From e8d40cc867a429f9f5344b22aa10439bcd2adf7f Mon Sep 17 00:00:00 2001
From: Patricia Zapata Blanco <patriciazapatablanco@gmail.com>
Date: Thu, 19 Oct 2023 20:50:54 +0200
Subject: [PATCH]  Completed visualization challenge

---
 your-code/challenge-1.ipynb | 623 +++++++++++++++++++++++++++++-
 your-code/challenge-2.ipynb | 748 +++++++++++++++++++++++++++++++++---
 2 files changed, 1307 insertions(+), 64 deletions(-)

diff --git a/your-code/challenge-1.ipynb b/your-code/challenge-1.ipynb
index 9df5e53..cfb6642 100644
--- a/your-code/challenge-1.ipynb
+++ b/your-code/challenge-1.ipynb
@@ -11,7 +11,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 20,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -35,11 +35,379 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 21,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# your code here\n"
+    "fitbit = pd.read_csv('https://raw.githubusercontent.com/Ironhack-data-bcn-oct-2023/lectures/main/faq-and-examples/lab-matplotlib-seaborn/data/Fitbit2.csv')\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "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>Date</th>\n",
+       "      <th>Calorie burned</th>\n",
+       "      <th>Steps</th>\n",
+       "      <th>Distance</th>\n",
+       "      <th>Floors</th>\n",
+       "      <th>Minutes Sedentary</th>\n",
+       "      <th>Minutes Lightly Active</th>\n",
+       "      <th>Minutes Fairly Active</th>\n",
+       "      <th>Minutes Very Active</th>\n",
+       "      <th>Activity Calories</th>\n",
+       "      <th>...</th>\n",
+       "      <th>Distance_miles</th>\n",
+       "      <th>Days</th>\n",
+       "      <th>Days_encoded</th>\n",
+       "      <th>Work_or_Weekend</th>\n",
+       "      <th>Hours Sleep</th>\n",
+       "      <th>Sleep efficiency</th>\n",
+       "      <th>Yesterday_sleep</th>\n",
+       "      <th>Yesterday_sleep_efficiency</th>\n",
+       "      <th>Months</th>\n",
+       "      <th>Months_encoded</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2015-05-08</td>\n",
+       "      <td>1934</td>\n",
+       "      <td>905</td>\n",
+       "      <td>0.65</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1.355</td>\n",
+       "      <td>46</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1680</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.403891</td>\n",
+       "      <td>Friday</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>6.400000</td>\n",
+       "      <td>92.086331</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>May</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2015-05-09</td>\n",
+       "      <td>3631</td>\n",
+       "      <td>18925</td>\n",
+       "      <td>14.11</td>\n",
+       "      <td>4</td>\n",
+       "      <td>611.000</td>\n",
+       "      <td>316</td>\n",
+       "      <td>61</td>\n",
+       "      <td>60</td>\n",
+       "      <td>2248</td>\n",
+       "      <td>...</td>\n",
+       "      <td>8.767545</td>\n",
+       "      <td>Saturday</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>7.566667</td>\n",
+       "      <td>92.464358</td>\n",
+       "      <td>6.400000</td>\n",
+       "      <td>92.086331</td>\n",
+       "      <td>May</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2015-05-10</td>\n",
+       "      <td>3204</td>\n",
+       "      <td>14228</td>\n",
+       "      <td>10.57</td>\n",
+       "      <td>1</td>\n",
+       "      <td>602.000</td>\n",
+       "      <td>226</td>\n",
+       "      <td>14</td>\n",
+       "      <td>77</td>\n",
+       "      <td>1719</td>\n",
+       "      <td>...</td>\n",
+       "      <td>6.567891</td>\n",
+       "      <td>Sunday</td>\n",
+       "      <td>6.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>6.450000</td>\n",
+       "      <td>88.761468</td>\n",
+       "      <td>7.566667</td>\n",
+       "      <td>92.464358</td>\n",
+       "      <td>May</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2015-05-11</td>\n",
+       "      <td>2673</td>\n",
+       "      <td>6756</td>\n",
+       "      <td>5.02</td>\n",
+       "      <td>8</td>\n",
+       "      <td>749.000</td>\n",
+       "      <td>190</td>\n",
+       "      <td>23</td>\n",
+       "      <td>4</td>\n",
+       "      <td>9620</td>\n",
+       "      <td>...</td>\n",
+       "      <td>3.119282</td>\n",
+       "      <td>Monday</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>5.183333</td>\n",
+       "      <td>88.857143</td>\n",
+       "      <td>6.450000</td>\n",
+       "      <td>88.761468</td>\n",
+       "      <td>May</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2015-05-12</td>\n",
+       "      <td>2495</td>\n",
+       "      <td>502</td>\n",
+       "      <td>3.73</td>\n",
+       "      <td>1</td>\n",
+       "      <td>876.000</td>\n",
+       "      <td>171</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>7360</td>\n",
+       "      <td>...</td>\n",
+       "      <td>2.317714</td>\n",
+       "      <td>Tuesday</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>6.783333</td>\n",
+       "      <td>82.892057</td>\n",
+       "      <td>5.183333</td>\n",
+       "      <td>88.857143</td>\n",
+       "      <td>May</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>2015-05-13</td>\n",
+       "      <td>276</td>\n",
+       "      <td>779</td>\n",
+       "      <td>5.79</td>\n",
+       "      <td>15</td>\n",
+       "      <td>726.000</td>\n",
+       "      <td>172</td>\n",
+       "      <td>34</td>\n",
+       "      <td>18</td>\n",
+       "      <td>1094</td>\n",
+       "      <td>...</td>\n",
+       "      <td>3.597738</td>\n",
+       "      <td>Wednesday</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>6.750000</td>\n",
+       "      <td>88.621444</td>\n",
+       "      <td>6.783333</td>\n",
+       "      <td>82.892057</td>\n",
+       "      <td>May</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>2015-05-14</td>\n",
+       "      <td>2687</td>\n",
+       "      <td>5614</td>\n",
+       "      <td>4.17</td>\n",
+       "      <td>2</td>\n",
+       "      <td>782.000</td>\n",
+       "      <td>216</td>\n",
+       "      <td>13</td>\n",
+       "      <td>1</td>\n",
+       "      <td>9830</td>\n",
+       "      <td>...</td>\n",
