+  color: #fff;
+  text-align: center;
+  text-shadow: 0 1px 2px rgba(0, 0, 0, 0.6);
+  background-color: rgba(0, 0, 0, 0);
+}
+.carousel-control.left {
+  background-image: -webkit-linear-gradient(left, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
+  background-image: -o-linear-gradient(left, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
+  background-image: linear-gradient(to right, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
+  background-repeat: repeat-x;
+  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#80000000', endColorstr='#00000000', GradientType=1);
+}
+.carousel-control.right {
+  left: auto;
+  right: 0;
+  background-image: -webkit-linear-gradient(left, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
+  background-image: -o-linear-gradient(left, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
+  background-image: linear-gradient(to right, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
+  background-repeat: repeat-x;
+  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#00000000', endColorstr='#80000000', GradientType=1);
+}
+.carousel-control:hover,
+.carousel-control:focus {
+  outline: 0;
+  color: #fff;
+  text-decoration: none;
+  opacity: 0.9;
+  filter: alpha(opacity=90);
+}
+.carousel-control .icon-prev,
+.carousel-control .icon-next,
+.carousel-control .glyphicon-chevron-left,
+.carousel-control .glyphicon-chevron-right {
+  position: absolute;
+  top: 50%;
+  margin-top: -10px;
+  z-index: 5;
+  display: inline-block;
+}
+.carousel-control .icon-prev,
+.carousel-control .glyphicon-chevron-left {
+  left: 50%;
+  margin-left: -10px;
+}
+.carousel-control .icon-next,
+.carousel-control .glyphicon-chevron-right {
+  right: 50%;
+  margin-right: -10px;
+}
+.carousel-control .icon-prev,
+.carousel-control .icon-next {
+  width: 20px;
+  height: 20px;
+  line-height: 1;
+  font-family: serif;
+}
+.carousel-control .icon-prev:before {
+  content: '\2039';
+}
+.carousel-control .icon-next:before {
+  content: '\203a';
+}
+.carousel-indicators {
+  position: absolute;
+  bottom: 10px;
+  left: 50%;
+  z-index: 15;
+  width: 60%;
+  margin-left: -30%;
+  padding-left: 0;
+  list-style: none;
+  text-align: center;
+}
+.carousel-indicators li {
+  display: inline-block;
+  width: 10px;
+  height: 10px;
+  margin: 1px;
+  text-indent: -999px;
+  border: 1px solid #fff;
+  border-radius: 10px;
+  cursor: pointer;
+  background-color: #000 \9;
+  background-color: rgba(0, 0, 0, 0);
+}
+.carousel-indicators .active {
+  margin: 0;
+  width: 12px;
+  height: 12px;
+  background-color: #fff;
+}
+.carousel-caption {
+  position: absolute;
+  left: 15%;
+  right: 15%;
+  bottom: 20px;
+  z-index: 10;
+  padding-top: 20px;
+  padding-bottom: 20px;
+  color: #fff;
+  text-align: center;
+  text-shadow: 0 1px 2px rgba(0, 0, 0, 0.6);
+}
+.carousel-caption .btn {
+  text-shadow: none;
+}
+@media screen and (min-width: 768px) {
+  .carousel-control .glyphicon-chevron-left,
+  .carousel-control .glyphicon-chevron-right,
+  .carousel-control .icon-prev,
+  .carousel-control .icon-next {
+    width: 30px;
+    height: 30px;
+    margin-top: -10px;
+    font-size: 30px;
+  }
+  .carousel-control .glyphicon-chevron-left,
+  .carousel-control .icon-prev {
+    margin-left: -10px;
+  }
+  .carousel-control .glyphicon-chevron-right,
+  .carousel-control .icon-next {
+    margin-right: -10px;
+  }
+  .carousel-caption {
+    left: 20%;
+    right: 20%;
+    padding-bottom: 30px;
+  }
+  .carousel-indicators {
+    bottom: 20px;
+  }
+}
+.clearfix:before,
+.clearfix:after,
+.dl-horizontal dd:before,
+.dl-horizontal dd:after,
+.container:before,
+.container:after,
+.container-fluid:before,
+.container-fluid:after,
+.row:before,
+.row:after,
+.form-horizontal .form-group:before,
+.form-horizontal .form-group:after,
+.btn-toolbar:before,
+.btn-toolbar:after,
+.btn-group-vertical > .btn-group:before,
+.btn-group-vertical > .btn-group:after,
+.nav:before,
+.nav:after,
+.navbar:before,
+.navbar:after,
+.navbar-header:before,
+.navbar-header:after,
+.navbar-collapse:before,
+.navbar-collapse:after,
+.pager:before,
+.pager:after,
+.panel-body:before,
+.panel-body:after,
+.modal-header:before,
+.modal-header:after,
+.modal-footer:before,
+.modal-footer:after,
+.item_buttons:before,
+.item_buttons:after {
+  content: " ";
+  display: table;
+}
+.clearfix:after,
+.dl-horizontal dd:after,
+.container:after,
+.container-fluid:after,
+.row:after,
+.form-horizontal .form-group:after,
+.btn-toolbar:after,
+.btn-group-vertical > .btn-group:after,
+.nav:after,
+.navbar:after,
+.navbar-header:after,
+.navbar-collapse:after,
+.pager:after,
+.panel-body:after,
+.modal-header:after,
+.modal-footer:after,
+.item_buttons:after {
+  clear: both;
+}
+.center-block {
+  display: block;
+  margin-left: auto;
+  margin-right: auto;
+}
+.pull-right {
+  float: right !important;
+}
+.pull-left {
+  float: left !important;
+}
+.hide {
+  display: none !important;
+}
+.show {
+  display: block !important;
+}
+.invisible {
+  visibility: hidden;
+}
+.text-hide {
+  font: 0/0 a;
+  color: transparent;
+  text-shadow: none;
+  background-color: transparent;
+  border: 0;
+}
+.hidden {
+  display: none !important;
+}
+.affix {
+  position: fixed;
+}
+@-ms-viewport {
+  width: device-width;
+}
+.visible-xs,
+.visible-sm,
+.visible-md,
+.visible-lg {
+  display: none !important;
+}
+.visible-xs-block,
+.visible-xs-inline,
+.visible-xs-inline-block,
+.visible-sm-block,
+.visible-sm-inline,
+.visible-sm-inline-block,
+.visible-md-block,
+.visible-md-inline,
+.visible-md-inline-block,
+.visible-lg-block,
+.visible-lg-inline,
+.visible-lg-inline-block {
+  display: none !important;
+}
+@media (max-width: 767px) {
+  .visible-xs {
+    display: block !important;
+  }
+  table.visible-xs {
+    display: table !important;
+  }
+  tr.visible-xs {
+    display: table-row !important;
+  }
+  th.visible-xs,
+  td.visible-xs {
+    display: table-cell !important;
+  }
+}
+@media (max-width: 767px) {
+  .visible-xs-block {
+    display: block !important;
+  }
+}
+@media (max-width: 767px) {
+  .visible-xs-inline {
+    display: inline !important;
+  }
+}
+@media (max-width: 767px) {
+  .visible-xs-inline-block {
+    display: inline-block !important;
+  }
+}
+@media (min-width: 768px) and (max-width: 991px) {
+  .visible-sm {
+    display: block !important;
+  }
+  table.visible-sm {
+    display: table !important;
+  }
+  tr.visible-sm {
+    display: table-row !important;
+  }
+  th.visible-sm,
+  td.visible-sm {
+    display: table-cell !important;
+  }
+}
+@media (min-width: 768px) and (max-width: 991px) {
+  .visible-sm-block {
+    display: block !important;
+  }
+}
+@media (min-width: 768px) and (max-width: 991px) {
+  .visible-sm-inline {
+    display: inline !important;
+  }
+}
+@media (min-width: 768px) and (max-width: 991px) {
+  .visible-sm-inline-block {
+    display: inline-block !important;
+  }
+}
+@media (min-width: 992px) and (max-width: 1199px) {
+  .visible-md {
+    display: block !important;
+  }
+  table.visible-md {
+    display: table !important;
+  }
+  tr.visible-md {
+    display: table-row !important;
+  }
+  th.visible-md,
+  td.visible-md {
+    display: table-cell !important;
+  }
+}
+@media (min-width: 992px) and (max-width: 1199px) {
+  .visible-md-block {
+    display: block !important;
+  }
+}
+@media (min-width: 992px) and (max-width: 1199px) {
+  .visible-md-inline {
+    display: inline !important;
+  }
+}
+@media (min-width: 992px) and (max-width: 1199px) {
+  .visible-md-inline-block {
+    display: inline-block !important;
+  }
+}
+@media (min-width: 1200px) {
+  .visible-lg {
+    display: block !important;
+  }
+  table.visible-lg {
+    display: table !important;
+  }
+  tr.visible-lg {
+    display: table-row !important;
+  }
+  th.visible-lg,
+  td.visible-lg {
+    display: table-cell !important;
+  }
+}
+@media (min-width: 1200px) {
+  .visible-lg-block {
+    display: block !important;
+  }
+}
+@media (min-width: 1200px) {
+  .visible-lg-inline {
+    display: inline !important;
+  }
+}
+@media (min-width: 1200px) {
+  .visible-lg-inline-block {
+    display: inline-block !important;
+  }
+}
+@media (max-width: 767px) {
+  .hidden-xs {
+    display: none !important;
+  }
+}
+@media (min-width: 768px) and (max-width: 991px) {
+  .hidden-sm {
+    display: none !important;
+  }
+}
+@media (min-width: 992px) and (max-width: 1199px) {
+  .hidden-md {
+    display: none !important;
+  }
+}
+@media (min-width: 1200px) {
+  .hidden-lg {
+    display: none !important;
+  }
+}
+.visible-print {
+  display: none !important;
+}
+@media print {
+  .visible-print {
+    display: block !important;
+  }
+  table.visible-print {
+    display: table !important;
+  }
+  tr.visible-print {
+    display: table-row !important;
+  }
+  th.visible-print,
+  td.visible-print {
+    display: table-cell !important;
+  }
+}
+.visible-print-block {
+  display: none !important;
+}
+@media print {
+  .visible-print-block {
+    display: block !important;
+  }
+}
+.visible-print-inline {
+  display: none !important;
+}
+@media print {
+  .visible-print-inline {
+    display: inline !important;
+  }
+}
+.visible-print-inline-block {
+  display: none !important;
+}
+@media print {
+  .visible-print-inline-block {
+    display: inline-block !important;
+  }
+}
+@media print {
+  .hidden-print {
+    display: none !important;
+  }
+}
+/*!
+*
+* Font Awesome
+*
+*/
+/*!
+ *  Font Awesome 4.7.0 by @davegandy - http://fontawesome.io - @fontawesome
+ *  License - http://fontawesome.io/license (Font: SIL OFL 1.1, CSS: MIT License)
+ */
+/* FONT PATH
+ * -------------------------- */
+@font-face {
+  font-family: 'FontAwesome';
+  src: url('../components/font-awesome/fonts/fontawesome-webfont.eot?v=4.7.0');
+  src: url('../components/font-awesome/fonts/fontawesome-webfont.eot?#iefix&v=4.7.0') format('embedded-opentype'), url('../components/font-awesome/fonts/fontawesome-webfont.woff2?v=4.7.0') format('woff2'), url('../components/font-awesome/fonts/fontawesome-webfont.woff?v=4.7.0') format('woff'), url('../components/font-awesome/fonts/fontawesome-webfont.ttf?v=4.7.0') format('truetype'), url('../components/font-awesome/fonts/fontawesome-webfont.svg?v=4.7.0#fontawesomeregular') format('svg');
+  font-weight: normal;
+  font-style: normal;
+}
+.fa {
+  display: inline-block;
+  font: normal normal normal 14px/1 FontAwesome;
+  font-size: inherit;
+  text-rendering: auto;
+  -webkit-font-smoothing: antialiased;
+  -moz-osx-font-smoothing: grayscale;
+}
+/* makes the font 33% larger relative to the icon container */
+.fa-lg {
+  font-size: 1.33333333em;
+  line-height: 0.75em;
+  vertical-align: -15%;
+}
+.fa-2x {
+  font-size: 2em;
+}
+.fa-3x {
+  font-size: 3em;
+}
+.fa-4x {
+  font-size: 4em;
+}
+.fa-5x {
+  font-size: 5em;
+}
+.fa-fw {
+  width: 1.28571429em;
+  text-align: center;
+}
+.fa-ul {
+  padding-left: 0;
+  margin-left: 2.14285714em;
+  list-style-type: none;
+}
+.fa-ul > li {
+  position: relative;
+}
+.fa-li {
+  position: absolute;
+  left: -2.14285714em;
+  width: 2.14285714em;
+  top: 0.14285714em;
+  text-align: center;
+}
+.fa-li.fa-lg {
+  left: -1.85714286em;
+}
+.fa-border {
+  padding: .2em .25em .15em;
+  border: solid 0.08em #eee;
+  border-radius: .1em;
+}
+.fa-pull-left {
+  float: left;
+}
+.fa-pull-right {
+  float: right;
+}
+.fa.fa-pull-left {
+  margin-right: .3em;
+}
+.fa.fa-pull-right {
+  margin-left: .3em;
+}
+/* Deprecated as of 4.4.0 */
+.pull-right {
+  float: right;
+}
+.pull-left {
+  float: left;
+}
+.fa.pull-left {
+  margin-right: .3em;
+}
+.fa.pull-right {
+  margin-left: .3em;
+}
+.fa-spin {
+  -webkit-animation: fa-spin 2s infinite linear;
+  animation: fa-spin 2s infinite linear;
+}
+.fa-pulse {
+  -webkit-animation: fa-spin 1s infinite steps(8);
+  animation: fa-spin 1s infinite steps(8);
+}
+@-webkit-keyframes fa-spin {
+  0% {
+    -webkit-transform: rotate(0deg);
+    transform: rotate(0deg);
+  }
+  100% {
+    -webkit-transform: rotate(359deg);
+    transform: rotate(359deg);
+  }
+}
+@keyframes fa-spin {
+  0% {
+    -webkit-transform: rotate(0deg);
+    transform: rotate(0deg);
+  }
+  100% {
+    -webkit-transform: rotate(359deg);
+    transform: rotate(359deg);
+  }
+}
+.fa-rotate-90 {
+  -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=1)";
+  -webkit-transform: rotate(90deg);
+  -ms-transform: rotate(90deg);
+  transform: rotate(90deg);
+}
+.fa-rotate-180 {
+  -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=2)";
+  -webkit-transform: rotate(180deg);
+  -ms-transform: rotate(180deg);
+  transform: rotate(180deg);
+}
+.fa-rotate-270 {
+  -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=3)";
+  -webkit-transform: rotate(270deg);
+  -ms-transform: rotate(270deg);
+  transform: rotate(270deg);
+}
+.fa-flip-horizontal {
+  -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=0, mirror=1)";
+  -webkit-transform: scale(-1, 1);
+  -ms-transform: scale(-1, 1);
+  transform: scale(-1, 1);
+}
+.fa-flip-vertical {
+  -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=2, mirror=1)";
+  -webkit-transform: scale(1, -1);
+  -ms-transform: scale(1, -1);
+  transform: scale(1, -1);
+}
+:root .fa-rotate-90,
+:root .fa-rotate-180,
+:root .fa-rotate-270,
+:root .fa-flip-horizontal,
+:root .fa-flip-vertical {
+  filter: none;
+}
+.fa-stack {
+  position: relative;
+  display: inline-block;
+  width: 2em;
+  height: 2em;
+  line-height: 2em;
+  vertical-align: middle;
+}
+.fa-stack-1x,
+.fa-stack-2x {
+  position: absolute;
+  left: 0;
+  width: 100%;
+  text-align: center;
+}
+.fa-stack-1x {
+  line-height: inherit;
+}
+.fa-stack-2x {
+  font-size: 2em;
+}
+.fa-inverse {
+  color: #fff;
+}
+/* Font Awesome uses the Unicode Private Use Area (PUA) to ensure screen
+   readers do not read off random characters that represent icons */
+.fa-glass:before {
+  content: "\f000";
+}
+.fa-music:before {
+  content: "\f001";
+}
+.fa-search:before {
+  content: "\f002";
+}
+.fa-envelope-o:before {
+  content: "\f003";
+}
+.fa-heart:before {
+  content: "\f004";
+}
+.fa-star:before {
+  content: "\f005";
+}
+.fa-star-o:before {
+  content: "\f006";
+}
+.fa-user:before {
+  content: "\f007";
+}
+.fa-film:before {
+  content: "\f008";
+}
+.fa-th-large:before {
+  content: "\f009";
+}
+.fa-th:before {
+  content: "\f00a";
+}
+.fa-th-list:before {
+  content: "\f00b";
+}
+.fa-check:before {
+  content: "\f00c";
+}
+.fa-remove:before,
+.fa-close:before,
+.fa-times:before {
+  content: "\f00d";
+}
+.fa-search-plus:before {
+  content: "\f00e";
+}
+.fa-search-minus:before {
+  content: "\f010";
+}
+.fa-power-off:before {
+  content: "\f011";
+}
+.fa-signal:before {
+  content: "\f012";
+}
+.fa-gear:before,
+.fa-cog:before {
+  content: "\f013";
+}
+.fa-trash-o:before {
+  content: "\f014";
+}
+.fa-home:before {
+  content: "\f015";
+}
+.fa-file-o:before {
+  content: "\f016";
+}
+.fa-clock-o:before {
+  content: "\f017";
+}
+.fa-road:before {
+  content: "\f018";
+}
+.fa-download:before {
+  content: "\f019";
+}
+.fa-arrow-circle-o-down:before {
+  content: "\f01a";
+}
+.fa-arrow-circle-o-up:before {
+  content: "\f01b";
+}
+.fa-inbox:before {
+  content: "\f01c";
+}
+.fa-play-circle-o:before {
+  content: "\f01d";
+}
+.fa-rotate-right:before,
+.fa-repeat:before {
+  content: "\f01e";
+}
+.fa-refresh:before {
+  content: "\f021";
+}
+.fa-list-alt:before {
+  content: "\f022";
+}
+.fa-lock:before {
+  content: "\f023";
+}
+.fa-flag:before {
+  content: "\f024";
+}
+.fa-headphones:before {
+  content: "\f025";
+}
+.fa-volume-off:before {
+  content: "\f026";
+}
+.fa-volume-down:before {
+  content: "\f027";
+}
+.fa-volume-up:before {
+  content: "\f028";
+}
+.fa-qrcode:before {
+  content: "\f029";
+}
+.fa-barcode:before {
+  content: "\f02a";
+}
+.fa-tag:before {
+  content: "\f02b";
+}
+.fa-tags:before {
+  content: "\f02c";
+}
+.fa-book:before {
+  content: "\f02d";
+}
+.fa-bookmark:before {
+  content: "\f02e";
+}
+.fa-print:before {
+  content: "\f02f";
+}
+.fa-camera:before {
+  content: "\f030";
+}
+.fa-font:before {
+  content: "\f031";
+}
+.fa-bold:before {
+  content: "\f032";
+}
+.fa-italic:before {
+  content: "\f033";
+}
+.fa-text-height:before {
+  content: "\f034";
+}
+.fa-text-width:before {
+  content: "\f035";
+}
+.fa-align-left:before {
+  content: "\f036";
+}
+.fa-align-center:before {
+  content: "\f037";
+}
+.fa-align-right:before {
+  content: "\f038";
+}
+.fa-align-justify:before {
+  content: "\f039";
+}
+.fa-list:before {
+  content: "\f03a";
+}
+.fa-dedent:before,
+.fa-outdent:before {
+  content: "\f03b";
+}
+.fa-indent:before {
+  content: "\f03c";
+}
+.fa-video-camera:before {
+  content: "\f03d";
+}
+.fa-photo:before,
+.fa-image:before,
+.fa-picture-o:before {
+  content: "\f03e";
+}
+.fa-pencil:before {
+  content: "\f040";
+}
+.fa-map-marker:before {
+  content: "\f041";
+}
+.fa-adjust:before {
+  content: "\f042";
+}
+.fa-tint:before {
+  content: "\f043";
+}
+.fa-edit:before,
+.fa-pencil-square-o:before {
+  content: "\f044";
+}
+.fa-share-square-o:before {
+  content: "\f045";
+}
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+  margin: -1px;
+  overflow: hidden;
+  clip: rect(0, 0, 0, 0);
+  border: 0;
+}
+.sr-only-focusable:active,
+.sr-only-focusable:focus {
+  position: static;
+  width: auto;
+  height: auto;
+  margin: 0;
+  overflow: visible;
+  clip: auto;
+}
+.sr-only-focusable:active,
+.sr-only-focusable:focus {
+  position: static;
+  width: auto;
+  height: auto;
+  margin: 0;
+  overflow: visible;
+  clip: auto;
+}
+/*!
+*
+* IPython base
+*
+*/
+.modal.fade .modal-dialog {
+  -webkit-transform: translate(0, 0);
+  -ms-transform: translate(0, 0);
+  -o-transform: translate(0, 0);
+  transform: translate(0, 0);
+}
+code {
+  color: #000;
+}
+pre {
+  font-size: inherit;
+  line-height: inherit;
+}
+label {
+  font-weight: normal;
+}
+/* Make the page background atleast 100% the height of the view port */
+/* Make the page itself atleast 70% the height of the view port */
+.border-box-sizing {
+  box-sizing: border-box;
+  -moz-box-sizing: border-box;
+  -webkit-box-sizing: border-box;
+}
+.corner-all {
+  border-radius: 2px;
+}
+.no-padding {
+  padding: 0px;
+}
+/* Flexible box model classes */
+/* Taken from Alex Russell http://infrequently.org/2009/08/css-3-progress/ */
+/* This file is a compatability layer.  It allows the usage of flexible box 
+model layouts accross multiple browsers, including older browsers.  The newest,
+universal implementation of the flexible box model is used when available (see
+`Modern browsers` comments below).  Browsers that are known to implement this 
+new spec completely include:
+
+    Firefox 28.0+
+    Chrome 29.0+
+    Internet Explorer 11+ 
+    Opera 17.0+
+
+Browsers not listed, including Safari, are supported via the styling under the
+`Old browsers` comments below.
+*/
+.hbox {
+  /* Old browsers */
+  display: -webkit-box;
+  -webkit-box-orient: horizontal;
+  -webkit-box-align: stretch;
+  display: -moz-box;
+  -moz-box-orient: horizontal;
+  -moz-box-align: stretch;
+  display: box;
+  box-orient: horizontal;
+  box-align: stretch;
+  /* Modern browsers */
+  display: flex;
+  flex-direction: row;
+  align-items: stretch;
+}
+.hbox > * {
+  /* Old browsers */
+  -webkit-box-flex: 0;
+  -moz-box-flex: 0;
+  box-flex: 0;
+  /* Modern browsers */
+  flex: none;
+}
+.vbox {
+  /* Old browsers */
+  display: -webkit-box;
+  -webkit-box-orient: vertical;
+  -webkit-box-align: stretch;
+  display: -moz-box;
+  -moz-box-orient: vertical;
+  -moz-box-align: stretch;
+  display: box;
+  box-orient: vertical;
+  box-align: stretch;
+  /* Modern browsers */
+  display: flex;
+  flex-direction: column;
+  align-items: stretch;
+}
+.vbox > * {
+  /* Old browsers */
+  -webkit-box-flex: 0;
+  -moz-box-flex: 0;
+  box-flex: 0;
+  /* Modern browsers */
+  flex: none;
+}
+.hbox.reverse,
+.vbox.reverse,
+.reverse {
+  /* Old browsers */
+  -webkit-box-direction: reverse;
+  -moz-box-direction: reverse;
+  box-direction: reverse;
+  /* Modern browsers */
+  flex-direction: row-reverse;
+}
+.hbox.box-flex0,
+.vbox.box-flex0,
+.box-flex0 {
+  /* Old browsers */
+  -webkit-box-flex: 0;
+  -moz-box-flex: 0;
+  box-flex: 0;
+  /* Modern browsers */
+  flex: none;
+  width: auto;
+}
+.hbox.box-flex1,
+.vbox.box-flex1,
+.box-flex1 {
+  /* Old browsers */
+  -webkit-box-flex: 1;
+  -moz-box-flex: 1;
+  box-flex: 1;
+  /* Modern browsers */
+  flex: 1;
+}
+.hbox.box-flex,
+.vbox.box-flex,
+.box-flex {
+  /* Old browsers */
+  /* Old browsers */
+  -webkit-box-flex: 1;
+  -moz-box-flex: 1;
+  box-flex: 1;
+  /* Modern browsers */
+  flex: 1;
+}
+.hbox.box-flex2,
+.vbox.box-flex2,
+.box-flex2 {
+  /* Old browsers */
+  -webkit-box-flex: 2;
+  -moz-box-flex: 2;
+  box-flex: 2;
+  /* Modern browsers */
+  flex: 2;
+}
+.box-group1 {
+  /*  Deprecated */
+  -webkit-box-flex-group: 1;
+  -moz-box-flex-group: 1;
+  box-flex-group: 1;
+}
+.box-group2 {
+  /* Deprecated */
+  -webkit-box-flex-group: 2;
+  -moz-box-flex-group: 2;
+  box-flex-group: 2;
+}
+.hbox.start,
+.vbox.start,
+.start {
+  /* Old browsers */
+  -webkit-box-pack: start;
+  -moz-box-pack: start;
+  box-pack: start;
+  /* Modern browsers */
+  justify-content: flex-start;
+}
+.hbox.end,
+.vbox.end,
+.end {
+  /* Old browsers */
+  -webkit-box-pack: end;
+  -moz-box-pack: end;
+  box-pack: end;
+  /* Modern browsers */
+  justify-content: flex-end;
+}
+.hbox.center,
+.vbox.center,
+.center {
+  /* Old browsers */
+  -webkit-box-pack: center;
+  -moz-box-pack: center;
+  box-pack: center;
+  /* Modern browsers */
+  justify-content: center;
+}
+.hbox.baseline,
+.vbox.baseline,
+.baseline {
+  /* Old browsers */
+  -webkit-box-pack: baseline;
+  -moz-box-pack: baseline;
+  box-pack: baseline;
+  /* Modern browsers */
+  justify-content: baseline;
+}
+.hbox.stretch,
+.vbox.stretch,
+.stretch {
+  /* Old browsers */
+  -webkit-box-pack: stretch;
+  -moz-box-pack: stretch;
+  box-pack: stretch;
+  /* Modern browsers */
+  justify-content: stretch;
+}
+.hbox.align-start,
+.vbox.align-start,
+.align-start {
+  /* Old browsers */
+  -webkit-box-align: start;
+  -moz-box-align: start;
+  box-align: start;
+  /* Modern browsers */
+  align-items: flex-start;
+}
+.hbox.align-end,
+.vbox.align-end,
+.align-end {
+  /* Old browsers */
+  -webkit-box-align: end;
+  -moz-box-align: end;
+  box-align: end;
+  /* Modern browsers */
+  align-items: flex-end;
+}
+.hbox.align-center,
+.vbox.align-center,
+.align-center {
+  /* Old browsers */
+  -webkit-box-align: center;
+  -moz-box-align: center;
+  box-align: center;
+  /* Modern browsers */
+  align-items: center;
+}
+.hbox.align-baseline,
+.vbox.align-baseline,
+.align-baseline {
+  /* Old browsers */
+  -webkit-box-align: baseline;
+  -moz-box-align: baseline;
+  box-align: baseline;
+  /* Modern browsers */
+  align-items: baseline;
+}
+.hbox.align-stretch,
+.vbox.align-stretch,
+.align-stretch {
+  /* Old browsers */
+  -webkit-box-align: stretch;
+  -moz-box-align: stretch;
+  box-align: stretch;
+  /* Modern browsers */
+  align-items: stretch;
+}
+div.error {
+  margin: 2em;
+  text-align: center;
+}
+div.error > h1 {
+  font-size: 500%;
+  line-height: normal;
+}
+div.error > p {
+  font-size: 200%;
+  line-height: normal;
+}
+div.traceback-wrapper {
+  text-align: left;
+  max-width: 800px;
+  margin: auto;
+}
+div.traceback-wrapper pre.traceback {
+  max-height: 600px;
+  overflow: auto;
+}
+/**
+ * Primary styles
+ *
+ * Author: Jupyter Development Team
+ */
+body {
+  background-color: #fff;
+  /* This makes sure that the body covers the entire window and needs to
+       be in a different element than the display: box in wrapper below */
+  position: absolute;
+  left: 0px;
+  right: 0px;
+  top: 0px;
+  bottom: 0px;
+  overflow: visible;
+}
+body > #header {
+  /* Initially hidden to prevent FLOUC */
+  display: none;
+  background-color: #fff;
+  /* Display over codemirror */
+  position: relative;
+  z-index: 100;
+}
+body > #header #header-container {
+  display: flex;
+  flex-direction: row;
+  justify-content: space-between;
+  padding: 5px;
+  padding-bottom: 5px;
+  padding-top: 5px;
+  box-sizing: border-box;
+  -moz-box-sizing: border-box;
+  -webkit-box-sizing: border-box;
+}
+body > #header .header-bar {
+  width: 100%;
+  height: 1px;
+  background: #e7e7e7;
+  margin-bottom: -1px;
+}
+@media print {
+  body > #header {
+    display: none !important;
+  }
+}
+#header-spacer {
+  width: 100%;
+  visibility: hidden;
+}
+@media print {
+  #header-spacer {
+    display: none;
+  }
+}
+#ipython_notebook {
+  padding-left: 0px;
+  padding-top: 1px;
+  padding-bottom: 1px;
+}
+[dir="rtl"] #ipython_notebook {
+  margin-right: 10px;
+  margin-left: 0;
+}
+[dir="rtl"] #ipython_notebook.pull-left {
+  float: right !important;
+  float: right;
+}
+.flex-spacer {
+  flex: 1;
+}
+#noscript {
+  width: auto;
+  padding-top: 16px;
+  padding-bottom: 16px;
+  text-align: center;
+  font-size: 22px;
+  color: red;
+  font-weight: bold;
+}
+#ipython_notebook img {
+  height: 28px;
+}
+#site {
+  width: 100%;
+  display: none;
+  box-sizing: border-box;
+  -moz-box-sizing: border-box;
+  -webkit-box-sizing: border-box;
+  overflow: auto;
+}
+@media print {
+  #site {
+    height: auto !important;
+  }
+}
+/* Smaller buttons */
+.ui-button .ui-button-text {
+  padding: 0.2em 0.8em;
+  font-size: 77%;
+}
+input.ui-button {
+  padding: 0.3em 0.9em;
+}
+span#kernel_logo_widget {
+  margin: 0 10px;
+}
+span#login_widget {
+  float: right;
+}
+[dir="rtl"] span#login_widget {
+  float: left;
+}
+span#login_widget > .button,
+#logout {
+  color: #333;
+  background-color: #fff;
+  border-color: #ccc;
+}
+span#login_widget > .button:focus,
+#logout:focus,
+span#login_widget > .button.focus,
+#logout.focus {
+  color: #333;
+  background-color: #e6e6e6;
+  border-color: #8c8c8c;
+}
+span#login_widget > .button:hover,
+#logout:hover {
+  color: #333;
+  background-color: #e6e6e6;
+  border-color: #adadad;
+}
+span#login_widget > .button:active,
+#logout:active,
+span#login_widget > .button.active,
+#logout.active,
+.open > .dropdown-togglespan#login_widget > .button,
+.open > .dropdown-toggle#logout {
+  color: #333;
+  background-color: #e6e6e6;
+  border-color: #adadad;
+}
+span#login_widget > .button:active:hover,
+#logout:active:hover,
+span#login_widget > .button.active:hover,
+#logout.active:hover,
+.open > .dropdown-togglespan#login_widget > .button:hover,
+.open > .dropdown-toggle#logout:hover,
+span#login_widget > .button:active:focus,
+#logout:active:focus,
+span#login_widget > .button.active:focus,
+#logout.active:focus,
+.open > .dropdown-togglespan#login_widget > .button:focus,
+.open > .dropdown-toggle#logout:focus,
+span#login_widget > .button:active.focus,
+#logout:active.focus,
+span#login_widget > .button.active.focus,
+#logout.active.focus,
+.open > .dropdown-togglespan#login_widget > .button.focus,
+.open > .dropdown-toggle#logout.focus {
+  color: #333;
+  background-color: #d4d4d4;
+  border-color: #8c8c8c;
+}
+span#login_widget > .button:active,
+#logout:active,
+span#login_widget > .button.active,
+#logout.active,
+.open > .dropdown-togglespan#login_widget > .button,
+.open > .dropdown-toggle#logout {
+  background-image: none;
+}
+span#login_widget > .button.disabled:hover,
+#logout.disabled:hover,
+span#login_widget > .button[disabled]:hover,
+#logout[disabled]:hover,
+fieldset[disabled] span#login_widget > .button:hover,
+fieldset[disabled] #logout:hover,
+span#login_widget > .button.disabled:focus,
+#logout.disabled:focus,
+span#login_widget > .button[disabled]:focus,
+#logout[disabled]:focus,
+fieldset[disabled] span#login_widget > .button:focus,
+fieldset[disabled] #logout:focus,
+span#login_widget > .button.disabled.focus,
+#logout.disabled.focus,
+span#login_widget > .button[disabled].focus,
+#logout[disabled].focus,
+fieldset[disabled] span#login_widget > .button.focus,
+fieldset[disabled] #logout.focus {
+  background-color: #fff;
+  border-color: #ccc;
+}
+span#login_widget > .button .badge,
+#logout .badge {
+  color: #fff;
+  background-color: #333;
+}
+.nav-header {
+  text-transform: none;
+}
+#header > span {
+  margin-top: 10px;
+}
+.modal_stretch .modal-dialog {
+  /* Old browsers */
+  display: -webkit-box;
+  -webkit-box-orient: vertical;
+  -webkit-box-align: stretch;
+  display: -moz-box;
+  -moz-box-orient: vertical;
+  -moz-box-align: stretch;
+  display: box;
+  box-orient: vertical;
+  box-align: stretch;
+  /* Modern browsers */
+  display: flex;
+  flex-direction: column;
+  align-items: stretch;
+  min-height: 80vh;
+}
+.modal_stretch .modal-dialog .modal-body {
+  max-height: calc(100vh - 200px);
+  overflow: auto;
+  flex: 1;
+}
+.modal-header {
+  cursor: move;
+}
+@media (min-width: 768px) {
+  .modal .modal-dialog {
+    width: 700px;
+  }
+}
+@media (min-width: 768px) {
+  select.form-control {
+    margin-left: 12px;
+    margin-right: 12px;
+  }
+}
+/*!
