diff --git a/your-code/challenge-1.ipynb b/your-code/challenge-1.ipynb
index 9df5e53..870c471 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": 1,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -35,11 +35,401 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 2,
    "metadata": {},
-   "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>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>...</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",
+       "      <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",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>362</th>\n",
+       "      <td>2016-05-03</td>\n",
+       "      <td>3796</td>\n",
+       "      <td>18588</td>\n",
+       "      <td>14.13</td>\n",
+       "      <td>16</td>\n",
+       "      <td>599.000</td>\n",
+       "      <td>275</td>\n",
+       "      <td>49</td>\n",
+       "      <td>79</td>\n",
+       "      <td>236</td>\n",
+       "      <td>...</td>\n",
+       "      <td>8.779972</td>\n",
+       "      <td>Tuesday</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>6.283333</td>\n",
+       "      <td>91.951220</td>\n",
+       "      <td>5.233333</td>\n",
+       "      <td>90.229885</td>\n",
+       "      <td>May</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>363</th>\n",
+       "      <td>2016-05-04</td>\n",
+       "      <td>3525</td>\n",
+       "      <td>16382</td>\n",
+       "      <td>12.39</td>\n",
+       "      <td>16</td>\n",
+       "      <td>684.000</td>\n",
+       "      <td>333</td>\n",
+       "      <td>10</td>\n",
+       "      <td>55</td>\n",
+       "      <td>2075</td>\n",
+       "      <td>...</td>\n",
+       "      <td>7.698787</td>\n",
+       "      <td>Wednesday</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>6.766667</td>\n",
+       "      <td>95.081967</td>\n",
+       "      <td>6.283333</td>\n",
+       "      <td>91.951220</td>\n",
+       "      <td>May</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>364</th>\n",
+       "      <td>2016-05-05</td>\n",
+       "      <td>3649</td>\n",
+       "      <td>21913</td>\n",
+       "      <td>16.40</td>\n",
+       "      <td>19</td>\n",
+       "      <td>701.000</td>\n",
+       "      <td>287</td>\n",
+       "      <td>29</td>\n",
+       "      <td>90</td>\n",
+       "      <td>2249</td>\n",
+       "      <td>...</td>\n",
+       "      <td>10.190484</td>\n",
+       "      <td>Thursday</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>4.666667</td>\n",
+       "      <td>88.888889</td>\n",
+       "      <td>6.766667</td>\n",
+       "      <td>95.081967</td>\n",
+       "      <td>May</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>365</th>\n",
+       "      <td>2016-05-06</td>\n",
+       "      <td>3539</td>\n",
+       "      <td>19023</td>\n",
+       "      <td>14.79</td>\n",
+       "      <td>15</td>\n",
+       "      <td>575.000</td>\n",
+       "      <td>298</td>\n",
+       "      <td>8</td>\n",
+       "      <td>85</td>\n",
+       "      <td>2112</td>\n",
+       "      <td>...</td>\n",
+       "      <td>9.190077</td>\n",
+       "      <td>Friday</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>6.166667</td>\n",
+       "      <td>89.805825</td>\n",
+       "      <td>4.666667</td>\n",
+       "      <td>88.888889</td>\n",
+       "      <td>May</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>366</th>\n",
+       "      <td>2016-05-07</td>\n",
+       "      <td>304</td>\n",
+       "      <td>9526</td>\n",
+       "      <td>7.08</td>\n",
+       "      <td>2</td>\n",
+       "      <td>564.000</td>\n",
+       "      <td>370</td>\n",
+       "      <td>13</td>\n",
+       "      <td>10</td>\n",
+       "      <td>1604</td>\n",
+       "      <td>...</td>\n",
+       "      <td>4.399307</td>\n",
+       "      <td>Saturday</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>8.366667</td>\n",
+       "      <td>89.165187</td>\n",
+       "      <td>6.166667</td>\n",
+       "      <td>89.805825</td>\n",
+       "      <td>May</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>367 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",
+       "..          ...             ...    ...       ...     ...                ...   \n",
+       "362  2016-05-03            3796  18588     14.13      16            599.000   \n",
+       "363  2016-05-04            3525  16382     12.39      16            684.000   \n",
+       "364  2016-05-05            3649  21913     16.40      19            701.000   \n",
+       "365  2016-05-06            3539  19023     14.79      15            575.000   \n",
+       "366  2016-05-07             304   9526      7.08       2            564.000   \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",
+       "..                      ...                    ...                  ...   \n",
+       "362                     275                     49                   79   \n",
+       "363                     333                     10                   55   \n",
+       "364                     287                     29                   90   \n",
+       "365                     298                      8                   85   \n",
+       "366                     370                     13                   10   \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",
+       "..                 ...  ...             ...        ...           ...   \n",
+       "362                236  ...        8.779972    Tuesday           1.0   \n",
+       "363               2075  ...        7.698787  Wednesday           2.0   \n",
+       "364               2249  ...       10.190484   Thursday           3.0   \n",
+       "365               2112  ...        9.190077     Friday           4.0   \n",
+       "366               1604  ...        4.399307   Saturday           5.0   \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",
+       "..               ...          ...              ...              ...   \n",
+       "362                1     6.283333        91.951220         5.233333   \n",
+       "363                1     6.766667        95.081967         6.283333   \n",
+       "364                1     4.666667        88.888889         6.766667   \n",
+       "365                1     6.166667        89.805825         4.666667   \n",
+       "366                0     8.366667        89.165187         6.166667   \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",
+       "..                          ...     ...             ...  \n",
+       "362                   90.229885     May               5  \n",