+       "      <td>2.591117</td>\n",
+       "      <td>Thursday</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>6.350000</td>\n",
+       "      <td>91.807229</td>\n",
+       "      <td>6.750000</td>\n",
+       "      <td>88.621444</td>\n",
+       "      <td>May</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>2015-05-15</td>\n",
+       "      <td>2793</td>\n",
+       "      <td>8169</td>\n",
+       "      <td>6.07</td>\n",
+       "      <td>14</td>\n",
+       "      <td>801.000</td>\n",
+       "      <td>218</td>\n",
+       "      <td>8</td>\n",
+       "      <td>7</td>\n",
+       "      <td>1092</td>\n",
+       "      <td>...</td>\n",
+       "      <td>3.771722</td>\n",
+       "      <td>Friday</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>4.483333</td>\n",
+       "      <td>87.908497</td>\n",
+       "      <td>6.350000</td>\n",
+       "      <td>91.807229</td>\n",
+       "      <td>May</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>2015-05-16</td>\n",
+       "      <td>4061</td>\n",
+       "      <td>19971</td>\n",
+       "      <td>14.84</td>\n",
+       "      <td>18</td>\n",
+       "      <td>532.000</td>\n",
+       "      <td>247</td>\n",
+       "      <td>101</td>\n",
+       "      <td>118</td>\n",
+       "      <td>27</td>\n",
+       "      <td>...</td>\n",
+       "      <td>9.221146</td>\n",
+       "      <td>Saturday</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>7.533333</td>\n",
+       "      <td>89.151874</td>\n",
+       "      <td>4.483333</td>\n",
+       "      <td>87.908497</td>\n",
+       "      <td>May</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>2015-05-17</td>\n",
+       "      <td>3349</td>\n",
+       "      <td>852</td>\n",
+       "      <td>6.33</td>\n",
+       "      <td>12</td>\n",
+       "      <td>606.000</td>\n",
+       "      <td>186</td>\n",
+       "      <td>46</td>\n",
+       "      <td>73</td>\n",
+       "      <td>1766</td>\n",
+       "      <td>...</td>\n",
+       "      <td>3.933278</td>\n",
+       "      <td>Sunday</td>\n",
+       "      <td>6.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>4.483333</td>\n",
+       "      <td>92.439863</td>\n",
+       "      <td>7.533333</td>\n",
+       "      <td>89.151874</td>\n",
+       "      <td>May</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>10 rows × 24 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "         Date  Calorie burned  Steps  Distance  Floors  Minutes Sedentary  \\\n",
+       "0  2015-05-08            1934    905      0.65       0              1.355   \n",
+       "1  2015-05-09            3631  18925     14.11       4            611.000   \n",
+       "2  2015-05-10            3204  14228     10.57       1            602.000   \n",
+       "3  2015-05-11            2673   6756      5.02       8            749.000   \n",
+       "4  2015-05-12            2495    502      3.73       1            876.000   \n",
+       "5  2015-05-13             276    779      5.79      15            726.000   \n",
+       "6  2015-05-14            2687   5614      4.17       2            782.000   \n",
+       "7  2015-05-15            2793   8169      6.07      14            801.000   \n",
+       "8  2015-05-16            4061  19971     14.84      18            532.000   \n",
+       "9  2015-05-17            3349    852      6.33      12            606.000   \n",
+       "\n",
+       "   Minutes Lightly Active  Minutes Fairly Active  Minutes Very Active  \\\n",
+       "0                      46                      0                    0   \n",
+       "1                     316                     61                   60   \n",
+       "2                     226                     14                   77   \n",
+       "3                     190                     23                    4   \n",
+       "4                     171                      0                    0   \n",
+       "5                     172                     34                   18   \n",
+       "6                     216                     13                    1   \n",
+       "7                     218                      8                    7   \n",
+       "8                     247                    101                  118   \n",
+       "9                     186                     46                   73   \n",
+       "\n",
+       "   Activity Calories  ...  Distance_miles       Days  Days_encoded  \\\n",
+       "0               1680  ...        0.403891     Friday           4.0   \n",
+       "1               2248  ...        8.767545   Saturday           5.0   \n",
+       "2               1719  ...        6.567891     Sunday           6.0   \n",
+       "3               9620  ...        3.119282     Monday           0.0   \n",
+       "4               7360  ...        2.317714    Tuesday           1.0   \n",
+       "5               1094  ...        3.597738  Wednesday           2.0   \n",
+       "6               9830  ...        2.591117   Thursday           3.0   \n",
+       "7               1092  ...        3.771722     Friday           4.0   \n",
+       "8                 27  ...        9.221146   Saturday           5.0   \n",
+       "9               1766  ...        3.933278     Sunday           6.0   \n",
+       "\n",
+       "   Work_or_Weekend  Hours Sleep Sleep efficiency  Yesterday_sleep  \\\n",
+       "0                1     6.400000        92.086331         0.000000   \n",
+       "1                0     7.566667        92.464358         6.400000   \n",
+       "2                0     6.450000        88.761468         7.566667   \n",
+       "3                1     5.183333        88.857143         6.450000   \n",
+       "4                1     6.783333        82.892057         5.183333   \n",
+       "5                1     6.750000        88.621444         6.783333   \n",
+       "6                1     6.350000        91.807229         6.750000   \n",
+       "7                1     4.483333        87.908497         6.350000   \n",
+       "8                0     7.533333        89.151874         4.483333   \n",
+       "9                0     4.483333        92.439863         7.533333   \n",
+       "\n",
+       "   Yesterday_sleep_efficiency  Months  Months_encoded  \n",