+*
+* IPython auth
+*
+*/
+.center-nav {
+  display: inline-block;
+  margin-bottom: -4px;
+}
+[dir="rtl"] .center-nav form.pull-left {
+  float: right !important;
+  float: right;
+}
+[dir="rtl"] .center-nav .navbar-text {
+  float: right;
+}
+[dir="rtl"] .navbar-inner {
+  text-align: right;
+}
+[dir="rtl"] div.text-left {
+  text-align: right;
+}
+/*!
+*
+* IPython tree view
+*
+*/
+/* We need an invisible input field on top of the sentense*/
+/* "Drag file onto the list ..." */
+.alternate_upload {
+  background-color: none;
+  display: inline;
+}
+.alternate_upload.form {
+  padding: 0;
+  margin: 0;
+}
+.alternate_upload input.fileinput {
+  position: absolute;
+  display: block;
+  width: 100%;
+  height: 100%;
+  overflow: hidden;
+  cursor: pointer;
+  opacity: 0;
+  z-index: 2;
+}
+.alternate_upload .btn-xs > input.fileinput {
+  margin: -1px -5px;
+}
+.alternate_upload .btn-upload {
+  position: relative;
+  height: 22px;
+}
+::-webkit-file-upload-button {
+  cursor: pointer;
+}
+/**
+ * Primary styles
+ *
+ * Author: Jupyter Development Team
+ */
+ul#tabs {
+  margin-bottom: 4px;
+}
+ul#tabs a {
+  padding-top: 6px;
+  padding-bottom: 4px;
+}
+[dir="rtl"] ul#tabs.nav-tabs > li {
+  float: right;
+}
+[dir="rtl"] ul#tabs.nav.nav-tabs {
+  padding-right: 0;
+}
+ul.breadcrumb a:focus,
+ul.breadcrumb a:hover {
+  text-decoration: none;
+}
+ul.breadcrumb i.icon-home {
+  font-size: 16px;
+  margin-right: 4px;
+}
+ul.breadcrumb span {
+  color: #5e5e5e;
+}
+.list_toolbar {
+  padding: 4px 0 4px 0;
+  vertical-align: middle;
+}
+.list_toolbar .tree-buttons {
+  padding-top: 1px;
+}
+[dir="rtl"] .list_toolbar .tree-buttons .pull-right {
+  float: left !important;
+  float: left;
+}
+[dir="rtl"] .list_toolbar .col-sm-4,
+[dir="rtl"] .list_toolbar .col-sm-8 {
+  float: right;
+}
+.dynamic-buttons {
+  padding-top: 3px;
+  display: inline-block;
+}
+.list_toolbar [class*="span"] {
+  min-height: 24px;
+}
+.list_header {
+  font-weight: bold;
+  background-color: #EEE;
+}
+.list_placeholder {
+  font-weight: bold;
+  padding-top: 4px;
+  padding-bottom: 4px;
+  padding-left: 7px;
+  padding-right: 7px;
+}
+.list_container {
+  margin-top: 4px;
+  margin-bottom: 20px;
+  border: 1px solid #ddd;
+  border-radius: 2px;
+}
+.list_container > div {
+  border-bottom: 1px solid #ddd;
+}
+.list_container > div:hover .list-item {
+  background-color: red;
+}
+.list_container > div:last-child {
+  border: none;
+}
+.list_item:hover .list_item {
+  background-color: #ddd;
+}
+.list_item a {
+  text-decoration: none;
+}
+.list_item:hover {
+  background-color: #fafafa;
+}
+.list_header > div,
+.list_item > div {
+  padding-top: 4px;
+  padding-bottom: 4px;
+  padding-left: 7px;
+  padding-right: 7px;
+  line-height: 22px;
+}
+.list_header > div input,
+.list_item > div input {
+  margin-right: 7px;
+  margin-left: 14px;
+  vertical-align: text-bottom;
+  line-height: 22px;
+  position: relative;
+  top: -1px;
+}
+.list_header > div .item_link,
+.list_item > div .item_link {
+  margin-left: -1px;
+  vertical-align: baseline;
+  line-height: 22px;
+}
+[dir="rtl"] .list_item > div input {
+  margin-right: 0;
+}
+.new-file input[type=checkbox] {
+  visibility: hidden;
+}
+.item_name {
+  line-height: 22px;
+  height: 24px;
+}
+.item_icon {
+  font-size: 14px;
+  color: #5e5e5e;
+  margin-right: 7px;
+  margin-left: 7px;
+  line-height: 22px;
+  vertical-align: baseline;
+}
+.item_modified {
+  margin-right: 7px;
+  margin-left: 7px;
+}
+[dir="rtl"] .item_modified.pull-right {
+  float: left !important;
+  float: left;
+}
+.item_buttons {
+  line-height: 1em;
+  margin-left: -5px;
+}
+.item_buttons .btn,
+.item_buttons .btn-group,
+.item_buttons .input-group {
+  float: left;
+}
+.item_buttons > .btn,
+.item_buttons > .btn-group,
+.item_buttons > .input-group {
+  margin-left: 5px;
+}
+.item_buttons .btn {
+  min-width: 13ex;
+}
+.item_buttons .running-indicator {
+  padding-top: 4px;
+  color: #5cb85c;
+}
+.item_buttons .kernel-name {
+  padding-top: 4px;
+  color: #5bc0de;
+  margin-right: 7px;
+  float: left;
+}
+[dir="rtl"] .item_buttons.pull-right {
+  float: left !important;
+  float: left;
+}
+[dir="rtl"] .item_buttons .kernel-name {
+  margin-left: 7px;
+  float: right;
+}
+.toolbar_info {
+  height: 24px;
+  line-height: 24px;
+}
+.list_item input:not([type=checkbox]) {
+  padding-top: 3px;
+  padding-bottom: 3px;
+  height: 22px;
+  line-height: 14px;
+  margin: 0px;
+}
+.highlight_text {
+  color: blue;
+}
+#project_name {
+  display: inline-block;
+  padding-left: 7px;
+  margin-left: -2px;
+}
+#project_name > .breadcrumb {
+  padding: 0px;
+  margin-bottom: 0px;
+  background-color: transparent;
+  font-weight: bold;
+}
+.sort_button {
+  display: inline-block;
+  padding-left: 7px;
+}
+[dir="rtl"] .sort_button.pull-right {
+  float: left !important;
+  float: left;
+}
+#tree-selector {
+  padding-right: 0px;
+}
+#button-select-all {
+  min-width: 50px;
+}
+[dir="rtl"] #button-select-all.btn {
+  float: right ;
+}
+#select-all {
+  margin-left: 7px;
+  margin-right: 2px;
+  margin-top: 2px;
+  height: 16px;
+}
+[dir="rtl"] #select-all.pull-left {
+  float: right !important;
+  float: right;
+}
+.menu_icon {
+  margin-right: 2px;
+}
+.tab-content .row {
+  margin-left: 0px;
+  margin-right: 0px;
+}
+.folder_icon:before {
+  display: inline-block;
+  font: normal normal normal 14px/1 FontAwesome;
+  font-size: inherit;
+  text-rendering: auto;
+  -webkit-font-smoothing: antialiased;
+  -moz-osx-font-smoothing: grayscale;
+  content: "\f114";
+}
+.folder_icon:before.fa-pull-left {
+  margin-right: .3em;
+}
+.folder_icon:before.fa-pull-right {
+  margin-left: .3em;
+}
+.folder_icon:before.pull-left {
+  margin-right: .3em;
+}
+.folder_icon:before.pull-right {
+  margin-left: .3em;
+}
+.notebook_icon:before {
+  display: inline-block;
+  font: normal normal normal 14px/1 FontAwesome;
+  font-size: inherit;
+  text-rendering: auto;
+  -webkit-font-smoothing: antialiased;
+  -moz-osx-font-smoothing: grayscale;
+  content: "\f02d";
+  position: relative;
+  top: -1px;
+}
+.notebook_icon:before.fa-pull-left {
+  margin-right: .3em;
+}
+.notebook_icon:before.fa-pull-right {
+  margin-left: .3em;
+}
+.notebook_icon:before.pull-left {
+  margin-right: .3em;
+}
+.notebook_icon:before.pull-right {
+  margin-left: .3em;
+}
+.running_notebook_icon:before {
+  display: inline-block;
+  font: normal normal normal 14px/1 FontAwesome;
+  font-size: inherit;
+  text-rendering: auto;
+  -webkit-font-smoothing: antialiased;
+  -moz-osx-font-smoothing: grayscale;
+  content: "\f02d";
+  position: relative;
+  top: -1px;
+  color: #5cb85c;
+}
+.running_notebook_icon:before.fa-pull-left {
+  margin-right: .3em;
+}
+.running_notebook_icon:before.fa-pull-right {
+  margin-left: .3em;
+}
+.running_notebook_icon:before.pull-left {
+  margin-right: .3em;
+}
+.running_notebook_icon:before.pull-right {
+  margin-left: .3em;
+}
+.file_icon:before {
+  display: inline-block;
+  font: normal normal normal 14px/1 FontAwesome;
+  font-size: inherit;
+  text-rendering: auto;
+  -webkit-font-smoothing: antialiased;
+  -moz-osx-font-smoothing: grayscale;
+  content: "\f016";
+  position: relative;
+  top: -2px;
+}
+.file_icon:before.fa-pull-left {
+  margin-right: .3em;
+}
+.file_icon:before.fa-pull-right {
+  margin-left: .3em;
+}
+.file_icon:before.pull-left {
+  margin-right: .3em;
+}
+.file_icon:before.pull-right {
+  margin-left: .3em;
+}
+#notebook_toolbar .pull-right {
+  padding-top: 0px;
+  margin-right: -1px;
+}
+ul#new-menu {
+  left: auto;
+  right: 0;
+}
+#new-menu .dropdown-header {
+  font-size: 10px;
+  border-bottom: 1px solid #e5e5e5;
+  padding: 0 0 3px;
+  margin: -3px 20px 0;
+}
+.kernel-menu-icon {
+  padding-right: 12px;
+  width: 24px;
+  content: "\f096";
+}
+.kernel-menu-icon:before {
+  content: "\f096";
+}
+.kernel-menu-icon-current:before {
+  content: "\f00c";
+}
+#tab_content {
+  padding-top: 20px;
+}
+#running .panel-group .panel {
+  margin-top: 3px;
+  margin-bottom: 1em;
+}
+#running .panel-group .panel .panel-heading {
+  background-color: #EEE;
+  padding-top: 4px;
+  padding-bottom: 4px;
+  padding-left: 7px;
+  padding-right: 7px;
+  line-height: 22px;
+}
+#running .panel-group .panel .panel-heading a:focus,
+#running .panel-group .panel .panel-heading a:hover {
+  text-decoration: none;
+}
+#running .panel-group .panel .panel-body {
+  padding: 0px;
+}
+#running .panel-group .panel .panel-body .list_container {
+  margin-top: 0px;
+  margin-bottom: 0px;
+  border: 0px;
+  border-radius: 0px;
+}
+#running .panel-group .panel .panel-body .list_container .list_item {
+  border-bottom: 1px solid #ddd;
+}
+#running .panel-group .panel .panel-body .list_container .list_item:last-child {
+  border-bottom: 0px;
+}
+.delete-button {
+  display: none;
+}
+.duplicate-button {
+  display: none;
+}
+.rename-button {
+  display: none;
+}
+.move-button {
+  display: none;
+}
+.download-button {
+  display: none;
+}
+.shutdown-button {
+  display: none;
+}
+.dynamic-instructions {
+  display: inline-block;
+  padding-top: 4px;
+}
+/*!
+*
+* IPython text editor webapp
+*
+*/
+.selected-keymap i.fa {
+  padding: 0px 5px;
+}
+.selected-keymap i.fa:before {
+  content: "\f00c";
+}
+#mode-menu {
+  overflow: auto;
+  max-height: 20em;
+}
+.edit_app #header {
+  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
+  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
+}
+.edit_app #menubar .navbar {
+  /* Use a negative 1 bottom margin, so the border overlaps the border of the
+    header */
+  margin-bottom: -1px;
+}
+.dirty-indicator {
+  display: inline-block;
+  font: normal normal normal 14px/1 FontAwesome;
+  font-size: inherit;
+  text-rendering: auto;
+  -webkit-font-smoothing: antialiased;
+  -moz-osx-font-smoothing: grayscale;
+  width: 20px;
+}
+.dirty-indicator.fa-pull-left {
+  margin-right: .3em;
+}
+.dirty-indicator.fa-pull-right {
+  margin-left: .3em;
+}
+.dirty-indicator.pull-left {
+  margin-right: .3em;
+}
+.dirty-indicator.pull-right {
+  margin-left: .3em;
+}
+.dirty-indicator-dirty {
+  display: inline-block;
+  font: normal normal normal 14px/1 FontAwesome;
+  font-size: inherit;
+  text-rendering: auto;
+  -webkit-font-smoothing: antialiased;
+  -moz-osx-font-smoothing: grayscale;
+  width: 20px;
+}
+.dirty-indicator-dirty.fa-pull-left {
+  margin-right: .3em;
+}
+.dirty-indicator-dirty.fa-pull-right {
+  margin-left: .3em;
+}
+.dirty-indicator-dirty.pull-left {
+  margin-right: .3em;
+}
+.dirty-indicator-dirty.pull-right {
+  margin-left: .3em;
+}
+.dirty-indicator-clean {
+  display: inline-block;
+  font: normal normal normal 14px/1 FontAwesome;
+  font-size: inherit;
+  text-rendering: auto;
+  -webkit-font-smoothing: antialiased;
+  -moz-osx-font-smoothing: grayscale;
+  width: 20px;
+}
+.dirty-indicator-clean.fa-pull-left {
+  margin-right: .3em;
+}
+.dirty-indicator-clean.fa-pull-right {
+  margin-left: .3em;
+}
+.dirty-indicator-clean.pull-left {
+  margin-right: .3em;
+}
+.dirty-indicator-clean.pull-right {
+  margin-left: .3em;
+}
+.dirty-indicator-clean:before {
+  display: inline-block;
+  font: normal normal normal 14px/1 FontAwesome;
+  font-size: inherit;
+  text-rendering: auto;
+  -webkit-font-smoothing: antialiased;
+  -moz-osx-font-smoothing: grayscale;
+  content: "\f00c";
+}
+.dirty-indicator-clean:before.fa-pull-left {
+  margin-right: .3em;
+}
+.dirty-indicator-clean:before.fa-pull-right {
+  margin-left: .3em;
+}
+.dirty-indicator-clean:before.pull-left {
+  margin-right: .3em;
+}
+.dirty-indicator-clean:before.pull-right {
+  margin-left: .3em;
+}
+#filename {
+  font-size: 16pt;
+  display: table;
+  padding: 0px 5px;
+}
+#current-mode {
+  padding-left: 5px;
+  padding-right: 5px;
+}
+#texteditor-backdrop {
+  padding-top: 20px;
+  padding-bottom: 20px;
+}
+@media not print {
+  #texteditor-backdrop {
+    background-color: #EEE;
+  }
+}
+@media print {
+  #texteditor-backdrop #texteditor-container .CodeMirror-gutter,
+  #texteditor-backdrop #texteditor-container .CodeMirror-gutters {
+    background-color: #fff;
+  }
+}
+@media not print {
+  #texteditor-backdrop #texteditor-container .CodeMirror-gutter,
+  #texteditor-backdrop #texteditor-container .CodeMirror-gutters {
+    background-color: #fff;
+  }
+}
+@media not print {
+  #texteditor-backdrop #texteditor-container {
+    padding: 0px;
+    background-color: #fff;
+    -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
+    box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
+  }
+}
+.CodeMirror-dialog {
+  background-color: #fff;
+}
+/*!
+*
+* IPython notebook
+*
+*/
+/* CSS font colors for translated ANSI escape sequences */
+/* The color values are a mix of
+   http://www.xcolors.net/dl/baskerville-ivorylight and
+   http://www.xcolors.net/dl/euphrasia */
+.ansi-black-fg {
+  color: #3E424D;
+}
+.ansi-black-bg {
+  background-color: #3E424D;
+}
+.ansi-black-intense-fg {
+  color: #282C36;
+}
+.ansi-black-intense-bg {
+  background-color: #282C36;
+}
+.ansi-red-fg {
+  color: #E75C58;
+}
+.ansi-red-bg {
+  background-color: #E75C58;
+}
+.ansi-red-intense-fg {
+  color: #B22B31;
+}
+.ansi-red-intense-bg {
+  background-color: #B22B31;
+}
+.ansi-green-fg {
+  color: #00A250;
+}
+.ansi-green-bg {
+  background-color: #00A250;
+}
+.ansi-green-intense-fg {
+  color: #007427;
+}
+.ansi-green-intense-bg {
+  background-color: #007427;
+}
+.ansi-yellow-fg {
+  color: #DDB62B;
+}
+.ansi-yellow-bg {
+  background-color: #DDB62B;
+}
+.ansi-yellow-intense-fg {
+  color: #B27D12;
+}
+.ansi-yellow-intense-bg {
+  background-color: #B27D12;
+}
+.ansi-blue-fg {
+  color: #208FFB;
+}
+.ansi-blue-bg {
+  background-color: #208FFB;
+}
+.ansi-blue-intense-fg {
+  color: #0065CA;
+}
+.ansi-blue-intense-bg {
+  background-color: #0065CA;
+}
+.ansi-magenta-fg {
+  color: #D160C4;
+}
+.ansi-magenta-bg {
+  background-color: #D160C4;
+}
+.ansi-magenta-intense-fg {
+  color: #A03196;
+}
+.ansi-magenta-intense-bg {
+  background-color: #A03196;
+}
+.ansi-cyan-fg {
+  color: #60C6C8;
+}
+.ansi-cyan-bg {
+  background-color: #60C6C8;
+}
+.ansi-cyan-intense-fg {
+  color: #258F8F;
+}
+.ansi-cyan-intense-bg {
+  background-color: #258F8F;
+}
+.ansi-white-fg {
+  color: #C5C1B4;
+}
+.ansi-white-bg {
+  background-color: #C5C1B4;
+}
+.ansi-white-intense-fg {
+  color: #A1A6B2;
+}
+.ansi-white-intense-bg {
+  background-color: #A1A6B2;
+}
+.ansi-default-inverse-fg {
+  color: #FFFFFF;
+}
+.ansi-default-inverse-bg {
+  background-color: #000000;
+}
+.ansi-bold {
+  font-weight: bold;
+}
+.ansi-underline {
+  text-decoration: underline;
+}
+/* The following styles are deprecated an will be removed in a future version */
+.ansibold {
+  font-weight: bold;
+}
+.ansi-inverse {
+  outline: 0.5px dotted;
+}
+/* use dark versions for foreground, to improve visibility */
+.ansiblack {
+  color: black;
+}
+.ansired {
+  color: darkred;
+}
+.ansigreen {
+  color: darkgreen;
+}
+.ansiyellow {
+  color: #c4a000;
+}
+.ansiblue {
+  color: darkblue;
+}
+.ansipurple {
+  color: darkviolet;
+}
+.ansicyan {
+  color: steelblue;
+}
+.ansigray {
+  color: gray;
+}
+/* and light for background, for the same reason */
+.ansibgblack {
+  background-color: black;
+}
+.ansibgred {
+  background-color: red;
+}
+.ansibggreen {
+  background-color: green;
+}
+.ansibgyellow {
+  background-color: yellow;
+}
+.ansibgblue {
+  background-color: blue;
+}
+.ansibgpurple {
+  background-color: magenta;
+}
+.ansibgcyan {
+  background-color: cyan;
+}
+.ansibggray {
+  background-color: gray;
+}
+div.cell {
+  /* Old browsers */
+  display: -webkit-box;
+  -webkit-box-orient: vertical;
+  -webkit-box-align: stretch;
+  display: -moz-box;
+  -moz-box-orient: vertical;
+  -moz-box-align: stretch;
+  display: box;
+  box-orient: vertical;
+  box-align: stretch;
+  /* Modern browsers */
+  display: flex;
+  flex-direction: column;
+  align-items: stretch;
+  border-radius: 2px;
+  box-sizing: border-box;
+  -moz-box-sizing: border-box;
+  -webkit-box-sizing: border-box;
+  border-width: 1px;
+  border-style: solid;
+  border-color: transparent;
+  width: 100%;
+  padding: 5px;
+  /* This acts as a spacer between cells, that is outside the border */
+  margin: 0px;
+  outline: none;
+  position: relative;
+  overflow: visible;
+}
+div.cell:before {
+  position: absolute;
+  display: block;
+  top: -1px;
+  left: -1px;
+  width: 5px;
+  height: calc(100% +  2px);
+  content: '';
+  background: transparent;
+}
+div.cell.jupyter-soft-selected {
+  border-left-color: #E3F2FD;
+  border-left-width: 1px;
+  padding-left: 5px;
+  border-right-color: #E3F2FD;
+  border-right-width: 1px;
+  background: #E3F2FD;
+}
+@media print {
+  div.cell.jupyter-soft-selected {
+    border-color: transparent;
+  }
+}
+div.cell.selected,
+div.cell.selected.jupyter-soft-selected {
+  border-color: #ababab;
+}
+div.cell.selected:before,
+div.cell.selected.jupyter-soft-selected:before {
+  position: absolute;
+  display: block;
+  top: -1px;
+  left: -1px;
+  width: 5px;
+  height: calc(100% +  2px);
+  content: '';
+  background: #42A5F5;
+}
+@media print {
+  div.cell.selected,
+  div.cell.selected.jupyter-soft-selected {
+    border-color: transparent;
+  }
+}
+.edit_mode div.cell.selected {
+  border-color: #66BB6A;
+}
+.edit_mode div.cell.selected:before {
+  position: absolute;
+  display: block;
+  top: -1px;
+  left: -1px;
+  width: 5px;
+  height: calc(100% +  2px);
+  content: '';
+  background: #66BB6A;
+}
+@media print {
+  .edit_mode div.cell.selected {
+    border-color: transparent;
+  }
+}
+.prompt {
+  /* This needs to be wide enough for 3 digit prompt numbers: In[100]: */
+  min-width: 14ex;
+  /* This padding is tuned to match the padding on the CodeMirror editor. */
+  padding: 0.4em;
+  margin: 0px;
+  font-family: monospace;
+  text-align: right;
+  /* This has to match that of the the CodeMirror class line-height below */
+  line-height: 1.21429em;
+  /* Don't highlight prompt number selection */
+  -webkit-touch-callout: none;
+  -webkit-user-select: none;
+  -khtml-user-select: none;
+  -moz-user-select: none;
+  -ms-user-select: none;
+  user-select: none;
+  /* Use default cursor */
+  cursor: default;
+}
+@media (max-width: 540px) {
+  .prompt {
+    text-align: left;
+  }
+}
+div.inner_cell {
+  min-width: 0;
+  /* Old browsers */
+  display: -webkit-box;
+  -webkit-box-orient: vertical;
+  -webkit-box-align: stretch;
+  display: -moz-box;
+  -moz-box-orient: vertical;
+  -moz-box-align: stretch;
+  display: box;
+  box-orient: vertical;
+  box-align: stretch;
+  /* Modern browsers */
+  display: flex;
+  flex-direction: column;
+  align-items: stretch;
+  /* Old browsers */
+  -webkit-box-flex: 1;
+  -moz-box-flex: 1;
+  box-flex: 1;
+  /* Modern browsers */
+  flex: 1;
+}
+/* input_area and input_prompt must match in top border and margin for alignment */
+div.input_area {
+  border: 1px solid #cfcfcf;
+  border-radius: 2px;
+  background: #f7f7f7;
+  line-height: 1.21429em;
+}
+/* This is needed so that empty prompt areas can collapse to zero height when there
+   is no content in the output_subarea and the prompt. The main purpose of this is
+   to make sure that empty JavaScript output_subareas have no height. */
+div.prompt:empty {
+  padding-top: 0;
+  padding-bottom: 0;
+}
+div.unrecognized_cell {
+  padding: 5px 5px 5px 0px;
+  /* Old browsers */
+  display: -webkit-box;
+  -webkit-box-orient: horizontal;
+  -webkit-box-align: stretch;
+  display: -moz-box;
+  -moz-box-orient: horizontal;
+  -moz-box-align: stretch;
+  display: box;
+  box-orient: horizontal;
+  box-align: stretch;
+  /* Modern browsers */
+  display: flex;
+  flex-direction: row;
+  align-items: stretch;
+}
+div.unrecognized_cell .inner_cell {
+  border-radius: 2px;
+  padding: 5px;
+  font-weight: bold;
+  color: red;
+  border: 1px solid #cfcfcf;
+  background: #eaeaea;
+}
+div.unrecognized_cell .inner_cell a {
+  color: inherit;
+  text-decoration: none;
+}
+div.unrecognized_cell .inner_cell a:hover {
+  color: inherit;
+  text-decoration: none;
+}
+@media (max-width: 540px) {
+  div.unrecognized_cell > div.prompt {
+    display: none;
+  }
+}
+div.code_cell {
+  /* avoid page breaking on code cells when printing */
+}
+@media print {
+  div.code_cell {
+    page-break-inside: avoid;
+  }
+}
+/* any special styling for code cells that are currently running goes here */
+div.input {
+  page-break-inside: avoid;
+  /* Old browsers */
+  display: -webkit-box;
+  -webkit-box-orient: horizontal;
+  -webkit-box-align: stretch;
+  display: -moz-box;
+  -moz-box-orient: horizontal;
+  -moz-box-align: stretch;
+  display: box;
+  box-orient: horizontal;
+  box-align: stretch;
+  /* Modern browsers */
+  display: flex;
+  flex-direction: row;
+  align-items: stretch;
+}
+@media (max-width: 540px) {
+  div.input {
+    /* Old browsers */
+    display: -webkit-box;
+    -webkit-box-orient: vertical;
+    -webkit-box-align: stretch;
+    display: -moz-box;
+    -moz-box-orient: vertical;
+    -moz-box-align: stretch;
+    display: box;
+    box-orient: vertical;
+    box-align: stretch;
+    /* Modern browsers */
+    display: flex;
+    flex-direction: column;
+    align-items: stretch;
+  }
+}
+/* input_area and input_prompt must match in top border and margin for alignment */
+div.input_prompt {
+  color: #303F9F;
+  border-top: 1px solid transparent;
+}
+div.input_area > div.highlight {
+  margin: 0.4em;
+  border: none;
+  padding: 0px;
+  background-color: transparent;
+}
+div.input_area > div.highlight > pre {
+  margin: 0px;
+  border: none;
+  padding: 0px;
+  background-color: transparent;
+}
+/* The following gets added to the <head> if it is detected that the user has a
+ * monospace font with inconsistent normal/bold/italic height.  See
+ * notebookmain.js.  Such fonts will have keywords vertically offset with
+ * respect to the rest of the text.  The user should select a better font.