+       "363                   91.951220     May               5  \n",
+       "364                   95.081967     May               5  \n",
+       "365                   88.888889     May               5  \n",
+       "366                   89.805825     May               5  \n",
+       "\n",
+       "[367 rows x 24 columns]"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# your code here\n"
+    "fitbit = pd.read_csv(r\"C:\\Users\\photo\\Desktop\\Ironhack\\lectures\\datasets\\faq-and-examples\\lab-matplotlib-seaborn\\data\\fitbit2.csv\")\n",
+    "\n",
+    "fitbit"
    ]
   },
   {
@@ -59,20 +449,36 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# your code here\n"
+    "sns.set_context(\"poster\")\n",
+    "sns.set(rc={\"figure.figsize\": (12.,4.)})\n",
+    "sns.set_style(\"whitegrid\")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x400 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
-    "# your code here\n"
+    "barplot = sns.barplot(x=\"Months\", y=\"Steps\", data=fitbit) \n",
+    "barplot.set_xticklabels=[\"JAN\", \"FEB\", \"MAR\" \"APR\", \"MAY\", \"JUN\", \"JUL\", \"AUG\", \"SEP\", \"OCT\", \"NOV\", \"DEC\"]\n",
+    "barplot.set(xlabel=\"Month\", ylabel=\"Average Steps\")\n",
+    "plt.savefig(r'C:\\Users\\photo\\Desktop\\Ironhack\\labs\\lab-matplotlib-seaborn\\figures\\challenge1.png')"
    ]
   },
   {
@@ -88,10 +494,33 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 5,
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x400 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "min_activity = ['Minutes Lightly Active', 'Minutes Very Active', 'Minutes Sedentary']\n",
+    "for min_activity in min_activity:\n",
+    "    plt.scatter(fitbit[min_activity], fitbit['Steps'], label=min_activity)\n",
+    "    \n",
+    "plt.xlabel('Minutes'), \n",
+    "plt.ylabel('Steps')\n",
+    "plt.title('Activity vs Steps'), \n",
+    "plt.legend() \n",
+    "plt.grid(True)\n",
+    "\n",
+    "plt.show()"
+   ]
   }
  ],
  "metadata": {
@@ -111,7 +540,7 @@
    "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..58035c4 100644
--- a/your-code/challenge-2.ipynb
+++ b/your-code/challenge-2.ipynb
@@ -11,7 +11,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 91,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -36,13 +36,269 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 92,
    "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>PassengerId</th>\n",
+       "      <th>Survived</th>\n",
+       "      <th>Pclass</th>\n",
+       "      <th>Name</th>\n",
+       "      <th>Gender</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>1</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Braund, Mr. Owen Harris</td>\n",
+       "      <td>male</td>\n",
+       "      <td>22.000000</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>A/5 21171</td>\n",
+       "      <td>7.2500</td>\n",
+       "      <td>U0</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
+       "      <td>female</td>\n",
+       "      <td>38.000000</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>3</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Heikkinen, Miss. Laina</td>\n",
+       "      <td>female</td>\n",
+       "      <td>26.000000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>STON/O2. 3101282</td>\n",
+       "      <td>7.9250</td>\n",
+       "      <td>U0</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
+       "      <td>female</td>\n",
+       "      <td>35.000000</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>5</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Allen, Mr. William Henry</td>\n",
+       "      <td>male</td>\n",
+       "      <td>35.000000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>373450</td>\n",
+       "      <td>8.0500</td>\n",
+       "      <td>U0</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",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1304</th>\n",
+       "      <td>1305</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Spector, Mr. Woolf</td>\n",
+       "      <td>male</td>\n",
+       "      <td>29.513190</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>A.5. 3236</td>\n",
+       "      <td>8.0500</td>\n",
+       "      <td>U0</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1305</th>\n",
+       "      <td>1306</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Oliva y Ocana, Dona. Fermina</td>\n",
+       "      <td>female</td>\n",
+       "      <td>39.000000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>PC 17758</td>\n",
+       "      <td>108.9000</td>\n",
+       "      <td>C105</td>\n",
+       "      <td>C</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1306</th>\n",
+       "      <td>1307</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Saether, Mr. Simon Sivertsen</td>\n",
+       "      <td>male</td>\n",
+       "      <td>38.500000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>SOTON/O.Q. 3101262</td>\n",
+       "      <td>7.2500</td>\n",
+       "      <td>U0</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1307</th>\n",
+       "      <td>1308</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Ware, Mr. Frederick</td>\n",
+       "      <td>male</td>\n",
+       "      <td>29.513190</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>359309</td>\n",
+       "      <td>8.0500</td>\n",
+       "      <td>U0</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1308</th>\n",
+       "      <td>1309</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Peter, Master. Michael J</td>\n",
+       "      <td>male</td>\n",
+       "      <td>25.315435</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2668</td>\n",
+       "      <td>22.3583</td>\n",
+       "      <td>U0</td>\n",
+       "      <td>C</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>1309 rows × 12 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      PassengerId  Survived  Pclass  \\\n",
+       "0               1       0.0       3   \n",
+       "1               2       1.0       1   \n",
+       "2               3       1.0       3   \n",
+       "3               4       1.0       1   \n",
+       "4               5       0.0       3   \n",
+       "...           ...       ...     ...   \n",
+       "1304         1305       NaN       3   \n",
+       "1305         1306       NaN       1   \n",
+       "1306         1307       NaN       3   \n",
+       "1307         1308       NaN       3   \n",
+       "1308         1309       NaN       3   \n",
+       "\n",
+       "                                                   Name  Gender        Age  \\\n",