+       "0                    0.000000     May               5  \n",
+       "1                   92.086331     May               5  \n",
+       "2                   92.464358     May               5  \n",
+       "3                   88.761468     May               5  \n",
+       "4                   88.857143     May               5  \n",
+       "5                   82.892057     May               5  \n",
+       "6                   88.621444     May               5  \n",
+       "7                   91.807229     May               5  \n",
+       "8                   87.908497     May               5  \n",
+       "9                   89.151874     May               5  \n",
+       "\n",
+       "[10 rows x 24 columns]"
+      ]
+     },
+     "execution_count": 39,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "fitbit.head(10)"
    ]
   },
   {
@@ -59,20 +427,213 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 31,
+   "metadata": {
+    "scrolled": true
+   },
+   "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>Months_encoded</th>\n",
+       "      <th>Steps</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>5</td>\n",
+       "      <td>905</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>5</td>\n",
+       "      <td>18925</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>5</td>\n",
+       "      <td>14228</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>5</td>\n",
+       "      <td>6756</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>502</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>362</th>\n",
+       "      <td>5</td>\n",
+       "      <td>18588</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>363</th>\n",
+       "      <td>5</td>\n",
+       "      <td>16382</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>364</th>\n",
+       "      <td>5</td>\n",
+       "      <td>21913</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>365</th>\n",
+       "      <td>5</td>\n",
+       "      <td>19023</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>366</th>\n",
+       "      <td>5</td>\n",
+       "      <td>9526</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>367 rows × 2 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     Months_encoded  Steps\n",
+       "0                 5    905\n",
+       "1                 5  18925\n",
+       "2                 5  14228\n",
+       "3                 5   6756\n",
+       "4                 5    502\n",
+       "..              ...    ...\n",
+       "362               5  18588\n",
+       "363               5  16382\n",
+       "364               5  21913\n",
+       "365               5  19023\n",
+       "366               5   9526\n",
+       "\n",
+       "[367 rows x 2 columns]"
+      ]
+     },
+     "execution_count": 31,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "fitbit[[\"Months_encoded\", \"Steps\"]]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\Usuario\\AppData\\Local\\Temp\\ipykernel_14708\\1297963010.py:1: FutureWarning: \n",
+      "\n",
+      "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n",
+      "\n",
+      "  sns.barplot(x=fitbit[\"Months_encoded\"], y=fitbit[\"Steps\"], palette=\"magma\"); #barplot with sns gives the mean by default\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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MjAxz2fbt21VZWamePXuaNbt27VJ5eblZk5qaqjZt2qhx48ZmTVpamt22U1NTFR4efrkODQAA1DMODU3FxcXKzMxUZmamJCk7O1uZmZk6efKkysvLde+992r//v1as2aNKioqlJubq9zcXJWVlUmS2rVrpwEDBmj06NHau3evPvnkE8XHx2v48OEKCQmRJD344INyd3dXbGysjhw5ojfffFOLFi3ShAkTzD7Gjh2rlJQUzZ8/X1988YWmT5+u/fv3Kz4+/op/TwAAgHNyaGjav3+/unbtqq5du0qSJkyYoK5duyoxMVGnTp3SO++8o3/961/q0qWLgoODzWn37t3mNtasWaO2bduqX79+GjRokHr37m33DCY/Pz9t27ZN2dnZ6t69u55++mklJibaPcupV69eWrt2rVasWKGwsDD9/e9/18aNG9WxY8cr980AAABOzaH3NN1+++0yDOMXxy80ViUgIEBr1669YE3nzp310UcfXbBm2LBhGjZs2EX3BwAAfpuc+p4mAAAAZ0FoAgAAsIDQBAAAYIHTP6cJAFB7nz/ydK3W+6nynN384bhn5dWgdr8ywlbNr9V6gLPhTBMAAIAFnGlyUoZhqKSkxJz39vaWzWZzYEcAgKsVv3OsITQ5qZKSEg0ZMsSc37Rpk3x8fBzYEQDgasXvHGu4PAcAAGABoQkAAMACQhMAAIAFhCYAAAALuBEcAK4wPqkE1E+EJgC4wvikElA/cXkOAADAAs40AQDqLS514koiNAEA6i0udeJK4vIcAACABYQmAAAACwhNAAAAFhCaAAAALCA0AQAAWEBoAgAAsIDQBAAAYAGhCQAAwAJCEwAAgAU8ERz4jXm2xzO1Wu+czkl+/5ufdft0udbyR8jz+1+s1XoA4EicaQIAALCA0AQAAGABl+cAJ2AzXHTdd53t5gEAzoXQBDgBm2yyGfxzBABnxuU5AAAAC/jTFrVmGIZKSkrMeW9vb9lsNgd2BEhuclF0ZXe7eQCoC4Qm1FpJSYmGDBlizm/atEk+Pj6XZV8Dm8fXel2jQYV0w//m7+2YIFvlpf8iff/k0lr3gCvHJpvc+dEG4DLg8hwAAIAFhCYAAAALHBqadu3apcGDByskJEQ2m00bN260GzcMQ4mJiQoODpaXl5ciIiJ0/Phxu5rTp08rJiZGvr6+8vf3V2xsrIqLi+1qDh48qD59+sjT01OhoaGaM2dOtV7eeusttW3bVp6enurUqZPee++9Oj9eAABQfzk0NJWUlCgsLEzLli2rcXzOnDlavHixkpKStGfPHnl7eysyMlJnz541a2JiYnTkyBGlpqZq8+bN2rVrl8aMGWOOFxUVqX///mrRooUyMjI0d+5cTZ8+XStWrDBrdu/erQceeECxsbH67LPPFB0drejoaB0+fPjyHTwAAKhXHHq35MCBAzVw4MAaxwzD0MKFCzVlyhTzZuPXXntNgYGB2rhxo4YPH65jx44pJSVF+/btU48ePSRJS5Ys0aBBgzRv3jyFhIRozZo1Kisr08qVK+Xu7q4OHTooMzNTCxYsMMPVokWLNGDAACUkJEiSZs2apdTUVC1dulRJSUlX4DsBAACcndPe05Sdna3c3FxFRESYy/z8/NSzZ0+lp6dLktLT0+Xv728GJkmKiIhQgwYNtGfPHrOmb9++cnd3N2siIyOVlZWlM2fOmDXn76eqpmo/NSktLVVRUZHdBAAArl5OG5pyc3MlSYGBgXbLAwMDzbHc3Fw1a9bMbtzV1VUBAQF2NTVt4/x9/FJN1XhNZs+eLT8/P3MKDQ291EMEAAD1iNOGJmc3efJkFRYWmlNOTo6jWwIAAJeR04amoKAgSVJeXp7d8ry8PHMsKChI+fn5duPnzp3T6dOn7Wpq2sb5+/ilmqrxmnh4eMjX19duAgAAVy+nfWxuq1atFBQUpLS0NHXp0kXSfz8Jt2fPHj3++OOSpPDwcBUUFCgjI0Pdu//3tQnbt29XZWWlevbsadY8++yzKi8vl5ubmyQpNTVVbdq0UePGjc2atLQ0jRs3ztx/amqqwsPDf9UxNPb7Xa3XdXGxKazrdeZ8y+bdVVFhXPJ2zhR+WeseAPx2edpc9Px1He3mAUdz9Ou7HBqaiouLdeLECXM+OztbmZmZCggIUPPmzTVu3Dg999xzuvHGG9WqVStNnTpVISEhio6OliS1a9dOAwYM0OjRo5WUlKTy8nLFx8dr+PDhCgkJkSQ9+OCDmjFjhmJjYzVp0iQdPnxYixYt0ssvv2zud+zYsbrttts0f/58RUVFad26ddq/f7/dYwkA4LfEZrPJy+a0f1fjN+pKvr6rJg79F7F//37dcccd5vyECRMkSSNHjlRycrImTpyokpISjRkzRgUFBerdu7dSUlLk6elprrNmzRrFx8erX79+atCggYYOHarFixeb435+ftq2bZvi4uLUvXt3NW3aVImJiXbPcurVq5fWrl2rKVOm6E9/+pNuvPFGbdy4UR07/u+vLAAA8Nvm0NB0++23yzB++ZKTzWbTzJkzNXPmzF+sCQgI0Nq1ay+4n86dO+ujjz66YM2wYcM0bNiwCzcMAAB+s5z2RnAAAABnwgVrAAAuI0ffvIy6Q2gCAOAycvTNy6g7XJ4DAACwgNAEAABgAZfnAAC4SpxJWVCr9UrOltvNF3ywTOWebrXaVuMBE2q1Xn3AmSYAAAALCE0AAAAWEJoAAAAsIDQBAABYQGgCAACwgNAEAABgAY8cAIBa2HLXM7Ve96xxzm5+6wPT5Wm79B/HUe+8WOsenEnO1HG1XrfkXIXd/L+enyxvV5dL3k7orIW17gG/HZxpAgAAsIDQBAAAYAGhCQAAwAJCEwAAgAWEJgAAAAv49BzU4droWq1na2Ao8Hf/m7+lXYyMSluttnXk1MZarQcAwJXCmSYAAAALCE0AAAAWEJoAAAAsqLPQVFBQUFebAgAAcDq1Ck0vvfSS3nzzTXP+vvvuU5MmTXTttdfq888/r7PmAAAAnEWtQlNSUpJCQ0MlSampqUpNTdX777+vgQMHKiEhoU4bBAAAcAa1euRAbm6uGZo2b96s++67T/3791fLli3Vs2fPOm0QAADAGdTqTFPjxo2Vk5MjSUpJSVFERIQkyTAMVVRUXGhVAACAeqlWZ5ruuecePfjgg7rxxhv1/fffa+DAgZKkzz77TK1bt67TBgEAAJxBrULTyy+/rJYtWyonJ0dz5syRj4+PJOm7777TE088UacNAgCAq0fRF29evOgXlPxYajf/w5dvq7KhxyVvx7ft/bXaf61Ck5ubm/74xz9WWz5+/PhaNQEAAODsav3uuaysLC1ZskTHjh2TJLVr105PPvmk2rRpU2fNAQAAOIta3Qj+j3/8Qx07dlRGRobCwsIUFhamAwcOqGPHjvrHP/5R1z0CAAA4XK3ONE2cOFGTJ0/WzJkz7ZZPmzZNEydO1NChQ+ukOQAAAGdRq9D03XffacSIEdWW/+EPf9DcuXN/dVMAADiTf/9lcq3XLSk7Zzf/n1Uz9JP7pf/6veb/Zte6B9SNWl2eu/322/XRRx9VW/7xxx+rT58+v7opAAAAZ1Or0HTXXXdp0qRJio+P1+uvv67XX39d8fHxeuaZZ3T33XfrnXfeMadfo6KiQlOnTlWrVq3k5eWlG264QbNmzZJhGGaNYRhKTExUcHCwvLy8FBERoePHj9tt5/Tp04qJiZGvr6/8/f0VGxur4uJiu5qDBw+qT58+8vT0VGhoqObMmfOrev+1KioMff7Zv8yposK4+ErAZeQiF/Uo7GpOLnJxdEsAcEXV6vJc1bOY/vznP+vPf/5zjWOSZLPZftUTwl966SUtX75cq1evVocOHbR//3498sgj8vPz01NPPSVJmjNnjhYvXqzVq1erVatWmjp1qiIjI3X06FF5enpKkmJiYvTdd98pNTVV5eXleuSRRzRmzBitXbtWklRUVKT+/fsrIiJCSUlJOnTokEaNGiV/f3+NGTOm1v3/WgQlOBObbHKt/QduAaDeq9VPwMrKyrruo0a7d+/WkCFDFBUVJUlq2bKl3njjDe3du1fSf88yLVy4UFOmTNGQIUMkSa+99poCAwO1ceNGDR8+XMeOHVNKSor27dunHj16SJKWLFmiQYMGad68eQoJCdGaNWtUVlamlStXyt3dXR06dFBmZqYWLFjg0NAEAACcR60uz53v7NmzddFHjXr16qW0tDR9+eWXkqTPP/9cH3/8sfnaluzsbOXm5prvvpMkPz8/9ezZU+np6ZKk9PR0+fv7m4FJkiIiItSgQQPt2bPHrOnbt6/c3d3NmsjISGVlZenMmTM19lZaWqqioiK7CQAAXL1qFZoqKio0a9YsXXvttfLx8dE///lPSdLUqVP16quv1llzzzzzjIYPH662bdvKzc1NXbt21bhx4xQTEyNJys3NlSQFBgbarRcYGGiO5ebmqlmzZnbjrq6uCggIsKupaRvn7+PnZs+eLT8/P3MKDQ39lUcLAACcWa1C0/PPP6/k5GTNmTPH7uxMx44d9de//rXOmlu/fr3WrFmjtWvX6sCBA1q9erXmzZun1atX19k+amvy5MkqLCw0p5ycHEe3BAAALqNa3dP02muvacWKFerXr58ee+wxc3lYWJi++OKLOmsuISHBPNskSZ06ddI333yj2bNna+TIkQoKCpIk5eXlKTg42FwvLy9PXbp0kSQFBQUpPz/fbrvnzp3T6dOnzfWDgoKUl5dnV1M1X1Xzcx4eHvLwuPSXBAIAgPqpVmeaTp06pdatW1dbXllZqfLy8l/dVJUff/xRDRrYt+ji4mLeiN6qVSsFBQUpLS3NHC8qKtKePXsUHh4uSQoPD1dBQYEyMjLMmu3bt6uyslI9e/Y0a3bt2mXXe2pqqtq0aaPGjRvX2fEAAID6q1ahqX379jU+3PLvf/+7unbt+qubqjJ48GA9//zz2rJli77++mtt2LBBCxYs0N133y3pv480GDdunJ577jm98847OnTokEaMGKGQkBBFR0dL+u+LhAcMGKDRo0dr7969+uSTTxQfH6/hw4crJCREkvTggw/K3d1dsbGxOnLkiN58800tWrRIEyZMqLNjAQAA9VutLs8lJiZq5MiROnXqlCorK/X2228rKytLr732mjZv3lxnzS1ZskRTp07VE088ofz8fIWEhOj//u//lJiYaNZMnDhRJSUlGjNmjAoKCtS7d2+lpKSYz2iSpDVr1ig+Pl79+vVTgwYNNHToUC1evNgc9/Pz07Zt2xQXF6fu3buradOmSkxM5HEDAADAVKvQNGTIEL377ruaOXOmvL29lZiYqG7duundd9/V//t//6/OmmvUqJEWLlyohQsX/mKNzWbTzJkzq708+HwBAQHmgyx/SefOnWs8e4arQGUDuX31O7t5AAAuVa0f79unTx+lpqbWZS/AZWGTTarklR8AgF+nVn9yX3/99fr++++rLS8oKND111//q5sCAABwNrUKTV9//XWN75QrLS3VqVOnfnVTAAAAzuaSLs+988475tdbt26Vn5+fOV9RUaG0tDS1bNmyzpoDAABwFpcUmqo+xm+z2TRy5Ei7MTc3N7Vs2VLz58+vs+YAAACcxSWFpvMfKrlv3z41bdr0sjQFAADgbC4pNKWnp+v7779Xdna2uey1117TtGnTVFJSoujoaC1ZsoTXi/xGGJVS3pc+dvMAgPqnoYerVj/Z324e1V3Sd2XGjBm64447dOedd0qSDh06pNjYWD388MNq166d5s6dq5CQEE2fPv1y9AqnYyMoAXCohi4NtOzm9nbzuHQ2m03enm6ObsPpXdL/XZ9//rn69etnzq9bt049e/bUK6+8ogkTJmjx4sVav359nTcJAEBNbDabvF1dzMlmszm6JVzFLik0nTlzRoGBgeb8zp07NXDgQHP+pptuUk5OTt11BwAA4CQuKTQFBgaa9zOVlZXpwIEDuuWWW8zxH374QW5unN4DAABXn0sKTYMGDdIzzzyjjz76SJMnT1bDhg3Vp08fc/zgwYO64YYb6rxJAAAAR7ukG8FnzZqle+65R7fddpt8fHy0evVqubu7m+MrV65U//79L7AFAACA+umSQlPTpk21a9cuFRYWysfHRy4u9i9Bfeutt+Tj4/MLawMAANRftXoQw/mvTzlfQEDAr2oGAADAWfH0KgC4wjzkoicadrWbB+D8CE0AcIXZbDZ58uMXuGQNvdz1+tyRdvNXEv9qAQBAvWCz2eTd0HGvaiM0AQBwGTV0c9Gr0d3s5lE/EZoAALiMbDabvN35dXs14M2GAAAAFhCaAAAALCA0AQAAWEBoAgAAsIDQBAAAYAGhCQAAwAJCEwAAgAWEJgAAAAsITQAAABYQmgAAACwgNAEAAFhAaAIAALCA0AQAAGABoQkAAMACQhMAAIAFTh+aTp06pT/84Q9q0qSJvLy81KlTJ+3fv98cNwxDiYmJCg4OlpeXlyIiInT8+HG7bZw+fVoxMTHy9fWVv7+/YmNjVVxcbFdz8OBB9enTR56engoNDdWcOXOuyPEBAID6walD05kzZ3TrrbfKzc1N77//vo4ePar58+ercePGZs2cOXO0ePFiJSUlac+ePfL29lZkZKTOnj1r1sTExOjIkSNKTU3V5s2btWvXLo0ZM8YcLyoqUv/+/dWiRQtlZGRo7ty5mj59ulasWHFFjxcAADgvV0c3cCEvvfSSQkNDtWrVKnNZq1atzK8Nw9DChQs1ZcoUDRkyRJL02muvKTAwUBs3btTw4cN17NgxpaSkaN++ferRo4ckacmSJRo0aJDmzZunkJAQrVmzRmVlZVq5cqXc3d3VoUMHZWZmasGCBXbhCgAA/HY59Zmmd955Rz169NCwYcPUrFkzde3aVa+88oo5np2drdzcXEVERJjL/Pz81LNnT6Wnp0uS0tPT5e/vbwYmSYqIiFCDBg20Z88es6Zv375yd3c3ayIjI5WVlaUzZ87U2FtpaamKiorsJgAAcPVy6tD0z3/+U8uXL9eNN96orVu36vHHH9dTTz2l1atXS5Jyc3MlSYGBgXbrBQYGmmO5ublq1qyZ3birq6sCAgLsamraxvn7+LnZs2fLz8/PnEJDQ3/l0QIAAGfm1KGpsrJS3bp10wsvvKCuXbtqzJgxGj16tJKSkhzdmiZPnqzCwkJzysnJcXRLAADgMnLq0BQcHKz27dvbLWvXrp1OnjwpSQoKCpIk5eXl2dXk5eWZY0FBQcrPz7cbP3funE6fPm1XU9M2zt/Hz3l4eMjX19duAgAAVy+nDk233nqrsrKy7JZ9+eWXatGihaT/3hQeFBSktLQ0c7yoqEh79uxReHi4JCk8PFwFBQXKyMgwa7Zv367Kykr17NnTrNm1a5fKy8vNmtTUVLVp08buk3oAAOC3y6lD0/jx4/Xpp5/qhRde0IkTJ7R27VqtWLFCcXFxkiSbzaZx48bpueee0zvvvKNDhw5pxIgRCgkJUXR0tKT/npkaMGCARo8erb179+qTTz5RfHy8hg8frpCQEEnSgw8+KHd3d8XGxurIkSN68803tWjRIk2YMMFRhw4AAJyMUz9y4KabbtKGDRs0efJkzZw5U61atdLChQsVExNj1kycOFElJSUaM2aMCgoK1Lt3b6WkpMjT09OsWbNmjeLj49WvXz81aNBAQ4cO1eLFi81xPz8/bdu2TXFxcerevbuaNm2qxMREHjcAAABMTh2aJOnOO+/UnXfe+YvjNptNM2fO1MyZM3+xJiAgQGvXrr3gfjp37qyPPvqo1n0CAICrm1NfngMAAHAWhCYAAAALCE0AAAAWEJoAAAAsIDQBAABYQGgCAACwgNAEAABgAaEJAADAAkITAACABYQmAAAACwhNAAAAFhCaAAAALCA0AQAAWEBoAgAAsIDQBAAAYAGhCQAAwAJCEwAAgAWEJgAAAAsITQAAABYQmgAAACwgNAEAAFhAaAIAALCA0AQAAGABoQkAAMACQhMAAIAFhCYAAAALCE0AAAAWEJoAAAAsIDQBAABYQGgCAACwgNAEAABgAaEJAADAAkITAACABYQmAAAACwhNAAAAFtSr0PTiiy/KZrNp3Lhx5rKzZ88qLi5OTZo0kY+Pj4YOHaq8vDy79U6ePKmoqCg1bNhQzZo1U0JCgs6dO2dXs2PHDnXr1k0eHh5q3bq1kpOTr8ARAQCA+qLehKZ9+/bpL3/5izp37my3fPz48Xr33Xf11ltvaefOnfr22291zz33mOMVFRWKiopSWVmZdu/erdWrVys5OVmJiYlmTXZ2tqKionTHHXcoMzNT48aN06OPPqqtW7deseMDAADOrV6EpuLiYsXExOiVV15R48aNzeWFhYV69dVXtWDBAv3+979X9+7dtWrVKu3evVuffvqpJGnbtm06evSoXn/9dXXp0kUDBw7UrFmztGzZMpWVlUmSkpKS1KpVK82fP1/t2rVTfHy87r33Xr388ssOOV4AAOB86kVoiouLU1RUlCIiIuyWZ2RkqLy83G5527Zt1bx5c6Wnp0uS0tPT1alTJwUGBpo1kZGRKioq0pEjR8yan287MjLS3EZNSktLVVRUZDcBAICrl6ujG7iYdevW6cCBA9q3b1+1sdzcXLm7u8vf399ueWBgoHJzc82a8wNT1XjV2IVqioqK9NNPP8nLy6vavmfPnq0ZM2bU+rgAAED94tRnmnJycjR27FitWbNGnp6ejm7HzuTJk1VYWGhOOTk5jm4JAABcRk4dmjIyMpSfn69u3brJ1dVVrq6u2rlzpxYvXixXV1cFBgaqrKxMBQUFduvl5eUpKChIkhQUFFTt03RV8xer8fX1rfEskyR5eHjI19fXbgIAAFcvpw5N/fr106FDh5SZmWlOPXr0UExMjPm1m5ub0tLSzHWysrJ08uRJhYeHS5LCw8N16NAh5efnmzWpqany9fVV+/btzZrzt1FVU7UNAAAAp76nqVGjRurYsaPdMm9vbzVp0sRcHhsbqwkTJiggIEC+vr568sknFR4erltuuUWS1L9/f7Vv314PPfSQ5syZo9zcXE2ZMkVxcXHy8PCQJD322GNaunSpJk6cqFGjRmn79u1av369tmzZcmUPGAAAOC2nDk1WvPzyy2rQoIGGDh2q0tJSRUZG6s9//rM57uLios2bN+vxxx9XeHi4vL29NXLkSM2cOdOsadWqlbZs2aLx48dr0aJFuu666/TXv/5VkZGRjjgkAADghOpdaNqxY4fdvKenp5YtW6Zly5b94jotWrTQe++9d8Ht3n777frss8/qokUAAHAVcup7mgAAAJwFoQkAAMACQhMAAIAFhCYAAAALCE0AAAAWEJoAAAAsIDQBAABYQGgCAACwgNAEAABgAaEJAADAAkITAACABYQmAAAACwhNAAAAFhCaAAAALCA0AQAAWEBoAgAAsIDQBAAAYAGhCQAAwAJCEwAAgAWEJgAAAAsITQAAABYQmgAAACwgNAEAAFhAaAIAALCA0AQAAGABoQkAAMACQhMAAIAFhCYAAAALCE0AAAAWEJoAAAAsIDQBAABYQGgCAACwgNAEAABgAaEJAADAAkITAACABYQmAAAAC5w+NM2ePVs33XSTGjVqpGbNmik6OlpZWVl2NWfPnlVcXJyaNGkiHx8fDR06VHl5eXY1J0+eVFRUlBo2bKhmzZopISFB586ds6vZsWOHunXrJg8PD7Vu3VrJycmX+/AAAEA94fShaefOnYqLi9Onn36q1NRUlZeXq3///iopKTFrxo8fr3fffVdvvfWWdu7cqW+//Vb33HOPOV5RUaGoqCiVlZVp9+7dWr16tZKTk5WYmGjWZGdnKyoqSnfccYcyMzM1btw4Pfroo9q6desVPV4AAOCcXB3dwMWkpKTYzScnJ6tZs2bKyMhQ3759VVhYqFdffVVr167V73//e0nSqlWr1K5dO3366ae65ZZbtG3bNh09elQffPCBAgMD1aVLF82aNUuTJk3S9OnT5e7urqSkJLVq1Urz58+XJLVr104ff/yxXn75ZUVGRl7x4wYAAM7F6c80/VxhYaEkKSAgQJKUkZGh8vJyRUREmDVt27ZV8+bNlZ6eLklKT09Xp06dFBgYaNZERkaqqKhIR44cMWvO30ZVTdU2fq60tFRFRUV2EwAAuHrVq9BUWVmpcePG6dZbb1XHjh0lSbm5uXJ3d5e/v79dbWBgoHJzc82a8wNT1XjV2IVqioqK9NNPP1XrZfbs2fLz8zOn0NDQOjlGAADgnOpVaIqLi9Phw4e1bt06R7eiyZMnq7Cw0JxycnIc3RIAALiMnP6epirx8fHavHmzdu3apeuuu85cHhQUpLKyMhUUFNidbcrLy1NQUJBZs3fvXrvtVX267vyan3/iLi8vT76+vvLy8qrWj4eHhzw8POrk2AAAgPNz+jNNhmEoPj5eGzZs0Pbt29WqVSu78e7du8vNzU1paWnmsqysLJ08eVLh4eGSpPDwcB06dEj5+flmTWpqqnx9fdW+fXuz5vxtVNVUbQMAAPy2Of2Zpri4OK1du1abNm1So0aNzHuQ/Pz85OXlJT8/P8XGxmrChAkKCAiQr6+vnnzySYWHh+uWW26RJPXv31/t27fXQw89pDlz5ig3N1dTpkxRXFycebboscce09KlSzVx4kSNGjVK27dv1/r167VlyxaHHTsAAHAeTn+mafny5SosLNTtt9+u4OBgc3rzzTfNmpdffll33nmnhg4dqr59+yooKEhvv/22Oe7i4qLNmzfLxcVF4eHh+sMf/qARI0Zo5syZZk2rVq20ZcsWpaamKiwsTPPnz9df//pXHjcAAAAk1YMzTYZhXLTG09NTy5Yt07Jly36xpkWLFnrvvfcuuJ3bb79dn3322SX3CAAArn5Of6YJAADAGRCaAAAALCA0AQAAWEBoAgAAsIDQBAAAYAGhCQAAwAJCEwAAgAWEJgAAAAsITQAAABYQmgAAACwgNAEAAFhAaAIAALCA0AQAAGABoQkAAMACQhMAAIAFhCYAAAALCE0AAAAWEJoAAAAsIDQBAABYQGgCAACwgNAEAABgAaEJAADAAkITAACABYQmAAAACwhNAAAAFhCaAAAALCA0AQAAWEBoAgAAsIDQBAAAYAGhCQAAwAJCEwAAgAWEJgAAAAsITQAAABYQmgAAACwgNAEAAFhAaPqZZcuWqWXLlvL09FTPnj21d+9eR7cEAACcAKHpPG+++aYmTJigadOm6cCBAwoLC1NkZKTy8/Md3RoAAHAwQtN5FixYoNGjR+uRRx5R+/btlZSUpIYNG2rlypWObg0AADiYq6MbcBZlZWXKyMjQ5MmTzWUNGjRQRESE0tPTq9WXlpaqtLTUnC8sLJQkFRUVmcsMo+IydmzN+f38korK8ivQyYVdrM9zlWVXqJNfdrEeyypKLzh+JVj5711aD/r86Zzz9/hjufP3KEnFZc7f5w+l9aDHnxzfo4eF/95FJWevQCcX5nKRPouKf7xCnVyoiaLzvvzv14ZhXHw9A4ZhGMapU6cMScbu3bvtlickJBg333xztfpp06YZkpiYmJiYmJiugiknJ+eiWYEzTbU0efJkTZgwwZyvrKzU6dOn1aRJE9lstjrZR1FRkUJDQ5WTkyNfX9862WZdqw89SvWjT3qsO/WhT3qsO/WhT3qsO3Xdp2EY+uGHHxQSEnLRWkLT/69p06ZycXFRXl6e3fK8vDwFBQVVq/fw8JCHh4fdMn9//8vSm6+vr1P/DyzVjx6l+tEnPdad+tAnPdad+tAnPdaduuzTz8/PUh03gv//3N3d1b17d6WlpZnLKisrlZaWpvDwcAd2BgAAnAFnms4zYcIEjRw5Uj169NDNN9+shQsXqqSkRI888oijWwMAAA5GaDrP/fffr3//+99KTExUbm6uunTpopSUFAUGBjqkHw8PD02bNq3aZUBnUh96lOpHn/RYd+pDn/RYd+pDn/RYdxzZp80wrHzGDgAA4LeNe5oAAAAsIDQBAABYQGgCAACwgNAEAABgAaHJCe3atUuDBw9WSEiIbDabNm7c6OiWqpk9e7ZuuukmNWrUSM2aNVN0dLSysrIc3Zad5cuXq3PnzuYD0MLDw/X+++87uq0LevHFF2Wz2TRu3DhHt2Jn+vTpstlsdlPbtm0d3VY1p06d0h/+8Ac1adJEXl5e6tSpk/bv3+/otuy0bNmy2vfSZrMpLi7O0a2ZKioqNHXqVLVq1UpeXl664YYbNGvWLGvv5rqCfvjhB40bN04tWrSQl5eXevXqpX379jm0p4v9/DYMQ4mJiQoODpaXl5ciIiJ0/Phxp+rx7bffVv/+/c03XGRmZl7R/i7WY3l5uSZNmqROnTrJ29tbISEhGjFihL799tvL3hehyQmVlJQoLCxMy5Ytc3Qrv2jnzp2Ki4vTp59+qtTUVJWXl6t///4qKSlxdGum6667Ti+++KIyMjK0f/9+/f73v9eQIUN05MgRR7dWo3379ukvf/mLOnfu7OhWatShQwd999135vTxxx87uiU7Z86c0a233io3Nze9//77Onr0qObPn6/GjRs7ujU7+/bts/s+pqamSpKGDRvm4M7+56WXXtLy5cu1dOlSHTt2TC+99JLmzJmjJUuWOLo1O48++qhSU1P1t7/9TYcOHVL//v0VERGhU6dOOayni/38njNnjhYvXqykpCTt2bNH3t7eioyM1NmzV+5FuxfrsaSkRL1799ZLL710xXqqqYdf6vHHH3/UgQMHNHXqVB04cEBvv/22srKydNddd13+xuriZbe4fCQZGzZscHQbF5Wfn29IMnbu3OnoVi6ocePGxl//+ldHt1HNDz/8YNx4441Gamqqcdtttxljx451dEt2pk2bZoSFhTm6jQuaNGmS0bt3b0e3ccnGjh1r3HDDDUZlZaWjWzFFRUUZo0aNslt2zz33GDExMQ7qqLoff/zRcHFxMTZv3my3vFu3bsazzz7roK7s/fznd2VlpREUFGTMnTvXXFZQUGB4eHgYb7zxhgM6vPDvmOzsbEOS8dlnn13Rnn7Oyu/BvXv3GpKMb7755rL2wpkm1InCwkJJUkBAgIM7qVlFRYXWrVunkpISp3wtTlxcnKKiohQREeHoVn7R8ePHFRISouuvv14xMTE6efKko1uy884776hHjx4aNmyYmjVrpq5du+qVV15xdFsXVFZWptdff12jRo2qsxd914VevXopLS1NX375pSTp888/18cff6yBAwc6uLP/OXfunCoqKuTp6Wm33MvLy+nOglbJzs5Wbm6u3b9zPz8/9ezZU+np6Q7srP4rLCyUzWa7bO+ArcITwfGrVVZWaty4cbr11lvVsWNHR7dj59ChQwoPD9fZs2fl4+OjDRs2qH379o5uy866det04MABh9+LcSE9e/ZUcnKy2rRpo++++04zZsxQnz59dPjwYTVq1MjR7UmS/vnPf2r58uWaMGGC/vSnP2nfvn166qmn5O7urpEjRzq6vRpt3LhRBQUFevjhhx3dip1nnnlGRUVFatu2rVxcXFRRUaHnn39eMTExjm7N1KhRI4WHh2vWrFlq166dAgMD9cYbbyg9PV2tW7d2dHs1ys3NlaRqb5kIDAw0x3Dpzp49q0mTJumBBx647C8aJjThV4uLi9Phw4ed8q+7Nm3aKDMzU4WFhfr73/+ukSNHaufOnU4TnHJycjR27FilpqZW+4vZmZx/hqFz587q2bOnWrRoofXr1ys2NtaBnf1PZWWlevTooRdeeEGS1LVrVx0+fFhJSUlOG5peffVVDRw4UCEhIY5uxc769eu1Zs0arV27Vh06dFBmZqbGjRunkJAQp/pe/u1vf9OoUaN07bXXysXFRd26ddMDDzygjIwMR7eGK6S8vFz33XefDMPQ8uXLL/v+uDyHXyU+Pl6bN2/Whx9+qOuuu87R7VTj7u6u1q1bq3v37po9e7bCwsK0aNEiR7dlysjIUH5+vrp16yZXV1e5urpq586dWrx4sVxdXVVRUeHoFmvk7++v3/3udzpx4oSjWzEFBwdXC8Pt2rVzusuIVb755ht98MEHevTRRx3dSjUJCQl65plnNHz4cHXq1EkPPfSQxo8fr9mzZzu6NTs33HCDdu7cqeLiYuXk5Gjv3r0qLy/X9ddf7+jWahQUFCRJysvLs1uel5dnjsG6qsD0zTffKDU19bKfZZIITaglwzAUHx+vDRs2aPv27WrVqpWjW7KksrJSpaWljm7D1K9fPx06dEiZmZnm1KNHD8XExCgzM1MuLi6ObrFGxcXF+uqrrxQcHOzoVky33nprtcdefPnll2rRooWDOrqwVatWqVmzZoqKinJ0K9X8+OOPatDA/teDi4uLKisrHdTRhXl7eys4OFhnzpzR1q1bNWTIEEe3VKNWrVopKChIaWlp5rKioiLt2bPHKe+1dGZVgen48eP64IMP1KRJkyuyXy7POaHi4mK7v+Czs7OVmZmpgIAANW/e3IGd/U9cXJzWrl2rTZs2qVGjRub1eD8/P3l5eTm4u/+aPHmyBg4cqObNm+uHH37Q2rVrtWPHDm3dutXRrZkaNWpU7T4wb29vNWnSxKnuD/vjH/+owYMHq0WLFvr22281bdo0ubi46IEHHnB0a6bx48erV69eeuGFF3Tfffdp7969WrFihVasWOHo1qqprKzUqlWrNHLkSLm6Ot+P4cGDB+v5559X8+bN1aFDB3322WdasGCBRo0a5ejW7GzdulWGYahNmzY6ceKEEhIS1LZtWz3yyCMO6+liP7/HjRun5557TjfeeKNatWqlqVOnKiQkRNHR0U7T4+nTp3Xy5EnzuUdVf4wEBQVdsTNiF+oxODhY9957rw4cOKDNmzeroqLC/B0UEBAgd3f3y9fYZf1sHmrlww8/NCRVm0aOHOno1kw19SfJWLVqlaNbM40aNcpo0aKF4e7ublxzzTVGv379jG3btjm6rYtyxkcO3H///UZwcLDh7u5uXHvttcb9999vnDhxwtFtVfPuu+8aHTt2NDw8PIy2bdsaK1ascHRLNdq6dashycjKynJ0KzUqKioyxo4dazRv3tzw9PQ0rr/+euPZZ581SktLHd2anTfffNO4/vrrDXd3dyMoKMiIi4szCgoKHNrTxX5+V1ZWGlOnTjUCAwMNDw8Po1+/flf8/4OL9bhq1aoax6dNm+YUPVY9CqGm6cMPP7ysfdkMw8ke8QoAAOCEuKcJAADAAkITAACABYQmAAAACwhNAAAAFhCaAAAALCA0AQAAWEBoAgAAsIDQBAAAYAGhCcBVw2azaePGjY5u44q6/fbbNW7cuF+1jeTkZPn7+9dJP8DVjNAE4Fd7+OGHZbPZ9Nhjj1Ubi4uLk81m08MPP1xn+5s+fbq6dOlSZ9sDACsITQDqRGhoqNatW6effvrJXHb27FmtXbvWaV40DQC/BqEJQJ3o1q2bQkND9fbbb5vL3n77bTVv3lxdu3Y1l5WWluqpp55Ss2bN5Onpqd69e2vfvn3m+I4dO2Sz2ZSWlqYePXqoYcOG6tWrl/mm9eTkZM2YMUOff