+ * See: https://github.com/ipython/ipython/issues/1503
+ *
+ * .CodeMirror span {
+ *      vertical-align: bottom;
+ * }
+ */
+.CodeMirror {
+  line-height: 1.21429em;
+  /* Changed from 1em to our global default */
+  font-size: 14px;
+  height: auto;
+  /* Changed to auto to autogrow */
+  background: none;
+  /* Changed from white to allow our bg to show through */
+}
+.CodeMirror-scroll {
+  /*  The CodeMirror docs are a bit fuzzy on if overflow-y should be hidden or visible.*/
+  /*  We have found that if it is visible, vertical scrollbars appear with font size changes.*/
+  overflow-y: hidden;
+  overflow-x: auto;
+}
+.CodeMirror-lines {
+  /* In CM2, this used to be 0.4em, but in CM3 it went to 4px. We need the em value because */
+  /* we have set a different line-height and want this to scale with that. */
+  /* Note that this should set vertical padding only, since CodeMirror assumes
+       that horizontal padding will be set on CodeMirror pre */
+  padding: 0.4em 0;
+}
+.CodeMirror-linenumber {
+  padding: 0 8px 0 4px;
+}
+.CodeMirror-gutters {
+  border-bottom-left-radius: 2px;
+  border-top-left-radius: 2px;
+}
+.CodeMirror pre {
+  /* In CM3 this went to 4px from 0 in CM2. This sets horizontal padding only,
+    use .CodeMirror-lines for vertical */
+  padding: 0 0.4em;
+  border: 0;
+  border-radius: 0;
+}
+.CodeMirror-cursor {
+  border-left: 1.4px solid black;
+}
+@media screen and (min-width: 2138px) and (max-width: 4319px) {
+  .CodeMirror-cursor {
+    border-left: 2px solid black;
+  }
+}
+@media screen and (min-width: 4320px) {
+  .CodeMirror-cursor {
+    border-left: 4px solid black;
+  }
+}
+/*
+
+Original style from softwaremaniacs.org (c) Ivan Sagalaev <Maniac@SoftwareManiacs.Org>
+Adapted from GitHub theme
+
+*/
+.highlight-base {
+  color: #000;
+}
+.highlight-variable {
+  color: #000;
+}
+.highlight-variable-2 {
+  color: #1a1a1a;
+}
+.highlight-variable-3 {
+  color: #333333;
+}
+.highlight-string {
+  color: #BA2121;
+}
+.highlight-comment {
+  color: #408080;
+  font-style: italic;
+}
+.highlight-number {
+  color: #080;
+}
+.highlight-atom {
+  color: #88F;
+}
+.highlight-keyword {
+  color: #008000;
+  font-weight: bold;
+}
+.highlight-builtin {
+  color: #008000;
+}
+.highlight-error {
+  color: #f00;
+}
+.highlight-operator {
+  color: #AA22FF;
+  font-weight: bold;
+}
+.highlight-meta {
+  color: #AA22FF;
+}
+/* previously not defined, copying from default codemirror */
+.highlight-def {
+  color: #00f;
+}
+.highlight-string-2 {
+  color: #f50;
+}
+.highlight-qualifier {
+  color: #555;
+}
+.highlight-bracket {
+  color: #997;
+}
+.highlight-tag {
+  color: #170;
+}
+.highlight-attribute {
+  color: #00c;
+}
+.highlight-header {
+  color: blue;
+}
+.highlight-quote {
+  color: #090;
+}
+.highlight-link {
+  color: #00c;
+}
+/* apply the same style to codemirror */
+.cm-s-ipython span.cm-keyword {
+  color: #008000;
+  font-weight: bold;
+}
+.cm-s-ipython span.cm-atom {
+  color: #88F;
+}
+.cm-s-ipython span.cm-number {
+  color: #080;
+}
+.cm-s-ipython span.cm-def {
+  color: #00f;
+}
+.cm-s-ipython span.cm-variable {
+  color: #000;
+}
+.cm-s-ipython span.cm-operator {
+  color: #AA22FF;
+  font-weight: bold;
+}
+.cm-s-ipython span.cm-variable-2 {
+  color: #1a1a1a;
+}
+.cm-s-ipython span.cm-variable-3 {
+  color: #333333;
+}
+.cm-s-ipython span.cm-comment {
+  color: #408080;
+  font-style: italic;
+}
+.cm-s-ipython span.cm-string {
+  color: #BA2121;
+}
+.cm-s-ipython span.cm-string-2 {
+  color: #f50;
+}
+.cm-s-ipython span.cm-meta {
+  color: #AA22FF;
+}
+.cm-s-ipython span.cm-qualifier {
+  color: #555;
+}
+.cm-s-ipython span.cm-builtin {
+  color: #008000;
+}
+.cm-s-ipython span.cm-bracket {
+  color: #997;
+}
+.cm-s-ipython span.cm-tag {
+  color: #170;
+}
+.cm-s-ipython span.cm-attribute {
+  color: #00c;
+}
+.cm-s-ipython span.cm-header {
+  color: blue;
+}
+.cm-s-ipython span.cm-quote {
+  color: #090;
+}
+.cm-s-ipython span.cm-link {
+  color: #00c;
+}
+.cm-s-ipython span.cm-error {
+  color: #f00;
+}
+.cm-s-ipython span.cm-tab {
+  background: url(data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAADAAAAAMCAYAAAAkuj5RAAAAAXNSR0IArs4c6QAAAGFJREFUSMft1LsRQFAQheHPowAKoACx3IgEKtaEHujDjORSgWTH/ZOdnZOcM/sgk/kFFWY0qV8foQwS4MKBCS3qR6ixBJvElOobYAtivseIE120FaowJPN75GMu8j/LfMwNjh4HUpwg4LUAAAAASUVORK5CYII=);
+  background-position: right;
+  background-repeat: no-repeat;
+}
+div.output_wrapper {
+  /* this position must be relative to enable descendents to be absolute within it */
+  position: relative;
+  /* Old browsers */
+  display: -webkit-box;
+  -webkit-box-orient: vertical;
+  -webkit-box-align: stretch;
+  display: -moz-box;
+  -moz-box-orient: vertical;
+  -moz-box-align: stretch;
+  display: box;
+  box-orient: vertical;
+  box-align: stretch;
+  /* Modern browsers */
+  display: flex;
+  flex-direction: column;
+  align-items: stretch;
+  z-index: 1;
+}
+/* class for the output area when it should be height-limited */
+div.output_scroll {
+  /* ideally, this would be max-height, but FF barfs all over that */
+  height: 24em;
+  /* FF needs this *and the wrapper* to specify full width, or it will shrinkwrap */
+  width: 100%;
+  overflow: auto;
+  border-radius: 2px;
+  -webkit-box-shadow: inset 0 2px 8px rgba(0, 0, 0, 0.8);
+  box-shadow: inset 0 2px 8px rgba(0, 0, 0, 0.8);
+  display: block;
+}
+/* output div while it is collapsed */
+div.output_collapsed {
+  margin: 0px;
+  padding: 0px;
+  /* Old browsers */
+  display: -webkit-box;
+  -webkit-box-orient: vertical;
+  -webkit-box-align: stretch;
+  display: -moz-box;
+  -moz-box-orient: vertical;
+  -moz-box-align: stretch;
+  display: box;
+  box-orient: vertical;
+  box-align: stretch;
+  /* Modern browsers */
+  display: flex;
+  flex-direction: column;
+  align-items: stretch;
+}
+div.out_prompt_overlay {
+  height: 100%;
+  padding: 0px 0.4em;
+  position: absolute;
+  border-radius: 2px;
+}
+div.out_prompt_overlay:hover {
+  /* use inner shadow to get border that is computed the same on WebKit/FF */
+  -webkit-box-shadow: inset 0 0 1px #000;
+  box-shadow: inset 0 0 1px #000;
+  background: rgba(240, 240, 240, 0.5);
+}
+div.output_prompt {
+  color: #D84315;
+}
+/* This class is the outer container of all output sections. */
+div.output_area {
+  padding: 0px;
+  page-break-inside: avoid;
+  /* Old browsers */
+  display: -webkit-box;
+  -webkit-box-orient: horizontal;
+  -webkit-box-align: stretch;
+  display: -moz-box;
+  -moz-box-orient: horizontal;
+  -moz-box-align: stretch;
+  display: box;
+  box-orient: horizontal;
+  box-align: stretch;
+  /* Modern browsers */
+  display: flex;
+  flex-direction: row;
+  align-items: stretch;
+}
+div.output_area .MathJax_Display {
+  text-align: left !important;
+}
+div.output_area .rendered_html table {
+  margin-left: 0;
+  margin-right: 0;
+}
+div.output_area .rendered_html img {
+  margin-left: 0;
+  margin-right: 0;
+}
+div.output_area img,
+div.output_area svg {
+  max-width: 100%;
+  height: auto;
+}
+div.output_area img.unconfined,
+div.output_area svg.unconfined {
+  max-width: none;
+}
+div.output_area .mglyph > img {
+  max-width: none;
+}
+/* This is needed to protect the pre formating from global settings such
+   as that of bootstrap */
+.output {
+  /* Old browsers */
+  display: -webkit-box;
+  -webkit-box-orient: vertical;
+  -webkit-box-align: stretch;
+  display: -moz-box;
+  -moz-box-orient: vertical;
+  -moz-box-align: stretch;
+  display: box;
+  box-orient: vertical;
+  box-align: stretch;
+  /* Modern browsers */
+  display: flex;
+  flex-direction: column;
+  align-items: stretch;
+}
+@media (max-width: 540px) {
+  div.output_area {
+    /* Old browsers */
+    display: -webkit-box;
+    -webkit-box-orient: vertical;
+    -webkit-box-align: stretch;
+    display: -moz-box;
+    -moz-box-orient: vertical;
+    -moz-box-align: stretch;
+    display: box;
+    box-orient: vertical;
+    box-align: stretch;
+    /* Modern browsers */
+    display: flex;
+    flex-direction: column;
+    align-items: stretch;
+  }
+}
+div.output_area pre {
+  margin: 0;
+  padding: 1px 0 1px 0;
+  border: 0;
+  vertical-align: baseline;
+  color: black;
+  background-color: transparent;
+  border-radius: 0;
+}
+/* This class is for the output subarea inside the output_area and after
+   the prompt div. */
+div.output_subarea {
+  overflow-x: auto;
+  padding: 0.4em;
+  /* Old browsers */
+  -webkit-box-flex: 1;
+  -moz-box-flex: 1;
+  box-flex: 1;
+  /* Modern browsers */
+  flex: 1;
+  max-width: calc(100% - 14ex);
+}
+div.output_scroll div.output_subarea {
+  overflow-x: visible;
+}
+/* The rest of the output_* classes are for special styling of the different
+   output types */
+/* all text output has this class: */
+div.output_text {
+  text-align: left;
+  color: #000;
+  /* This has to match that of the the CodeMirror class line-height below */
+  line-height: 1.21429em;
+}
+/* stdout/stderr are 'text' as well as 'stream', but execute_result/error are *not* streams */
+div.output_stderr {
+  background: #fdd;
+  /* very light red background for stderr */
+}
+div.output_latex {
+  text-align: left;
+}
+/* Empty output_javascript divs should have no height */
+div.output_javascript:empty {
+  padding: 0;
+}
+.js-error {
+  color: darkred;
+}
+/* raw_input styles */
+div.raw_input_container {
+  line-height: 1.21429em;
+  padding-top: 5px;
+}
+pre.raw_input_prompt {
+  /* nothing needed here. */
+}
+input.raw_input {
+  font-family: monospace;
+  font-size: inherit;
+  color: inherit;
+  width: auto;
+  /* make sure input baseline aligns with prompt */
+  vertical-align: baseline;
+  /* padding + margin = 0.5em between prompt and cursor */
+  padding: 0em 0.25em;
+  margin: 0em 0.25em;
+}
+input.raw_input:focus {
+  box-shadow: none;
+}
+p.p-space {
+  margin-bottom: 10px;
+}
+div.output_unrecognized {
+  padding: 5px;
+  font-weight: bold;
+  color: red;
+}
+div.output_unrecognized a {
+  color: inherit;
+  text-decoration: none;
+}
+div.output_unrecognized a:hover {
+  color: inherit;
+  text-decoration: none;
+}
+.rendered_html {
+  color: #000;
+  /* any extras will just be numbers: */
+}
+.rendered_html em {
+  font-style: italic;
+}
+.rendered_html strong {
+  font-weight: bold;
+}
+.rendered_html u {
+  text-decoration: underline;
+}
+.rendered_html :link {
+  text-decoration: underline;
+}
+.rendered_html :visited {
+  text-decoration: underline;
+}
+.rendered_html h1 {
+  font-size: 185.7%;
+  margin: 1.08em 0 0 0;
+  font-weight: bold;
+  line-height: 1.0;
+}
+.rendered_html h2 {
+  font-size: 157.1%;
+  margin: 1.27em 0 0 0;
+  font-weight: bold;
+  line-height: 1.0;
+}
+.rendered_html h3 {
+  font-size: 128.6%;
+  margin: 1.55em 0 0 0;
+  font-weight: bold;
+  line-height: 1.0;
+}
+.rendered_html h4 {
+  font-size: 100%;
+  margin: 2em 0 0 0;
+  font-weight: bold;
+  line-height: 1.0;
+}
+.rendered_html h5 {
+  font-size: 100%;
+  margin: 2em 0 0 0;
+  font-weight: bold;
+  line-height: 1.0;
+  font-style: italic;
+}
+.rendered_html h6 {
+  font-size: 100%;
+  margin: 2em 0 0 0;
+  font-weight: bold;
+  line-height: 1.0;
+  font-style: italic;
+}
+.rendered_html h1:first-child {
+  margin-top: 0.538em;
+}
+.rendered_html h2:first-child {
+  margin-top: 0.636em;
+}
+.rendered_html h3:first-child {
+  margin-top: 0.777em;
+}
+.rendered_html h4:first-child {
+  margin-top: 1em;
+}
+.rendered_html h5:first-child {
+  margin-top: 1em;
+}
+.rendered_html h6:first-child {
+  margin-top: 1em;
+}
+.rendered_html ul:not(.list-inline),
+.rendered_html ol:not(.list-inline) {
+  padding-left: 2em;
+}
+.rendered_html ul {
+  list-style: disc;
+}
+.rendered_html ul ul {
+  list-style: square;
+  margin-top: 0;
+}
+.rendered_html ul ul ul {
+  list-style: circle;
+}
+.rendered_html ol {
+  list-style: decimal;
+}
+.rendered_html ol ol {
+  list-style: upper-alpha;
+  margin-top: 0;
+}
+.rendered_html ol ol ol {
+  list-style: lower-alpha;
+}
+.rendered_html ol ol ol ol {
+  list-style: lower-roman;
+}
+.rendered_html ol ol ol ol ol {
+  list-style: decimal;
+}
+.rendered_html * + ul {
+  margin-top: 1em;
+}
+.rendered_html * + ol {
+  margin-top: 1em;
+}
+.rendered_html hr {
+  color: black;
+  background-color: black;
+}
+.rendered_html pre {
+  margin: 1em 2em;
+  padding: 0px;
+  background-color: #fff;
+}
+.rendered_html code {
+  background-color: #eff0f1;
+}
+.rendered_html p code {
+  padding: 1px 5px;
+}
+.rendered_html pre code {
+  background-color: #fff;
+}
+.rendered_html pre,
+.rendered_html code {
+  border: 0;
+  color: #000;
+  font-size: 100%;
+}
+.rendered_html blockquote {
+  margin: 1em 2em;
+}
+.rendered_html table {
+  margin-left: auto;
+  margin-right: auto;
+  border: none;
+  border-collapse: collapse;
+  border-spacing: 0;
+  color: black;
+  font-size: 12px;
+  table-layout: fixed;
+}
+.rendered_html thead {
+  border-bottom: 1px solid black;
+  vertical-align: bottom;
+}
+.rendered_html tr,
+.rendered_html th,
+.rendered_html td {
+  text-align: right;
+  vertical-align: middle;
+  padding: 0.5em 0.5em;
+  line-height: normal;
+  white-space: normal;
+  max-width: none;
+  border: none;
+}
+.rendered_html th {
+  font-weight: bold;
+}
+.rendered_html tbody tr:nth-child(odd) {
+  background: #f5f5f5;
+}
+.rendered_html tbody tr:hover {
+  background: rgba(66, 165, 245, 0.2);
+}
+.rendered_html * + table {
+  margin-top: 1em;
+}
+.rendered_html p {
+  text-align: left;
+}
+.rendered_html * + p {
+  margin-top: 1em;
+}
+.rendered_html img {
+  display: block;
+  margin-left: auto;
+  margin-right: auto;
+}
+.rendered_html * + img {
+  margin-top: 1em;
+}
+.rendered_html img,
+.rendered_html svg {
+  max-width: 100%;
+  height: auto;
+}
+.rendered_html img.unconfined,
+.rendered_html svg.unconfined {
+  max-width: none;
+}
+.rendered_html .alert {
+  margin-bottom: initial;
+}
+.rendered_html * + .alert {
+  margin-top: 1em;
+}
+[dir="rtl"] .rendered_html p {
+  text-align: right;
+}
+div.text_cell {
+  /* Old browsers */
+  display: -webkit-box;
+  -webkit-box-orient: horizontal;
+  -webkit-box-align: stretch;
+  display: -moz-box;
+  -moz-box-orient: horizontal;
+  -moz-box-align: stretch;
+  display: box;
+  box-orient: horizontal;
+  box-align: stretch;
+  /* Modern browsers */
+  display: flex;
+  flex-direction: row;
+  align-items: stretch;
+}
+@media (max-width: 540px) {
+  div.text_cell > div.prompt {
+    display: none;
+  }
+}
+div.text_cell_render {
+  /*font-family: "Helvetica Neue", Arial, Helvetica, Geneva, sans-serif;*/
+  outline: none;
+  resize: none;
+  width: inherit;
+  border-style: none;
+  padding: 0.5em 0.5em 0.5em 0.4em;
+  color: #000;
+  box-sizing: border-box;
+  -moz-box-sizing: border-box;
+  -webkit-box-sizing: border-box;
+}
+a.anchor-link:link {
+  text-decoration: none;
+  padding: 0px 20px;
+  visibility: hidden;
+}
+h1:hover .anchor-link,
+h2:hover .anchor-link,
+h3:hover .anchor-link,
+h4:hover .anchor-link,
+h5:hover .anchor-link,
+h6:hover .anchor-link {
+  visibility: visible;
+}
+.text_cell.rendered .input_area {
+  display: none;
+}
+.text_cell.rendered .rendered_html {
+  overflow-x: auto;
+  overflow-y: hidden;
+}
+.text_cell.rendered .rendered_html tr,
+.text_cell.rendered .rendered_html th,
+.text_cell.rendered .rendered_html td {
+  max-width: none;
+}
+.text_cell.unrendered .text_cell_render {
+  display: none;
+}
+.text_cell .dropzone .input_area {
+  border: 2px dashed #bababa;
+  margin: -1px;
+}
+.cm-header-1,
+.cm-header-2,
+.cm-header-3,
+.cm-header-4,
+.cm-header-5,
+.cm-header-6 {
+  font-weight: bold;
+  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
+}
+.cm-header-1 {
+  font-size: 185.7%;
+}
+.cm-header-2 {
+  font-size: 157.1%;
+}
+.cm-header-3 {
+  font-size: 128.6%;
+}
+.cm-header-4 {
+  font-size: 110%;
+}
+.cm-header-5 {
+  font-size: 100%;
+  font-style: italic;
+}
+.cm-header-6 {
+  font-size: 100%;
+  font-style: italic;
+}
+/*!
+*
+* IPython notebook webapp
+*
+*/
+@media (max-width: 767px) {
+  .notebook_app {
+    padding-left: 0px;
+    padding-right: 0px;
+  }
+}
+#ipython-main-app {
+  box-sizing: border-box;
+  -moz-box-sizing: border-box;
+  -webkit-box-sizing: border-box;
+  height: 100%;
+}
+div#notebook_panel {
+  margin: 0px;
+  padding: 0px;
+  box-sizing: border-box;
+  -moz-box-sizing: border-box;
+  -webkit-box-sizing: border-box;
+  height: 100%;
+}
+div#notebook {
+  font-size: 14px;
+  line-height: 20px;
+  overflow-y: hidden;
+  overflow-x: auto;
+  width: 100%;
+  /* This spaces the page away from the edge of the notebook area */
+  padding-top: 20px;
+  margin: 0px;
+  outline: none;
+  box-sizing: border-box;
+  -moz-box-sizing: border-box;
+  -webkit-box-sizing: border-box;
+  min-height: 100%;
+}
+@media not print {
+  #notebook-container {
+    padding: 15px;
+    background-color: #fff;
+    min-height: 0;
+    -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
+    box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
+  }
+}
+@media print {
+  #notebook-container {
+    width: 100%;
+  }
+}
+div.ui-widget-content {
+  border: 1px solid #ababab;
+  outline: none;
+}
+pre.dialog {
+  background-color: #f7f7f7;
+  border: 1px solid #ddd;
+  border-radius: 2px;
+  padding: 0.4em;
+  padding-left: 2em;
+}
+p.dialog {
+  padding: 0.2em;
+}
+/* Word-wrap output correctly.  This is the CSS3 spelling, though Firefox seems
+   to not honor it correctly.  Webkit browsers (Chrome, rekonq, Safari) do.
+ */
+pre,
+code,
+kbd,
+samp {
+  white-space: pre-wrap;
+}
+#fonttest {
+  font-family: monospace;
+}
+p {
+  margin-bottom: 0;
+}
+.end_space {
+  min-height: 100px;
+  transition: height .2s ease;
+}
+.notebook_app > #header {
+  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
+  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
+}
+@media not print {
+  .notebook_app {
+    background-color: #EEE;
+  }
+}
+kbd {
+  border-style: solid;
+  border-width: 1px;
+  box-shadow: none;
+  margin: 2px;
+  padding-left: 2px;
+  padding-right: 2px;
+  padding-top: 1px;
+  padding-bottom: 1px;
+}
+.jupyter-keybindings {
+  padding: 1px;
+  line-height: 24px;
+  border-bottom: 1px solid gray;
+}
+.jupyter-keybindings input {
+  margin: 0;
+  padding: 0;
+  border: none;
+}
+.jupyter-keybindings i {
+  padding: 6px;
+}
+.well code {
+  background-color: #ffffff;
+  border-color: #ababab;
+  border-width: 1px;
+  border-style: solid;
+  padding: 2px;
+  padding-top: 1px;
+  padding-bottom: 1px;
+}
+/* CSS for the cell toolbar */
+.celltoolbar {
+  border: thin solid #CFCFCF;
+  border-bottom: none;
+  background: #EEE;
+  border-radius: 2px 2px 0px 0px;
+  width: 100%;
+  height: 29px;
+  padding-right: 4px;
+  /* Old browsers */
+  display: -webkit-box;
+  -webkit-box-orient: horizontal;
+  -webkit-box-align: stretch;
+  display: -moz-box;
+  -moz-box-orient: horizontal;
+  -moz-box-align: stretch;
+  display: box;
+  box-orient: horizontal;
+  box-align: stretch;
+  /* Modern browsers */
+  display: flex;
+  flex-direction: row;
+  align-items: stretch;
+  /* Old browsers */
+  -webkit-box-pack: end;
+  -moz-box-pack: end;
+  box-pack: end;
+  /* Modern browsers */
+  justify-content: flex-end;
+  display: -webkit-flex;
+}
+@media print {
+  .celltoolbar {
+    display: none;
+  }
+}
+.ctb_hideshow {
+  display: none;
+  vertical-align: bottom;
+}
+/* ctb_show is added to the ctb_hideshow div to show the cell toolbar.
+   Cell toolbars are only shown when the ctb_global_show class is also set.