+       "0                               Braund, Mr. Owen Harris    male  22.000000   \n",
+       "1     Cumings, Mrs. John Bradley (Florence Briggs Th...  female  38.000000   \n",
+       "2                                Heikkinen, Miss. Laina  female  26.000000   \n",
+       "3          Futrelle, Mrs. Jacques Heath (Lily May Peel)  female  35.000000   \n",
+       "4                              Allen, Mr. William Henry    male  35.000000   \n",
+       "...                                                 ...     ...        ...   \n",
+       "1304                                 Spector, Mr. Woolf    male  29.513190   \n",
+       "1305                       Oliva y Ocana, Dona. Fermina  female  39.000000   \n",
+       "1306                       Saether, Mr. Simon Sivertsen    male  38.500000   \n",
+       "1307                                Ware, Mr. Frederick    male  29.513190   \n",
+       "1308                           Peter, Master. Michael J    male  25.315435   \n",
+       "\n",
+       "      SibSp  Parch              Ticket      Fare Cabin Embarked  \n",
+       "0         1      0           A/5 21171    7.2500    U0        S  \n",
+       "1         1      0            PC 17599   71.2833   C85        C  \n",
+       "2         0      0    STON/O2. 3101282    7.9250    U0        S  \n",
+       "3         1      0              113803   53.1000  C123        S  \n",
+       "4         0      0              373450    8.0500    U0        S  \n",
+       "...     ...    ...                 ...       ...   ...      ...  \n",
+       "1304      0      0           A.5. 3236    8.0500    U0        S  \n",
+       "1305      0      0            PC 17758  108.9000  C105        C  \n",
+       "1306      0      0  SOTON/O.Q. 3101262    7.2500    U0        S  \n",
+       "1307      0      0              359309    8.0500    U0        S  \n",
+       "1308      1      1                2668   22.3583    U0        C  \n",
+       "\n",
+       "[1309 rows x 12 columns]"
+      ]
+     },
+     "execution_count": 92,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# your code here\n"
+    "titanic = pd.read_csv(r\"C:\\Users\\photo\\Desktop\\Ironhack\\labs\\lab-matplotlib-seaborn\\data\\titanic.csv\")\n",
+    "\n",
+    "titanic"
    ]
   },
   {
@@ -54,10 +310,34 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
+   "execution_count": 93,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "PassengerId      int64\n",
+      "Survived       float64\n",
+      "Pclass           int64\n",
+      "Name            object\n",
+      "Gender          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\n"
+     ]
+    }
+   ],
+   "source": [
+    "titanic_types = titanic.dtypes\n",
+    "\n",
+    "print(titanic_types)"
+   ]
   },
   {
    "cell_type": "markdown",
@@ -69,10 +349,26 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
+   "execution_count": 94,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Index(['PassengerId', 'Survived', 'Pclass', 'Age', 'SibSp', 'Parch', 'Fare'], dtype='object')\n",
+      "Index(['Name', 'Gender', 'Ticket', 'Cabin', 'Embarked'], dtype='object')\n"
+     ]
+    }
+   ],
+   "source": [
+    "numerical = titanic.select_dtypes(include=['int64', 'float64'])\n",
+    "categorical = titanic.select_dtypes(include=['object'])\n",
+    "\n",
+    "print(numerical.columns)\n",
+    "\n",
+    "print(categorical.columns)"
+   ]
   },
   {
    "cell_type": "markdown",
@@ -84,11 +380,23 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 42,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 95,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 960x480 with 0 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
-    "# your code here\n"
+    "plt.style.use('classic')\n",
+    "plt.figure(figsize=(12, 6))\n",
+    "plt.show()"
    ]
   },
   {
@@ -100,11 +408,29 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 96,
+   "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"
+    "titanic_age = titanic['Age'].dropna()  # Elimina valores nulos de la columna Age\n",
+    "\n",
+    "plt.hist(titanic_age, bins=20, color='skyblue', edgecolor='black')\n",
+    "plt.title('Titanic - Age of Passengers')\n",
+    "plt.xlabel('Age')\n",
+    "plt.ylabel('Passengers')\n",
+    "\n",
+    "plt.show()"
    ]
   },
   {
@@ -116,13 +442,24 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 97,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "\"''\\nThe choice of bin size in a histogram is very imporant because it determines the clarity and interpretation of the data. \\n\""
+      ]
+     },
+     "execution_count": 97,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "\"\"\"\n",
-    "your comments here\n",
-    "\"\"\""
+    "'''''\n",
+    "The choice of bin size in a histogram is very imporant because it determines the clarity and interpretation of the data. \n",
+    "'''''"
    ]
   },
   {
@@ -135,22 +472,59 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 98,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 480x320 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "# Method 1 - matplotlib\n",
-    "# your code here"
+    "gender_matplot = titanic['Gender'].value_counts()\n",
+    "\n",
+    "plt.figure(figsize=(6, 4))\n",
+    "gender_matplot.plot(kind='bar', color='skyblue')\n",
+    "plt.title('Gender Distribution (Matplotlib)')\n",
+    "plt.xlabel('Gender')\n",
+    "plt.ylabel('Pclass')\n",
+    "plt.xticks(rotation=0)\n",
+    "plt.show()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 99,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 480x320 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "# Method 2 - seaborn\n",
-    "# your code here"
+    "\n",
+    "sns.set(style=\"whitegrid\")\n",
+    "plt.figure(figsize=(6, 4))\n",
+    "sns.countplot(x='Gender', data=titanic, hue='Gender', palette='Set2')\n",
+    "plt.title('Total Passengers Gender)')\n",
+    "plt.xlabel('Gender')\n",
+    "plt.ylabel('Count')\n",
+    "plt.show()"
    ]
   },
   {