/65bDabbDabkpOTzfX/85//6O6771bDhg1144036p133jHHzpw5o5iYGF1zzTXy8vLSjTfeqFWrVlk6vpycHN13333y9/dXQECAhgwZoq+//tocf/jhhxUdHa158+YpODhYTZo0UVxcnMrLy+2OfdKkSQoNDZWHh4dat26tV1991RzfuXOnbr75Znl4eCg4OFjPPPOMzp07Z46XlJRoxIgR8vHxUXBwsObPn1+tz9LSUv3xj3/UtddeK29vb/Xs2VM7duywq0lOTlbz5s3VsGFD3X333fr+++8tfQ+A3zpCE4A6M2rUKLsQsnLlSj3yyCN2NRMnTtQ//vEPrV69WgcOHFDr1q0VGRmp06dP29U9++yzmj9/vvbv3y9XV1eNGjVKknT//ffr6aefVocOHfTdd9/pu+++0/3332+uN2PGDN133306ePCgBg0apJiYGHPbU6dO1dGjR/X+++/r2LFjWr58uZo2bXrR4yovL1dkZKQaNWqkjz76SJ988ol8fHw0YMAAlZWVmXUffvihvvrqK3344YdavXq1kpOT7QLdiBEj9MYbb2jx4sU6duyY/vKXv8jHx0eSdOrUKQ0aNEg33XSTPv/8cy1fvlyvvvqqnnvuOXP9hIQE7dy5U5s2bdK2bdu0Y8cOHThwwK7X+Ph4paena926dTp48KCGDRumAQMG6Pjx45KkPXv2KDY2VvHx8crMzNQdd9xhtw8AF2AAwK80cuRIY8iQIUZ+fr7h4eFhfP3118bXX39teHp6Gv/+97+NIUOGGCNHjjSKi4sNNzc3Y82aNea6ZWVlRkhIiDFnzhzDMAzjww8/NCQZH3zwgVmzZcsWQ5Lx008/GYZhGNOmTTPCwsKq9SHJmDJlijlfXFxsSDLef/99wzAMY/DgwcYjjzxyycf3t7/9zWjTpo1RWVlpListLTW8vLyMrVu3mt+DFi1aGOfOnTNrhg0bZtx///2GYRhGVlaWIclITU2tcR9/+tOfqu1j2bJlho+Pj1FRUWH88MMPhru7u7F+/Xpz/Pvvvze8vLyMsWPHGoZhGN98843h4uJinDp1ym7b/fr1MyZPnmwYhmE88MADxqBBg+zG77//fsPPz+8SvyvAb4+rQxMbgKvKNddco6ioKCUnJ8swDEVFRdmdyfnqq69UXl6uW2+91Vzm5uamm2++WceOHbPbVufOnc2vg4ODJUn5+fkXvT/q/PW8vb3l6+ur/Px8SdLjjz+uoUOH6sCBA+rfv7+io6PVq1evix7X559/rhMnTqhRo0Z2y8+ePauvvvrKnO/QoYNcXFzs+j506JAkKTMzUy4uLrrttttq3MexY8cUHh4um81mLrv11ltVXFysf/3rXzpz5ozKysrUs2dPczwgIEBt2rQx5w8dOqSKigr97ne/s9t2aWmpmjRpYu7n7rvvthsPDw9XSkrKRb8PwG8doQlAnRo1apTi4+MlScuWLav1dtzc3Myvq4JEZWXlJa1XtW7VegMHDtQ333yj9957T6mpqerXr5/i4uI0b968C26zuLhY3bt315o1a6qNXXPNNZb27eXlddHef63i4mK5uLgoIyPDLrxJMi8DAqg97mkCUKeq7vOpug/ofDfccIPc3d31ySefmMvKy8u1b98+tW/f3vI+3N3dVVFRUav+rrnmGo0cOVKvv/66Fi5cqBUrVlx0nW7duun48eNq1qyZWrdubTf5+flZ2m+nTp1UWVmpnTt31jjerl07paenyzAMc9knn3yiRo0a6brrrtMNN9wgNzc37dmzxxw/c+aMvvzyS3O+a9euqqioUH5+frU+g4KCzP2cvw1J+vTTTy0dA/BbR2gCUKdcXFx07NgxHT16tNrZDm9vbz3++ONKSEhQSkqKjh49qtGjR+vHH39UbGys5X20bNlS2dnZyszM1H/+8x+VlpZaWi8xMVGbNm3SiRMndOTIEW3evFnt2rW76HoxMTFq2rSphgwZoo8++kjZ2dnasWOHnnrqKf3rX/+y3PPIkSM1atQobdy40dzG+vXrJUlPPPGEcnJy9OSTT+qLL77Qpk2bNG3aNE2YMEENGjSQj4+PYmNjlZCQoO3bt+vw4cN6+OGH1aDB/36M/+53v1NMTIxGjBiht99+W9nZ2dq7d69mz56tLVu2SJKeeuoppaSkaN68eTp+/LiWLl3KpTnAIkITgDrn6+srX1/fGsdefPFFDR06VA899JC6deumEydOaOvWrWrcuLHl7Q8dOlQDBgzQHXfcoWuuuUZvvPGGpfXc3d01efJkde7cWX379pWLi4vWrVt30fUaNmyoXbt2qXnz5rrnnnvUrl07xcbG6uzZs794nDVZvny57r33Xj3xxBNq27atRo8erZKSEknStddeq/fee0979+5VWFiYHnvsMcXGxmrKlCnm+nPnzlWfPn00ePBgRUREqHfv3urevbvdPlatWqURI0bo6aefVps2bRQdHa19+/aZ94LdcssteuWVV7Ro0SKFhYVp27ZtdvsA8MtsxvnnggEAAFAjzjQBAABYQGgC8Jv3wgsvyMfHp8Zp4MCBjm4PgJPg8hyA37zTp09XeyJ5FS8vL1177bVXuCMAzojQBAAAYAGX5wAAACwgNAEAAFhAaAIAALCA0AQAAGABoQkAAMACQhMAAIAFhCYAAAAL/j/ly7AA8FqKAwAAAABJRU5ErkJggg==",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "#plot with the mean\n",
+    "sns.barplot(x=fitbit[\"Months_encoded\"], y=fitbit[\"Steps\"], palette=\"magma\"); #barplot with sns gives the mean by default"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
-    "# your code here\n"
+    "#plot with the median\n",
+    "fitbit_1 = fitbit[[\"Months_encoded\", \"Steps\"]]\n",
+    "fitbit_2 = fitbit_1.groupby([\"Months_encoded\"]).median()\n",
+    "fitbit_2.plot.bar(y='Steps', rot=0);"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 55,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fitbit_1 = fitbit[[\"Work_or_Weekend\", \"Steps\"]]\n",
+    "fitbit_2 = fitbit_1.groupby([\"Work_or_Weekend\"]).mean()\n",
+    "sns.barplot(fitbit_2, x=\"Work_or_Weekend\", y=\"Steps\", color=\"green\");"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 53,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# your code here\n"
+    "#The fitbitter works out more on workdays (slightly).\n",
+    "#We use the mean instead of sum because if not since there are more work days than weekends \n",
+    "#the graph can be missleading"
    ]
   },
   {
@@ -86,6 +647,50 @@
     "* Minutes Sedentary vs Steps  "
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 64,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fitbit_list = [\"Minutes Lightly Active\",\"Minutes Very Active\",\"Minutes Sedentary\"]\n",
+    "\n",
+    "for i in fitbit_list:\n",
+    "    plt.figure()\n",
+    "    sns.scatterplot(data = fitbit, x = i, y = \"Steps\" )"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -111,7 +716,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.12"
+   "version": "3.11.5"
   },
   "nbTranslate": {
    "displayLangs": [
diff --git a/your-code/challenge-2.ipynb b/your-code/challenge-2.ipynb
index d7465f0..9dbcf73 100644
--- a/your-code/challenge-2.ipynb
+++ b/your-code/challenge-2.ipynb
@@ -40,9 +40,140 @@
    "metadata": {
     "scrolled": true
    },
-   "outputs": [],
+   "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>Survived</th>\n",
+       "      <th>Pclass</th>\n",
+       "      <th>Name</th>\n",
+       "      <th>Sex</th>\n",
+       "      <th>Age</th>\n",
+       "      <th>SibSp</th>\n",
+       "      <th>Parch</th>\n",
+       "      <th>Ticket</th>\n",
+       "      <th>Fare</th>\n",
+       "      <th>Cabin</th>\n",
+       "      <th>Embarked</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Braund, Mr. Owen Harris</td>\n",
+       "      <td>male</td>\n",
+       "      <td>22.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>A/5 21171</td>\n",
+       "      <td>7.2500</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
+       "      <td>female</td>\n",
+       "      <td>38.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>PC 17599</td>\n",
+       "      <td>71.2833</td>\n",
+       "      <td>C85</td>\n",
+       "      <td>C</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Heikkinen, Miss. Laina</td>\n",
+       "      <td>female</td>\n",
+       "      <td>26.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>STON/O2. 3101282</td>\n",
+       "      <td>7.9250</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
+       "      <td>female</td>\n",
+       "      <td>35.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>113803</td>\n",
+       "      <td>53.1000</td>\n",
+       "      <td>C123</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Allen, Mr. William Henry</td>\n",
+       "      <td>male</td>\n",
+       "      <td>35.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>373450</td>\n",