+*/
+.ctb_global_show .ctb_show.ctb_hideshow {
+  display: block;
+}
+.ctb_global_show .ctb_show + .input_area,
+.ctb_global_show .ctb_show + div.text_cell_input,
+.ctb_global_show .ctb_show ~ div.text_cell_render {
+  border-top-right-radius: 0px;
+  border-top-left-radius: 0px;
+}
+.ctb_global_show .ctb_show ~ div.text_cell_render {
+  border: 1px solid #cfcfcf;
+}
+.celltoolbar {
+  font-size: 87%;
+  padding-top: 3px;
+}
+.celltoolbar select {
+  display: block;
+  width: 100%;
+  height: 32px;
+  padding: 6px 12px;
+  font-size: 13px;
+  line-height: 1.42857143;
+  color: #555555;
+  background-color: #fff;
+  background-image: none;
+  border: 1px solid #ccc;
+  border-radius: 2px;
+  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
+  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
+  -webkit-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
+  -o-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
+  transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
+  height: 30px;
+  padding: 5px 10px;
+  font-size: 12px;
+  line-height: 1.5;
+  border-radius: 1px;
+  width: inherit;
+  font-size: inherit;
+  height: 22px;
+  padding: 0px;
+  display: inline-block;
+}
+.celltoolbar select:focus {
+  border-color: #66afe9;
+  outline: 0;
+  -webkit-box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
+  box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
+}
+.celltoolbar select::-moz-placeholder {
+  color: #999;
+  opacity: 1;
+}
+.celltoolbar select:-ms-input-placeholder {
+  color: #999;
+}
+.celltoolbar select::-webkit-input-placeholder {
+  color: #999;
+}
+.celltoolbar select::-ms-expand {
+  border: 0;
+  background-color: transparent;
+}
+.celltoolbar select[disabled],
+.celltoolbar select[readonly],
+fieldset[disabled] .celltoolbar select {
+  background-color: #eeeeee;
+  opacity: 1;
+}
+.celltoolbar select[disabled],
+fieldset[disabled] .celltoolbar select {
+  cursor: not-allowed;
+}
+textarea.celltoolbar select {
+  height: auto;
+}
+select.celltoolbar select {
+  height: 30px;
+  line-height: 30px;
+}
+textarea.celltoolbar select,
+select[multiple].celltoolbar select {
+  height: auto;
+}
+.celltoolbar label {
+  margin-left: 5px;
+  margin-right: 5px;
+}
+.tags_button_container {
+  width: 100%;
+  display: flex;
+}
+.tag-container {
+  display: flex;
+  flex-direction: row;
+  flex-grow: 1;
+  overflow: hidden;
+  position: relative;
+}
+.tag-container > * {
+  margin: 0 4px;
+}
+.remove-tag-btn {
+  margin-left: 4px;
+}
+.tags-input {
+  display: flex;
+}
+.cell-tag:last-child:after {
+  content: "";
+  position: absolute;
+  right: 0;
+  width: 40px;
+  height: 100%;
+  /* Fade to background color of cell toolbar */
+  background: linear-gradient(to right, rgba(0, 0, 0, 0), #EEE);
+}
+.tags-input > * {
+  margin-left: 4px;
+}
+.cell-tag,
+.tags-input input,
+.tags-input button {
+  display: block;
+  width: 100%;
+  height: 32px;
+  padding: 6px 12px;
+  font-size: 13px;
+  line-height: 1.42857143;
+  color: #555555;
+  background-color: #fff;
+  background-image: none;
+  border: 1px solid #ccc;
+  border-radius: 2px;
+  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
+  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
+  -webkit-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
+  -o-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
+  transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
+  height: 30px;
+  padding: 5px 10px;
+  font-size: 12px;
+  line-height: 1.5;
+  border-radius: 1px;
+  box-shadow: none;
+  width: inherit;
+  font-size: inherit;
+  height: 22px;
+  line-height: 22px;
+  padding: 0px 4px;
+  display: inline-block;
+}
+.cell-tag:focus,
+.tags-input input:focus,
+.tags-input button:focus {
+  border-color: #66afe9;
+  outline: 0;
+  -webkit-box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
+  box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
+}
+.cell-tag::-moz-placeholder,
+.tags-input input::-moz-placeholder,
+.tags-input button::-moz-placeholder {
+  color: #999;
+  opacity: 1;
+}
+.cell-tag:-ms-input-placeholder,
+.tags-input input:-ms-input-placeholder,
+.tags-input button:-ms-input-placeholder {
+  color: #999;
+}
+.cell-tag::-webkit-input-placeholder,
+.tags-input input::-webkit-input-placeholder,
+.tags-input button::-webkit-input-placeholder {
+  color: #999;
+}
+.cell-tag::-ms-expand,
+.tags-input input::-ms-expand,
+.tags-input button::-ms-expand {
+  border: 0;
+  background-color: transparent;
+}
+.cell-tag[disabled],
+.tags-input input[disabled],
+.tags-input button[disabled],
+.cell-tag[readonly],
+.tags-input input[readonly],
+.tags-input button[readonly],
+fieldset[disabled] .cell-tag,
+fieldset[disabled] .tags-input input,
+fieldset[disabled] .tags-input button {
+  background-color: #eeeeee;
+  opacity: 1;
+}
+.cell-tag[disabled],
+.tags-input input[disabled],
+.tags-input button[disabled],
+fieldset[disabled] .cell-tag,
+fieldset[disabled] .tags-input input,
+fieldset[disabled] .tags-input button {
+  cursor: not-allowed;
+}
+textarea.cell-tag,
+textarea.tags-input input,
+textarea.tags-input button {
+  height: auto;
+}
+select.cell-tag,
+select.tags-input input,
+select.tags-input button {
+  height: 30px;
+  line-height: 30px;
+}
+textarea.cell-tag,
+textarea.tags-input input,
+textarea.tags-input button,
+select[multiple].cell-tag,
+select[multiple].tags-input input,
+select[multiple].tags-input button {
+  height: auto;
+}
+.cell-tag,
+.tags-input button {
+  padding: 0px 4px;
+}
+.cell-tag {
+  background-color: #fff;
+  white-space: nowrap;
+}
+.tags-input input[type=text]:focus {
+  outline: none;
+  box-shadow: none;
+  border-color: #ccc;
+}
+.completions {
+  position: absolute;
+  z-index: 110;
+  overflow: hidden;
+  border: 1px solid #ababab;
+  border-radius: 2px;
+  -webkit-box-shadow: 0px 6px 10px -1px #adadad;
+  box-shadow: 0px 6px 10px -1px #adadad;
+  line-height: 1;
+}
+.completions select {
+  background: white;
+  outline: none;
+  border: none;
+  padding: 0px;
+  margin: 0px;
+  overflow: auto;
+  font-family: monospace;
+  font-size: 110%;
+  color: #000;
+  width: auto;
+}
+.completions select option.context {
+  color: #286090;
+}
+#kernel_logo_widget .current_kernel_logo {
+  display: none;
+  margin-top: -1px;
+  margin-bottom: -1px;
+  width: 32px;
+  height: 32px;
+}
+[dir="rtl"] #kernel_logo_widget {
+  float: left !important;
+  float: left;
+}
+.modal .modal-body .move-path {
+  display: flex;
+  flex-direction: row;
+  justify-content: space;
+  align-items: center;
+}
+.modal .modal-body .move-path .server-root {
+  padding-right: 20px;
+}
+.modal .modal-body .move-path .path-input {
+  flex: 1;
+}
+#menubar {
+  box-sizing: border-box;
+  -moz-box-sizing: border-box;
+  -webkit-box-sizing: border-box;
+  margin-top: 1px;
+}
+#menubar .navbar {
+  border-top: 1px;
+  border-radius: 0px 0px 2px 2px;
+  margin-bottom: 0px;
+}
+#menubar .navbar-toggle {
+  float: left;
+  padding-top: 7px;
+  padding-bottom: 7px;
+  border: none;
+}
+#menubar .navbar-collapse {
+  clear: left;
+}
+[dir="rtl"] #menubar .navbar-toggle {
+  float: right;
+}
+[dir="rtl"] #menubar .navbar-collapse {
+  clear: right;
+}
+[dir="rtl"] #menubar .navbar-nav {
+  float: right;
+}
+[dir="rtl"] #menubar .nav {
+  padding-right: 0px;
+}
+[dir="rtl"] #menubar .navbar-nav > li {
+  float: right;
+}
+[dir="rtl"] #menubar .navbar-right {
+  float: left !important;
+}
+[dir="rtl"] ul.dropdown-menu {
+  text-align: right;
+  left: auto;
+}
+[dir="rtl"] ul#new-menu.dropdown-menu {
+  right: auto;
+  left: 0;
+}
+.nav-wrapper {
+  border-bottom: 1px solid #e7e7e7;
+}
+i.menu-icon {
+  padding-top: 4px;
+}
+[dir="rtl"] i.menu-icon.pull-right {
+  float: left !important;
+  float: left;
+}
+ul#help_menu li a {
+  overflow: hidden;
+  padding-right: 2.2em;
+}
+ul#help_menu li a i {
+  margin-right: -1.2em;
+}
+[dir="rtl"] ul#help_menu li a {
+  padding-left: 2.2em;
+}
+[dir="rtl"] ul#help_menu li a i {
+  margin-right: 0;
+  margin-left: -1.2em;
+}
+[dir="rtl"] ul#help_menu li a i.pull-right {
+  float: left !important;
+  float: left;
+}
+.dropdown-submenu {
+  position: relative;
+}
+.dropdown-submenu > .dropdown-menu {
+  top: 0;
+  left: 100%;
+  margin-top: -6px;
+  margin-left: -1px;
+}
+[dir="rtl"] .dropdown-submenu > .dropdown-menu {
+  right: 100%;
+  margin-right: -1px;
+}
+.dropdown-submenu:hover > .dropdown-menu {
+  display: block;
+}
+.dropdown-submenu > a:after {
+  display: inline-block;
+  font: normal normal normal 14px/1 FontAwesome;
+  font-size: inherit;
+  text-rendering: auto;
+  -webkit-font-smoothing: antialiased;
+  -moz-osx-font-smoothing: grayscale;
+  display: block;
+  content: "\f0da";
+  float: right;
+  color: #333333;
+  margin-top: 2px;
+  margin-right: -10px;
+}
+.dropdown-submenu > a:after.fa-pull-left {
+  margin-right: .3em;
+}
+.dropdown-submenu > a:after.fa-pull-right {
+  margin-left: .3em;
+}
+.dropdown-submenu > a:after.pull-left {
+  margin-right: .3em;
+}
+.dropdown-submenu > a:after.pull-right {
+  margin-left: .3em;
+}
+[dir="rtl"] .dropdown-submenu > a:after {
+  float: left;
+  content: "\f0d9";
+  margin-right: 0;
+  margin-left: -10px;
+}
+.dropdown-submenu:hover > a:after {
+  color: #262626;
+}
+.dropdown-submenu.pull-left {
+  float: none;
+}
+.dropdown-submenu.pull-left > .dropdown-menu {
+  left: -100%;
+  margin-left: 10px;
+}
+#notification_area {
+  float: right !important;
+  float: right;
+  z-index: 10;
+}
+[dir="rtl"] #notification_area {
+  float: left !important;
+  float: left;
+}
+.indicator_area {
+  float: right !important;
+  float: right;
+  color: #777;
+  margin-left: 5px;
+  margin-right: 5px;
+  width: 11px;
+  z-index: 10;
+  text-align: center;
+  width: auto;
+}
+[dir="rtl"] .indicator_area {
+  float: left !important;
+  float: left;
+}
+#kernel_indicator {
+  float: right !important;
+  float: right;
+  color: #777;
+  margin-left: 5px;
+  margin-right: 5px;
+  width: 11px;
+  z-index: 10;
+  text-align: center;
+  width: auto;
+  border-left: 1px solid;
+}
+#kernel_indicator .kernel_indicator_name {
+  padding-left: 5px;
+  padding-right: 5px;
+}
+[dir="rtl"] #kernel_indicator {
+  float: left !important;
+  float: left;
+  border-left: 0;
+  border-right: 1px solid;
+}
+#modal_indicator {
+  float: right !important;
+  float: right;
+  color: #777;
+  margin-left: 5px;
+  margin-right: 5px;
+  width: 11px;
+  z-index: 10;
+  text-align: center;
+  width: auto;
+}
+[dir="rtl"] #modal_indicator {
+  float: left !important;
+  float: left;
+}
+#readonly-indicator {
+  float: right !important;
+  float: right;
+  color: #777;
+  margin-left: 5px;
+  margin-right: 5px;
+  width: 11px;
+  z-index: 10;
+  text-align: center;
+  width: auto;
+  margin-top: 2px;
+  margin-bottom: 0px;
+  margin-left: 0px;
+  margin-right: 0px;
+  display: none;
+}
+.modal_indicator:before {
+  width: 1.28571429em;
+  text-align: center;
+}
+.edit_mode .modal_indicator:before {
+  display: inline-block;
+  font: normal normal normal 14px/1 FontAwesome;
+  font-size: inherit;
+  text-rendering: auto;
+  -webkit-font-smoothing: antialiased;
+  -moz-osx-font-smoothing: grayscale;
+  content: "\f040";
+}
+.edit_mode .modal_indicator:before.fa-pull-left {
+  margin-right: .3em;
+}
+.edit_mode .modal_indicator:before.fa-pull-right {
+  margin-left: .3em;
+}
+.edit_mode .modal_indicator:before.pull-left {
+  margin-right: .3em;
+}
+.edit_mode .modal_indicator:before.pull-right {
+  margin-left: .3em;
+}
+.command_mode .modal_indicator:before {
+  display: inline-block;
+  font: normal normal normal 14px/1 FontAwesome;
+  font-size: inherit;
+  text-rendering: auto;
+  -webkit-font-smoothing: antialiased;
+  -moz-osx-font-smoothing: grayscale;
+  content: ' ';
+}
+.command_mode .modal_indicator:before.fa-pull-left {
+  margin-right: .3em;
+}
+.command_mode .modal_indicator:before.fa-pull-right {
+  margin-left: .3em;
+}
+.command_mode .modal_indicator:before.pull-left {
+  margin-right: .3em;
+}
+.command_mode .modal_indicator:before.pull-right {
+  margin-left: .3em;
+}
+.kernel_idle_icon:before {
+  display: inline-block;
+  font: normal normal normal 14px/1 FontAwesome;
+  font-size: inherit;
+  text-rendering: auto;
+  -webkit-font-smoothing: antialiased;
+  -moz-osx-font-smoothing: grayscale;
+  content: "\f10c";
+}
+.kernel_idle_icon:before.fa-pull-left {
+  margin-right: .3em;
+}
+.kernel_idle_icon:before.fa-pull-right {
+  margin-left: .3em;
+}
+.kernel_idle_icon:before.pull-left {
+  margin-right: .3em;
+}
+.kernel_idle_icon:before.pull-right {
+  margin-left: .3em;
+}
+.kernel_busy_icon:before {
+  display: inline-block;
+  font: normal normal normal 14px/1 FontAwesome;
+  font-size: inherit;
+  text-rendering: auto;
+  -webkit-font-smoothing: antialiased;
+  -moz-osx-font-smoothing: grayscale;
+  content: "\f111";
+}
+.kernel_busy_icon:before.fa-pull-left {
+  margin-right: .3em;
+}
+.kernel_busy_icon:before.fa-pull-right {
+  margin-left: .3em;
+}
+.kernel_busy_icon:before.pull-left {
+  margin-right: .3em;
+}
+.kernel_busy_icon:before.pull-right {
+  margin-left: .3em;
+}
+.kernel_dead_icon:before {
+  display: inline-block;
+  font: normal normal normal 14px/1 FontAwesome;
+  font-size: inherit;
+  text-rendering: auto;
+  -webkit-font-smoothing: antialiased;
+  -moz-osx-font-smoothing: grayscale;
+  content: "\f1e2";
+}
+.kernel_dead_icon:before.fa-pull-left {
+  margin-right: .3em;
+}
+.kernel_dead_icon:before.fa-pull-right {
+  margin-left: .3em;
+}
+.kernel_dead_icon:before.pull-left {
+  margin-right: .3em;
+}
+.kernel_dead_icon:before.pull-right {
+  margin-left: .3em;
+}
+.kernel_disconnected_icon:before {
+  display: inline-block;
+  font: normal normal normal 14px/1 FontAwesome;
+  font-size: inherit;
+  text-rendering: auto;
+  -webkit-font-smoothing: antialiased;
+  -moz-osx-font-smoothing: grayscale;
+  content: "\f127";
+}
+.kernel_disconnected_icon:before.fa-pull-left {
+  margin-right: .3em;
+}
+.kernel_disconnected_icon:before.fa-pull-right {
+  margin-left: .3em;
+}
+.kernel_disconnected_icon:before.pull-left {
+  margin-right: .3em;
+}
+.kernel_disconnected_icon:before.pull-right {
+  margin-left: .3em;
+}
+.notification_widget {
+  color: #777;
+  z-index: 10;
+  background: rgba(240, 240, 240, 0.5);
+  margin-right: 4px;
+  color: #333;
+  background-color: #fff;
+  border-color: #ccc;
+}
+.notification_widget:focus,
+.notification_widget.focus {
+  color: #333;
+  background-color: #e6e6e6;
+  border-color: #8c8c8c;
+}
+.notification_widget:hover {
+  color: #333;
+  background-color: #e6e6e6;
+  border-color: #adadad;
+}
+.notification_widget:active,
+.notification_widget.active,
+.open > .dropdown-toggle.notification_widget {
+  color: #333;
+  background-color: #e6e6e6;
+  border-color: #adadad;
+}
+.notification_widget:active:hover,
+.notification_widget.active:hover,
+.open > .dropdown-toggle.notification_widget:hover,
+.notification_widget:active:focus,
+.notification_widget.active:focus,
+.open > .dropdown-toggle.notification_widget:focus,
+.notification_widget:active.focus,
+.notification_widget.active.focus,
+.open > .dropdown-toggle.notification_widget.focus {
+  color: #333;
+  background-color: #d4d4d4;
+  border-color: #8c8c8c;
+}
+.notification_widget:active,
+.notification_widget.active,
+.open > .dropdown-toggle.notification_widget {
+  background-image: none;
+}
+.notification_widget.disabled:hover,
+.notification_widget[disabled]:hover,
+fieldset[disabled] .notification_widget:hover,
+.notification_widget.disabled:focus,
+.notification_widget[disabled]:focus,
+fieldset[disabled] .notification_widget:focus,
+.notification_widget.disabled.focus,
+.notification_widget[disabled].focus,
+fieldset[disabled] .notification_widget.focus {
+  background-color: #fff;
+  border-color: #ccc;
+}
+.notification_widget .badge {
+  color: #fff;
+  background-color: #333;
+}
+.notification_widget.warning {
+  color: #fff;
+  background-color: #f0ad4e;
+  border-color: #eea236;
+}
+.notification_widget.warning:focus,
+.notification_widget.warning.focus {
+  color: #fff;
+  background-color: #ec971f;
+  border-color: #985f0d;
+}
+.notification_widget.warning:hover {
+  color: #fff;
+  background-color: #ec971f;
+  border-color: #d58512;
+}
+.notification_widget.warning:active,
+.notification_widget.warning.active,
+.open > .dropdown-toggle.notification_widget.warning {
+  color: #fff;
+  background-color: #ec971f;
+  border-color: #d58512;
+}
+.notification_widget.warning:active:hover,
+.notification_widget.warning.active:hover,
+.open > .dropdown-toggle.notification_widget.warning:hover,
+.notification_widget.warning:active:focus,
+.notification_widget.warning.active:focus,
+.open > .dropdown-toggle.notification_widget.warning:focus,
+.notification_widget.warning:active.focus,
+.notification_widget.warning.active.focus,
+.open > .dropdown-toggle.notification_widget.warning.focus {
+  color: #fff;
+  background-color: #d58512;
+  border-color: #985f0d;
+}
+.notification_widget.warning:active,
+.notification_widget.warning.active,
+.open > .dropdown-toggle.notification_widget.warning {
+  background-image: none;
+}
+.notification_widget.warning.disabled:hover,
+.notification_widget.warning[disabled]:hover,
+fieldset[disabled] .notification_widget.warning:hover,
+.notification_widget.warning.disabled:focus,
+.notification_widget.warning[disabled]:focus,
+fieldset[disabled] .notification_widget.warning:focus,
+.notification_widget.warning.disabled.focus,
+.notification_widget.warning[disabled].focus,
+fieldset[disabled] .notification_widget.warning.focus {
+  background-color: #f0ad4e;
+  border-color: #eea236;
+}
+.notification_widget.warning .badge {
+  color: #f0ad4e;
+  background-color: #fff;
+}
+.notification_widget.success {
+  color: #fff;
+  background-color: #5cb85c;
+  border-color: #4cae4c;
+}
+.notification_widget.success:focus,
+.notification_widget.success.focus {
+  color: #fff;
+  background-color: #449d44;
+  border-color: #255625;
+}
+.notification_widget.success:hover {
+  color: #fff;
+  background-color: #449d44;
+  border-color: #398439;
+}
+.notification_widget.success:active,
+.notification_widget.success.active,
+.open > .dropdown-toggle.notification_widget.success {
+  color: #fff;
+  background-color: #449d44;
+  border-color: #398439;
+}
+.notification_widget.success:active:hover,
+.notification_widget.success.active:hover,
+.open > .dropdown-toggle.notification_widget.success:hover,
+.notification_widget.success:active:focus,
+.notification_widget.success.active:focus,
+.open > .dropdown-toggle.notification_widget.success:focus,
+.notification_widget.success:active.focus,
+.notification_widget.success.active.focus,
+.open > .dropdown-toggle.notification_widget.success.focus {
+  color: #fff;
+  background-color: #398439;
+  border-color: #255625;
+}
+.notification_widget.success:active,
+.notification_widget.success.active,
+.open > .dropdown-toggle.notification_widget.success {
+  background-image: none;
+}
+.notification_widget.success.disabled:hover,
+.notification_widget.success[disabled]:hover,
+fieldset[disabled] .notification_widget.success:hover,
+.notification_widget.success.disabled:focus,
+.notification_widget.success[disabled]:focus,
+fieldset[disabled] .notification_widget.success:focus,
+.notification_widget.success.disabled.focus,
+.notification_widget.success[disabled].focus,
+fieldset[disabled] .notification_widget.success.focus {
+  background-color: #5cb85c;
+  border-color: #4cae4c;
+}
+.notification_widget.success .badge {
+  color: #5cb85c;
+  background-color: #fff;
+}
+.notification_widget.info {
+  color: #fff;
+  background-color: #5bc0de;
+  border-color: #46b8da;
+}
+.notification_widget.info:focus,
+.notification_widget.info.focus {
+  color: #fff;
+  background-color: #31b0d5;
+  border-color: #1b6d85;
+}
+.notification_widget.info:hover {
+  color: #fff;
+  background-color: #31b0d5;
+  border-color: #269abc;
+}
+.notification_widget.info:active,
+.notification_widget.info.active,
+.open > .dropdown-toggle.notification_widget.info {
+  color: #fff;
+  background-color: #31b0d5;
+  border-color: #269abc;
+}
+.notification_widget.info:active:hover,
+.notification_widget.info.active:hover,
+.open > .dropdown-toggle.notification_widget.info:hover,
+.notification_widget.info:active:focus,
+.notification_widget.info.active:focus,
+.open > .dropdown-toggle.notification_widget.info:focus,
+.notification_widget.info:active.focus,
+.notification_widget.info.active.focus,
+.open > .dropdown-toggle.notification_widget.info.focus {
+  color: #fff;
+  background-color: #269abc;
+  border-color: #1b6d85;
+}
+.notification_widget.info:active,
+.notification_widget.info.active,
+.open > .dropdown-toggle.notification_widget.info {
+  background-image: none;
+}
+.notification_widget.info.disabled:hover,
+.notification_widget.info[disabled]:hover,
+fieldset[disabled] .notification_widget.info:hover,
+.notification_widget.info.disabled:focus,
+.notification_widget.info[disabled]:focus,
+fieldset[disabled] .notification_widget.info:focus,
+.notification_widget.info.disabled.focus,
+.notification_widget.info[disabled].focus,
+fieldset[disabled] .notification_widget.info.focus {
+  background-color: #5bc0de;
+  border-color: #46b8da;
+}
+.notification_widget.info .badge {
+  color: #5bc0de;
+  background-color: #fff;
+}
+.notification_widget.danger {
+  color: #fff;
+  background-color: #d9534f;
+  border-color: #d43f3a;
+}
+.notification_widget.danger:focus,
+.notification_widget.danger.focus {
+  color: #fff;
+  background-color: #c9302c;
+  border-color: #761c19;
+}
+.notification_widget.danger:hover {
+  color: #fff;
+  background-color: #c9302c;
+  border-color: #ac2925;
+}
+.notification_widget.danger:active,
+.notification_widget.danger.active,
+.open > .dropdown-toggle.notification_widget.danger {
+  color: #fff;
+  background-color: #c9302c;
+  border-color: #ac2925;
+}
+.notification_widget.danger:active:hover,
+.notification_widget.danger.active:hover,
+.open > .dropdown-toggle.notification_widget.danger:hover,
+.notification_widget.danger:active:focus,
+.notification_widget.danger.active:focus,
+.open > .dropdown-toggle.notification_widget.danger:focus,
+.notification_widget.danger:active.focus,
+.notification_widget.danger.active.focus,
+.open > .dropdown-toggle.notification_widget.danger.focus {
+  color: #fff;
+  background-color: #ac2925;
+  border-color: #761c19;
+}
+.notification_widget.danger:active,
+.notification_widget.danger.active,
+.open > .dropdown-toggle.notification_widget.danger {
+  background-image: none;
+}
+.notification_widget.danger.disabled:hover,
+.notification_widget.danger[disabled]:hover,
+fieldset[disabled] .notification_widget.danger:hover,
+.notification_widget.danger.disabled:focus,
+.notification_widget.danger[disabled]:focus,
+fieldset[disabled] .notification_widget.danger:focus,
+.notification_widget.danger.disabled.focus,
+.notification_widget.danger[disabled].focus,
+fieldset[disabled] .notification_widget.danger.focus {
+  background-color: #d9534f;
+  border-color: #d43f3a;
+}
+.notification_widget.danger .badge {
+  color: #d9534f;
+  background-color: #fff;
+}
+div#pager {
+  background-color: #fff;
+  font-size: 14px;
+  line-height: 20px;
+  overflow: hidden;
+  display: none;
+  position: fixed;
+  bottom: 0px;
+  width: 100%;
+  max-height: 50%;
+  padding-top: 8px;
+  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
+  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
+  /* Display over codemirror */
+  z-index: 100;
+  /* Hack which prevents jquery ui resizable from changing top. */
+  top: auto !important;
+}
+div#pager pre {
+  line-height: 1.21429em;
+  color: #000;
+  background-color: #f7f7f7;
+  padding: 0.4em;
+}
+div#pager #pager-button-area {
+  position: absolute;
+  top: 8px;
+  right: 20px;
+}
+div#pager #pager-contents {
+  position: relative;
+  overflow: auto;
+  width: 100%;
+  height: 100%;
+}
+div#pager #pager-contents #pager-container {
+  position: relative;
+  padding: 15px 0px;
+  box-sizing: border-box;
+  -moz-box-sizing: border-box;
+  -webkit-box-sizing: border-box;
+}
+div#pager .ui-resizable-handle {
+  top: 0px;
+  height: 8px;
+  background: #f7f7f7;
+  border-top: 1px solid #cfcfcf;
+  border-bottom: 1px solid #cfcfcf;
+  /* This injects handle bars (a short, wide = symbol) for 
+        the resize handle. */
+}
+div#pager .ui-resizable-handle::after {
+  content: '';
+  top: 2px;
+  left: 50%;
+  height: 3px;
+  width: 30px;
+  margin-left: -15px;
+  position: absolute;
+  border-top: 1px solid #cfcfcf;
+}
+.quickhelp {
+  /* Old browsers */
+  display: -webkit-box;
+  -webkit-box-orient: horizontal;
+  -webkit-box-align: stretch;
+  display: -moz-box;
+  -moz-box-orient: horizontal;
+  -moz-box-align: stretch;
+  display: box;
+  box-orient: horizontal;
+  box-align: stretch;
+  /* Modern browsers */
+  display: flex;
+  flex-direction: row;
+  align-items: stretch;
+  line-height: 1.8em;
+}
+.shortcut_key {
+  display: inline-block;
+  width: 21ex;
+  text-align: right;
+  font-family: monospace;
+}
+.shortcut_descr {
+  display: inline-block;
+  /* Old browsers */
+  -webkit-box-flex: 1;
+  -moz-box-flex: 1;
+  box-flex: 1;
+  /* Modern browsers */
+  flex: 1;
+}
+span.save_widget {
+  height: 30px;
+  margin-top: 4px;
+  display: flex;
+  justify-content: flex-start;
+  align-items: baseline;
+  width: 50%;
+  flex: 1;
+}
+span.save_widget span.filename {
+  height: 100%;
+  line-height: 1em;
+  margin-left: 16px;
+  border: none;
+  font-size: 146.5%;
+  text-overflow: ellipsis;
+  overflow: hidden;
+  white-space: nowrap;
+  border-radius: 2px;
+}
+span.save_widget span.filename:hover {
+  background-color: #e6e6e6;
+}
+[dir="rtl"] span.save_widget.pull-left {
+  float: right !important;
+  float: right;
+}
+[dir="rtl"] span.save_widget span.filename {
+  margin-left: 0;
+  margin-right: 16px;
+}
+span.checkpoint_status,
+span.autosave_status {
+  font-size: small;
+  white-space: nowrap;
+  padding: 0 5px;
+}
+@media (max-width: 767px) {
+  span.save_widget {
+    font-size: small;
+    padding: 0 0 0 5px;
+  }
+  span.checkpoint_status,
+  span.autosave_status {
+    display: none;
+  }
+}
+@media (min-width: 768px) and (max-width: 991px) {
+  span.checkpoint_status {
+    display: none;
+  }
+  span.autosave_status {
+    font-size: x-small;
+  }
+}
+.toolbar {
+  padding: 0px;
+  margin-left: -5px;
+  margin-top: 2px;
+  margin-bottom: 5px;
+  box-sizing: border-box;
+  -moz-box-sizing: border-box;
+  -webkit-box-sizing: border-box;
+}
+.toolbar select,
+.toolbar label {
+  width: auto;
+  vertical-align: middle;
+  margin-right: 2px;
+  margin-bottom: 0px;
+  display: inline;
+  font-size: 92%;
+  margin-left: 0.3em;
+  margin-right: 0.3em;
+  padding: 0px;
+  padding-top: 3px;
+}
+.toolbar .btn {
+  padding: 2px 8px;
+}
+.toolbar .btn-group {
+  margin-top: 0px;
+  margin-left: 5px;
+}
+.toolbar-btn-label {
+  margin-left: 6px;
+}
+#maintoolbar {
+  margin-bottom: -3px;
+  margin-top: -8px;
+  border: 0px;
+  min-height: 27px;
+  margin-left: 0px;
+  padding-top: 11px;
+  padding-bottom: 3px;
+}
+#maintoolbar .navbar-text {
+  float: none;
+  vertical-align: middle;
+  text-align: right;
+  margin-left: 5px;
+  margin-right: 0px;
+  margin-top: 0px;
+}
+.select-xs {
+  height: 24px;
+}
+[dir="rtl"] .btn-group > .btn,
+.btn-group-vertical > .btn {
+  float: right;
+}
+.pulse,
+.dropdown-menu > li > a.pulse,
+li.pulse > a.dropdown-toggle,
+li.pulse.open > a.dropdown-toggle {
+  background-color: #F37626;
+  color: white;
+}
+/**
+ * Primary styles
+ *
+ * Author: Jupyter Development Team
+ */
+/** WARNING IF YOU ARE EDITTING THIS FILE, if this is a .css file, It has a lot
+ * of chance of beeing generated from the ../less/[samename].less file, you can
+ * try to get back the less file by reverting somme commit in history
+ **/
+/*
+ * We'll try to get something pretty, so we
+ * have some strange css to have the scroll bar on
+ * the left with fix button on the top right of the tooltip
+ */
+@-moz-keyframes fadeOut {
+  from {
+    opacity: 1;
+  }
+  to {
+    opacity: 0;
+  }
+}
+@-webkit-keyframes fadeOut {
+  from {
+    opacity: 1;
+  }
+  to {
+    opacity: 0;
+  }
+}
+@-moz-keyframes fadeIn {
+  from {
+    opacity: 0;
+  }
+  to {
+    opacity: 1;
+  }
+}
+@-webkit-keyframes fadeIn {
+  from {
+    opacity: 0;
+  }
+  to {
+    opacity: 1;
+  }
+}
+/*properties of tooltip after "expand"*/
+.bigtooltip {
+  overflow: auto;
+  height: 200px;
+  -webkit-transition-property: height;
+  -webkit-transition-duration: 500ms;
+  -moz-transition-property: height;
+  -moz-transition-duration: 500ms;
+  transition-property: height;
+  transition-duration: 500ms;
+}
+/*properties of tooltip before "expand"*/
+.smalltooltip {
+  -webkit-transition-property: height;
+  -webkit-transition-duration: 500ms;
+  -moz-transition-property: height;
+  -moz-transition-duration: 500ms;
+  transition-property: height;
+  transition-duration: 500ms;
+  text-overflow: ellipsis;
+  overflow: hidden;
+  height: 80px;
+}
+.tooltipbuttons {
+  position: absolute;
+  padding-right: 15px;
+  top: 0px;
+  right: 0px;
+}
+.tooltiptext {
+  /*avoid the button to overlap on some docstring*/
+  padding-right: 30px;
+}
+.ipython_tooltip {
+  max-width: 700px;
+  /*fade-in animation when inserted*/
+  -webkit-animation: fadeOut 400ms;
+  -moz-animation: fadeOut 400ms;
+  animation: fadeOut 400ms;
+  -webkit-animation: fadeIn 400ms;
+  -moz-animation: fadeIn 400ms;
+  animation: fadeIn 400ms;
+  vertical-align: middle;
+  background-color: #f7f7f7;
+  overflow: visible;
+  border: #ababab 1px solid;
+  outline: none;
+  padding: 3px;
+  margin: 0px;
+  padding-left: 7px;
+  font-family: monospace;
+  min-height: 50px;
+  -moz-box-shadow: 0px 6px 10px -1px #adadad;
+  -webkit-box-shadow: 0px 6px 10px -1px #adadad;
+  box-shadow: 0px 6px 10px -1px #adadad;
+  border-radius: 2px;
+  position: absolute;
+  z-index: 1000;
+}
+.ipython_tooltip a {
+  float: right;
+}
+.ipython_tooltip .tooltiptext pre {
+  border: 0;
+  border-radius: 0;
+  font-size: 100%;
+  background-color: #f7f7f7;
+}
+.pretooltiparrow {
+  left: 0px;
+  margin: 0px;
+  top: -16px;
+  width: 40px;
+  height: 16px;
+  overflow: hidden;
+  position: absolute;
+}
+.pretooltiparrow:before {
+  background-color: #f7f7f7;
+  border: 1px #ababab solid;
+  z-index: 11;
+  content: "";
+  position: absolute;
+  left: 15px;
+  top: 10px;
+  width: 25px;
+  height: 25px;
+  -webkit-transform: rotate(45deg);
+  -moz-transform: rotate(45deg);
+  -ms-transform: rotate(45deg);
+  -o-transform: rotate(45deg);
+}
+ul.typeahead-list i {
+  margin-left: -10px;
+  width: 18px;
+}
+[dir="rtl"] ul.typeahead-list i {
+  margin-left: 0;
+  margin-right: -10px;
+}
+ul.typeahead-list {
+  max-height: 80vh;
+  overflow: auto;
+}
+ul.typeahead-list > li > a {
+  /** Firefox bug **/
+  /* see https://github.com/jupyter/notebook/issues/559 */
+  white-space: normal;
+}
+ul.typeahead-list  > li > a.pull-right {
+  float: left !important;
+  float: left;
+}
+[dir="rtl"] .typeahead-list {
+  text-align: right;
+}
+.cmd-palette .modal-body {
+  padding: 7px;
+}
+.cmd-palette form {
+  background: white;
+}
+.cmd-palette input {
+  outline: none;
+}
+.no-shortcut {
+  min-width: 20px;
+  color: transparent;
+}
+[dir="rtl"] .no-shortcut.pull-right {
+  float: left !important;
+  float: left;
+}
+[dir="rtl"] .command-shortcut.pull-right {
+  float: left !important;
+  float: left;
+}
+.command-shortcut:before {
+  content: "(command mode)";
+  padding-right: 3px;
+  color: #777777;
+}
+.edit-shortcut:before {
+  content: "(edit)";
+  padding-right: 3px;
+  color: #777777;
+}
+[dir="rtl"] .edit-shortcut.pull-right {
+  float: left !important;
+  float: left;
+}
+#find-and-replace #replace-preview .match,
+#find-and-replace #replace-preview .insert {
+  background-color: #BBDEFB;
+  border-color: #90CAF9;
+  border-style: solid;
+  border-width: 1px;
+  border-radius: 0px;
+}
+[dir="ltr"] #find-and-replace .input-group-btn + .form-control {
+  border-left: none;
+}
+[dir="rtl"] #find-and-replace .input-group-btn + .form-control {
+  border-right: none;
+}
+#find-and-replace #replace-preview .replace .match {
+  background-color: #FFCDD2;
+  border-color: #EF9A9A;
+  border-radius: 0px;
+}
+#find-and-replace #replace-preview .replace .insert {
+  background-color: #C8E6C9;
+  border-color: #A5D6A7;
+  border-radius: 0px;
+}
+#find-and-replace #replace-preview {
+  max-height: 60vh;
+  overflow: auto;
+}
+#find-and-replace #replace-preview pre {
+  padding: 5px 10px;
+}
+.terminal-app {
+  background: #EEE;
+}
+.terminal-app #header {
+  background: #fff;
+  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
+  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
+}
+.terminal-app .terminal {
+  width: 100%;
+  float: left;
+  font-family: monospace;
+  color: white;
+  background: black;
+  padding: 0.4em;
+  border-radius: 2px;
+  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.4);
+  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.4);
+}
+.terminal-app .terminal,
+.terminal-app .terminal dummy-screen {
+  line-height: 1em;
+  font-size: 14px;
+}
+.terminal-app .terminal .xterm-rows {
+  padding: 10px;
+}
+.terminal-app .terminal-cursor {
+  color: black;
+  background: white;
+}
+.terminal-app #terminado-container {
+  margin-top: 20px;
+}
+/*# sourceMappingURL=style.min.css.map */
+    </style>
+<style type="text/css">
+    .highlight .hll { background-color: #ffffcc }
+.highlight  { background: #f8f8f8; }
+.highlight .c { color: #408080; font-style: italic } /* Comment */
+.highlight .err { border: 1px solid #FF0000 } /* Error */
+.highlight .k { color: #008000; font-weight: bold } /* Keyword */
+.highlight .o { color: #666666 } /* Operator */
+.highlight .ch { color: #408080; font-style: italic } /* Comment.Hashbang */
+.highlight .cm { color: #408080; font-style: italic } /* Comment.Multiline */
+.highlight .cp { color: #BC7A00 } /* Comment.Preproc */
+.highlight .cpf { color: #408080; font-style: italic } /* Comment.PreprocFile */
+.highlight .c1 { color: #408080; font-style: italic } /* Comment.Single */
+.highlight .cs { color: #408080; font-style: italic } /* Comment.Special */
+.highlight .gd { color: #A00000 } /* Generic.Deleted */
+.highlight .ge { font-style: italic } /* Generic.Emph */
+.highlight .gr { color: #FF0000 } /* Generic.Error */
+.highlight .gh { color: #000080; font-weight: bold } /* Generic.Heading */
+.highlight .gi { color: #00A000 } /* Generic.Inserted */
+.highlight .go { color: #888888 } /* Generic.Output */
+.highlight .gp { color: #000080; font-weight: bold } /* Generic.Prompt */
+.highlight .gs { font-weight: bold } /* Generic.Strong */
+.highlight .gu { color: #800080; font-weight: bold } /* Generic.Subheading */
+.highlight .gt { color: #0044DD } /* Generic.Traceback */
+.highlight .kc { color: #008000; font-weight: bold } /* Keyword.Constant */
+.highlight .kd { color: #008000; font-weight: bold } /* Keyword.Declaration */
+.highlight .kn { color: #008000; font-weight: bold } /* Keyword.Namespace */
+.highlight .kp { color: #008000 } /* Keyword.Pseudo */
+.highlight .kr { color: #008000; font-weight: bold } /* Keyword.Reserved */
+.highlight .kt { color: #B00040 } /* Keyword.Type */
+.highlight .m { color: #666666 } /* Literal.Number */
+.highlight .s { color: #BA2121 } /* Literal.String */
+.highlight .na { color: #7D9029 } /* Name.Attribute */
+.highlight .nb { color: #008000 } /* Name.Builtin */
+.highlight .nc { color: #0000FF; font-weight: bold } /* Name.Class */
+.highlight .no { color: #880000 } /* Name.Constant */
+.highlight .nd { color: #AA22FF } /* Name.Decorator */
+.highlight .ni { color: #999999; font-weight: bold } /* Name.Entity */
+.highlight .ne { color: #D2413A; font-weight: bold } /* Name.Exception */
+.highlight .nf { color: #0000FF } /* Name.Function */
+.highlight .nl { color: #A0A000 } /* Name.Label */
+.highlight .nn { color: #0000FF; font-weight: bold } /* Name.Namespace */
+.highlight .nt { color: #008000; font-weight: bold } /* Name.Tag */
+.highlight .nv { color: #19177C } /* Name.Variable */
+.highlight .ow { color: #AA22FF; font-weight: bold } /* Operator.Word */
+.highlight .w { color: #bbbbbb } /* Text.Whitespace */
+.highlight .mb { color: #666666 } /* Literal.Number.Bin */
+.highlight .mf { color: #666666 } /* Literal.Number.Float */
+.highlight .mh { color: #666666 } /* Literal.Number.Hex */
+.highlight .mi { color: #666666 } /* Literal.Number.Integer */
+.highlight .mo { color: #666666 } /* Literal.Number.Oct */
+.highlight .sa { color: #BA2121 } /* Literal.String.Affix */
+.highlight .sb { color: #BA2121 } /* Literal.String.Backtick */
+.highlight .sc { color: #BA2121 } /* Literal.String.Char */
+.highlight .dl { color: #BA2121 } /* Literal.String.Delimiter */
+.highlight .sd { color: #BA2121; font-style: italic } /* Literal.String.Doc */
+.highlight .s2 { color: #BA2121 } /* Literal.String.Double */
+.highlight .se { color: #BB6622; font-weight: bold } /* Literal.String.Escape */
+.highlight .sh { color: #BA2121 } /* Literal.String.Heredoc */
+.highlight .si { color: #BB6688; font-weight: bold } /* Literal.String.Interpol */
+.highlight .sx { color: #008000 } /* Literal.String.Other */
+.highlight .sr { color: #BB6688 } /* Literal.String.Regex */
+.highlight .s1 { color: #BA2121 } /* Literal.String.Single */
+.highlight .ss { color: #19177C } /* Literal.String.Symbol */
+.highlight .bp { color: #008000 } /* Name.Builtin.Pseudo */
+.highlight .fm { color: #0000FF } /* Name.Function.Magic */
+.highlight .vc { color: #19177C } /* Name.Variable.Class */
+.highlight .vg { color: #19177C } /* Name.Variable.Global */
+.highlight .vi { color: #19177C } /* Name.Variable.Instance */
+.highlight .vm { color: #19177C } /* Name.Variable.Magic */
+.highlight .il { color: #666666 } /* Literal.Number.Integer.Long */
+    </style>
+
+
+<style type="text/css">
+/* Overrides of notebook CSS for static HTML export */
+body {
+  overflow: visible;
+  padding: 8px;
+}
+
+div#notebook {
+  overflow: visible;
+  border-top: none;
+}@media print {
+  div.cell {
+    display: block;
+    page-break-inside: avoid;
+  } 
+  div.output_wrapper { 
+    display: block;
+    page-break-inside: avoid; 
+  }
+  div.output { 
+    display: block;
+    page-break-inside: avoid; 
+  }
+}
+</style>
+
+<!-- Custom stylesheet, it must be in the same directory as the html file -->
+<link rel="stylesheet" href="custom.css">
+
+<!-- Loading mathjax macro -->
+<!-- Load mathjax -->
+    <script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/latest.js?config=TeX-AMS_HTML"></script>
+    <!-- MathJax configuration -->
+    <script type="text/x-mathjax-config">
+    MathJax.Hub.Config({
+        tex2jax: {
+            inlineMath: [ ['$','$'], ["\\(","\\)"] ],
+            displayMath: [ ['$$','$$'], ["\\[","\\]"] ],
+            processEscapes: true,
+            processEnvironments: true
+        },
+        // Center justify equations in code and markdown cells. Elsewhere
+        // we use CSS to left justify single line equations in code cells.