@@ -162,11 +536,28 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 100,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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3asWKFbLZbLp06ZJ69+6tsLCwW9a3cOFCffbZZzLGqHz58oqMjFTNmjULYc8AAMWBU5anJP3f//2f3njjDTVs2FDjxo3TpEmTtHHjRpUoUULdunXT9u3btWLFCr333nuqUKGCzp49qyeffFKhoaG51rNx40YdOXJEK1eulKenp+Li4jR8+HBt2bKlkPYMAFDUOW15VqpUSQ0bNpQkVa9eXVlZWSpVqpQkqWrVqsrMzNTChQu1a9cunTx5UsePH5cxRhkZGbnWs2PHDv3444/q06ePY9rVq1d19epVlSlT5l7tDgCgGHHa8vT09Mz12MPDI9fjpKQkde/eXSEhIWrQoIH69Omj7du3yxiTa7mcnBwNHjxYgwcPliTZ7XYlJSWpdOnSBZofAFB8FdkThry8vOTr66vhw4erTZs22r17t4wxysnJybXcE088obVr1yo5OVmSFBsbqyFDhhRGZABAMeG07zzvxtPTUzVr1lTHjh3l6+urRx55RDVr1lRCQoK8vLwcy/Xu3Vvnz59X//795erqqjJlymjOnDlycXEpxPQAgKLMxfx+nBO3SE9P19GjR6XpM2Ti4ws7DgAUW66+vmr85c4CW39qaqri4+NVr149+fj4/MfrKbLDtgAAFBbKEwAAiyhPAAAsojwBALCI8gQAwCLKEwAAiyhPAAAsojwBALCI8gQAwCLKEwAAiyhPAAAsojwBALCI8gQAwCLKEwAAiyhPAAAsojwBALCI8gQAwCLKEwAAiyhPAAAsojwBALCI8gQAwCLKEwAAiyhPAAAsojwBALCI8gQAwCLKEwAAiyhPAAAsojwBALCI8gQAwCLKEwAAiyhPAAAsojwBALCI8gQAwCLKEwAAiyhPAAAsojwBALCI8gQAwCLKEwAAiyhPAAAsynN5hoeHKy0trSCzAABQJOS5PA8cOCAPD4+CzAIAQJHgntcF27dvr+eff14dOnRQxYoV5eLi4pjXoUOHAgkHAIAzynN57tmzR5K0dOnSXNNdXFwoTwDAfSXP5bljx46CzAEAQJFh6WzbpKQkLVmyRFFRUUpLS1NcXFxB5QIAwGnluTwPHjyozp0765tvvtHatWt19epVjRkzRitWrCjIfAAAOJ08D9tOmTJF0dHR6tChg5o0aaJq1appwYIFGjdunPr371+QGZ2GW4kSyvH1LewYAFBsuRWR37F5Ls9ff/1V7dq1kyTHmbaBgYG6fPlywSRzQrVnvysfH5/CjgEAxVpOVrZcPZ37q5F5HratVq2a9u/fn2vaoUOH5Ofnl++hnJXdbi/sCH/Ibrfr8OHDZMwHRSEnGfNPUch5v2V09uKULLzzDA8P14svvqiuXbsqKytL06ZN09q1a/XWW28VZD5YkJOTU9gR7qooZJSKRk4y5p+ikJOMziXP7zyDg4MVGxsrNzc3NW3aVCkpKZo7d65jKBcAgPtFnt95SpK/v7/8/f0LKgsAAEXCXctz4MCBuS7FdzuxsbH5FggAAGd312Hbv/zlL2rbtq2qV6+uX375RY0bN1b37t3VrFkzJSQk6NFHH70XOQEAcBp3fec5dOhQSVKvXr20ZMkS1a1b1zGvY8eOCg8PL7h0AAA4oTyfMJSQkKBatWrlmubn56fExMR8DwUAgDPLc3k2bNhQEydOdFwUISkpSZGRkXr88ccLLBwAAM4oz2fbRkVFacSIEWrRooXc3d1lt9vVtGlT/eMf/yjIfAAAOJ08l2eVKlW0atUqnT59WklJSapUqZKqVq1akNkAAHBKlr7n+cMPP+jEiRMyxujkyZOO6T179szvXAAAOK08l+fUqVMVGxuratWqycMj93UHKU8AwP0kz+W5adMmLVu2TEFBQQWZBwAAp5fns23tdrsaNWpUkFkAACgS8lyeffv21ezZs3X9+vWCzAMAgNPL87Dt9u3blZCQoPnz56tEiRK55h06dCjfgwEA4KzyXJ6TJk0qyBwAABQZeS7Ppk2bSpKuXLmi06dPq379+rLZbPL09CywcAAAOKM8f+aZkpKi4cOHq3nz5ho0aJASEhIUHBysn3/+uSDzAQDgdPJcnjExMSpRooT27Nkjd3d31ahRQz179lRUVFRB5gMAwOnkedh2z549+t///V/5+PjIxcVFrq6uCg8PV8uWLQsyHwAATifP7zw9PDxu+ZpKWlqaSpYsme+hAABwZnkuz06dOik8PFyHDh2SMUbHjx/XuHHj1LFjx4LMBwtcXfP8chaaopBRKho5i0JGoLjK809fRESE6tatq6FDhyo1NVW9evVS5cqVNXLkyAKM51zc3NwKO8IfcnNzU6NGjciYD4pCznudMdtmvyfbAYqKPH3meeXKFV25ckWRkZFyc3NTVlaWJKly5cry9vYu0IDOJPKDL5VwKb2wYwD3lI+Xhz56tXthxwCcyl3L88SJEwoNDdXgwYM1bNgwrVq1Sp06dZIkzZs3T/Xq1dMTTzxR4EGdwfVsm9IzbYUdAwBQyO5annPmzFGfPn00bNiwG09wd1dMTIwkqWbNmvr444/vm/IEAEDKw2ee+/btU2ho6G3n9erVS0eOHMn3UAAAOLO7lmd6eroqVqzoeDx8+HDHvx988EHusgIAuO/ctTxLlSqlq1evOh4/++yzjn9fuHBBZcqUKYhcAAA4rbuWZ/PmzbVy5crbzlu5cqVatWqV76EAAHBmdz1h6IUXXlDv3r2Vlpamvn37qkqVKkpKStKaNWv04YcfasOGDfcgJgAAzuOu5VmzZk3FxsZqwoQJWrhwoVxcXCRJdevW1ZIlS1S1atUCDwkAgDPJ00US6tevr9WrVysxMVHnz59X+fLlVa1atYLOBgCAU8rzXVWkG1cUqly5ckFlAQCgSODK0gAAWER5AgBgEeUJAIBFlCcAABZRngAAWER5AgBgEeUJAIBFlCcAABZRngAAWER5AgBgEeUJAIBFlCcAABZRngAAWER5AgBgEeUJAIBFlCcAABZRngAAWER5AgBgEeUJAIBFlCcAABZRngAAWER5AgBgEeUJAIBFlCcAABZRngAAWER5AgBgEeUJAIBFlCcAABZRngAAWER5AgBgEeUJAIBFlCcAABZRngAAWER5AgBgEeUJAIBF97Q8582bp7Zt22rkyJEFup3g4GAdOHCgQLcBALh/ud/Lja1evVrR0dFq0aLFvdwsAAD56p6VZ3h4uM6fP68JEyYoNDRU8fHxOnr0qLKzsxUQEKBx48apZMmSCg4OVrdu3bRz505duXJFQ4YMUVJSkvbv36+UlBTFxMQoMDBQp06d0oQJE3Tt2jVduHBB1apV08yZM1WuXLlc2z1y5IimTZuma9euyRijwYMHq2fPnvdqtwEAxdA9G7adNWuWKlasqOjoaMXHx+vhhx/WunXrtGnTJpUsWVLTp093LHv16lVt2rRJ06dP15QpUxQYGKg1a9boqaee0qJFiyTdeBfbqVMnffLJJ4qLi5Obm5s2bNiQa5vJycl69dVXFRUVpfXr12vp0qWaO3eujhw5cq92GwBQDN3TYdubduzYocOHD2vTpk2SpOzsbJUvX94xv1OnTpKkP/3pT5KkNm3aOB7v3r1bkjRy5Ejt3btXixcv1smTJ3X8+HEFBgbm2s7333+vpKQkhYeHO6bZbDb985//VIMGDQpuBwEAxVqhlGdOTo7eeecdPfbYY5KktLQ0ZWdnO+Z7eHjkWv73jyXplVdeUXp6urp06aIWLVooIyNDxphcy9jtdlWvXl0bN250TLtw4YJKly6dn7sDALjPFMpXVVq3bq0PPvhAdrtddrtdY8eO1YwZMyytY/fu3XrxxRfVrVs3lSpVSnv37pXdbs+1TMOGDZWYmKivvvpKknTq1Cl16dJF//rXv/JtXwAA959CeecZGRmpmJgYde/eXXa7Xf7+/hozZoyldbzyyisaPXq0SpcuLQ8PDzVr1kwnT57MtUy5cuX03nvv6Z133tHUqVNls9n02muvqVGjRvm5OwCA+4yL+f1YJ26Rnp6uo0ePavHXZ/VrUnphxwHuKR8vd62LDLH8PLvdru+//14NGzaUm5tbASTLH0UhJxnzT2pqquLj41WvXj35+Pj8x+vhCkMAAFhEeQIAYBHlCQCARZQnAAAWUZ4AAFhEeQIAYBHlCQCARZQnAAAWUZ4AAFhEeQIAYBHlCQCARZQnAAAWUZ4AAFhEeQIAYBHlCQCARZQnAAAWUZ4AAFhEeQIAYBHlCQCARZQnAAAWUZ4AAFhEeQIAYBHlCQCARZQnAAAWUZ4AAFhEeQIAYBHlCQCARZQnAAAWUZ4AAFhEeQIAYBHlCQCARZQnAAAWUZ4AAFhEeQIAYBHlCQCARZQnAAAWUZ4AAFhEeQIAYBHlCQCARZQnAAAWUZ4AAFhEeQIAYBHlCQCARZQnAAAWUZ4AAFhEeQIAYJF7YQcoSrw93OXjxSHD/cXHy6OwIwBOhyaw4K1n28jHx6ewYwD3XLbNLg93t8KOATgNhm0tsNvthR3hD9ntdh0+fJiM+aAo5LzXGSlOIDfKsxjJyckp7Ah3VRQySkUjZ1HICBRXlCcAABZRngAAWER5AgBgEeUJAIBFlCcAABZRngAAWER5AgBgEeUJAIBFXJ4vD25+Gf369etyc3POK63cvNJMeno6Gf9LRSEnGfNPUchJxvxz/fp1Sf/9RUZcjDEmPwIVZ5cuXVJCQkJhxwAA5JMaNWqofPny//HzKc88sNlsSk5OlpeXl1xdGekGgKIqJydHmZmZKl26tNzd//PBV8oTAACLeBsFAIBFlCcAABZRngAAWER5AgBgEeUJAIBFlCcAABZRngAAWER5AgBgEeUJAIBFXBj+Lvbs2aN33nlHmZmZqlKliqZMmaKKFSsWWp6ZM2cqKSlJUVFRkqSNGzdqwYIFstlsqlevnt566y2VLFlSkrR48WKtXr1adrtdrVq10uuvvy4PD48Cy/bxxx9rxYoVcnFxUYkSJfTGG28oICDgD3Pk5ORo2rRp2rFjh+x2u3r27KmXX35ZLi4uBZZRktauXatly5ZJksqWLauJEyeqZs2aTpdTko4cOaLQ0FDFxcWpcuXKTvV6S9K4ceO0b98+lSpVSpL00EMPadasWU51LI8dO6ZJkyYpNTVVrq6uGj9+vBo2bOg0x3L16tX66KOPHI+vXbum06dPa/v27YqLi3Oa4yhJcXFxevfdd+Xq6qqSJUtq0qRJqlWrllO93h9//LFiY2Pl4eGhqlWrasKECapcuXL+ZzT4Q5cuXTJNmzY1P/30kzHGmA8++MAMHTq0ULKcOnXKvPTSSyYgIMC8/vrrxhhj4uPjTfPmzU1iYqIxxpiYmBjz5ptvGmOM2bVrl+nUqZNJSUkxNpvNhIeHm/nz5xdYvoMHD5q2bduaS5cuGWOM2bFjh2nZsuUdcyxfvtwMGDDAZGZmmoyMDPPMM8+YzZs3F1hGY4w5fvy4ad68ubl48aIxxpjY2FgzYMAAp8tpjDEXL140PXr0MLVr1zbnzp1zqtf7pvbt25uff/451zRnOpYZGRmmVatWZvv27cYYY3bu3Gnatm3rlMfSGGNsNpsZMGCAWbRokVMdR2NuHEt/f39z7NgxY8yNn53Q0FCnyvntt9+ali1bmjNnzhhjjFm/fr3p06dPgWRk2PYOvvrqK9WpU0d16tSRJD3zzDPat2+fkpKS7nmWlStXqkWLFhoyZIhjWlxcnNq0aaNKlSpJkkJDQ/Xpp58qJydHn3/+ubp06aJSpUrJzc1N/fr10/r16wssX+nSpTV58mSVK1dOkhQQEKBLly7dMcfnn3+ukJAQeXp6ytvbW7179y7QjJL08MMP68svv1T58uVls9l09uxZlS1b1uly2mw2jRo1Sq+++qpjmjO93pJ08eJFnT17VrNmzVK3bt0UFhamM2fOONWx/Oqrr1ShQgV16NBBktSmTRu9//77Tncsb1q2bJnc3Nw0dOhQpzqO0o1bjrm4uCg5OVnSjVuPeXt7O1XOH3/8UU2bNlXVqlUlSR06dNCRI0e0bdu2fM9Ied5BYmKiqlSp4njs6empsmXL6ty5c/c8y+jRoxUaGprrPnnnzp3Lla9y5cpKT0/X1atXbzuvIHPXqlVLrVq1knTjrgXR0dFq27btHXOcO3dOlStXvmcZb/Lw8NCBAwfUpk0brVy5UkOGDHG6nFOnTlWzZs3UsmVLxzRner0l6cKFC2rVqpXGjRunTZs2KSAgQC+++KLOnDnjNMfyxIkTqlixoiIjI9WrVy89++yzysrKcrpjKUkpKSmaP3++IiMj5eLi4nT/J319fTVx4kQ9++yzeuKJJ7RkyRK9+uqrTpUzICBA3333nU6dOiVJ2rBhg6Qb/1fzOyPleQfGmNuOezvTbclul+/mtN/Puxef0aWlpWn48OE6c+aMpkyZcscctzu+9+rYBgUF6euvv9bUqVM1bNgwp8q5efNm/fbbb/qf//mfW+Y50+v92GOPad68efLz85OLi4uef/55nTlzRq6urk5zLG02m77++mv17NlT69at03PPPadhw4bJZrM51bGUpFWrVqlFixZ65JFH/nC7hfmz8/PPP2vWrFnatGmTdu/ercjISP3tb39TTk6O0+Rs0qSJRowYofDwcIWEhCg9PV1lypQpkIzO0wJOqGrVqjp//rzjcVZWlq5cueIYEihsv893/vx5+fr6qnTp0redV9C5T5w4od69e6tkyZL64IMP9MADD9wxh5+f3y3z/v2vw4Jw+vRp7d271/G4Xbt2jpMGnCXn2rVr9dtvv6lnz57q0aOHJOm5555TxYoVner1Pnz4sLZt25ZrmjFG2dnZTnMsK1WqpBo1aigoKEjSjWFbd3d3p/vZkaTPPvtMISEhjsfO9rPz1Vdfyd/fXw8//LAkqVu3brLb7bLb7U6T89q1awoKCtL69eu1du1ahYSEKDU1VdWqVcv3jJTnHbRs2VL/+te/FB8fL+nGWXENGjRwfK5X2J588kl9+eWXjhd++fLlateunVxdXdW+fXtt2bJFKSkpysnJ0SeffOL43KcgnD17VqGhoerTp4+mTp0qLy8vSbpjjvbt22vdunXKysrS9evXtXbt2gLNKEnJyckaOXKkEhMTJUlffvmlXF1dNXjwYKfJuXTpUn322WfauHGjNm7cKOnG2Z8dO3Z0mtdbuvHH5OTJk3XhwgVJ0ocffqhatWrpueeec5pj+cQTT+jcuXP6/vvvJUkHDx5UVlaW2rVr51THMjU1VfHx8WrSpIljmrP97NSvX18HDx50/Ozs379fNpvNqX52Lly4oNDQUMfnsnPnzlVwcHCBHEu+qnIH5cqV04wZMzRmzBhlZmaqfPnymjp1amHHcnj00Uf12muv6fnnn1d2drZq1qypt99+W9KNXxrHjx9Xv379ZLPZ1Lhx49sOA+aXxYsXKyUlRZs2bdKmTZsc0xcsWKCQkJDb5ujbt69Onz6tp556StnZ2WrXrl2uv7wLQv369TVmzBj97W9/k6urqx544AEtXLhQ9erV06+//uo0OW/HmV5vSWrWrJleeuklDRkyRHa7XVWrVtW7774rPz8/pzmWDz74oObPn6/o6Gilp6fLzc1Ns2fPVt26dZ3qWCYkJKhcuXLy9vZ2TLtTjsL4P/n444/r5Zdf1pAhQ+Th4SEfHx+9//77aty4sU6ePOkUOWvWrKmwsDD169dPdrtdjz32mKKjo/XAAw/k+7F0McaYAtsTAACKIYZtAQCwiPIEAMAiyhMAAIsoTwAALKI8AQCwiPIEAMAiyhMAAIu4SAJQxNWpU0fe3t6O63G6uLioXr16ioiIcFyW7o+MHTtWPj4+Gj9+/L2IChQblCdQDHz00Ufy9/eXdOOuNrGxsRo2bJh27typ0qVLF3I6oPhh2BYoZlxdXdW3b19du3ZNv/32myRpx44d6t69uxo1aqQuXbpo165dtzwvOTlZr776qoKDg9WgQQN17NhRcXFxjvkzZsxQq1at1KxZM4WGhurIkSOSbtxJJzw8XM2aNVPr1q0VFhamS5cu3ZN9BQoL5QkUM2lpaVq4cKEqVKigRx55RMePH9eIESP00ksv6cCBA4qIiFBYWNgtN3WfPn260tPTtXnzZh08eFBdunTR5MmTJUl79+7V2rVrtWHDBu3du1dNmzZ1zFu0aJGuX7+u3bt3a/v27UpPT9fixYvv+X4D9xLDtkAxMGjQIMeN0t3d3VWvXj29//77KlGihLZu3aqmTZuqU6dOkm7chm358uXy9fXNtY4RI0bIw8NDnp6eOnfunHx9fR13HfHw8FBycrJWrVqlJ598UmFhYRoxYoQkycvLSz///LM2bdqk1q1ba+HChU51z1ugIFCeQDEQGxvr+Mzz9y5cuHDL/QkDAgJuu1xUVJTi4+NVo0YNVa5cWTfvGxEUFKTp06dr+fLlmjdvnsqWLavhw4erT58+GjZsmNzc3LRixQqNHz9edevW1fjx49WoUaP831HASfDnIVDMVa5c2XEPxpvmzZvnuE/tTaNGjVKrVq307bffatWqVerbt69j3rlz5+Tn56cPPvhA3333nSIiIhQZGalTp07p2LFj+utf/6r169fr66+/VmBgoEaPHn1P9g0oLJQnUMx17txZ+/fv144dO5STk6MvvvhCCxcuvOUs3JSUFHl5ecnV1VWnT5/WnDlzJN246fUPP/ygF154QcePH5e3t7fKli0rT09P+fr6avXq1XrjjTd09epVlS5dWj4+PipTpkwh7Clw7zBsCxRzNWvW1OzZszVjxgy98sorql69uubMmaNKlSrlWi4qKkrR0dGaNWuWKlSooGeeeUb//Oc/dezYMXXs2FHHjh3TkCFDlJKSIj8/P82cOVPlypVTRESE/v73v6tjx47KysqSv7+/pk2bVkh7C9wb3AwbAACLGLYFAMAiyhMAAIsoTwAALKI8AQCwiPIEAMAiyhMAAIsoTwAALKI8AQCwiPIEAMCi/wfsiC+cKHk2QgAAAABJRU5ErkJggg==",
+      "text/plain": [
+       "<Figure size 480x320 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
-    "# your code here"
+    "sns.set(style=\"whitegrid\")\n",
+    "plt.figure(figsize=(6, 4))\n",
+    "sns.countplot(y='Gender', data=titanic, hue='Gender', palette='Set1')\n",
+    "plt.title('Total Passengers Gender')\n",
+    "plt.xlabel('Pclass')\n",
+    "plt.ylabel('Gender')\n",
+    "plt.show()"
    ]
   },
   {
@@ -185,21 +576,48 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 101,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x640 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
-    "# your code here"
+    "plt.figure(figsize=(10, 8))\n",
+    "sns.boxplot(data=titanic, x=\"Pclass\", y=\"Age\")\n",
+    "plt.title('Summary Statistics of Age')\n",
+    "plt.xlabel('Age')\n",
+    "plt.ylabel('Passengers')\n",
+    "plt.show()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 102,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'\\nI think the boxplot it is a good method for summarizing and comparing data distributions across categories. You can visualize central tendency.\\n'"
+      ]
+     },
+     "execution_count": 102,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "\"\"\"\n",
-    "your comments here\n",
+    "I think the boxplot it is a good method for summarizing and comparing data distributions across categories. You can visualize central tendency.\n",
     "\"\"\""
    ]
   },
@@ -213,22 +631,56 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 103,
+   "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.figure(figsize=(8, 6))\n",
+    "plt.scatter(titanic['Age'], titanic['Fare'], color='blue', alpha=0.5)\n",
+    "plt.title('Fare vs. Age')\n",
+    "plt.xlabel('Age')\n",
+    "plt.ylabel('Fare')\n",
+    "plt.grid(True)\n",
+    "plt.show()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 104,
+   "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"
+    "plt.figure(figsize=(8, 6))\n",
+    "sns.scatterplot(x='Age', y='Fare', data=titanic, color='blue', alpha=0.5)\n",
+    "plt.title('Fare vs. Age')\n",
+    "plt.xlabel('Age')\n",
+    "plt.ylabel('Fare')\n",
+    "plt.grid(True)\n",
+    "plt.show()"
    ]
   },
   {
@@ -240,11 +692,29 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 105,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x640 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
-    "# your code here"
+    "numeric_columns = titanic.select_dtypes(include=['number'])\n",
+    "\n",
+    "correlation_matrix = numeric_columns.corr()\n",
+    "\n",
+    "plt.figure(figsize=(10, 8))\n",
+    "sns.heatmap(correlation_matrix, annot=True, cmap='coolwarm', linewidths=0.5)\n",
+    "plt.title('Correlation Matrix')\n",
+    "plt.show()"
    ]
   },
   {
@@ -256,12 +726,27 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 106,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'\\nEach square shows the correlation between the variables on each axis. \\nCorrelation ranges from -1 to +1. \\nValues closer to zero means there is no linear trend between the two variables. \\nValues close to 1 means a good correlation between them, that is as one increases so does the other and the closer to 1 the stronger this relationship is. \\nA correlation closer to -1 is similar, but instead of both increasing one variable will decrease as the other increases.\\n'"
+      ]
+     },
+     "execution_count": 106,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "\"\"\"\n",
-    "your comments here\n",
+    "Each square shows the correlation between the variables on each axis. \n",
+    "Correlation ranges from -1 to +1. \n",
+    "Values closer to zero means there is no linear trend between the two variables. \n",
+    "Values close to 1 means a good correlation between them, that is as one increases so does the other and the closer to 1 the stronger this relationship is. \n",
+    "A correlation closer to -1 is similar, but instead of both increasing one variable will decrease as the other increases.\n",
     "\"\"\""
    ]
   },
@@ -274,13 +759,31 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 107,
    "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"
+    "plt.figure(figsize=(8, 6))\n",
+    "sns.boxplot(data=titanic, x=\"Pclass\", y=\"Age\", hue=\"Pclass\", palette=\"Set2\", showfliers=False)\n",
+    "plt.xlabel(\"Pclass\")\n",
+    "plt.ylabel(\"Age\")\n",
+    "plt.title(\"Age Distribution by Passenger Class\")\n",
+    "plt.show()\n",
+    "\n",
+    "#I think the boxplot is the graphic where you can see easily the ages and Pclasses, it is very clear."
    ]
   },
   {
@@ -293,11 +796,29 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 108,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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djP9MqBdCCCGE35AERwghhBA+RxIcIYQQQvgcSXCEEEKIbubQoUM89NBDTJw4kZEjRzJ+/HjuvfdeDh482Ol1LViwgOuuu67Ty/U2SXCEEEKIbmTXrl1cdtll9O7dm48//pitW7eydOlSevXqxTXXXEN5ebm3Q+wRJMERooOcLs8t7NWVdQghupfHH3+cq666it/+9rdERkYCYLFYuPfee7nhhhuoqKigsbGR559/nsmTJzN+/HgeeughqqqqAFi/fj3Tp0/npZdeYty4cUyYMIHnn3++tfyCggLmzZvHyJEjueSSS8jKympT/zfffMPFF1/M6NGjmTNnDps2bWo9NmXKFP74xz9y1llnnXBXgu5CpokL0UE6VWHp6kzsDpdHyjfoVWZP7uuRsoUQ3VNhYSEZGRm89NJLxz1+6623AvDUU0+xe/duFi9eTGBgII8//ji///3v+dvf/gbA4cOHAVi7di3btm3jhhtuYPr06YwYMYJ77rmHPn368NNPP3Hw4EFuvPFG+vZtvtZkZGRw//338/rrr3PGGWewatUq/t//+398/vnnWCwWALKysvj666+7/crKkuAIcRrsDhcOp2cSHCGE/7FarQDExcW13vfPf/6T1157DQCHw8EVV1zB4sWLWbBgATExMQA8/PDDnH322W26r2699VYMBgNnnHEGSUlJHD58mKioKLZv387rr7+OyWRi0KBBXHHFFWzZsgWADz/8kAsuuICzzjoLgBkzZrB48WKWL1/OzTffDMC0adMwm82e/2WcJklwhBBCiG4iKioKgJKSEhITEwG44YYbuOGGG4DmRKapqYmGhgb+3//7fyiK0vpck8lEXl4eAGazuU0SYjAYcLlclJSUoNfriY6Obj2WlJTUmuAUFBSwfv16vvzyy9bjTqeTlJSU1tuxsbGde9IeIgmOEEII0U0kJyczcOBAlixZwl133XXCxxmNRhYtWkS/fv2A5pad7OxsevfuzebNm0/4PIvFgsPhwGq1tnY5tbQatRyfO3cuDz30UOt9ubm5hIWFtd4+OqnqzmSQsRBCCNGNPPXUU/zrX//ilVdeaU0+SkpKeOutt1ixYgUWi4XZs2fz5z//mfLycpqamnj55Ze5/vrrT7npZ2JiImeeeSbPP/88NpuNzMxMPvjgg9bjs2fP5qOPPmLz5s1omsbmzZu5+OKLWb9+vUfP2ROkBUcIIYToRtLT0/n444956623uPrqq6moqMBkMjFixAheeeUVJk+eTH19PX/5y1+49NJLqampYfDgwfzjH/8gICDglOX/5S9/4bHHHmPChAlYLBbOP/98MjMzARg9ejR/+tOfeOKJJ8jLyyMyMpL77ruPqVOnevq0O50kOEIIIUQ3k5SUxJNPPnnC44GBgfz+97/n97///THHxo4dy9atW9vc9+mnn7b+Pzo6mr///e8nLHvatGlMmzbtuMe++eabU4XebUgXlRBCCCF8jiQ4QgghhPA5kuAIIYQQwudIgiOEEEIInyMJjhBCCCF8jiQ4QgghhPA5kuAIIYQQwudIgiOEEEJ0MqdL84k6ejJZ6E8IL9I0jfpGJ7YGO00OF5EhJgJM8rYUoqfTqQpLV2did7g8Ur5BrzJ7cl+PlO0r5EoqhBfYHS4O5lexN7scW0PbvWPCgo2kxIcyJC36BM8WQvQEdocLh9MzCU5XWr9+PY8++igrV670dijtIgmOEF0sp6iGjXuKaLK7MBl19E0KIyjQgF6nUlpVj7XMxvYDpWQX1jBqQAwDekd6O2QhhOhxJMERoou4NI0dB0rZc7gck1HHGYMspCSEotf9PBSuPxE4XS52Hypn98EyHnx1LXdfNZIpY3p5MXIhRE+2fv16XnjhBRITE9m/fz+apvHQQw+xaNEiDh48SO/evXnttddYsWIF//3vf3E4HJSVlTFnzhzuvPPOY8p7++23+fzzz9E0jaioKB599FFSU1O9cGYnJwmOEF3A6dL4fls+BaV1RIUFcPbwBMwBhuM+VqeqpPeJJjU+jJ92FfLKoq0YdDrOGZnYxVELIXxFRkYGf/jDHxgxYgSPPPIITz75JMuWLSMwMJBZs2bx5Zdf8t///pe//e1vxMTEUFBQwHnnncfcuXPblLNs2TK2b9/OBx98gNFoZNWqVdxxxx189tlnXjqzE5MERwgP0zSN9TsLKSitIyU+lDOHWNCpp57AGB5i4ulbJ/Dw377nhf9uxmhQGTs0vgsiFkL4GovFwogRIwBITk6mqamJkJAQABISEmhsbOTtt99m9erVZGdnk5WV1TwJor6+TTnffPMNO3fu5PLLL2+9r7KyksrKSsLDw7vqdNwi08SF8CBN09i6r4TsohqSYoMZOyTOreSmRXx0EE/dOp4Qs4GX3t9CcbnNg9EKIXyV0Whsc9tgaNuCXFJSwkUXXUR2djbDhw/n4YcfBpqvYUdzuVzccMMNLFu2jGXLlvHRRx+xZMkSwsLCPHsCHSAJjhAelJVfxb6cCmLCAzkrPR5VVdpdRrIlhPuuHo2twcFfFm3BJWtfCNEjGPQqep1nfgz6zv34NplMBAUFcccddzBp0iS+++47NE3D5Wo7C2zixIksWbKEqqoqAP71r38xb968To2ls0gXlRAeUlXbyJa9xZgD9EwcmdhmMHF7jRoYy8wJqXz2wyGWfZcl618I0c05XZrH36dOl4auA1+ajsdoNJKamsr06dMJCgqib9++pKamcvjwYUwmU+vj5syZg9Vq5ZprrkFVVcLDw3nttddQlM6JozNJgiOEBzidLn7MKMTl0hifHo/RoDvtMm+4cDDb9hfzr8/3MGaQhWRLSCdEKoTwhM5KPDqjjrFjx7ZZw+a3v/1tm+MLFiwA4LrrrjthGS3PVxSFO+64gzvuuKO94XY56aISwgO2Z5ZSWdPIkLQoYiLMnVJmgFHP3VeOwuF08e5nuzulTCGE8FWS4AjRycqrG9ifXUFUWABD0qI6texBqZFMGJbA+l1F7DpY1qllCyGEL5EER4hOpGkam/ZYAThjsKVDg4pP5foLBqFTFRZ+uuuYGQ5CCCGaSYIjRCfKyq+irKqB/r0iiAgJ8EgdCTHBTB/Xm33ZFazLKPRIHUII0dNJgiNEJ2lscrL9QAmBJh3pfTu3a+qXrpo2gECTjv98uVdacYQQ4jgkwRGik+w6VEaT3cWI/rEY9Kc/a+pkIkICmDY2hZyiGrbuK/FoXUII0RNJgiNEJ7A12DmQW0l4iInecV0zffuic9JQVYWlazK7pD4hhPs0l9Mn6ujJZB0c4XOaF5zq2kWndmaV4XJpDO8b3WULXsVGmpkwLIG12/I5XFjdJXUKIdyjqDoqfvoEzWn3TPk6AxHjLnLrsW+88QaLFi1ixIgRvPzyyx6JB2DKlCnMnz+fMWPGeKyO9pAER/gcRVHQ6VSWrs7E7nCd+gkdEGjSMeucPgBU1zVxsKCKmPBA4qODPFLfiVwyqQ9rt+Wz7LuDTBrQpVULIU5Bc9rB6fBM2e147