+       "      <td>8.0500</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   Survived  Pclass                                               Name  \\\n",
+       "0         0       3                            Braund, Mr. Owen Harris   \n",
+       "1         1       1  Cumings, Mrs. John Bradley (Florence Briggs Th...   \n",
+       "2         1       3                             Heikkinen, Miss. Laina   \n",
+       "3         1       1       Futrelle, Mrs. Jacques Heath (Lily May Peel)   \n",
+       "4         0       3                           Allen, Mr. William Henry   \n",
+       "\n",
+       "      Sex   Age  SibSp  Parch            Ticket     Fare Cabin Embarked  \n",
+       "0    male  22.0      1      0         A/5 21171   7.2500   NaN        S  \n",
+       "1  female  38.0      1      0          PC 17599  71.2833   C85        C  \n",
+       "2  female  26.0      0      0  STON/O2. 3101282   7.9250   NaN        S  \n",
+       "3  female  35.0      1      0            113803  53.1000  C123        S  \n",
+       "4    male  35.0      0      0            373450   8.0500   NaN        S  "
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# your code here\n"
+    "titanic = pd.read_csv('https://raw.githubusercontent.com/Ironhack-data-bcn-oct-2023/lectures/main/datasets/titanic.csv')\n",
+    "titanic.head()"
    ]
   },
   {
@@ -54,10 +185,34 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Survived      int64\n",
+       "Pclass        int64\n",
+       "Name         object\n",
+       "Sex          object\n",
+       "Age         float64\n",
+       "SibSp         int64\n",
+       "Parch         int64\n",
+       "Ticket       object\n",
+       "Fare        float64\n",
+       "Cabin        object\n",
+       "Embarked     object\n",
+       "dtype: object"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "titanic.dtypes"
+   ]
   },
   {
    "cell_type": "markdown",
@@ -69,10 +224,336 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 5,
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "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>Age</th>\n",
+       "      <th>Fare</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>22.0</td>\n",
+       "      <td>7.2500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>38.0</td>\n",
+       "      <td>71.2833</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>26.0</td>\n",
+       "      <td>7.9250</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>35.0</td>\n",
+       "      <td>53.1000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>35.0</td>\n",
+       "      <td>8.0500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>886</th>\n",
+       "      <td>27.0</td>\n",
+       "      <td>13.0000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>887</th>\n",
+       "      <td>19.0</td>\n",
+       "      <td>30.0000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>888</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>23.4500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>889</th>\n",
+       "      <td>26.0</td>\n",
+       "      <td>30.0000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>890</th>\n",
+       "      <td>32.0</td>\n",
+       "      <td>7.7500</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>891 rows × 2 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      Age     Fare\n",
+       "0    22.0   7.2500\n",
+       "1    38.0  71.2833\n",
+       "2    26.0   7.9250\n",
+       "3    35.0  53.1000\n",
+       "4    35.0   8.0500\n",
+       "..    ...      ...\n",
+       "886  27.0  13.0000\n",
+       "887  19.0  30.0000\n",
+       "888   NaN  23.4500\n",
+       "889  26.0  30.0000\n",
+       "890  32.0   7.7500\n",
+       "\n",
+       "[891 rows x 2 columns]"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#Numerical variables: Age, Fare\n",
+    "titanic.select_dtypes(float)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "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>Survived</th>\n",
+       "      <th>Pclass</th>\n",
+       "      <th>Name</th>\n",
+       "      <th>Sex</th>\n",
+       "      <th>SibSp</th>\n",
+       "      <th>Parch</th>\n",
+       "      <th>Ticket</th>\n",
+       "      <th>Cabin</th>\n",
+       "      <th>Embarked</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Braund, Mr. Owen Harris</td>\n",
+       "      <td>male</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>A/5 21171</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
+       "      <td>female</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>PC 17599</td>\n",
+       "      <td>C85</td>\n",
+       "      <td>C</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Heikkinen, Miss. Laina</td>\n",
+       "      <td>female</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>STON/O2. 3101282</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
+       "      <td>female</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>113803</td>\n",
+       "      <td>C123</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Allen, Mr. William Henry</td>\n",
+       "      <td>male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>373450</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>886</th>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Montvila, Rev. Juozas</td>\n",
+       "      <td>male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>211536</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>887</th>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Graham, Miss. Margaret Edith</td>\n",
+       "      <td>female</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>112053</td>\n",
+       "      <td>B42</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>888</th>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Johnston, Miss. Catherine Helen \"Carrie\"</td>\n",
+       "      <td>female</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>W./C. 6607</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>889</th>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Behr, Mr. Karl Howell</td>\n",
+       "      <td>male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>111369</td>\n",
+       "      <td>C148</td>\n",