+        displayAlign: 'center',
+        "HTML-CSS": {
+            styles: {'.MathJax_Display': {"margin": 0}},
+            linebreaks: { automatic: true }
+        }
+    });
+    </script>
+    <!-- End of mathjax configuration --></head>
+<body>
+  <div tabindex="-1" id="notebook" class="border-box-sizing">
+    <div class="container" id="notebook-container">
+
+<div class="cell border-box-sizing code_cell rendered">
+<div class="input">
+<div class="prompt input_prompt">In&nbsp;[1]:</div>
+<div class="inner_cell">
+    <div class="input_area">
+<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
+<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
+<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
+<span class="kn">import</span> <span class="nn">seaborn</span> <span class="k">as</span> <span class="nn">sns</span>
+</pre></div>
+
+    </div>
+</div>
+</div>
+
+</div>
+<div class="cell border-box-sizing code_cell rendered">
+<div class="input">
+<div class="prompt input_prompt">In&nbsp;[2]:</div>
+<div class="inner_cell">
+    <div class="input_area">
+<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">sklearn.linear_model</span> <span class="k">import</span> <span class="n">LinearRegression</span>
+<span class="kn">from</span> <span class="nn">sklearn.linear_model</span> <span class="k">import</span> <span class="n">LogisticRegression</span>
+<span class="kn">from</span> <span class="nn">sklearn.ensemble</span> <span class="k">import</span> <span class="n">RandomForestClassifier</span>
+</pre></div>
+
+    </div>
+</div>
+</div>
+
+</div>
+<div class="cell border-box-sizing code_cell rendered">
+<div class="input">
+<div class="prompt input_prompt">In&nbsp;[3]:</div>
+<div class="inner_cell">
+    <div class="input_area">
+<div class=" highlight hl-ipython3"><pre><span></span><span class="n">train_df</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="s1">&#39;../../data/training_dataset_500.csv&#39;</span><span class="p">)</span>
+<span class="n">test_df</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="s1">&#39;../../data/test_dataset_500.csv&#39;</span><span class="p">)</span>
+</pre></div>
+
+    </div>
+</div>
+</div>
+
+</div>
+<div class="cell border-box-sizing code_cell rendered">
+<div class="input">
+<div class="prompt input_prompt">In&nbsp;[4]:</div>
+<div class="inner_cell">
+    <div class="input_area">
+<div class=" highlight hl-ipython3"><pre><span></span><span class="n">train_df</span><span class="o">.</span><span class="n">head</span><span class="p">(</span><span class="mi">12</span><span class="p">)</span>
+</pre></div>
+
+    </div>
+</div>
+</div>
+
+<div class="output_wrapper">
+<div class="output">
+
+
+<div class="output_area">
+
+    <div class="prompt output_prompt">Out[4]:</div>
+
+
+
+<div class="output_html rendered_html output_subarea output_execute_result">
+<div>
+<style scoped>
+    .dataframe tbody tr th:only-of-type {
+        vertical-align: middle;
+    }
+
+    .dataframe tbody tr th {
+        vertical-align: top;
+    }
+
+    .dataframe thead th {
+        text-align: right;
+    }
+</style>
+<table border="1" class="dataframe">
+  <thead>
+    <tr style="text-align: right;">
+      <th></th>
+      <th>ID</th>
+      <th>Label</th>
+      <th>House</th>
+      <th>Year</th>
+      <th>Month</th>
+      <th>Temperature</th>
+      <th>Daylight</th>
+      <th>EnergyProduction</th>
+    </tr>
+  </thead>
+  <tbody>
+    <tr>
+      <td>0</td>
+      <td>0</td>
+      <td>0</td>
+      <td>1</td>
+      <td>2011</td>
+      <td>7</td>
+      <td>26.2</td>
+      <td>178.9</td>
+      <td>740</td>
+    </tr>
+    <tr>
+      <td>1</td>
+      <td>1</td>
+      <td>1</td>
+      <td>1</td>
+      <td>2011</td>
+      <td>8</td>
+      <td>25.8</td>
+      <td>169.7</td>
+      <td>731</td>
+    </tr>
+    <tr>
+      <td>2</td>
+      <td>2</td>
+      <td>2</td>
+      <td>1</td>
+      <td>2011</td>
+      <td>9</td>
+      <td>22.8</td>
+      <td>170.2</td>
+      <td>694</td>
+    </tr>
+    <tr>
+      <td>3</td>
+      <td>3</td>
+      <td>3</td>
+      <td>1</td>
+      <td>2011</td>
+      <td>10</td>
+      <td>16.4</td>
+      <td>169.1</td>
+      <td>688</td>
+    </tr>
+    <tr>
+      <td>4</td>
+      <td>4</td>
+      <td>4</td>
+      <td>1</td>
+      <td>2011</td>
+      <td>11</td>
+      <td>11.4</td>
+      <td>169.1</td>
+      <td>650</td>
+    </tr>
+    <tr>
+      <td>5</td>
+      <td>5</td>
+      <td>5</td>
+      <td>1</td>
+      <td>2011</td>
+      <td>12</td>
+      <td>4.2</td>
+      <td>199.5</td>
+      <td>763</td>
+    </tr>
+    <tr>
+      <td>6</td>
+      <td>6</td>
+      <td>6</td>
+      <td>1</td>
+      <td>2012</td>
+      <td>1</td>
+      <td>1.8</td>
+      <td>203.1</td>
+      <td>765</td>
+    </tr>
+    <tr>
+      <td>7</td>
+      <td>7</td>
+      <td>7</td>
+      <td>1</td>
+      <td>2012</td>
+      <td>2</td>
+      <td>2.8</td>
+      <td>178.2</td>
+      <td>706</td>
+    </tr>
+    <tr>
+      <td>8</td>
+      <td>8</td>
+      <td>8</td>
+      <td>1</td>
+      <td>2012</td>
+      <td>3</td>
+      <td>6.7</td>
+      <td>172.7</td>
+      <td>788</td>
+    </tr>
+    <tr>
+      <td>9</td>
+      <td>9</td>
+      <td>9</td>
+      <td>1</td>
+      <td>2012</td>
+      <td>4</td>
+      <td>12.6</td>
+      <td>182.2</td>
+      <td>831</td>
+    </tr>
+    <tr>
+      <td>10</td>
+      <td>10</td>
+      <td>10</td>
+      <td>1</td>
+      <td>2012</td>
+      <td>5</td>
+      <td>17.6</td>
+      <td>214.2</td>
+      <td>955</td>
+    </tr>
+    <tr>
+      <td>11</td>
+      <td>11</td>
+      <td>11</td>
+      <td>1</td>
+      <td>2012</td>
+      <td>6</td>
+      <td>20.8</td>
+      <td>143.0</td>
+      <td>837</td>
+    </tr>
+  </tbody>
+</table>
+</div>
+</div>
+
+</div>
+
+</div>
+</div>
+
+</div>
+<div class="cell border-box-sizing code_cell rendered">
+<div class="input">
+<div class="prompt input_prompt">In&nbsp;[5]:</div>
+<div class="inner_cell">
+    <div class="input_area">
+<div class=" highlight hl-ipython3"><pre><span></span><span class="n">train_df</span><span class="o">.</span><span class="n">tail</span><span class="p">(</span><span class="mi">12</span><span class="p">)</span>
+</pre></div>
+
+    </div>
+</div>
+</div>
+
+<div class="output_wrapper">
+<div class="output">
+
+
+<div class="output_area">
+
+    <div class="prompt output_prompt">Out[5]:</div>
+
+
+
+<div class="output_html rendered_html output_subarea output_execute_result">
+<div>
+<style scoped>
+    .dataframe tbody tr th:only-of-type {
+        vertical-align: middle;
+    }
+
+    .dataframe tbody tr th {
+        vertical-align: top;
+    }
+
+    .dataframe thead th {
+        text-align: right;
+    }
+</style>
+<table border="1" class="dataframe">
+  <thead>
+    <tr style="text-align: right;">
+      <th></th>
+      <th>ID</th>
+      <th>Label</th>
+      <th>House</th>
+      <th>Year</th>
+      <th>Month</th>
+      <th>Temperature</th>
+      <th>Daylight</th>
+      <th>EnergyProduction</th>
+    </tr>
+  </thead>
+  <tbody>
+    <tr>
+      <td>11488</td>
+      <td>11987</td>
+      <td>11</td>
+      <td>500</td>
+      <td>2012</td>
+      <td>6</td>
+      <td>21.8</td>
+      <td>152.1</td>
+      <td>645</td>
+    </tr>
+    <tr>
+      <td>11489</td>
+      <td>11988</td>
+      <td>12</td>
+      <td>500</td>
+      <td>2012</td>
+      <td>7</td>
+      <td>26.2</td>
+      <td>169.8</td>
+      <td>661</td>
+    </tr>
+    <tr>
+      <td>11490</td>
+      <td>11989</td>
+      <td>13</td>
+      <td>500</td>
+      <td>2012</td>
+      <td>8</td>
+      <td>27.8</td>
+      <td>257.9</td>
+      <td>822</td>
+    </tr>
+    <tr>
+      <td>11491</td>
+      <td>11990</td>
+      <td>14</td>
+      <td>500</td>
+      <td>2012</td>
+      <td>9</td>
+      <td>24.7</td>
+      <td>183.2</td>
+      <td>665</td>
+    </tr>
+    <tr>
+      <td>11492</td>
+      <td>11991</td>
+      <td>15</td>
+      <td>500</td>
+      <td>2012</td>
+      <td>10</td>
+      <td>17.4</td>
+      <td>201.2</td>
+      <td>655</td>
+    </tr>
+    <tr>
+      <td>11493</td>
+      <td>11992</td>
+      <td>16</td>
+      <td>500</td>
+      <td>2012</td>
+      <td>11</td>
+      <td>9.7</td>
+      <td>203.5</td>
+      <td>582</td>
+    </tr>
+    <tr>
+      <td>11494</td>
+      <td>11993</td>
+      <td>17</td>
+      <td>500</td>
+      <td>2012</td>
+      <td>12</td>
+      <td>3.8</td>
+      <td>194.2</td>
+      <td>534</td>
+    </tr>
+    <tr>
+      <td>11495</td>
+      <td>11994</td>
+      <td>18</td>
+      <td>500</td>
+      <td>2013</td>
+      <td>1</td>
+      <td>2.0</td>
+      <td>234.6</td>
+      <td>640</td>
+    </tr>
+    <tr>
+      <td>11496</td>
+      <td>11995</td>
+      <td>19</td>
+      <td>500</td>
+      <td>2013</td>
+      <td>2</td>
+      <td>4.2</td>
+      <td>201.8</td>
+      <td>638</td>
+    </tr>
+    <tr>
+      <td>11497</td>
+      <td>11996</td>
+      <td>20</td>
+      <td>500</td>
+      <td>2013</td>
+      <td>3</td>
+      <td>11.2</td>
+      <td>234.0</td>
+      <td>778</td>
+    </tr>
+    <tr>
+      <td>11498</td>
+      <td>11997</td>
+      <td>21</td>
+      <td>500</td>
+      <td>2013</td>
+      <td>4</td>
+      <td>13.6</td>
+      <td>237.1</td>
+      <td>758</td>
+    </tr>
+    <tr>
+      <td>11499</td>
+      <td>11998</td>
+      <td>22</td>
+      <td>500</td>
+      <td>2013</td>
+      <td>5</td>
+      <td>19.2</td>
+      <td>258.4</td>
+      <td>838</td>
+    </tr>
+  </tbody>
+</table>
+</div>
+</div>
+
+</div>
+
+</div>
+</div>
+
+</div>
+<div class="cell border-box-sizing code_cell rendered">
+<div class="input">
+<div class="prompt input_prompt">In&nbsp;[6]:</div>
+<div class="inner_cell">
+    <div class="input_area">
+<div class=" highlight hl-ipython3"><pre><span></span><span class="n">train_df</span><span class="o">.</span><span class="n">shape</span><span class="p">,</span> <span class="n">test_df</span><span class="o">.</span><span class="n">shape</span>
+</pre></div>
+
+    </div>
+</div>
+</div>
+
+<div class="output_wrapper">
+<div class="output">
+
+
+<div class="output_area">
+
+    <div class="prompt output_prompt">Out[6]:</div>
+
+
+
+
+<div class="output_text output_subarea output_execute_result">
+<pre>((11500, 8), (500, 8))</pre>
+</div>
+
+</div>
+
+</div>
+</div>
+
+</div>
+<div class="cell border-box-sizing code_cell rendered">
+<div class="input">
+<div class="prompt input_prompt">In&nbsp;[7]:</div>
+<div class="inner_cell">
+    <div class="input_area">
+<div class=" highlight hl-ipython3"><pre><span></span><span class="n">train_df_hde</span> <span class="o">=</span> <span class="n">train_df</span><span class="o">.</span><span class="n">drop</span><span class="p">([</span><span class="s1">&#39;Label&#39;</span><span class="p">,</span><span class="s1">&#39;Year&#39;</span><span class="p">,</span><span class="s1">&#39;Month&#39;</span><span class="p">,</span><span class="s1">&#39;Temperature&#39;</span><span class="p">],</span> <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
+</pre></div>
+
+    </div>
+</div>
+</div>
+
+</div>
+<div class="cell border-box-sizing code_cell rendered">
+<div class="input">
+<div class="prompt input_prompt">In&nbsp;[8]:</div>
+<div class="inner_cell">
+    <div class="input_area">
+<div class=" highlight hl-ipython3"><pre><span></span><span class="n">train_df_hde</span><span class="o">.</span><span class="n">tail</span><span class="p">()</span>
+</pre></div>
+
+    </div>
+</div>
+</div>
+
+<div class="output_wrapper">
+<div class="output">
+
+
+<div class="output_area">
+
+    <div class="prompt output_prompt">Out[8]:</div>
+
+
+
+<div class="output_html rendered_html output_subarea output_execute_result">
+<div>
+<style scoped>
+    .dataframe tbody tr th:only-of-type {
+        vertical-align: middle;
+    }
+
+    .dataframe tbody tr th {
+        vertical-align: top;
+    }
+
+    .dataframe thead th {
+        text-align: right;
+    }
+</style>
+<table border="1" class="dataframe">
+  <thead>
+    <tr style="text-align: right;">
+      <th></th>
+      <th>ID</th>
+      <th>House</th>
+      <th>Daylight</th>
+      <th>EnergyProduction</th>
+    </tr>
+  </thead>
+  <tbody>
+    <tr>
+      <td>11495</td>
+      <td>11994</td>
+      <td>500</td>
+      <td>234.6</td>
+      <td>640</td>
+    </tr>
+    <tr>
+      <td>11496</td>
+      <td>11995</td>
+      <td>500</td>
+      <td>201.8</td>
+      <td>638</td>
+    </tr>
+    <tr>
+      <td>11497</td>
+      <td>11996</td>
+      <td>500</td>
+      <td>234.0</td>
+      <td>778</td>
+    </tr>
+    <tr>
+      <td>11498</td>
+      <td>11997</td>
+      <td>500</td>
+      <td>237.1</td>
+      <td>758</td>
+    </tr>
+    <tr>
+      <td>11499</td>
+      <td>11998</td>
+      <td>500</td>
+      <td>258.4</td>
+      <td>838</td>
+    </tr>
+  </tbody>
+</table>
+</div>
+</div>
+
+</div>
+
+</div>
+</div>
+
+</div>
+<div class="cell border-box-sizing code_cell rendered">
+<div class="input">
+<div class="prompt input_prompt">In&nbsp;[9]:</div>
+<div class="inner_cell">
+    <div class="input_area">
+<div class=" highlight hl-ipython3"><pre><span></span><span class="n">train_df_hde</span><span class="p">[[</span><span class="s1">&#39;House&#39;</span><span class="p">,</span><span class="s1">&#39;Daylight&#39;</span><span class="p">,</span><span class="s1">&#39;EnergyProduction&#39;</span><span class="p">]]</span><span class="o">.</span><span class="n">corr</span><span class="p">()</span>
+</pre></div>
+
+    </div>
+</div>
+</div>
+
+<div class="output_wrapper">
+<div class="output">
+
+
+<div class="output_area">
+
+    <div class="prompt output_prompt">Out[9]:</div>
+
+
+
+<div class="output_html rendered_html output_subarea output_execute_result">
+<div>
+<style scoped>
+    .dataframe tbody tr th:only-of-type {
+        vertical-align: middle;
+    }
+
+    .dataframe tbody tr th {
+        vertical-align: top;
+    }
+
+    .dataframe thead th {
+        text-align: right;
+    }
+</style>
+<table border="1" class="dataframe">
+  <thead>
+    <tr style="text-align: right;">
+      <th></th>
+      <th>House</th>
+      <th>Daylight</th>
+      <th>EnergyProduction</th>
+    </tr>
+  </thead>
+  <tbody>
+    <tr>
+      <td>House</td>
+      <td>1.000000</td>
+      <td>0.001583</td>
+      <td>-0.008303</td>
+    </tr>
+    <tr>
+      <td>Daylight</td>
+      <td>0.001583</td>
+      <td>1.000000</td>
+      <td>0.531577</td>
+    </tr>
+    <tr>
+      <td>EnergyProduction</td>
+      <td>-0.008303</td>
+      <td>0.531577</td>
+      <td>1.000000</td>
+    </tr>
+  </tbody>
+</table>
+</div>
+</div>
+
+</div>
+
+</div>
+</div>
+
+</div>
+<div class="cell border-box-sizing code_cell rendered">
+<div class="input">
+<div class="prompt input_prompt">In&nbsp;[10]:</div>
+<div class="inner_cell">
+    <div class="input_area">
+<div class=" highlight hl-ipython3"><pre><span></span><span class="n">lr</span> <span class="o">=</span> <span class="n">LinearRegression</span><span class="p">()</span>
+<span class="n">X</span> <span class="o">=</span> <span class="n">train_df_hde</span><span class="p">[[</span><span class="s1">&#39;Daylight&#39;</span><span class="p">]]</span><span class="o">.</span><span class="n">values</span>
+<span class="n">Y</span> <span class="o">=</span> <span class="n">train_df_hde</span><span class="p">[[</span><span class="s1">&#39;EnergyProduction&#39;</span><span class="p">]]</span><span class="o">.</span><span class="n">values</span>
+<span class="n">lr</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">X</span><span class="p">,</span><span class="n">Y</span><span class="p">)</span>
+</pre></div>
+
+    </div>
+</div>
+</div>
+
+<div class="output_wrapper">
+<div class="output">
+
+
+<div class="output_area">
+
+    <div class="prompt output_prompt">Out[10]:</div>
+
+
+
+
+<div class="output_text output_subarea output_execute_result">
+<pre>LinearRegression(copy_X=True, fit_intercept=True, n_jobs=None, normalize=False)</pre>
+</div>
+
+</div>
+
+</div>
+</div>
+
+</div>
+<div class="cell border-box-sizing code_cell rendered">
+<div class="input">
+<div class="prompt input_prompt">In&nbsp;[11]:</div>
+<div class="inner_cell">
+    <div class="input_area">
+<div class=" highlight hl-ipython3"><pre><span></span><span class="nb">print</span><span class="p">(</span><span class="s1">&#39;coefficient = &#39;</span><span class="p">,</span> <span class="n">lr</span><span class="o">.</span><span class="n">coef_</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span> <span class="c1"># 説明変数の係数を出力</span>
+<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;intercept = &#39;</span><span class="p">,</span> <span class="n">lr</span><span class="o">.</span><span class="n">intercept_</span><span class="p">)</span> <span class="c1"># 切片を出力</span>
+</pre></div>
+
+    </div>
+</div>
+</div>
+
+<div class="output_wrapper">
+<div class="output">
+
+
+<div class="output_area">
+
+    <div class="prompt"></div>
+
+
+<div class="output_subarea output_stream output_stdout output_text">
+<pre>coefficient =  [2.56478737]
+intercept =  [127.69148663]
+</pre>
+</div>
+</div>
+
+</div>
+</div>
+
+</div>
+<div class="cell border-box-sizing code_cell rendered">
+<div class="input">
+<div class="prompt input_prompt">In&nbsp;[12]:</div>
+<div class="inner_cell">
+    <div class="input_area">
+<div class=" highlight hl-ipython3"><pre><span></span><span class="n">plt</span><span class="o">.</span><span class="n">scatter</span><span class="p">(</span><span class="n">X</span><span class="p">,</span> <span class="n">Y</span><span class="p">,</span> <span class="n">color</span> <span class="o">=</span> <span class="s1">&#39;blue&#39;</span><span class="p">)</span>         <span class="c1"># 説明変数と目的変数のデータ点の散布図をプロット</span>
+<span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">X</span><span class="p">,</span> <span class="n">lr</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">X</span><span class="p">),</span> <span class="n">color</span> <span class="o">=</span> <span class="s1">&#39;red&#39;</span><span class="p">)</span> <span class="c1"># 回帰直線をプロット</span>
+
+<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s1">&#39;Regression Line&#39;</span><span class="p">)</span>            <span class="c1"># 図のタイトル</span>
+<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s1">&#39;Daylight&#39;</span><span class="p">)</span>                     <span class="c1"># x軸のラベル</span>
+<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s1">&#39;EnergyProduction&#39;</span><span class="p">)</span>    <span class="c1"># y軸のラベル</span>
+<span class="n">plt</span><span class="o">.</span><span class="n">grid</span><span class="p">()</span>                                 <span class="c1"># グリッド線を表示</span>
+
+<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>                                 <span class="c1"># 図の表示</span>
+</pre></div>
+
+    </div>
+</div>
+</div>
+
+<div class="output_wrapper">
+<div class="output">
+
+
+<div class="output_area">
+
+    <div class="prompt"></div>
+
+
+
+
+<div class="output_png output_subarea ">
+<img 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
+"
+>
+</div>
+
+</div>
+
+</div>
+</div>
+
+</div>
+<div class="cell border-box-sizing code_cell rendered">
+<div class="input">
+<div class="prompt input_prompt">In&nbsp;[13]:</div>
+<div class="inner_cell">
+    <div class="input_area">
+<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># DaylightとEnergyProductionに相関はあるが、ばらつきが大きい。</span>
+<span class="c1"># Houseごとに、発電能力に差があるためでは？</span>
+<span class="n">MeanEnergy</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">train_df_hde</span><span class="p">[</span><span class="s1">&#39;EnergyProduction&#39;</span><span class="p">])</span>
+</pre></div>
+
+    </div>
+</div>
+</div>
+
+</div>
+<div class="cell border-box-sizing code_cell rendered">
+<div class="input">
+<div class="prompt input_prompt">In&nbsp;[14]:</div>
+<div class="inner_cell">
+    <div class="input_area">
+<div class=" highlight hl-ipython3"><pre><span></span><span class="nb">print</span><span class="p">(</span><span class="n">MeanEnergy</span><span class="p">)</span>
+</pre></div>
+
+    </div>
+</div>
+</div>
+
+<div class="output_wrapper">
+<div class="output">
+
+
+<div class="output_area">
+
+    <div class="prompt"></div>
+
+
+<div class="output_subarea output_stream output_stdout output_text">
+<pre>612.7488695652174
+</pre>
+</div>
+</div>
+
+</div>
+</div>
+
+</div>
+<div class="cell border-box-sizing code_cell rendered">
+<div class="input">
+<div class="prompt input_prompt">In&nbsp;[15]:</div>
+<div class="inner_cell">
+    <div class="input_area">
+<div class=" highlight hl-ipython3"><pre><span></span><span class="n">pivot_House</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">pivot_table</span><span class="p">(</span><span class="n">train_df_hde</span><span class="p">,</span> <span class="n">index</span><span class="o">=</span><span class="s1">&#39;House&#39;</span><span class="p">)</span>
+<span class="c1"># 各Houseごとの発電量の平均を求める</span>
+</pre></div>
+
+    </div>
+</div>
+</div>
+
+</div>
+<div class="cell border-box-sizing code_cell rendered">
+<div class="input">
+<div class="prompt input_prompt">In&nbsp;[16]:</div>
+<div class="inner_cell">
+    <div class="input_area">
+<div class=" highlight hl-ipython3"><pre><span></span><span class="n">cases_House</span> <span class="o">=</span> <span class="n">train_df</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">/</span><span class="n">pivot_House</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
+<span class="nb">print</span><span class="p">(</span><span class="n">cases_House</span><span class="p">)</span>
+</pre></div>
+
+    </div>
+</div>
+</div>
+
+<div class="output_wrapper">
+<div class="output">
+
+
+<div class="output_area">
+
+    <div class="prompt"></div>
+
+
+<div class="output_subarea output_stream output_stdout output_text">
+<pre>23.0
+</pre>
+</div>
+</div>
+
+</div>
+</div>
+
+</div>
+<div class="cell border-box-sizing code_cell rendered">
+<div class="input">
+<div class="prompt input_prompt">In&nbsp;[17]:</div>
+<div class="inner_cell">
+    <div class="input_area">
+<div class=" highlight hl-ipython3"><pre><span></span><span class="n">eachHouse_perMeanEnergy</span> <span class="o">=</span> <span class="n">pivot_House</span><span class="o">/</span><span class="n">MeanEnergy</span>
+<span class="c1"># 各Houseごとの平均を、全体の平均から求める係数を算出する</span>
+</pre></div>
+
+    </div>
+</div>
+</div>
+
+</div>
+<div class="cell border-box-sizing code_cell rendered">
+<div class="input">
+<div class="prompt input_prompt">In&nbsp;[18]:</div>
+<div class="inner_cell">
+    <div class="input_area">
+<div class=" highlight hl-ipython3"><pre><span></span><span class="n">k_Energy_House_Mean</span> <span class="o">=</span> <span class="n">eachHouse_perMeanEnergy</span><span class="p">[[</span><span class="s1">&#39;EnergyProduction&#39;</span><span class="p">]]</span>
+</pre></div>
+
+    </div>
+</div>
+</div>
+
+</div>
+<div class="cell border-box-sizing code_cell rendered">
+<div class="input">
+<div class="prompt input_prompt">In&nbsp;[19]:</div>
+<div class="inner_cell">
+    <div class="input_area">
+<div class=" highlight hl-ipython3"><pre><span></span><span class="n">k_Energy_House_Mean_array</span> <span class="o">=</span> <span class="n">k_Energy_House_Mean</span><span class="o">.</span><span class="n">values</span>
+</pre></div>
+
+    </div>
+</div>
+</div>
+
+</div>
+<div class="cell border-box-sizing code_cell rendered">
+<div class="input">
+<div class="prompt input_prompt">In&nbsp;[20]:</div>
+<div class="inner_cell">
+    <div class="input_area">
+<div class=" highlight hl-ipython3"><pre><span></span><span class="n">k_Energy_House_Mean_array</span><span class="o">.</span><span class="n">shape</span>
+</pre></div>
+
+    </div>
+</div>
+</div>
+
+<div class="output_wrapper">
+<div class="output">
+
+
+<div class="output_area">
+
+    <div class="prompt output_prompt">Out[20]:</div>
+
+
+
+
+<div class="output_text output_subarea output_execute_result">
+<pre>(500, 1)</pre>
+</div>
+
+</div>
+
+</div>
+</div>
+
+</div>
+<div class="cell border-box-sizing code_cell rendered">
+<div class="input">
+<div class="prompt input_prompt">In&nbsp;[21]:</div>
+<div class="inner_cell">
+    <div class="input_area">
+<div class=" highlight hl-ipython3"><pre><span></span><span class="n">test_X</span> <span class="o">=</span> <span class="n">test_df</span><span class="p">[[</span><span class="s1">&#39;Daylight&#39;</span><span class="p">]]</span><span class="o">.</span><span class="n">values</span>
+<span class="n">test_Y</span> <span class="o">=</span> <span class="n">test_df</span><span class="p">[[</span><span class="s1">&#39;EnergyProduction&#39;</span><span class="p">]]</span><span class="o">.</span><span class="n">values</span>
+</pre></div>
+
+    </div>
+</div>
+</div>
+
+</div>
+<div class="cell border-box-sizing code_cell rendered">
+<div class="input">
+<div class="prompt input_prompt">In&nbsp;[22]:</div>
+<div class="inner_cell">
+    <div class="input_area">
+<div class=" highlight hl-ipython3"><pre><span></span><span class="n">plt</span><span class="o">.</span><span class="n">scatter</span><span class="p">(</span><span class="n">test_X</span><span class="p">,</span> <span class="n">test_Y</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="s1">&#39;blue&#39;</span><span class="p">)</span>
+<span class="n">plt</span><span class="o">.</span><span class="n">scatter</span><span class="p">(</span><span class="n">test_X</span><span class="p">,</span> <span class="n">lr</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">test_X</span><span class="p">),</span> <span class="n">color</span><span class="o">=</span><span class="s1">&#39;black&#39;</span><span class="p">)</span>
+</pre></div>
+
+    </div>
+</div>
+</div>
+
+<div class="output_wrapper">
+<div class="output">
+
+
+<div class="output_area">
+
+    <div class="prompt output_prompt">Out[22]:</div>
+
+
+
+
+<div class="output_text output_subarea output_execute_result">
+<pre>&lt;matplotlib.collections.PathCollection at 0x7fa7cbd2c750&gt;</pre>
+</div>
+
+</div>
+
+<div class="output_area">
+
+    <div class="prompt"></div>
+
+
+
+
+<div class="output_png output_subarea ">
+<img src="data:image/png;base64,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
+"
+>
+</div>
+
+</div>
+
+</div>
+</div>
+
+</div>
+<div class="cell border-box-sizing code_cell rendered">
+<div class="input">
+<div class="prompt input_prompt">In&nbsp;[23]:</div>
+<div class="inner_cell">
+    <div class="input_area">
+<div class=" highlight hl-ipython3"><pre><span></span> <span class="n">sim_Y</span> <span class="o">=</span> <span class="n">k_Energy_House_Mean_array</span> <span class="o">*</span> <span class="n">lr</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">test_X</span><span class="p">)</span>
+</pre></div>
+
+    </div>
+</div>
+</div>
+
+</div>
+<div class="cell border-box-sizing code_cell rendered">
+<div class="input">
+<div class="prompt input_prompt">In&nbsp;[24]:</div>
+<div class="inner_cell">
+    <div class="input_area">
+<div class=" highlight hl-ipython3"><pre><span></span><span class="n">plt</span><span class="o">.</span><span class="n">scatter</span><span class="p">(</span><span class="n">test_X</span><span class="p">,</span> <span class="n">lr</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">test_X</span><span class="p">),</span> <span class="n">color</span> <span class="o">=</span> <span class="s1">&#39;black&#39;</span><span class="p">)</span> 
+<span class="n">plt</span><span class="o">.</span><span class="n">scatter</span><span class="p">(</span><span class="n">test_X</span><span class="p">,</span> <span class="n">sim_Y</span><span class="p">,</span> <span class="n">color</span> <span class="o">=</span> <span class="s1">&#39;red&#39;</span><span class="p">)</span> 
+<span class="n">plt</span><span class="o">.</span><span class="n">scatter</span><span class="p">(</span><span class="n">test_X</span><span class="p">,</span> <span class="n">test_Y</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="s1">&#39;blue&#39;</span><span class="p">)</span>
+<span class="c1"># ばらつき具合は、Houseごとの係数を考慮することで表現できている。</span>
+<span class="c1"># 全体的に、発電量が小さい。北半球6月なら、太陽の角度が大きいことを考慮できていないため？</span>
+</pre></div>
+
+    </div>
+</div>
+</div>
+
+<div class="output_wrapper">
+<div class="output">
+
+
+<div class="output_area">
+
+    <div class="prompt output_prompt">Out[24]:</div>
+
+
+
+
+<div class="output_text output_subarea output_execute_result">
+<pre>&lt;matplotlib.collections.PathCollection at 0x7fa7cbfc9a50&gt;</pre>
+</div>
+
+</div>
+
+<div class="output_area">
+
+    <div class="prompt"></div>
+
+
+
+
+<div class="output_png output_subarea ">
+<img src="data:image/png;base64,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
+"
+>
+</div>
+
+</div>
+
+</div>
+</div>
+
+</div>
+<div class="cell border-box-sizing code_cell rendered">
+<div class="input">
+<div class="prompt input_prompt">In&nbsp;[25]:</div>
+<div class="inner_cell">
+    <div class="input_area">
+<div class=" highlight hl-ipython3"><pre><span></span><span class="n">test_df</span><span class="o">.</span><span class="n">tail</span><span class="p">()</span>
+</pre></div>
+
+    </div>
+</div>
+</div>
+
+<div class="output_wrapper">
+<div class="output">
+
+
+<div class="output_area">
+
+    <div class="prompt output_prompt">Out[25]:</div>
+
+
+
+<div class="output_html rendered_html output_subarea output_execute_result">
+<div>
+<style scoped>
+    .dataframe tbody tr th:only-of-type {
+        vertical-align: middle;
+    }
+
+    .dataframe tbody tr th {
+        vertical-align: top;
+    }
+
+    .dataframe thead th {
+        text-align: right;
+    }
+</style>
+<table border="1" class="dataframe">
+  <thead>
+    <tr style="text-align: right;">
+      <th></th>
+      <th>ID</th>
+      <th>Label</th>
+      <th>House</th>
+      <th>Year</th>
+      <th>Month</th>
+      <th>Temperature</th>
+      <th>Daylight</th>
+      <th>EnergyProduction</th>
+    </tr>
+  </thead>
+  <tbody>
+    <tr>
+      <td>495</td>
+      <td>11903</td>
+      <td>23</td>
+      <td>496</td>
+      <td>2013</td>
+      <td>6</td>
+      <td>19.3</td>
+      <td>125.9</td>
+      <td>483</td>
+    </tr>
+    <tr>
+      <td>496</td>
+      <td>11927</td>
+      <td>23</td>
+      <td>497</td>
+      <td>2013</td>
+      <td>6</td>
+      <td>21.9</td>
+      <td>122.4</td>
+      <td>628</td>
+    </tr>
+    <tr>
+      <td>497</td>
+      <td>11951</td>
+      <td>23</td>
+      <td>498</td>
+      <td>2013</td>
+      <td>6</td>
+      <td>22.8</td>
+      <td>127.2</td>
+      <td>673</td>
+    </tr>
+    <tr>
+      <td>498</td>
+      <td>11975</td>
+      <td>23</td>
+      <td>499</td>
+      <td>2013</td>
+      <td>6</td>
+      <td>21.9</td>
+      <td>126.8</td>
+      <td>735</td>
+    </tr>
+    <tr>
+      <td>499</td>
+      <td>11999</td>
+      <td>23</td>
+      <td>500</td>
+      <td>2013</td>
+      <td>6</td>
+      <td>22.7</td>
+      <td>122.9</td>
+      <td>586</td>
+    </tr>
+  </tbody>
+</table>
+</div>
+</div>
+
+</div>
+
+</div>
+</div>
+
+</div>
+<div class="cell border-box-sizing code_cell rendered">
+<div class="input">
+<div class="prompt input_prompt">In&nbsp;[26]:</div>
+<div class="inner_cell">
+    <div class="input_area">
+<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># RandomForestを使い、Month, Daylight, House, TemperatureからEnergyProductionを推測してみる。</span>
+</pre></div>
+
+    </div>
+</div>
+</div>
+
+</div>
+<div class="cell border-box-sizing code_cell rendered">
+<div class="input">
+<div class="prompt input_prompt">In&nbsp;[27]:</div>
+<div class="inner_cell">
+    <div class="input_area">
+<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">sklearn.ensemble</span> <span class="k">import</span> <span class="n">RandomForestClassifier</span>
+<span class="n">model</span> <span class="o">=</span> <span class="n">RandomForestClassifier</span><span class="p">(</span><span class="n">max_depth</span><span class="o">=</span><span class="mi">1000</span><span class="p">)</span>
+</pre></div>
+
+    </div>
+</div>
+</div>
+
+</div>
+<div class="cell border-box-sizing code_cell rendered">
+<div class="input">
+<div class="prompt input_prompt">In&nbsp;[28]:</div>
+<div class="inner_cell">
+    <div class="input_area">
+<div class=" highlight hl-ipython3"><pre><span></span><span class="n">X</span> <span class="o">=</span> <span class="n">train_df</span><span class="o">.</span><span class="n">drop</span><span class="p">([</span><span class="s1">&#39;ID&#39;</span><span class="p">,</span> <span class="s1">&#39;Label&#39;</span><span class="p">,</span> <span class="s1">&#39;Year&#39;</span><span class="p">],</span> <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
+<span class="n">test_X</span> <span class="o">=</span> <span class="n">test_df</span><span class="o">.</span><span class="n">drop</span><span class="p">([</span><span class="s1">&#39;ID&#39;</span><span class="p">,</span> <span class="s1">&#39;Label&#39;</span><span class="p">,</span> <span class="s1">&#39;Year&#39;</span><span class="p">],</span> <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
+</pre></div>
+
+    </div>
+</div>
+</div>
+
+</div>
+<div class="cell border-box-sizing code_cell rendered">
+<div class="input">
+<div class="prompt input_prompt">In&nbsp;[29]:</div>
+<div class="inner_cell">
+    <div class="input_area">
+<div class=" highlight hl-ipython3"><pre><span></span><span class="n">model</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">X</span><span class="p">,</span><span class="n">Y</span><span class="p">)</span>
+<span class="n">predicted</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">test_X</span><span class="p">)</span>
+<span class="n">model</span><span class="o">.</span><span class="n">score</span><span class="p">(</span><span class="n">test_X</span><span class="p">,</span> <span class="n">test_Y</span><span class="p">)</span>
+</pre></div>
+
+    </div>
+</div>
+</div>
+
+<div class="output_wrapper">
+<div class="output">
+
+
+<div class="output_area">
+
+    <div class="prompt"></div>
+
+
+<div class="output_subarea output_stream output_stderr output_text">
+<pre>/Users/saber/opt/anaconda3/lib/python3.7/site-packages/sklearn/ensemble/forest.py:245: FutureWarning: The default value of n_estimators will change from 10 in version 0.20 to 100 in 0.22.
+  &#34;10 in version 0.20 to 100 in 0.22.&#34;, FutureWarning)
+/Users/saber/opt/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:1: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().
+  &#34;&#34;&#34;Entry point for launching an IPython kernel.
+</pre>
+</div>
+</div>
+
+<div class="output_area">
+
+    <div class="prompt output_prompt">Out[29]:</div>
+
+
+
+
+<div class="output_text output_subarea output_execute_result">
+<pre>0.08</pre>
+</div>
+
+</div>
+
+</div>
+</div>
+
+</div>
+<div class="cell border-box-sizing code_cell rendered">
+<div class="input">
+<div class="prompt input_prompt">In&nbsp;[47]:</div>
+<div class="inner_cell">
+    <div class="input_area">
+<div class=" highlight hl-ipython3"><pre><span></span><span class="n">model</span><span class="o">.</span><span class="n">score</span><span class="p">(</span><span class="n">test_X</span><span class="p">,</span> <span class="n">predicted</span><span class="p">)</span>
+</pre></div>
+
+    </div>
+</div>
+</div>
+
+<div class="output_wrapper">
+<div class="output">
+
+
+<div class="output_area">
+
+    <div class="prompt output_prompt">Out[47]:</div>
+
+
+
+
+<div class="output_text output_subarea output_execute_result">
+<pre>1.0</pre>
+</div>
+
+</div>
+
+</div>
+</div>
+
+</div>
+<div class="cell border-box-sizing code_cell rendered">
+<div class="input">
+<div class="prompt input_prompt">In&nbsp;[30]:</div>
+<div class="inner_cell">
+    <div class="input_area">
+<div class=" highlight hl-ipython3"><pre><span></span><span class="n">plt</span><span class="o">.</span><span class="n">scatter</span><span class="p">(</span><span class="n">test_X</span><span class="p">[[</span><span class="s1">&#39;House&#39;</span><span class="p">]]</span><span class="o">.</span><span class="n">values</span><span class="p">,</span> <span class="n">predicted</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="s1">&#39;red&#39;</span><span class="p">)</span>
+<span class="n">plt</span><span class="o">.</span><span class="n">scatter</span><span class="p">(</span><span class="n">test_X</span><span class="p">[[</span><span class="s1">&#39;House&#39;</span><span class="p">]]</span><span class="o">.</span><span class="n">values</span><span class="p">,</span> <span class="n">test_Y</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="s1">&#39;blue&#39;</span><span class="p">)</span>
+</pre></div>
+
+    </div>
+</div>
+</div>
+
+<div class="output_wrapper">
+<div class="output">
+
+
+<div class="output_area">
+
+    <div class="prompt output_prompt">Out[30]:</div>
+
+
+
+
+<div class="output_text output_subarea output_execute_result">
+<pre>&lt;matplotlib.collections.PathCollection at 0x7fa7c7b66150&gt;</pre>
+</div>
+
+</div>
+
+<div class="output_area">
+
+    <div class="prompt"></div>
+
+
+
+
+<div class="output_png output_subarea ">
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
+"
+>
+</div>
+
+</div>
+
+</div>
+</div>
+
+</div>
+<div class="cell border-box-sizing code_cell rendered">
+<div class="input">
+<div class="prompt input_prompt">In&nbsp;[31]:</div>
+<div class="inner_cell">
+    <div class="input_area">
+<div class=" highlight hl-ipython3"><pre><span></span><span class="n">plt</span><span class="o">.</span><span class="n">scatter</span><span class="p">(</span><span class="n">test_X</span><span class="p">[[</span><span class="s1">&#39;Daylight&#39;</span><span class="p">]]</span><span class="o">.</span><span class="n">values</span><span class="p">,</span> <span class="n">predicted</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="s1">&#39;red&#39;</span><span class="p">)</span>
+<span class="n">plt</span><span class="o">.</span><span class="n">scatter</span><span class="p">(</span><span class="n">test_X</span><span class="p">[[</span><span class="s1">&#39;Daylight&#39;</span><span class="p">]]</span><span class="o">.</span><span class="n">values</span><span class="p">,</span> <span class="n">test_Y</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="s1">&#39;blue&#39;</span><span class="p">)</span>
+</pre></div>
+
+    </div>
+</div>
+</div>
+
+<div class="output_wrapper">
+<div class="output">
+
+
+<div class="output_area">
+
+    <div class="prompt output_prompt">Out[31]:</div>
+
+
+
+
+<div class="output_text output_subarea output_execute_result">
+<pre>&lt;matplotlib.collections.PathCollection at 0x7fa7cbce7750&gt;</pre>
+</div>
+
+</div>
+
+<div class="output_area">
+
+    <div class="prompt"></div>
+
+
+
+
+<div class="output_png output_subarea ">
+<img src="data:image/png;base64,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
+"
+>
+</div>
+
+</div>
+
+</div>
+</div>
+
+</div>
+<div class="cell border-box-sizing code_cell rendered">
+<div class="input">
+<div class="prompt input_prompt">In&nbsp;[32]:</div>
+<div class="inner_cell">
+    <div class="input_area">
+<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># RandomForestを使い、Month, Daylight, HouseからEnergyProductionを推測してみる。（Temperatureを除いた場合）</span>
+<span class="n">X_hdm</span> <span class="o">=</span> <span class="n">train_df</span><span class="o">.</span><span class="n">drop</span><span class="p">([</span><span class="s1">&#39;ID&#39;</span><span class="p">,</span> <span class="s1">&#39;Label&#39;</span><span class="p">,</span> <span class="s1">&#39;Year&#39;</span><span class="p">,</span> <span class="s1">&#39;Temperature&#39;</span><span class="p">],</span> <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
+<span class="n">test_X_hdm</span> <span class="o">=</span> <span class="n">test_df</span><span class="o">.</span><span class="n">drop</span><span class="p">([</span><span class="s1">&#39;ID&#39;</span><span class="p">,</span> <span class="s1">&#39;Label&#39;</span><span class="p">,</span> <span class="s1">&#39;Year&#39;</span><span class="p">,</span> <span class="s1">&#39;Temperature&#39;</span><span class="p">],</span> <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
+</pre></div>
+
+    </div>
+</div>
+</div>
+
+</div>
+<div class="cell border-box-sizing code_cell rendered">
+<div class="input">
+<div class="prompt input_prompt">In&nbsp;[33]:</div>
+<div class="inner_cell">
+    <div class="input_area">
+<div class=" highlight hl-ipython3"><pre><span></span><span class="n">model_hdm</span> <span class="o">=</span> <span class="n">RandomForestClassifier</span><span class="p">(</span><span class="n">max_depth</span><span class="o">=</span><span class="mi">1000</span><span class="p">)</span>
+<span class="n">model_hdm</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">X_hdm</span><span class="p">,</span><span class="n">Y</span><span class="p">)</span>
+<span class="n">predicted_hdm</span> <span class="o">=</span> <span class="n">model_hdm</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">test_X_hdm</span><span class="p">)</span>
+</pre></div>
+
+    </div>
+</div>
+</div>
+
+<div class="output_wrapper">
+<div class="output">
+
+
+<div class="output_area">
+
+    <div class="prompt"></div>
+
+
+<div class="output_subarea output_stream output_stderr output_text">
+<pre>/Users/saber/opt/anaconda3/lib/python3.7/site-packages/sklearn/ensemble/forest.py:245: FutureWarning: The default value of n_estimators will change from 10 in version 0.20 to 100 in 0.22.
+  &#34;10 in version 0.20 to 100 in 0.22.&#34;, FutureWarning)
+/Users/saber/opt/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:2: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().
+  
+</pre>
+</div>
+</div>
+
+</div>
+</div>
+
+</div>
+<div class="cell border-box-sizing code_cell rendered">
+<div class="input">
+<div class="prompt input_prompt">In&nbsp;[34]:</div>
+<div class="inner_cell">
+    <div class="input_area">
+<div class=" highlight hl-ipython3"><pre><span></span><span class="n">plt</span><span class="o">.</span><span class="n">scatter</span><span class="p">(</span><span class="n">test_X_hdm</span><span class="p">[[</span><span class="s1">&#39;House&#39;</span><span class="p">]]</span><span class="o">.</span><span class="n">values</span><span class="p">,</span> <span class="n">predicted</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="s1">&#39;red&#39;</span><span class="p">)</span>
+<span class="n">plt</span><span class="o">.</span><span class="n">scatter</span><span class="p">(</span><span class="n">test_X_hdm</span><span class="p">[[</span><span class="s1">&#39;House&#39;</span><span class="p">]]</span><span class="o">.</span><span class="n">values</span><span class="p">,</span> <span class="n">test_Y</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="s1">&#39;blue&#39;</span><span class="p">)</span>
+</pre></div>
+
+    </div>
+</div>
+</div>
+
+<div class="output_wrapper">
+<div class="output">
+
+
+<div class="output_area">
+
+    <div class="prompt output_prompt">Out[34]:</div>
+
+
+
+
+<div class="output_text output_subarea output_execute_result">
+<pre>&lt;matplotlib.collections.PathCollection at 0x7fa7cc179450&gt;</pre>
+</div>
+
+</div>
+
+<div class="output_area">
+
+    <div class="prompt"></div>
+
+
+
+
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
+"
+>
+</div>
+
+</div>
+
+</div>
+</div>
+
+</div>
+<div class="cell border-box-sizing code_cell rendered">
+<div class="input">
+<div class="prompt input_prompt">In&nbsp;[35]:</div>
+<div class="inner_cell">
+    <div class="input_area">
+<div class=" highlight hl-ipython3"><pre><span></span><span class="n">plt</span><span class="o">.</span><span class="n">scatter</span><span class="p">(</span><span class="n">test_X_hdm</span><span class="p">[[</span><span class="s1">&#39;Daylight&#39;</span><span class="p">]]</span><span class="o">.</span><span class="n">values</span><span class="p">,</span> <span class="n">predicted</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="s1">&#39;red&#39;</span><span class="p">)</span>
+<span class="n">plt</span><span class="o">.</span><span class="n">scatter</span><span class="p">(</span><span class="n">test_X_hdm</span><span class="p">[[</span><span class="s1">&#39;Daylight&#39;</span><span class="p">]]</span><span class="o">.</span><span class="n">values</span><span class="p">,</span> <span class="n">test_Y</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="s1">&#39;blue&#39;</span><span class="p">)</span>
+</pre></div>
+
+    </div>
+</div>
+</div>
+
+<div class="output_wrapper">
+<div class="output">
+
+
+<div class="output_area">
+
+    <div class="prompt output_prompt">Out[35]:</div>
+
+
+
+
+<div class="output_text output_subarea output_execute_result">
+<pre>&lt;matplotlib.collections.PathCollection at 0x7fa7b5172450&gt;</pre>
+</div>
+
+</div>
+
+<div class="output_area">
+
+    <div class="prompt"></div>
+
+
+
+
+<div class="output_png output_subarea ">
+<img src="data:image/png;base64,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
+"
+>
+</div>
+
+</div>
+
+</div>
+</div>
+
+</div>
+<div class="cell border-box-sizing code_cell rendered">
+<div class="input">
+<div class="prompt input_prompt">In&nbsp;[36]:</div>
+<div class="inner_cell">
+    <div class="input_area">
+<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Temperatureの影響があるかは、はっきりしない。</span>
+<span class="n">model_hdm</span><span class="o">.</span><span class="n">score</span><span class="p">(</span><span class="n">test_X_hdm</span><span class="p">,</span> <span class="n">test_Y</span><span class="p">)</span>
+</pre></div>
+
+    </div>
+</div>
+</div>
+
+<div class="output_wrapper">
+<div class="output">
+
+
+<div class="output_area">
+
+    <div class="prompt output_prompt">Out[36]:</div>
+
+
+
+
+<div class="output_text output_subarea output_execute_result">
+<pre>0.146</pre>
+</div>
+
+</div>
+
+</div>
+</div>
+
+</div>
+<div class="cell border-box-sizing code_cell rendered">
+<div class="input">
+<div class="prompt input_prompt">In&nbsp;[39]:</div>
+<div class="inner_cell">
+    <div class="input_area">
+<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># SVCも試してみる。</span>
+<span class="kn">from</span> <span class="nn">sklearn.svm</span> <span class="k">import</span> <span class="n">SVC</span>
+<span class="n">model_svc</span> <span class="o">=</span> <span class="n">SVC</span><span class="p">(</span><span class="n">gamma</span><span class="o">=</span><span class="s1">&#39;scale&#39;</span><span class="p">)</span>
+<span class="n">model_svc</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">X</span><span class="p">,</span> <span class="n">Y</span><span class="p">)</span>
+</pre></div>
+
+    </div>
+</div>
+</div>
+
+<div class="output_wrapper">
+<div class="output">
+
+
+<div class="output_area">
+
+    <div class="prompt"></div>
+
+
+<div class="output_subarea output_stream output_stderr output_text">