+       "      <td>C</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>890</th>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Dooley, Mr. Patrick</td>\n",
+       "      <td>male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>370376</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Q</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>891 rows × 9 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     Survived  Pclass                                               Name  \\\n",
+       "0           0       3                            Braund, Mr. Owen Harris   \n",
+       "1           1       1  Cumings, Mrs. John Bradley (Florence Briggs Th...   \n",
+       "2           1       3                             Heikkinen, Miss. Laina   \n",
+       "3           1       1       Futrelle, Mrs. Jacques Heath (Lily May Peel)   \n",
+       "4           0       3                           Allen, Mr. William Henry   \n",
+       "..        ...     ...                                                ...   \n",
+       "886         0       2                              Montvila, Rev. Juozas   \n",
+       "887         1       1                       Graham, Miss. Margaret Edith   \n",
+       "888         0       3           Johnston, Miss. Catherine Helen \"Carrie\"   \n",
+       "889         1       1                              Behr, Mr. Karl Howell   \n",
+       "890         0       3                                Dooley, Mr. Patrick   \n",
+       "\n",
+       "        Sex  SibSp  Parch            Ticket Cabin Embarked  \n",
+       "0      male      1      0         A/5 21171   NaN        S  \n",
+       "1    female      1      0          PC 17599   C85        C  \n",
+       "2    female      0      0  STON/O2. 3101282   NaN        S  \n",
+       "3    female      1      0            113803  C123        S  \n",
+       "4      male      0      0            373450   NaN        S  \n",
+       "..      ...    ...    ...               ...   ...      ...  \n",
+       "886    male      0      0            211536   NaN        S  \n",
+       "887  female      0      0            112053   B42        S  \n",
+       "888  female      1      2        W./C. 6607   NaN        S  \n",
+       "889    male      0      0            111369  C148        C  \n",
+       "890    male      0      0            370376   NaN        Q  \n",
+       "\n",
+       "[891 rows x 9 columns]"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#Categorical variables: Survived, Pclass, Name, Sex, SibSp, Parch, Ticket, Cabin, Embarked\n",
+    "titanic.select_dtypes(exclude = float)"
+   ]
   },
   {
    "cell_type": "markdown",
@@ -84,11 +565,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 42,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 1200x600 with 0 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
-    "# your code here\n"
+    "sns.set_style(\"dark\")\n",
+    "plt.figure(figsize=(12,6));"
    ]
   },
   {
@@ -100,11 +592,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
-    "# your code here\n"
+    "sns.histplot(titanic, x=\"Age\", bins=10);"
    ]
   },
   {
@@ -121,7 +624,9 @@
    "outputs": [],
    "source": [
     "\"\"\"\n",
-    "your comments here\n",
+    "It makes it more or less readible. If we have too many bins, even though \n",
+    "data is more precise, information is hard to read and we won't be able to take clear conclusions.\n",
+    "If we have too little we might miss important information about certain group ages.\n",
     "\"\"\""
    ]
   },
@@ -135,22 +640,44 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "# Method 1 - matplotlib\n",
-    "# your code here"
+    "titanic [\"Sex\"].value_counts().plot(kind = \"bar\");"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "# Method 2 - seaborn\n",
-    "# your code here"
+    "sns.countplot(titanic, x=\"Sex\");"
    ]
   },
   {
@@ -162,11 +689,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
-    "# your code here"
+    "sns.countplot(x=titanic.Pclass);"
    ]
   },
   {
@@ -185,11 +723,32 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Axes: xlabel='Age'>"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
-    "# your code here"
+    "sns.boxplot(titanic, x=\"Age\")"
    ]
   },
   {
@@ -199,7 +758,11 @@
    "outputs": [],
    "source": [
     "\"\"\"\n",
-    "your comments here\n",
+    "Q1 = 20\n",
+    "Q2 = Median = slightly under 28\n",
+    "Q3 = slightly under 40\n",
+    "Some outliers of older people\n",
+    "\n",
     "\"\"\""
    ]
   },
@@ -213,22 +776,54 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 28,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "# Method 1 - matplotlib\n",
-    "# your code here"
+    "plt.scatter(data = titanic, x=\"Age\", y=\"Fare\");"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Axes: xlabel='Age', ylabel='Fare'>"
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "# Method 2 - seaborn\n",
-    "# your code here"
+    "sns.scatterplot(titanic, x=\"Age\", y=\"Fare\")"
    ]
   },
   {
@@ -240,11 +835,23 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 34,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
-    "# your code here"
+    "sns.heatmap(titanic.select_dtypes(exclude = object).corr());\n",
+    "plt.show()"
    ]
   },
   {
@@ -261,7 +868,7 @@
    "outputs": [],
    "source": [
     "\"\"\"\n",
-    "your comments here\n",
+    "Pclass and Fare are very correlated\n",
     "\"\"\""
    ]
   },
@@ -274,13 +881,24 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 35,
    "metadata": {
     "scrolled": true
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
-    "# your code here"
+    "sns.boxplot(titanic, x = \"Pclass\", y = \"Age\");"
    ]
   },
   {
@@ -291,14 +909,34 @@
     "**Hint**: Use Facetgrid."
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 300x600 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "g = sns.FacetGrid(titanic, row=\"Sex\")\n",
+    "g.map(plt.hist, \"Age\", bins = 20)\n",
+    "plt.show()"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
-   "source": [
-    "# your code here"
-   ]
+   "source": []
   }
  ],
  "metadata": {
@@ -318,7 +956,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.12"
+   "version": "3.11.5"
   },
   "nbTranslate": {
    "displayLangs": [