+<pre>/Users/saber/opt/anaconda3/lib/python3.7/site-packages/sklearn/utils/validation.py:724: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
+  y = column_or_1d(y, warn=True)
+</pre>
+</div>
+</div>
+
+<div class="output_area">
+
+    <div class="prompt output_prompt">Out[39]:</div>
+
+
+
+
+<div class="output_text output_subarea output_execute_result">
+<pre>SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0,
+    decision_function_shape=&#39;ovr&#39;, degree=3, gamma=&#39;scale&#39;, kernel=&#39;rbf&#39;,
+    max_iter=-1, probability=False, random_state=None, shrinking=True,
+    tol=0.001, verbose=False)</pre>
+</div>
+
+</div>
+
+</div>
+</div>
+
+</div>
+<div class="cell border-box-sizing code_cell rendered">
+<div class="input">
+<div class="prompt input_prompt">In&nbsp;[40]:</div>
+<div class="inner_cell">
+    <div class="input_area">
+<div class=" highlight hl-ipython3"><pre><span></span><span class="n">test_Y_svc</span> <span class="o">=</span> <span class="n">model_svc</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">test_X</span><span class="p">)</span>
+</pre></div>
+
+    </div>
+</div>
+</div>
+
+</div>
+<div class="cell border-box-sizing code_cell rendered">
+<div class="input">
+<div class="prompt input_prompt">In&nbsp;[41]:</div>
+<div class="inner_cell">
+    <div class="input_area">
+<div class=" highlight hl-ipython3"><pre><span></span><span class="n">plt</span><span class="o">.</span><span class="n">scatter</span><span class="p">(</span><span class="n">test_X</span><span class="p">[[</span><span class="s1">&#39;House&#39;</span><span class="p">]]</span><span class="o">.</span><span class="n">values</span><span class="p">,</span> <span class="n">test_Y_svc</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="s1">&#39;red&#39;</span><span class="p">)</span>
+<span class="n">plt</span><span class="o">.</span><span class="n">scatter</span><span class="p">(</span><span class="n">test_X</span><span class="p">[[</span><span class="s1">&#39;House&#39;</span><span class="p">]]</span><span class="o">.</span><span class="n">values</span><span class="p">,</span> <span class="n">test_Y</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="s1">&#39;blue&#39;</span><span class="p">)</span>
+</pre></div>
+
+    </div>
+</div>
+</div>
+
+<div class="output_wrapper">
+<div class="output">
+
+
+<div class="output_area">
+
+    <div class="prompt output_prompt">Out[41]:</div>
+
+
+
+
+<div class="output_text output_subarea output_execute_result">
+<pre>&lt;matplotlib.collections.PathCollection at 0x7fa7b53d8d90&gt;</pre>
+</div>
+
+</div>
+
+<div class="output_area">
+
+    <div class="prompt"></div>
+
+
+
+
+<div class="output_png output_subarea ">
+<img 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
+"
+>
+</div>
+
+</div>
+
+</div>
+</div>
+
+</div>
+<div class="cell border-box-sizing code_cell rendered">
+<div class="input">
+<div class="prompt input_prompt">In&nbsp;[42]:</div>
+<div class="inner_cell">
+    <div class="input_area">
+<div class=" highlight hl-ipython3"><pre><span></span><span class="n">model_svc</span><span class="o">.</span><span class="n">score</span><span class="p">(</span><span class="n">test_X</span><span class="p">,</span> <span class="n">test_Y</span><span class="p">)</span>
+</pre></div>
+
+    </div>
+</div>
+</div>
+
+<div class="output_wrapper">
+<div class="output">
+
+
+<div class="output_area">
+
+    <div class="prompt output_prompt">Out[42]:</div>
+
+
+
+
+<div class="output_text output_subarea output_execute_result">
+<pre>0.0</pre>
+</div>
+
+</div>
+
+</div>
+</div>
+
+</div>
+<div class="cell border-box-sizing code_cell rendered">
+<div class="input">
+<div class="prompt input_prompt">In&nbsp;[43]:</div>
+<div class="inner_cell">
+    <div class="input_area">
+<div class=" highlight hl-ipython3"><pre><span></span><span class="n">model_svc_hdm</span> <span class="o">=</span> <span class="n">SVC</span><span class="p">(</span><span class="n">gamma</span><span class="o">=</span><span class="s1">&#39;scale&#39;</span><span class="p">)</span>
+<span class="n">model_svc_hdm</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">X_hdm</span><span class="p">,</span> <span class="n">Y</span><span class="p">)</span>
+</pre></div>
+
+    </div>
+</div>
+</div>
+
+<div class="output_wrapper">
+<div class="output">
+
+
+<div class="output_area">
+
+    <div class="prompt"></div>
+
+
+<div class="output_subarea output_stream output_stderr output_text">
+<pre>/Users/saber/opt/anaconda3/lib/python3.7/site-packages/sklearn/utils/validation.py:724: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
+  y = column_or_1d(y, warn=True)
+</pre>
+</div>
+</div>
+
+<div class="output_area">
+
+    <div class="prompt output_prompt">Out[43]:</div>
+
+
+
+
+<div class="output_text output_subarea output_execute_result">
+<pre>SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0,
+    decision_function_shape=&#39;ovr&#39;, degree=3, gamma=&#39;scale&#39;, kernel=&#39;rbf&#39;,
+    max_iter=-1, probability=False, random_state=None, shrinking=True,
+    tol=0.001, verbose=False)</pre>
+</div>
+
+</div>
+
+</div>
+</div>
+
+</div>
+<div class="cell border-box-sizing code_cell rendered">
+<div class="input">
+<div class="prompt input_prompt">In&nbsp;[48]:</div>
+<div class="inner_cell">
+    <div class="input_area">
+<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># RandomForestを使い、Month, Daylight, HouseからEnergyProductionを推測したものが、この中では一番よかった。</span>
+<span class="n">plt</span><span class="o">.</span><span class="n">scatter</span><span class="p">(</span><span class="n">test_X</span><span class="p">[[</span><span class="s1">&#39;House&#39;</span><span class="p">]]</span><span class="o">.</span><span class="n">values</span><span class="p">,</span> <span class="n">predicted</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="s1">&#39;red&#39;</span><span class="p">)</span>
+<span class="n">plt</span><span class="o">.</span><span class="n">scatter</span><span class="p">(</span><span class="n">test_X</span><span class="p">[[</span><span class="s1">&#39;House&#39;</span><span class="p">]]</span><span class="o">.</span><span class="n">values</span><span class="p">,</span> <span class="n">test_Y</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="s1">&#39;blue&#39;</span><span class="p">)</span>
+</pre></div>
+
+    </div>
+</div>
+</div>
+
+<div class="output_wrapper">
+<div class="output">
+
+
+<div class="output_area">
+
+    <div class="prompt output_prompt">Out[48]:</div>
+
+
+
+
+<div class="output_text output_subarea output_execute_result">
+<pre>&lt;matplotlib.collections.PathCollection at 0x7fa7cbfc9610&gt;</pre>
+</div>
+
+</div>
+
+<div class="output_area">
+
+    <div class="prompt"></div>
+
+
+
+
+<div class="output_png output_subarea ">
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QsAriKi6wL4FggEAkEgfJ37ewB8svj/tcz8NQAo/l5b3H8dgPOVOs8W96ZARMeI6AwRnbl48aInGwKBQCAwwdm5E9EagJ8B8Ke2oop7M7EfZv4YMx9m5sPXXHONKxsCgUAgcIDPyP2dAP6Wmb9efP56GW4p/l4o7j8L4PWVetcDeC6WUWe4LDv2Wf6sa7e+fNn1vq5N35OjY9v34dMHTSzz96XZ5mnTbbfV1CncMfzUt0JQbU0Q2l51mb7qvXV9f030muqHeZ8urptprV8A/hjAz1U+/yaAO4v/7wTwG8X/PwXgL5CP4G8G8EVb20myZZjdUqBMaXE+G0rHbmrtmyJoS/Xybd9n8+2U+k+xibWNZmoaqemkTK3ztdnYsvV6rumgMe2trdnTFkP6o8l+aMkuEbv9AIB1AM8D+O7KvQGAB5CnQj4A4GBxnwDcBeApAI8AOGxrP5lzd1x2nOEID/E0E3Z5iKc5w5G955rl7so6/b72vpJ2zNLqan0dP4b2vfgPXRKt48ukh1i46GLR6IS25bMM3rNsKD9lPWCX+3iVUdQf4VSwfDZbrdOyvr8O/IfK7fr+NWL7nMC5N30lc+4OxyhlOMLreHH6CxUv7hmI4tTbDEeVdUY4ZW6rflXbjjj5WsdPhqPK9nUy6/k/yiHQ83VEr4dIOOliwegEt+VzUrNH2VB+VPX2rnGQfD626vr++vAfKrfp/WvK9pmXybk7jIbzb/7ZR0M8zbpv1mH/vLJOPnpQtXVWTT/RyF3Hz7B/Xtm+TmYt/9V2fNSv46vUrUoPkXDSxYLRCW6roZF7KD+6elrzdZDP11Zd3l9f/kPl1r1/Tdk+M/PyOHeHmC9hV/mIsKuNiVFtFLJ3qe8Txo3G3HX8EMbK9nUyG/kPgJ6vXb0eIuGkiwWjE9xWQ3H0UH7074X6cpHP11Zd3l9f/kPl1r1/Tdk+My+Rc2e2LjseDi4rO2bYP69VvO5L2Bhad1mu7LIsX1HfeVBQtK8dDTlMDfhAy1f/fGOHXbY0QEpKJ6otn2XwjmWb3NHWVz7d+2nbndf0/vryn2zqI2ZLFEcsl3Nn+7Yjqn2lVKee67aFKL+EUyeb+MjnQ1dVvpRHJ1foNhop9GH6zqtvEzMYzCY/6fozBq4JEi56i9GT75Y6LvVTJo3ortLOVP1pa5PIvB9aPZHM57uv6aSler3Uvn6pnPtoNOuwys9156BybibHXW+HWd9hDQ7co9pXyVyVK/YLy3W/JlN9k8NQZbJWnbnK2af6wvUdNNi+cH1fdFWm4Oqq3kHXv+RMfRvqeLJsdg8zn0v1Banap6w66ADU+/iF2G6M3L7vXxN2uTTOPcvsSSiuu/TqfgYOBuZRZclH6pC76ovFpgsVD7oXsfxJafvJmXJkpGorZJ7Zh39fGVyRQm+2Mrq+K20y1MG6hEuqfWNzqKH0be9EvQ9d6bqGzmLtwubMY3jTYWmcu6uBD4dxL4PuKh2Xi4OJoe/yje/bfpmhZcrg8h2dmvSgaytUJy78M6cLHdURqzeXMjb5Y3Wng8mRxtCt07fZbJVPH/t2yT6MtQvfwZoPbyYsjXN3NTQie9mYYy5dUlxjXwrbN75v+y4jX98JKJMedG3F6N3Gv8vzUMTqzaWMTf6mbKmJgZCKvs1mq3z62LdL38baRewvzlAsjXNPOXIP/blpclypRu4lnRBdDAb2UInuue+6DJMeTC+nb8zdZ2eGptaWxOrNpYwpLBM6cnQZnaYYnbvQt70TVT5d3x/X0XesXYToSGLuHnAx8GrMXdchg8Fee9UYnMvEkSnkEBNzV9Hx1YXr5Jnuue/oxsSDLWRjmtcI5T9EBh/E6M11rqD+xVY/0bCqN53t9Pt+cWWXcEn1c3Ui1/RLTDUpbXsnXcr6yueq/xgd1fWSaq5naZw7s1+2hiqzxjelUFc3VbaM6uVJkTYXgpC4pI6HpmLfTcjQBk1Xvnz61Ne+ffivtmd6x3z17cNzKvlC+HSp34Qzr2OpnLsvfB2gbVS5CDw2iZS8zEuuedBNkS3TFF2fdsqRsWrknYoHn/KLZI/zsCuTc6f8+XwhZ6gKBAKBP1KeoSoQCASCfQBx7gKBQNBBiHMXCASCDqKbzt337EjbmY2q81dN55LOU54U7Zmet3GOqE3HMfynlsG13VRnbvrSSHWmrc+5w3Wab3/7Xp1eD3jNa+wy6t5JG62YM3tj7WJedqeDbqa1zSv5lr8+e177nNloOn+1qZy61Ll7tvZsCfKpeNG1ZVs9FruKqalcyFi9xZbR5eLZNjgJ3QbRh0cf+qZ3UpUX6rqwJab/XDAnu8NSpUL6rEYwrTyIXQc/D3lStJdy/4EQPmT/gbAyMUuebbLb2o5deu1av86nz5L0mP5zwZzszuTcu5cK2evlaquDCBiP3crGQEUnBj7ypGjP9BxIx0tq3bvw7/I8FLF6c+ErhIYLbLLb+sqFR1f6pvp1Pl1pufRtrF3Mye6WKxXy0CH3+7qyANDvp6UfCh95UrRnep6SF12dWL3HyBeDWL3Flonh31bX53msLZjq15+50nIpF2sX87I7E3RD+jYvibknkidFexJzT69Xibm705eYuxewVDF3Zv/1y9Vdlsot9nTtdGH/AVt7pudtrPe26TiG/9QyuLbrQjO2jM1ebZstucgG2PcfqNPc3t6rQ8R84IBdRt07aaMVKp+qLV+7mIPdLZ9znzNC+7Apn+ODReBhmeHq3+u7PvZ6uV8zteHaty7fEaHfTb5o611q2u6ban8pnLvrl6Zu4JHKiLa33XaqU9Vz+SWaQhe6Mr6/HJt48Zp8yeb1xeXjVG07C45G6qhF9VLZn49dukR36rtB+p4Rmo0e5GH/PAO73MerDOwyYYeBMQNjHtAlHm0/FhTJcLXjKg+E3Vn5th/jYf88E3Z52D/P2ehBe18XbVbrNBSRYeYlcO4h4a66kaYyIt1VzXjyqVffxzpWF6YytvNVfen48tfkS9Bk26noumT2pT44IzS70JUXpe2MHuR1vOhAY+zcposMU++gAw8zDh8vGh28qs11vMiDA98JksMFnXfuoSmm5aVLrQ41It2LEFIPSKuLEPqq02hC03ZN9ULbTKWXJuBDt8kTj1z7NjUPStvpn0/eposMU+9gIA/D/nl9X2vbVH9JxZ7+xcxscu6dyHMPTTG1ITb9t4rhEDh71r8e4Fc2Jl1ahyrvPnR8+QPC2nRBU+ntKelubQHPPNMcLyrU+zY1D0rboTE4Igtb1WYVOhmm3sFAHghjjFldT98mAyAjP6HofJ57aIppCV1qdWz6bwki4ORJ/3oAMBi4lzW17ZJKPBgA6+vT99bXp3n3oePLX5OpwPNIM/ale/LkrP5TgGb9yuR+vW9VPKyuAmtrbm1WobWd/nP2yiUdTH8D6tqsQiVDvZ6Nhzpdl3q6ZwP6hvN7lRS6IX2bV5dj7kR7WQw+9YA8XBSSjRWbLh06+Scx93i6Vf3rJilHI/t5vmVoopyErfOgsksVD6aMStvkr2ky1SXmvoaX80nNYdpJex0PeYx9nMu3/Zgyfh4Scy8nVSVbJhCLki3jmmarquea2uvLU1Npa5It0zzdmPTFVDzE8qas65At45KdEgNVZovP85A2U8Pk3DsRcxcIBIJlROdj7gKBQCCYRnecu8tG+dUDAFwO5gihazssQHfowfHj7gcU2GQOPQTDF6HttXUYiA/d/V439KCImMMuFu1wClea8+BrHrR18Zo2r+iYu8uMqm5Zn26TsFQzqq4zuzrefGc0dbLYNuTynV20yWLarG2/zaguet2QjAIXmwjtx1i5QxGbTdA0GqCN2AlVAFcB+DMAjwN4DMBbARwEcD+AJ4q/VxdlCcBHATwJ4GEAb7a1H+3cF30VkysfPjzo2tLJ4nIIhs+KHhdZVO3tx1VMi1431P5dD0bx7cdYuUMRs4Kv6dVsDdE2OXenCVUiuhfAg8z8B0S0BmAdwH8C8A1m/jUiurNw7r9IRLcAOAHgFgBvAfDbzPwWU/vRE6qLvoophg8dD/M+aMSFvs8BKYu8imnR6zZl/yZe53UoigmxB540uZqtIdpRE6pE9M8A/CiAewCAmV9h5m8BuBXAvUWxewG8q/j/VgCfKL5YvgDgKiK6LohzVyz6KiZXPnxo+B524XIIhg9/oQcg7MdVTIteN9T+XQ9G8e1Hl+dNINWhKE2hbdq6IX15AXgTgC8C+DiAvwPwBwA2AHyrVu6bxd/PAPiRyv0HABw20ZCYu+aSmLvE3CXm7g6JuU/7bt2DSQHgMIAdAG8pPv82gP9icO7/XeHcb1K0ewzAGQBnDh06FCzcBC6rOOrL+nQHcwwGzBsb6nImui71dHy4rGJyXTGl00Wddq+X/62u6vI57KAuu+vBJXU+6v2QajWXid8YWZtYiaST27Vu1e6qm7vbeKjT3djY+1zdgctmj66HqpT36nank6te1mZnpj4u69ZlK2UOsQPVe2t6l2PsSIFY5/49AM5WPv/LwoF/FcB1xb3rAHy1+P/3ARyplJ+U010LdViHbpRv21w91Sgrtn3fNmxXE6OaeY3eXXloG6E2F1u3rK/aR0A12aprM8b2fUbYvvYZYu+mNkPb8+kPT0Q597w+HgTw/cX/vwLgN4vrzuLenQB+o/j/pwD8BfKsmZsBfNHW/kI5d1MWiGlWO1VmQ2z7obKZrtSZBPPKmHHloW2E2lxsXVt91zZjbV9V3ocv34yy1HLO6z1i5hTO/U1FCOVhAH8O4GoAgyLk8kTx92BRlgDcBeApAI/Y4u3M7Tl3p19Epg2tTRswE3GGIzzE0/m+EniaMxyZqZPhKA9wgSd7aOCCspwLXxN6rkeJKWiPcGqK5/pnJ97Y89emSVeOeoyGy6bfofIF8KKU2WZzlbpBNsW5Taj6f2avF1ObGv4zHJ3WGY6anV+17Uqb1f1nBrjAA1zQ2sZUP1X1WHlfqu152bzmHbS9U9W+TG1H0c696asN5+78K3w41L8shm/ebHBCvSPc4MQUD6t4ecam1/DyVDklCr5KoxngAq/V2rL9QlXRnj1IYGyUIUq3Drpy0WMS1PQ5eQkVfdx0BEclM2GXRzhlHe1lgxO8itmTflxsKsuY1+kliz3Y21Txv4rv8Br+aVpn9NLUl0fVwdZ1r2pTdVVtQxlhwneKd3n2KD1vm1e8g328Ym2v7MtscCK5HYlzZ/dfjtnoQf3LYtjhbTi4rG5/cNnKQ72cCq7bpDbyC9XCm2+Ew6QrFz2mgGl71lj5fKGTmbBr3VVQVzem33xtwcSDSiatk67I6tNmyVNs1MQmp/vxgGq5mzhuz+Tcl2ZXSNf1A6aTaEwnp8SegGRbx+B6Qk4Ta55iTlfy4aXpdUxVuJzWU6LpdS+mvrGd1hNjU6nW1KVaTxd6WlmqtVqqNqto6qSsGDuSXSHhvn7g3Dl9G6ZnMesnbM9stG3tnD6dG34oDh4072mm4/3gQfUeSSHrmA4eDOVeDZ0+y/vV/Z10uqvyGrO/l6nvn3nG3KarTfnSdWnThQcfVPskZD1dyrVAKt01dQRiY+undEP6Nq9FirmHJh+4rp8IzVpz+cnpm33mcrlkxemy6VSnCGVZngasojUaxWf2ucIUanHRWch6HV250cjtYGpdmzZ9xdK19YFr/9toVd8vnVy+coZcMesOTddgkH7uBhJzz+G6HiQm5Th0rYoL76oXyLb2IiYO2e+bj3Orv4xV2XX1XLIdTXVTweSQdfz1+2pdp8iCdXW0Kh3YbMqXbvnZtoapzoNuvZLpaD6Tk7MdJVjypeNDdUyhKUmq1ImL7nRXr8e8vT1Lp7qMQ7Jl5ohQB9wGX76G4TMyUxl8RGaod5tle55ZisHQ6dOXvmt5W7kqPyE618GHbvI0zxpUi051NF1s16YPnWyuMvu+P23rVJz7EsM0CrUZqmmUXT73pesycp/3+iLv7B/H8j7tptTBvPUZCpdRc9MypFjj1SRMzr3zE6qnj/81tlaeRY/G2Fp5FqeP/3Wj9UztbNLz2Ow979xmCh5OngTW13am7q2v7eDYsdn79TK3vPFxvHjueQA883xtZRe3vPFxLX+3vPFxEKZTANbXdnDypJ6nkyfNPJfPm4YvfVV5gHHpmctT/X3LGx9XtqvSo67N55+5bE5lHvUAABq0SURBVLQDlc3MU5+uNuzKdxVtyKCyY9X70BY/XtB5/TavpkbuPrnMKeq5tOPaZioeOMs4W/3A9GKd1Q8wj0acrX6gslhrjw5hl7fxWQXv1VV4v6PlT8U7YZdHdPck8KjkqfKb2fi8afjSL8qrdFnXz4jurq0IvUutx+17eIS7GIq8cN2aC63NbN8zF3262rAr3zOrUxuWQWfH2/hL9UKsNm20AJYtLJONHuRh/7z2RRv2z0/KEHYnn0vkddX1fKBrx6XNUB5m5Nq4Y1K5vrrO5Ixyo1Xfp4lRq/nT8o6no+Iyo/7vFXTH3MerPLrx8+568PhSzDbuUL+8G3eo2y34zetY+htPT93Q1clXP6p1XPZDXSa93s+a9d0Q9PY/nuoTb74VMpj6OzT+bbRjxYMMRyZ1bPMJqbBUzt1tFdmucUShW0VH2PXiRb/c2d5mCA/aERCOcIYjnqvr9CNQmzyq0Wap99AZ1RFOKXgaKx18zK8ek/3kS+pfnm232DvEub8rN1yXxKuuukxGmzHpuyHY9FHy7813TQZTf8dsHeHDl+n9anKz0aVy7i6jZdOo09TGoo/cTSMNl1Gli45c5DGN+kNH7sY2E+jOp89m9XuWGWlH7j76tvf/WbO+G4Kr/ceO3E39HTOZ7DNyt/VjU6peKufuMlrQjSzLUfF+jbmbRhouo8oqHVVM3aVeNnpQq19gdy/Z1/MUH/1IduylBxt89DTV7vq6w6+jMWf9903dzHrv1cxteNC22cz2PXPZu97lV3S5f44z3woZjHYfkVZr+iVcb9BmN039SFoq5+4S53MZ2cXEbKuotjPAJR7QJec2fXnQytU7x0OcdXAW40lsmbNsir4tBu8UQ+2dqwhnCYTWni/0yL1/fsJvhiNaXge4pJS73s8DuuRH28Vm2kxmV/Bjmv9y5ltzClNTI/cJX71ze5O4G3fsne4ETILrNruRkXsssoyztQ9YR7zJMlEU9J1eoOpKDtsywNFob3am38+Xv2loZNv3aEYaR62jysmIRDMTpG27+CKYEs80EjOtDjPob/S9n1I4iFrMveJgtfQtK1pU9lNe2pi7a/ZH3b408qrqu9IOssEWZv+cdKJz5Jaj9YxzTYMTvL5S09vaq9NNuC6vNdhuluXtGt+tBvS7HM69sm/AzD7d2/fMFk80Mp+iH3vUGDC9z4FuExYVjaJd7aEPqGfLVH5F1Mp5t62Qc0a/2/eY93Uw6a94NsKp6WyZ7/2UVq9TvJb0HQ+JVh7qUNiIq91Yy1nsRVU/tk0nG2wwXGPk3/ZeWHicattg96q0W6eNcWzvaiV9VrlXfUP6XQ7nHrqUMhVilymq6rgsIy3L+yyl6/fd+XFt26ZjW//ELGl10X/sUt3UaGLZaCobnMfS1VRLQV3bsdmFLx8+7STUr8m5d2c/95iNrVPAddNvl02nyzrlBuc2mDZC16Esa+PHte2YzcNtG7mbntk2y0+x2XcT9tPEJvGpbLCN96UO3/6JPbgg1SbwIe0k1O9y7Oces1l6k/Tr9114Kcv0++60fWSstmur59q2SzshNGzPbO3bNvt20XET9uNqL020GdNXTcGXZqz+Um0CH9JOW/rVDenbvFLH3Keu1BuBm+gvQMx96lmvp64zGrnxY2rbJqdKP5ExdyPNgPRKXczdW7YQxKyuiW1zTjF3b95D+sSlHZtdBMbcnfiXmHsgsmy+e/XOOVtGSb9ev+rYVfzoMiccUtKc9BOYLeOkW8/0SlW2TLBsIWgiPXFBs2WcEJgtY2ynzHTxtQvPbJmpdurvdTnIajlbpjthGQCncRs2cQkEBoGxiUs4jdtapb+Fs+hhjC2c1dIuyxEYPYyN/B7H3VjBDgiMFezg7fgfWhoq+vX6x3G3kZ+yrKntTVzCJi5Z5VTRMfWPSX8uurWV0T1PIVsIXO2liTZd+rxt6PrBt09mdPC2u/PDWcfj/O9tdruo3zuOu+2+5bbb8vaZcfqPxtga5mVXaHc++tV5/TavFCN3icpIVEaiMhKV8dVrqqiMqyyp9YtlCMtIJqRbWUAyIeu6iJUtBJIJ6ceTK4++ek2VCenTZkr9mpx7Z1IhJRPS3m4VZVnJhLRDMiGbR9OZkLGZkz58tKnfpUiFlExIt7L1diUTUs+Xre0YSCZkHE1f/TWhb139hdGvbkjf5rUoMfds9CAPcIknJw7RpZll3wO6xIMD31EmXNTjbPlOceOppf4b+Dabdv1rPuY+5gN0ebL02xQfnPBPl3htZUfLg+7keJf+6ff3khBMJ8bb4qjb27Ntr66WbY+ZsKPQ+5ivwD8aZcvr7M7YhLNdKjaOA3aV/BCpk5mcaSn7csyD3vMzh1foZF7t7/Cg93zwthy6LQZsiUqq/tfaW9EfZfuj0d69vWv2nVIl4/jQVV26pBmJuXM6585cz7QrjBpH9elNFS1nowd5Fd+ZdT54ZWbDpqnOWnt1chpPhqOTHfDct44dGw1lJhPyxme1u9RlODr9bHCCR9uPVQy/wndlM6Ns9GAtK26W/1V8hwe4yITx9IuhanfjDmXqWj0TcmNj1slMXtyyWlFpan+QweUpPY22H1M67h659UEfrxSnUpkOGqk4C7zM2RU/Z03Nczs4RmFPupffIWUzy5gHV8wOIKqbdKltfcwbK46bk1V52TMazjbuUG7gNdp+bGZTrfW1V/P7eKnW/+PJu1DPhFTZZQ//pOj76Wu1v5NPnGs29qrSrdszCnufzoSs6/almU33Zt+pZjJNl8a5T5ApzsDsvZez/vu0GwiFbPU6ccq4MNVu7ijc6w8Hl93l6r23cjxeeZ7pKeM5k8PeOQ3tsfLsR50uetjJ9yMvdTa4rHlRdpzOutTVH+DC5MtYJW+VB84y7sE08na9Zkd8pquHHbt8gTaltIeaTWvPE80yrf3ZDqOxHWKj4qW6SZZpW2adDn3eh5h3tE92G9GVqfKjs9lyM7u2z1NdOueeDU64b5k6OMHMYYc0TDsG02fz5Xp8XzY4ofx1YTuU2TYarerBpos1vOyts3r7djpjzgYntPJWecgGJ7z1nfryl8/fHlQ2reLBpI+yXd+j/er82Hhxt083erH6NPPgx0+szafG0jl3n6PLhng6rxMxKoi9Sh5SylW9XI7Mq/JgPXig1FmAnl3lsR0NGMJD230YPHL31JWzzhKN3Js+slH3PkSN3B140MpffTcibT41TM69M9kyVZyD+3R0WfbksbNYxcsB1Njz/jTW8RJODj7sVNZHrip20cM6XnJu++SxszDxP9HZ4MPWdlXtT+gMPqylcw6HjPKWz/Rl3PSfCkr5jp111k8JnT249L1ZZ1z0q5qvdbyEYzf+tfJ+Wc+Hl6l21z6u0IP+vdG9Dyq+e3jF0FaFB/y+sS90Zer9EWvzrULn9du8ko/ctXExxbdrJZ5Wz5bRxQSr8dYBLirLDK74tjHWaIvXxspVl9F63Fktzjm4Uk9rUraIvTr9MtDEkXX6Gw4uG+Ut29PH/XXnau54TnbPTkY7y8ds1Xvs/ISrzgZXfFvJ10xWi8NhJDZeZo5eVMyBad+bcr5Fgxn+bjzJI5zS6rePV3Odjkb2OYtaGWV/TM03mO3CeS4tAli2sEyWzc6Mr/Z3ZjIzjJkJmnbWV4p4b5GlkI0eVGYCTFL4LPV9Jl2yLJdD7YTUBlaXUcmTQg86WmsrO9Nls8weDzboOc8oeUmrPxsPSnnwIo9u/Pzs8WorL2v7ZYbnMmaaZdbyNjsy6r3ItLJm3jjy4Nq/MTDxoqVVy1RTvjd4KexEtNGIM7pNfdRe0YczPOg2IzNk1NVlyXB0xnab0rkOS+fcmdV95NJvLu34lAmhaeOnvjldddM7lw30XHlS0TKVDd1Y0aY/1834fN7TaibfzIhLwXOMfC5y+tY38ZDa5ky8AOGpfk28G03LraMZo4cYmJx7Z7YfEAgEgmVD9PYDRHSWiB4hoi8R0Zni3kEiup+Inij+Xl3cJyL6KBE9SUQPE9Gb04kiEAgEAhf4ZMv8ODO/qfItcSeAB5j5BgAPFJ8B4J0AbiiuYwB+NxWzAoFAIHBDTCrkrQDuLf6/F8C7Kvc/UYSEvgDgKiK6LoKOQCAQCDzh6twZwF8R0UNEdKy491pm/hoAFH+vLe6/DsD5St1ni3tTIKJjRHSGiM5cvHgxjHuBQCAQKLHiWO5tzPwcEV0L4H4ietxQVrUL+cysLTN/DMDHgHxC1ZEPgUAgEDjAaeTOzM8Vfy8A+BSAHwbw9TLcUvy9UBR/FsDrK9WvB/BcKoYFAoFAYIfVuRPRBhG9pvwfwE8CeBTAfQBuL4rdDuDTxf/3AXh/kTVzM4AXyvDNwuD0aWBrKz8yZWsr/9wGzc3N/BgWovz/06f9eNGVbUKeapubm/lVbV9FMyUfIfRVOH4cWFnJdb6ykn92oRnaFzHPQvhwQYjd1O2139+z23pfzAs2PR0/nj8rZXjNa8L4je2PefgbwL6ICcAbAHy5uL4C4JeL+wPkWTJPFH8PFvcJwF0AngLwCIDDNhpNLGLSQrWTftOnAmeGkyrqJ/HqeNHxrTrhuYmTlqvX6urs9sm997rL0gR91bL90Wh6H3g8ne+7rToRw8cuVFtKV7bcDXoWwkeoLm12o9tqGUcUSzEX6ETtKi+jEY9wqnIoypgP4AXO6L3eK62sfdZkfQuwjCtUtWjiZOJQmrrL59Rd3QnPTZy0XFwZjqiXeqte/hA+QunXtljVLkmn29xpKvhXbbdQ3XI35FkIH1G6NNiNcavlVH0cC4ueRvgdVm3LsYJXvLbideqzBuvbIM69Ct2ZWkTt09RdKl5StJGIX922p0M8nYaPGPoVuJYz0lTwb2o39FkIHyl0qaJj3Wq5zXfHV66CF9Nmdj5b8XrZUAP1bTA5905u+WuE7nRaZnM8LCYGnOL0X98Tng8e9I/zlTIwG4vptjJV3i/59ok7WvTlSj+IT4f7pnZDn030cvCgMx9O8LWbXs9pq2UrjabjzJb+2oX+5HPrVrwV3o195jB/4WWDqaHz+m1ercfcVfHv8lLFEB1iwMZ4c9sxdxs/Or2YZHQaOZ9V0/SNI1v6aIizevqVNocHLqnLHbjkrl8Fj7otb01b7hqfVUfDIX1ngo/dWPp3hlef9yV1bN5Cw3SsnnEr3lq71l+plvkLkz2kACQsU0N1m0Gl5ofT5X1j5qp2dNsb+mxl57r9oU4+U2zUJGN1C8J+XxPzfkm/fW1IHFknQ7+v3ia4cuB3VV26bX+99Kso5rXNs+mZaq5iMGhnu8Tq/UoMPsMRfcxdc/j5FNqa1zL012jErIy593bN6qzx7jS/ZJq/MNhDCohzr4NokkVRPeB3kk1RjyFWyis3+scRdVbGPGKRCn6d+HGtU5SbzaQ42io/GY6qszlqbTa1DWzoNs9Tz/D01OHmc7UbhY1v4IWJgzRt92xra15yjUbTofkDBxxkUPBuPIC+cPJGW21wK2Jx7jWYDpdQZl1YDqOwHb7dNkJm6F3rNNm2T52msxDawCLJkJKXRZLLFyHZTiP8ztzkXV7nPhrN/mQaDo1HyAGz8bDg4+0OXJp8ZWeDEzzY2Pupa4zKaIYcU2UHlycnOmWDEzwcXN6LymjkU8aarTKOp6MyPfURddWj/PLRy9l89DIY6GPkhrjj4MBsWABg7mOHM7pNHwtdeXavz/t9zrbvyXWGcX4sG45qh9P56Ovs3hFu2/fMnsRQVcZgwLyxMcvExobTaR7aI/FwkYe9c9N86E4sMZ1mMpHraNEvY31UxtSv9UNCrry8N0Kl2/bWDRQFtX2j6++QoW2WnwA2GS0XfJrKu5x0oo2R0zPaORztwdqV4yibGrovp3PPg24zV4YjbDv7UBGJCHLuhN0JTVUMUzmfuqLOJc7overj5HBK8atCd17nrtawQmWs0tTFJrXnmWp+pWeZmVZOR3dG6u5UX2vjpbXJXq/cfd9LM5mo1/nYzsfaWm7jqonn8plOLvN8qpJ9U19kOMK8vT0p6NXfIZOvxcKgGblMR/wZhdijp82wxK7h7F3N+0aB8nlgOZ27ZpLDlAlQXsnmU4sZdReaqnoufLscTj3VrmZSK1RGGx/G/G41K068mOjZdDYpMxxOiHnl7gcZw6ywPjpX8qGbyKs809qNoapvuTpvXv0dMvlq+nXgQ0NRUcuOwY61tjgMlM8Dy+ncNZ2o//bNr6BMSF3MvRht2WjWr+ro08637leIZvSnGS57ZEIqdWbiQ/XrYh0vagcvbr8ixjM6IezyCKesOpvol2hCzKRf68S5U6fO6l2tc70edTRNPPna3my/uly7M/yofi0o+ztk0RaR368DF4OqTH6qfgkPcEFrx8r7pbwNL5pcTuceMHK3HRadx24dsmWG+cSMC00lHx4jdye/UnV6hhFDKaNLm/3+dAhx0Hte7ySKF2DKARkmm/x+RehDGD4j9zzzxkzL9iVu7lS13rOMK/MUTzvxMaGpTUsttlgw6EA3Iq/3q0tfEHbNXziG92rRRu7M+bu7l4lVs+ONj0/8gDZbpiqvjNybibmPcKr4yTTmasrczAvqEwJTbKo0ScXrv29qtqrcMCiPD8+ONHQx92385YTvPl7lEU4pY+4+1xBPOwvqEaKcoDpZrHQaeHXvhajqKYC+/cr7hLDDK3hF7Rirm2StfoB70C96caVXXht4YfrL37ZRVM1WXEbbQ5xlHo30k9UHLnG2+gG1k/LYb861L4ZX/kPYBllZwMZaWcaj3u/N6ClFzL0sP8BFtZzVSVJHBcrGYYmhW8QAMK/2d1ySGZTIsry+qt21lZ2pTIRZZ7zHjy5bZntbxfeYR9uPeY2s65dpMlUnp0NywQQ+E7IuizhU9EMd74ED+mwZdT+lvWzyqnigyYBANzk+zvVuSA5Q2Z8imcb6HlTL2eQM6Wffemp9jZWbfSqFsBh0PqFvmCRVtalRoCxiasC52yaCUm+yV2839NeYju+qUZna1j3r99MunqjD90snRP+uk4A62X0Wz6a+QhcH62QeDPK6hoW8Se0+tA9s9AKjMt51fAYrpv6o0nD5cmx6se5SOneb0TW1yV7Zbug8iqntqV8F+q24tb9Am9x62zeUEqL/GOeq01d8Cmi8vCE82DIhU9t9aB/Y6AXOp3rV8Y3KmPrD5R2Mlc8HS+ncuzZyr9c1jRqyrLmRmwnVsFET+jf9KglxkLZfOqo1cKFX6MjddJlG9U2NGE36CqHXxsjdcz5VW778teTDg4zcG4u5q6/YTfZ0Gxaurfl/s/vw7fNt3/SIIYYHIEz/Np2adKfTha1N3XPdqDnE3uInkP3lCoVJHyH0AtcwedXxyIR0bt/1/Wp4DdNyOndm7e4DSQy8HutUbazkOmFVx4EDasPx+bZvesQQw0N1BOQLm06rfV6Ovm26sLWpe66yA8B59wElDR8nbhsth9qfK6+2zUld6YXU86njO3J3ad/n/WqqH5iX2LnvV6T4tm96xLBfeFgkPlyg4lW3xXsTx+d2Eb4x99A256F7ce77ECm+7ZscMewnHhaJDxeoeE09Wl42+Kb2+rY5L92bnDvlz+eLw4cP85kzZ+bNhkAgEOwrENFDzHxY9Wz5zlAVCASCJYA4d4FAIOggxLkLBAJBByHOXSAQCDoIce4CgUDQQYhzFwgEgg5CnLtAIBB0EAuR505EFwE8k6CpTQCXErSzH7BMsgIib9ch8oZhyMzXqB4shHNPBSI6o0vo7xqWSVZA5O06RN70kLCMQCAQdBDi3AUCgaCD6Jpz/9i8GWgRyyQrIPJ2HSJvYnQq5i4QCASCHF0buQsEAoEA4twFAoGgk+iEcyeidxDRV4noSSK6c978pAAR/SERXSCiRyv3DhLR/UT0RPH36uI+EdFHC/kfJqI3z4/zMBDR64no80T0GBF9hYg+VNzvnMxEdCURfZGIvlzI+qvF/e8jor8pZP0TIlor7l9RfH6yeL41T/5DQUR9Ivo7IvpM8bmz8hLRWSJ6hIi+RERninut2vK+d+5E1AdwF4B3ArgRwBEiunG+XCXBxwG8o3bvTgAPMPMNAB4oPgO57DcU1zEAv9sSjymxA+A/MPMPALgZwM8X/dhFmf8JwE8w8w8BeBOAdxDRzQB+HcBHClm/CeCDRfkPAvgmM78RwEeKcvsRHwLwWOVz1+X9cWZ+UyWfvV1b1h3RtF8uAG8F8NnK518C8Evz5iuRbFsAHq18/iqA64r/rwPw1eL/3wdwRFVuv14APg3gX3VdZgDrAP4WwFuQr1hcKe5P7BrAZwG8tfh/pShH8+bdU87rkTu0nwDwGQDUcXnPAtis3WvVlvf9yB3A6wCcr3x+trjXRbyWmb8GAMXfa4v7ndJB8TP8XwD4G3RU5iJE8SUAFwDcD+ApAN9i5p2iSFWeiazF8xcADNrlOBq/BeA/AhgXnwfotrwM4K+I6CEiOlbca9WWV2IbWACQ4t6y5Xd2RgdEdADAfwXwC8z8bSKVaHlRxb19IzMz7wJ4ExFdBeBTAH5AVaz4u69lJaKfBnCBmR8ioh8rbyuKdkLeAm9j5ueI6FoA9xPR44ayjcjbhZH7swBeX/l8PYDn5sRL0/g6EV0HAMXfC8X9TuiAiFaRO/bTzPzfitudlpmZvwXgfyKfZ7iKiMoBV1WeiazF8+8G8I12OY3C2wD8DBGdBfDHyEMzv4Xuygtmfq74ewH5l/cPo2Vb7oJz/z8Abihm3tcAvAfAfXPmqSncB+D24v/bkcely/vvL2bdbwbwQvnzb7+A8iH6PQAeY+YPVx51TmYiuqYYsYOIvgvA25FPNH4ewLuLYnVZSx28G8DnuAjO7gcw8y8x8/XMvIX8/fwcM9+GjspLRBtE9JryfwA/CeBRtG3L8554SDR5cQuA/4s8bvnL8+YnkUyfBPA1AK8i/2b/IPK44wMAnij+HizKEvKMoacAPALg8Lz5D5D3R5D/FH0YwJeK65YuygzgnwP4u0LWRwH85+L+GwB8EcCTAP4UwBXF/SuLz08Wz98wbxkiZP8xAJ/psryFXF8urq+UPqltW5btBwQCgaCD6EJYRiAQCAQ1iHMXCASCDkKcu0AgEHQQ4twFAoGggxDnLhAIBB2EOHeBQCDoIMS5CwQCQQfx/wGMbEjeF0fExQAAAABJRU5ErkJggg==
+"
+>
+</div>
+
+</div>
+
+</div>
+</div>
+
+</div>
+<div class="cell border-box-sizing code_cell rendered">
+<div class="input">
+<div class="prompt input_prompt">In&nbsp;[54]:</div>
+<div class="inner_cell">
+    <div class="input_area">
+<div class=" highlight hl-ipython3"><pre><span></span><span class="n">solution</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">({</span><span class="s1">&#39;House&#39;</span><span class="p">:</span> <span class="n">test_df</span><span class="p">[</span><span class="s1">&#39;House&#39;</span><span class="p">],</span> <span class="s1">&#39;EnergyProduction&#39;</span><span class="p">:</span> <span class="n">predicted</span><span class="p">})</span>
+</pre></div>
+
+    </div>
+</div>
+</div>
+
+</div>
+<div class="cell border-box-sizing code_cell rendered">
+<div class="input">
+<div class="prompt input_prompt">In&nbsp;[55]:</div>
+<div class="inner_cell">
+    <div class="input_area">
+<div class=" highlight hl-ipython3"><pre><span></span><span class="n">solution</span><span class="o">.</span><span class="n">info</span>
+</pre></div>
+
+    </div>
+</div>
+</div>
+
+<div class="output_wrapper">
+<div class="output">
+
+
+<div class="output_area">
+
+    <div class="prompt output_prompt">Out[55]:</div>
+
+
+
+
+<div class="output_text output_subarea output_execute_result">
+<pre>&lt;bound method DataFrame.info of      House  EnergyProduction
+0        1               794
+1        2               605
+2        3               714
+3        4               549
+4        5               549
+..     ...               ...
+495    496               486
+496    497               714
+497    498               645
+498    499               714
+499    500               605
+
+[500 rows x 2 columns]&gt;</pre>
+</div>
+
+</div>
+
+</div>
+</div>
+
+</div>
+<div class="cell border-box-sizing code_cell rendered">
+<div class="input">
+<div class="prompt input_prompt">In&nbsp;[56]:</div>
+<div class="inner_cell">
+    <div class="input_area">
+<div class=" highlight hl-ipython3"><pre><span></span><span class="n">solution</span><span class="o">.</span><span class="n">to_csv</span><span class="p">(</span><span class="s2">&quot;predicted_energy_production.csv&quot;</span><span class="p">)</span>
+</pre></div>
+
+    </div>
+</div>
+</div>
+
+</div>
+<div class="cell border-box-sizing code_cell rendered">
+<div class="input">
+<div class="prompt input_prompt">In&nbsp;[&nbsp;]:</div>
+<div class="inner_cell">
+    <div class="input_area">
+<div class=" highlight hl-ipython3"><pre><span></span> 
+</pre></div>
+
+    </div>
+</div>
+</div>
+
+</div>
+    </div>
+  </div>
+</body>
+
+ 
+
+
+</html>
diff --git a/challenge1/analysis/shino/Challenge1.ipynb b/challenge1/analysis/shino/Challenge1.ipynb
new file mode 100644
index 000000000..32fed455e
--- /dev/null
+++ b/challenge1/analysis/shino/Challenge1.ipynb
@@ -0,0 +1,1524 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "import seaborn as sns"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from sklearn.linear_model import LinearRegression\n",
+    "from sklearn.linear_model import LogisticRegression\n",
+    "from sklearn.ensemble import RandomForestClassifier"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "train_df = pd.read_csv('../../data/training_dataset_500.csv')\n",
+    "test_df = pd.read_csv('../../data/test_dataset_500.csv')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>ID</th>\n",
+       "      <th>Label</th>\n",
+       "      <th>House</th>\n",
+       "      <th>Year</th>\n",
+       "      <th>Month</th>\n",
+       "      <th>Temperature</th>\n",
+       "      <th>Daylight</th>\n",
+       "      <th>EnergyProduction</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>7</td>\n",
+       "      <td>26.2</td>\n",
+       "      <td>178.9</td>\n",
+       "      <td>740</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>8</td>\n",
+       "      <td>25.8</td>\n",
+       "      <td>169.7</td>\n",
+       "      <td>731</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>9</td>\n",
+       "      <td>22.8</td>\n",
+       "      <td>170.2</td>\n",
+       "      <td>694</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>3</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>10</td>\n",
+       "      <td>16.4</td>\n",
+       "      <td>169.1</td>\n",
+       "      <td>688</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>4</td>\n",
+       "      <td>4</td>\n",
+       "      <td>4</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>11</td>\n",
+       "      <td>11.4</td>\n",
+       "      <td>169.1</td>\n",
+       "      <td>650</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>5</td>\n",
+       "      <td>5</td>\n",
+       "      <td>5</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>12</td>\n",
+       "      <td>4.2</td>\n",
+       "      <td>199.5</td>\n",
+       "      <td>763</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>6</td>\n",
+       "      <td>6</td>\n",
+       "      <td>6</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1.8</td>\n",
+       "      <td>203.1</td>\n",
+       "      <td>765</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>7</td>\n",
+       "      <td>7</td>\n",
+       "      <td>7</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2.8</td>\n",
+       "      <td>178.2</td>\n",
+       "      <td>706</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>8</td>\n",
+       "      <td>8</td>\n",
+       "      <td>8</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>6.7</td>\n",
+       "      <td>172.7</td>\n",
+       "      <td>788</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>9</td>\n",
+       "      <td>9</td>\n",
+       "      <td>9</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>4</td>\n",
+       "      <td>12.6</td>\n",
+       "      <td>182.2</td>\n",
+       "      <td>831</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>10</td>\n",
+       "      <td>10</td>\n",
+       "      <td>10</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>5</td>\n",
+       "      <td>17.6</td>\n",
+       "      <td>214.2</td>\n",
+       "      <td>955</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>11</td>\n",
+       "      <td>11</td>\n",
+       "      <td>11</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>6</td>\n",
+       "      <td>20.8</td>\n",
+       "      <td>143.0</td>\n",
+       "      <td>837</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    ID  Label  House  Year  Month  Temperature  Daylight  EnergyProduction\n",
+       "0    0      0      1  2011      7         26.2     178.9               740\n",
+       "1    1      1      1  2011      8         25.8     169.7               731\n",
+       "2    2      2      1  2011      9         22.8     170.2               694\n",
+       "3    3      3      1  2011     10         16.4     169.1               688\n",
+       "4    4      4      1  2011     11         11.4     169.1               650\n",
+       "5    5      5      1  2011     12          4.2     199.5               763\n",
+       "6    6      6      1  2012      1          1.8     203.1               765\n",
+       "7    7      7      1  2012      2          2.8     178.2               706\n",
+       "8    8      8      1  2012      3          6.7     172.7               788\n",
+       "9    9      9      1  2012      4         12.6     182.2               831\n",
+       "10  10     10      1  2012      5         17.6     214.2               955\n",
+       "11  11     11      1  2012      6         20.8     143.0               837"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_df.head(12)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>ID</th>\n",
+       "      <th>Label</th>\n",
+       "      <th>House</th>\n",
+       "      <th>Year</th>\n",
+       "      <th>Month</th>\n",
+       "      <th>Temperature</th>\n",
+       "      <th>Daylight</th>\n",
+       "      <th>EnergyProduction</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>11488</td>\n",
+       "      <td>11987</td>\n",
+       "      <td>11</td>\n",
+       "      <td>500</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>6</td>\n",
+       "      <td>21.8</td>\n",
+       "      <td>152.1</td>\n",
+       "      <td>645</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>11489</td>\n",
+       "      <td>11988</td>\n",
+       "      <td>12</td>\n",
+       "      <td>500</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>7</td>\n",
+       "      <td>26.2</td>\n",
+       "      <td>169.8</td>\n",
+       "      <td>661</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>11490</td>\n",
+       "      <td>11989</td>\n",
+       "      <td>13</td>\n",
+       "      <td>500</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>8</td>\n",
+       "      <td>27.8</td>\n",
+       "      <td>257.9</td>\n",
+       "      <td>822</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>11491</td>\n",
+       "      <td>11990</td>\n",
+       "      <td>14</td>\n",
+       "      <td>500</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>9</td>\n",
+       "      <td>24.7</td>\n",
+       "      <td>183.2</td>\n",
+       "      <td>665</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>11492</td>\n",
+       "      <td>11991</td>\n",
+       "      <td>15</td>\n",
+       "      <td>500</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>10</td>\n",
+       "      <td>17.4</td>\n",
+       "      <td>201.2</td>\n",
+       "      <td>655</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>11493</td>\n",
+       "      <td>11992</td>\n",
+       "      <td>16</td>\n",
+       "      <td>500</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>11</td>\n",
+       "      <td>9.7</td>\n",
+       "      <td>203.5</td>\n",
+       "      <td>582</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>11494</td>\n",
+       "      <td>11993</td>\n",
+       "      <td>17</td>\n",
+       "      <td>500</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>12</td>\n",
+       "      <td>3.8</td>\n",
+       "      <td>194.2</td>\n",
+       "      <td>534</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>11495</td>\n",
+       "      <td>11994</td>\n",
+       "      <td>18</td>\n",
+       "      <td>500</td>\n",
+       "      <td>2013</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>234.6</td>\n",
+       "      <td>640</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>11496</td>\n",
+       "      <td>11995</td>\n",
+       "      <td>19</td>\n",
+       "      <td>500</td>\n",
+       "      <td>2013</td>\n",
+       "      <td>2</td>\n",
+       "      <td>4.2</td>\n",
+       "      <td>201.8</td>\n",
+       "      <td>638</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>11497</td>\n",
+       "      <td>11996</td>\n",
+       "      <td>20</td>\n",
+       "      <td>500</td>\n",
+       "      <td>2013</td>\n",
+       "      <td>3</td>\n",
+       "      <td>11.2</td>\n",
+       "      <td>234.0</td>\n",
+       "      <td>778</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>11498</td>\n",
+       "      <td>11997</td>\n",
+       "      <td>21</td>\n",
+       "      <td>500</td>\n",
+       "      <td>2013</td>\n",
+       "      <td>4</td>\n",
+       "      <td>13.6</td>\n",
+       "      <td>237.1</td>\n",
+       "      <td>758</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>11499</td>\n",
+       "      <td>11998</td>\n",
+       "      <td>22</td>\n",
+       "      <td>500</td>\n",
+       "      <td>2013</td>\n",
+       "      <td>5</td>\n",
+       "      <td>19.2</td>\n",
+       "      <td>258.4</td>\n",
+       "      <td>838</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "          ID  Label  House  Year  Month  Temperature  Daylight  \\\n",
+       "11488  11987     11    500  2012      6         21.8     152.1   \n",
+       "11489  11988     12    500  2012      7         26.2     169.8   \n",
+       "11490  11989     13    500  2012      8         27.8     257.9   \n",
+       "11491  11990     14    500  2012      9         24.7     183.2   \n",
+       "11492  11991     15    500  2012     10         17.4     201.2   \n",
+       "11493  11992     16    500  2012     11          9.7     203.5   \n",
+       "11494  11993     17    500  2012     12          3.8     194.2   \n",
+       "11495  11994     18    500  2013      1          2.0     234.6   \n",
+       "11496  11995     19    500  2013      2          4.2     201.8   \n",
+       "11497  11996     20    500  2013      3         11.2     234.0   \n",
+       "11498  11997     21    500  2013      4         13.6     237.1   \n",
+       "11499  11998     22    500  2013      5         19.2     258.4   \n",
+       "\n",
+       "       EnergyProduction  \n",
+       "11488               645  \n",
+       "11489               661  \n",
+       "11490               822  \n",
+       "11491               665  \n",
+       "11492               655  \n",
+       "11493               582  \n",
+       "11494               534  \n",
+       "11495               640  \n",
+       "11496               638  \n",
+       "11497               778  \n",
+       "11498               758  \n",
+       "11499               838  "
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_df.tail(12)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "((11500, 8), (500, 8))"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_df.shape, test_df.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "train_df_hde = train_df.drop(['Label','Year','Month','Temperature'], axis=1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>ID</th>\n",
+       "      <th>House</th>\n",
+       "      <th>Daylight</th>\n",
+       "      <th>EnergyProduction</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>11495</td>\n",
+       "      <td>11994</td>\n",
+       "      <td>500</td>\n",
+       "      <td>234.6</td>\n",
+       "      <td>640</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>11496</td>\n",
+       "      <td>11995</td>\n",
+       "      <td>500</td>\n",
+       "      <td>201.8</td>\n",
+       "      <td>638</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>11497</td>\n",
+       "      <td>11996</td>\n",
+       "      <td>500</td>\n",
+       "      <td>234.0</td>\n",
+       "      <td>778</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>11498</td>\n",
+       "      <td>11997</td>\n",
+       "      <td>500</td>\n",
+       "      <td>237.1</td>\n",
+       "      <td>758</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>11499</td>\n",
+       "      <td>11998</td>\n",
+       "      <td>500</td>\n",
+       "      <td>258.4</td>\n",
+       "      <td>838</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "          ID  House  Daylight  EnergyProduction\n",
+       "11495  11994    500     234.6               640\n",
+       "11496  11995    500     201.8               638\n",
+       "11497  11996    500     234.0               778\n",
+       "11498  11997    500     237.1               758\n",
+       "11499  11998    500     258.4               838"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_df_hde.tail()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>House</th>\n",
+       "      <th>Daylight</th>\n",
+       "      <th>EnergyProduction</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>House</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.001583</td>\n",
+       "      <td>-0.008303</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>Daylight</td>\n",
+       "      <td>0.001583</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.531577</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>EnergyProduction</td>\n",
+       "      <td>-0.008303</td>\n",
+       "      <td>0.531577</td>\n",
+       "      <td>1.000000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                     House  Daylight  EnergyProduction\n",
+       "House             1.000000  0.001583         -0.008303\n",
+       "Daylight          0.001583  1.000000          0.531577\n",
+       "EnergyProduction -0.008303  0.531577          1.000000"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_df_hde[['House','Daylight','EnergyProduction']].corr()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "LinearRegression(copy_X=True, fit_intercept=True, n_jobs=None, normalize=False)"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "lr = LinearRegression()\n",
+    "X = train_df_hde[['Daylight']].values\n",
+    "Y = train_df_hde[['EnergyProduction']].values\n",
+    "lr.fit(X,Y)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "coefficient =  [2.56478737]\n",
+      "intercept =  [127.69148663]\n"
+     ]
+    }
+   ],
+   "source": [
+    "print('coefficient = ', lr.coef_[0]) # 説明変数の係数を出力\n",
+    "print('intercept = ', lr.intercept_) # 切片を出力"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.scatter(X, Y, color = 'blue')         # 説明変数と目的変数のデータ点の散布図をプロット\n",
+    "plt.plot(X, lr.predict(X), color = 'red') # 回帰直線をプロット\n",
+    "\n",
+    "plt.title('Regression Line')            # 図のタイトル\n",
+    "plt.xlabel('Daylight')                     # x軸のラベル\n",
+    "plt.ylabel('EnergyProduction')    # y軸のラベル\n",
+    "plt.grid()                                 # グリッド線を表示\n",
+    "\n",
+    "plt.show()                                 # 図の表示"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# DaylightとEnergyProductionに相関はあるが、ばらつきが大きい。\n",
+    "# Houseごとに、発電能力に差があるためでは？\n",
+    "MeanEnergy = np.mean(train_df_hde['EnergyProduction'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "612.7488695652174\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(MeanEnergy)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "pivot_House = pd.pivot_table(train_df_hde, index='House')\n",
+    "# 各Houseごとの発電量の平均を求める"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "23.0\n"
+     ]
+    }
+   ],
+   "source": [
+    "cases_House = train_df.shape[0]/pivot_House.shape[0]\n",
+    "print(cases_House)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "eachHouse_perMeanEnergy = pivot_House/MeanEnergy\n",
+    "# 各Houseごとの平均を、全体の平均から求める係数を算出する"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "k_Energy_House_Mean = eachHouse_perMeanEnergy[['EnergyProduction']]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "k_Energy_House_Mean_array = k_Energy_House_Mean.values"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(500, 1)"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "k_Energy_House_Mean_array.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "test_X = test_df[['Daylight']].values\n",
+    "test_Y = test_df[['EnergyProduction']].values"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.PathCollection at 0x7fa7cbd2c750>"
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.scatter(test_X, test_Y, color='blue')\n",
+    "plt.scatter(test_X, lr.predict(test_X), color='black')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    " sim_Y = k_Energy_House_Mean_array * lr.predict(test_X)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.PathCollection at 0x7fa7cbfc9a50>"
+      ]
+     },
+     "execution_count": 24,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.scatter(test_X, lr.predict(test_X), color = 'black') \n",
+    "plt.scatter(test_X, sim_Y, color = 'red') \n",
+    "plt.scatter(test_X, test_Y, color='blue')\n",
+    "# ばらつき具合は、Houseごとの係数を考慮することで表現できている。\n",
+    "# 全体的に、発電量が小さい。北半球6月なら、太陽の角度が大きいことを考慮できていないため？"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>ID</th>\n",
+       "      <th>Label</th>\n",
+       "      <th>House</th>\n",
+       "      <th>Year</th>\n",
+       "      <th>Month</th>\n",
+       "      <th>Temperature</th>\n",
+       "      <th>Daylight</th>\n",
+       "      <th>EnergyProduction</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>495</td>\n",
+       "      <td>11903</td>\n",
+       "      <td>23</td>\n",
+       "      <td>496</td>\n",
+       "      <td>2013</td>\n",
+       "      <td>6</td>\n",
+       "      <td>19.3</td>\n",
+       "      <td>125.9</td>\n",
+       "      <td>483</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>496</td>\n",
+       "      <td>11927</td>\n",
+       "      <td>23</td>\n",
+       "      <td>497</td>\n",
+       "      <td>2013</td>\n",
+       "      <td>6</td>\n",
+       "      <td>21.9</td>\n",
+       "      <td>122.4</td>\n",
+       "      <td>628</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>497</td>\n",
+       "      <td>11951</td>\n",
+       "      <td>23</td>\n",
+       "      <td>498</td>\n",
+       "      <td>2013</td>\n",
+       "      <td>6</td>\n",
+       "      <td>22.8</td>\n",
+       "      <td>127.2</td>\n",
+       "      <td>673</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>498</td>\n",
+       "      <td>11975</td>\n",
+       "      <td>23</td>\n",
+       "      <td>499</td>\n",
+       "      <td>2013</td>\n",
+       "      <td>6</td>\n",
+       "      <td>21.9</td>\n",
+       "      <td>126.8</td>\n",
+       "      <td>735</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>499</td>\n",
+       "      <td>11999</td>\n",
+       "      <td>23</td>\n",
+       "      <td>500</td>\n",
+       "      <td>2013</td>\n",
+       "      <td>6</td>\n",
+       "      <td>22.7</td>\n",
+       "      <td>122.9</td>\n",
+       "      <td>586</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        ID  Label  House  Year  Month  Temperature  Daylight  EnergyProduction\n",
+       "495  11903     23    496  2013      6         19.3     125.9               483\n",
+       "496  11927     23    497  2013      6         21.9     122.4               628\n",
+       "497  11951     23    498  2013      6         22.8     127.2               673\n",
+       "498  11975     23    499  2013      6         21.9     126.8               735\n",
+       "499  11999     23    500  2013      6         22.7     122.9               586"
+      ]
+     },
+     "execution_count": 25,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "test_df.tail()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# RandomForestを使い、Month, Daylight, House, TemperatureからEnergyProductionを推測してみる。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from sklearn.ensemble import RandomForestClassifier\n",
+    "model = RandomForestClassifier(max_depth=1000)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "X = train_df.drop(['ID', 'Label', 'Year'], axis=1)\n",
+    "test_X = test_df.drop(['ID', 'Label', 'Year'], axis=1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/saber/opt/anaconda3/lib/python3.7/site-packages/sklearn/ensemble/forest.py:245: FutureWarning: The default value of n_estimators will change from 10 in version 0.20 to 100 in 0.22.\n",
+      "  \"10 in version 0.20 to 100 in 0.22.\", FutureWarning)\n",
+      "/Users/saber/opt/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:1: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().\n",
+      "  \"\"\"Entry point for launching an IPython kernel.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "0.08"
+      ]
+     },
+     "execution_count": 29,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "model.fit(X,Y)\n",
+    "predicted = model.predict(test_X)\n",
+    "model.score(test_X, test_Y)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "1.0"
+      ]
+     },
+     "execution_count": 47,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "model.score(test_X, predicted)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.PathCollection at 0x7fa7c7b66150>"
+      ]
+     },
+     "execution_count": 30,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.scatter(test_X[['House']].values, predicted, color='red')\n",
+    "plt.scatter(test_X[['House']].values, test_Y, color='blue')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.PathCollection at 0x7fa7cbce7750>"
+      ]
+     },
+     "execution_count": 31,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.scatter(test_X[['Daylight']].values, predicted, color='red')\n",
+    "plt.scatter(test_X[['Daylight']].values, test_Y, color='blue')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# RandomForestを使い、Month, Daylight, HouseからEnergyProductionを推測してみる。（Temperatureを除いた場合）\n",
+    "X_hdm = train_df.drop(['ID', 'Label', 'Year', 'Temperature'], axis=1)\n",
+    "test_X_hdm = test_df.drop(['ID', 'Label', 'Year', 'Temperature'], axis=1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/saber/opt/anaconda3/lib/python3.7/site-packages/sklearn/ensemble/forest.py:245: FutureWarning: The default value of n_estimators will change from 10 in version 0.20 to 100 in 0.22.\n",
+      "  \"10 in version 0.20 to 100 in 0.22.\", FutureWarning)\n",
+      "/Users/saber/opt/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:2: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().\n",
+      "  \n"
+     ]
+    }
+   ],
+   "source": [
+    "model_hdm = RandomForestClassifier(max_depth=1000)\n",
+    "model_hdm.fit(X_hdm,Y)\n",
+    "predicted_hdm = model_hdm.predict(test_X_hdm)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.PathCollection at 0x7fa7cc179450>"
+      ]
+     },
+     "execution_count": 34,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.scatter(test_X_hdm[['House']].values, predicted, color='red')\n",
+    "plt.scatter(test_X_hdm[['House']].values, test_Y, color='blue')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.PathCollection at 0x7fa7b5172450>"
+      ]
+     },
+     "execution_count": 35,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.scatter(test_X_hdm[['Daylight']].values, predicted, color='red')\n",
+    "plt.scatter(test_X_hdm[['Daylight']].values, test_Y, color='blue')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.146"
+      ]
+     },
+     "execution_count": 36,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Temperatureの影響があるかは、はっきりしない。\n",
+    "model_hdm.score(test_X_hdm, test_Y)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/saber/opt/anaconda3/lib/python3.7/site-packages/sklearn/utils/validation.py:724: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().\n",
+      "  y = column_or_1d(y, warn=True)\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0,\n",
+       "    decision_function_shape='ovr', degree=3, gamma='scale', kernel='rbf',\n",
+       "    max_iter=-1, probability=False, random_state=None, shrinking=True,\n",
+       "    tol=0.001, verbose=False)"
+      ]
+     },
+     "execution_count": 39,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# SVCも試してみる。\n",
+    "from sklearn.svm import SVC\n",
+    "model_svc = SVC(gamma='scale')\n",
+    "model_svc.fit(X, Y)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "test_Y_svc = model_svc.predict(test_X)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.PathCollection at 0x7fa7b53d8d90>"
+      ]
+     },
+     "execution_count": 41,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.scatter(test_X[['House']].values, test_Y_svc, color='red')\n",
+    "plt.scatter(test_X[['House']].values, test_Y, color='blue')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.0"
+      ]
+     },
+     "execution_count": 42,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "model_svc.score(test_X, test_Y)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/saber/opt/anaconda3/lib/python3.7/site-packages/sklearn/utils/validation.py:724: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().\n",
+      "  y = column_or_1d(y, warn=True)\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0,\n",
+       "    decision_function_shape='ovr', degree=3, gamma='scale', kernel='rbf',\n",
+       "    max_iter=-1, probability=False, random_state=None, shrinking=True,\n",
+       "    tol=0.001, verbose=False)"
+      ]
+     },
+     "execution_count": 43,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "model_svc_hdm = SVC(gamma='scale')\n",
+    "model_svc_hdm.fit(X_hdm, Y)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.PathCollection at 0x7fa7cbfc9610>"
+      ]
+     },
+     "execution_count": 48,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# RandomForestを使い、Month, Daylight, HouseからEnergyProductionを推測したものが、この中では一番よかった。\n",
+    "plt.scatter(test_X[['House']].values, predicted, color='red')\n",
+    "plt.scatter(test_X[['House']].values, test_Y, color='blue')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "solution = pd.DataFrame({'House': test_df['House'], 'EnergyProduction': predicted})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<bound method DataFrame.info of      House  EnergyProduction\n",
+       "0        1               794\n",
+       "1        2               605\n",
+       "2        3               714\n",
+       "3        4               549\n",
+       "4        5               549\n",
+       "..     ...               ...\n",
+       "495    496               486\n",
+       "496    497               714\n",
+       "497    498               645\n",
+       "498    499               714\n",
+       "499    500               605\n",
+       "\n",
+       "[500 rows x 2 columns]>"
+      ]
+     },
+     "execution_count": 55,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "solution.info"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "solution.to_csv(\"predicted_energy_production.csv\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/challenge1/analysis/shino/predicted_energy_production.csv b/challenge1/analysis/shino/predicted_energy_production.csv
new file mode 100644
index 000000000..0eb120308
--- /dev/null
+++ b/challenge1/analysis/shino/predicted_energy_production.csv
@@ -0,0 +1,501 @@
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diff --git a/challenge1/analysis/shino/test.py b/challenge1/analysis/shino/test.py
new file mode 100644
index 000000000..b142986b4
--- /dev/null
+++ b/challenge1/analysis/shino/test.py
@@ -0,0 +1,35 @@
+import numpy as np
+import pandas as pd
+import matplotlib.pyplot as plt
+import seaborn as sns
+
+train_df = pd.read_csv('../../data/training_dataset_500.csv')
+test_df = pd.read_csv('../../data/test_dataset_500.csv')
+
+from sklearn.ensemble import RandomForestClassifier
+
+model = RandomForestClassifier(max_depth=1000)
+
+X = train_df.drop(['ID', 'Label', 'Year'], axis=1)
+test_X = test_df.drop(['ID', 'Label', 'Year'], axis=1)
+Y = train_df[['EnergyProduction']].values
+test_Y = test_df[['EnergyProduction']].values
+
+model.fit(X,Y)
+predicted = model.predict(test_X)
+model.score(test_X, test_Y)
+
+plt.scatter(test_X[['House']].values, predicted, color='red')
+plt.scatter(test_X[['House']].values, test_Y, color='blue')
+
+X_hdm = train_df.drop(['ID', 'Label', 'Year', 'Temperature'], axis=1)
+test_X_hdm = test_df.drop(['ID', 'Label', 'Year', 'Temperature'], axis=1)
+
+model_hdm = RandomForestClassifier(max_depth=1000)
+model_hdm.fit(X_hdm,Y)
+predicted_hdm = model_hdm.predict(test_X_hdm)
+
+plt.scatter(test_X_hdm[['House']].values, predicted, color='red')
+plt.scatter(test_X_hdm[['House']].values, test_Y, color='blue')
+
+model_hdm.score(test_X_hdm, test_Y)
\ No newline at end of file