OLFi3nmmWcYP368R2LpriTBET7L7nDhcHomwbE7fu7d3ZlViqbB8H5d13rTon+vCIakRbF2Wz6jesV1ad1CiO7vrrvuwmq18n//93/MnTuX/fv3s2fPHux2O8OGDeORRx4hODiYKVOmMGvWLL799lsqKiqYN28eJSUlbNy4kerqap599llGjx5Nbm4u//d//0ddXR3FxcUkJSXx8ssvExkZ2abe7du38+c//5m6ujo0TeOGG27gkksu6dJzlzE4QpyG6romcopqiIsyd9qKxe110TlpOJwa2w7WeaV+IUT39de//pXY2FieeeYZ9u/fT1paGh999BGffPIJwcHBvPjii62Prays5JNPPuHFF1/k+eefZ/To0Xz44YfMnj2bf/zjH0Bza9CMGTNYtGgRq1atQqfT8fHHH7eps6qqigceeICnn36apUuXsnDhQl5//XW2b9/elafunRacl19+mZKSEp5++mkAXnvtNVasWIGqqkRFRfH444+TmpqKy+Xiz3/+M9988w1Op5NLLrmE22+/vVtu6iX80+5DZWjAkFTPTgs/mTOHxBEWbGRrlk2mjAshTuibb75h69atfPLJJwDY7Xaion6+ds2YMQOAXr16ATBp0qTW29999x0A99xzD+vWrWPBggVkZ2eTlZXF6NGj29Szbds2SkpKuOuuu1rvczgc7Nq1i+HDh3vuBH+hSxOcvLw8nn32Wb7//nsuvPBCAJYvX863337L4sWLMZvN/Pvf/+bBBx9k8eLFLFq0iJ07d7J8+XJcLhfz5s0jNTWVmTNndmXYQhxXeXUDWXlVRIUFEBMR6LU49DqVyaOSWPbdQXYfKmdYv1ivxSKE6L5cLhcvvPACgwcPBqC2tha7/edB0AaDoc3jf3kb4He/+x02m42ZM2cyfvx46uvrj/li5XQ6SU5OZtmyZa33FRcXExYW1pmnc0pd2kX1wQcfMH78eObNm9d6X+/evXn00Ucxm5ub94cNG0Z+fj7QvHvpZZddhtFoJCAggDlz5rB06dKuDFmIE/rkuyxcmsbg1Eivtyqef0YyAKs25no1DiFE93XOOefw7rvv4nQ6cTqdPPzww/zlL39pVxnfffcdt956K7NmzSIkJIR169bhdLadrj5ixAiKior4/vvvAcjNzWXmzJns3t21mwR3aQvO/fffD8Crr77aet+wYcNa/9/Y2Mif//xnLrjgAgAKCwuJi/t54GRcXByFhR1bmt7lch3zR/BlLefqT+cMbc9X01y4XJ4ZZNzYZGfFusOEBRmJjzJ7pB7tyNcPd/6GCdFmkqKM/LCjgJsvGkJQ4LHfvHyRv7/O5by972SxKDpDu2Y7tYeia/97/NFHH+XZZ5/loosuwul0kp6ezkMPPdSuMn73u99x//33ExYWhsFgYOzYsWRnZ7d5TGRkJH/729944YUXmD9/Pg6HgwcffJCRI0eetOxf/i5P97qqaF7otH/11VcpKipqHYMDzc1Xd911F5GRkbz88ssYjUamT5/Ok08+ydixYwH44YcfeO6551i+fLnbddlsNvbs2dPp5yC6L1VVGTlyJH/99xqa7J65EBZXOdmTa2NIbzPRIZ5Ztdho0HHXtZPYunWrW2/0zZl1LN9QwYVnhDOmX7BHYhJCHN+IESPQ6X6+FmguJ4rq2RXNu6KOruB0Otm2bdsJjw8aNKi1l6c9usU08e3bt3PHHXdw8cUXc99996GqzV9dExMTsVqtrY+zWq3Ex8d3qI6+ffsSHOw/F32n00lGRgbp6elt3nS+zul0smvXLgAsFotH1sHRNI0tB7MJDTIyrH8iLg99RTDom98HR7dynojT6aTRvp2vtlZzoFjh5stHeCaobsafX+dy3t3jvFti+qWuSDx8Ibk52i//rrW1tWRmdnyldq8nOLt27eLGG2/kySefPGbw8NSpU/noo4+YMWMGLpeLJUuWMHv27A7Vo6pqt3lDdCWdTueX5w2gKCqqB0aZ5ZfUUmOzc/l5/dDr9R5ba0dRmoN39+9nMqicOdjC2u0FlFU3Euulaeve4K+vczlv4Ut++XdVT/MC7vV1cF599VVcLhdvvfUWF198cesPwBVXXMGQIUOYPXs2F110EcOHD+eyyy7zcsTC3x3IqURR4FdnpXo7lGNMGJ4AwPfbCrwciRBCeJdXWnDuvPPO1v+/8cYbJ3ycTqfjgQce4IEHHuiKsIQ4pZq6JgrL6ugdF+rVqeEnMmpADOYAPWu353PpuX29HY4QQniN11twhOhJ9udWAjAoJfLkD/QCVVUxGnSMHRJHZm4lhaWysrEQwn95fQyOED2Fw+niUEEVoUFG4qI8P75FVRWcLg2deuo1dnQ6XesUzHNGJPLt5jy+357P5ef1P+nz3C1fCHFy3Wnqek/jqd+dJDhCuCmvuBa7w8XQPmFdsrCfqijoVMWtXdE1zYXVasViseDSFIwGleVrD3KyRSAMepXZk6UbS4jToSgKer3+uDOphPv0en2nX1clwRHCTQfzq1AVSI0P7dJ63dkV3eVy0WR3Yne4UFWVpNgQDuZXUV7dQGiQsYsiFcL/qKpKenq6R/eB647T4zuboiinPWvqlyTBEcINNbYmrOU2ki0hmIzd/22THBvMwfwq8oprGOzFjUCF8Aed/cF8IjI9vn1kkLEQbjiUXwVAn8Su3SyuoyxRZvQ6hfySWm+HIoQQXiEJjhCn4HJpHCyoxhyg75LBxZ1Bp6rERwdRWtlAfaPD2+EIIUSXkwRHiFMoKqujvtFBWkLXDC7uLIkxzVuTFEgrjhDCD0mCI8QpHC6sBiA1oWsHF5+uhJhgFAXyS2Q9HCGE/5EER4iTsDtc5BXXEh0eQLC5Z81GMhl0xIQHUlRW57H9soQQoruSBEeIk8grrsHp0kjp4qnhnSUxNhinS6OoTFpxhBD+RRIcIU7icGE1igK9LD0zwUk6Mg5HuqmEEP5GEhwhTqC+0YG1zEZCdDAmY89ceyLYbCQ0yEhhaa1HFyITQojuRhIcIU4gu6gaDXps91SLhOgg6hudVNY0ejsUIYToMpLgCHEC2YU1GPQqCTFB3g7ltMRHN8dfKONwhBB+RBIcIY6j1tZEeXUDiTHB6HU9+20SExGIXqdQUCoJjhDCf/TsK7cQHpJjrQGgV1yIlyM5fTpVxRJpprSynia709vhCCFEl5AER4jjyLU2d0/FRfXs7qkW8VFBaBpYy23eDkUIIbqEJDhC/EKNrYny6kaSYoPRqT1na4aTaR2HI91UQgg/IQmOEL+Q29I9Zen53VMtgs1GQsxGCkrrZLq4EMIvSIIjxC/kFDV3T1l8pHuqRfN0cQdVtU3eDkUIITxOEhwhjlJja6Kixre6p1rERZkBKCqXbiohhO+TBEeIo+RZawFI9qHuqRYxEWZUBaxlMtBYCOH7JMER4ih5JTXodQpxkWZvh9LpDHqVqPBAiitsuFwyDkcI4dskwRHiiPpGB6WVDcRHB6Pr4Yv7nUhcpBmHU6O0qt7boQghhEf55lVciA7IL2nunkqKDfZyJJ7Tsq6PdFMJIXydJDhCHJFXXIuqNM828lWRoQEY9KoMNBZC+DxJcIQA7A4n1jIbsZFmjAadt8PxGFVViI0wU1bVINs2CCF8miQ4QgAFpXW4NI2kWN+bPfVLcVFm2bZBCOHzJMERgubuKYDEGN8df9OiZT2cwjLpphJC+C5JcITfc7k0CkvriAoNwByg93Y4HhdiNhJo0stAYyGET5MER/i90sp67A4XCTG+O7j4aIqiEBsRSGVtI1W1jd4ORwghPEISHOH3WqaHJ/hB91SL2CMLGe48WOblSIQQwjMkwRF+r6C0jkCTnogQk7dD6TKWiCMJTmaplyMRQgjPkARH+LUaWxPVdU0kRAehKL61uebJBJsNmE16dmRJgiOE8E2S4Ai/VlDSPJPIn7qnoHkcjiXKTE5RDZU1Mg5HCOF7JMERfi2/pBZV9c3NNU/FcuScd8k4HCGED5IER/gtu8NJSYUNS6QZvd7/3gqWyOZZYxnSTSWE8EH+d1UX4ghruQ2X5tt7T51MiNlAVFiAJDhCCJ8kCY7wW4WlzeNv4v00wVEUhfQ+0TIORwjhkyTBEX5J05pXLw42GwgxG70djtek940GZByOEML3SIIj/FKNrYm6BgfxUf7ZetMivU9zgrMjs8TLkQghROeSBEf4pcLS5n2Y/LV7qkVclJnosAAysqQFRwjhWyTBEX6psLQOVVFaV/T1V4qiMLRvNLlWGYcjhPAtkuAIv+NwuiiusBETEeiX08N/qaWbaudBmU0lhPAdcnUXfqekoh6nS/P77qkWLQlOhuxLJYTwIV5JcF5++WX+8Ic/tN5etmwZM2fOZPr06dxzzz3U1ta2HluwYAEzZsxg6tSpPPHEE9jtdm+ELHxI6/RwPx9g3CIuykx0eKCMwxFC+JQuTXDy8vK4/fbbWbhwYet9Bw4c4Pnnn+edd97hyy+/JC4ujvnz5wOwZs0aPvzwQxYvXswXX3xBeXl5m+cK0RFFZc27h4cF++/08KM1r4cTRa61hoqaBm+HI4QQnaJLE5wPPviA8ePHM2/evNb7Vq1axaRJk7BYLADMnTuX5cuX43K5WLlyJTNnziQkJASdTsfVV1/N0qVLuzJk4WNsDQ6q6pqwRJr9avfwU2kdhyOtOEIIH6Hvysruv/9+AF599dXW+woLC4mPj2+9HRcXh81mo7KyksLCQkaOHNnmWGFhYYfqdrlcOJ3ODkbe87Scqz+dM7Q9X01z4XK52hwvKmvu/rREBh5zrD00zXXCOjpLe+rQNK31X3fj0Y58vXE6nQxOjQCa18MZnx7XwYi7nr+/zuW8/YO/nvfpXlu7NME5keN9k26575fHOvqtOzMzs0PP6+kyMjK8HUKXU9XmT26r1UqTve0F4XB+PQCKo5aiIluH6wg2G4H+FBcX09jk6HA5nV2H1Wp1u3yjQQcMZMeOHTidTkLNOjbvzmdbas+7iPrj6xzkvP2Nv553R3k9wUlISCAvL6/1ttVqJSgoiLCwMBISEtpcsK1WKwkJCR2qp2/fvgQHB592vD2F0+kkIyOD9PR0dDqdt8PpMk6nk127dgFgsViwO37+BqBpGuv3HyI0yEjv5I69jloEmprfOrGxsW3q6EztqUPTNKxWKxaLxe0vAYYjU+SHDRsGwMi9W1mzNZ+0foMJDeoZ45P8+XUu5y3n7etqa2tPq3HC6wnOeeedx4033th6cf7Pf/7D+eefj6qqTJ06lfnz5zN37lyCg4NZtGgR06ZN61A9qqr61QujhU6n88vzBlAUFfWoUWZVtY00NDnpHRfa2spzOmUfr47O1J46WppyFUVx+9xaym95fQztE82arfnsza7grPTTSwC7mr++zuW8/Yu/nffpXqe9nuD069ePBx98kJtvvhm73U5qairPPfccABMnTiQrK4urr74ah8PBqFGjuO2227wcseipisqau6QsUf69evGJDEmLAmDnwbIel+AIIcQveSXBufPOO9vcnjVrFrNmzTruY+fNm9dm1pUQHVVUVoeiQKyfb89wIkmxwYQHm2QmlRDCJ8hKxsIvuFwaxRU2osMCW8eeiLYURWFIWhSHCqqoq5cFNYUQPZtc6YVfKKtuwOHUpHvqFIakRaFpsOdwubdDEUKI0yIJjvALxeVHxt9ESoJzMkP7HBmHkyX7UgkhejZJcIRfsJbb0KkKUWEB3g6lW+sdF0pQoIGdB2UcjhCiZ5MER/g8p0ujtLKe6PBAdJ6a0+0jVFVhSGoUmbmVNDR6ZgFDIYToCnK1Fz6vvKoep0sjNiLQ26H0CEPSonC6NPZmyzgcIUTPJQmO8HnFFc3bM8TK+Bu3tI7DkW4qIUQPJgmO8Hky/qZ9+iSGEWDUsUsSHCFEDyYJjvBpMv6m/XQ6lUEpkezLrjhms1IhhOgp5IovfJqMv+mYoX2isTtcHMit9HYoQgjRIZLgCJ9mPTL+Rta/aZ+f96WS9XCEED2TJDjCpxUfGX8TKeNv2qV/r3CMelX2pRJC9FiS4Aif5XS6ZPxNBxn0Ogb0jmTv4XIcTpe3wxFCiHaTq77wWWVVDc3jb6R7qkOGpEXR0OTkYH6Vt0MRQoh2kwRH+Kyilv2nZIBxhwxNk32phBA9lyQ4wmdZy+tk/M1pGJASgU5VZME/IUSPJAmO8El2h5OSChl/czoCjHr6JYez+2AZTpfm7XCEEKJd5MovfNL+nEoZf3MKqqqcMnEZkhZFXYOD7MLqDtcjyZEQwhv03g5ACE/IODJuRMbfnJiqKOhUhaWrM7E7jj9TqqKmEYD3VuxhUEpku+sw6FVmT+57WnEKIURHuNWC8+WXX9LU1OTpWIToNBmZpUfG30iCcyp2hwuH8/g/ESEmFMBaVnfCx5zs50SJkxBCeJpbCc5jjz2GoiiejkWITuFwauw9XE5MhBmdKq/b02E06AgPMVFcUY+mSVeTEKLncCvBGTt2LP/73/+ora31dDxCnLb8siaaHC4skdJ60xliI8002p1U10krrhCi53BrDM7evXtZuXIlTz31FAEBAW1ac7Zs2eKx4IToiJyS5nEjsREywLgzxEYEsi+7gpKKesKCTd4ORwgh3OJWgvP00097Og4hOk12cQM6VSE6XFpwOkPMkd9jcYWNvsnh3g1GCCHc5FaCc+aZZwJQUVFBXl4eQ4YMweFwYDQaPRqcEO3lcmnkljTRNykcvU6VfZQ6gcmoJyzY2DoOR8bjCSF6ArfG4FRXV3PHHXdw1llncf3113P48GGmTJnCvn37PB2fEO2SV1xLfZOLQantn9IsTiw2wkx9o4Paeru3QxFCCLe4leA8++yzBAYGsnbtWvR6PSkpKVxyySXSdSW6nT2HywEYnBrl5Uh8S8yR9YRKKuq9HIkQQrjHrS6qtWvX8tVXX2E2m1EUBVVVueuuu5gwYYKn4xOiXXa3JjiR5FprvByN72gZsF1cYSMtMczL0QghxKm51YJjMBhoaGhoc19tbS3BwcEeCUqIjtpzqJzoUL3M9ulkgSY9IWYDxdKCI4ToIdxKcGbMmMFdd93Fli1b0DSNrKwsHnnkEaZPn+7p+IRwW2llPcUV9fSKkeTGE2IizNTV26lrkHE4Qojuz60E595772XgwIHceOON1NTUcOmll2KxWLjnnns8HJ4Q7ttzqLl7qnesJDieECvjcIQQPYhbY3CMRiOPPvoojz76KOXl5URERMhUUdHt7D5UBkAvSXA84uhxOCnxoV6ORgghTu6kCc7HH398ygIuueSSTgpFiNOz+1A54cEmIoPdyttFOwUFGjAH6KUFRwjRI5z0k2DBggUA2O12srOzsVgsJCYmUlxcTG5uLiNGjJAER3QLdfV2DhdWMXZonLQuelBshJnDhdU0NDoIMEkiKYTovk56hVq+fDkAjz/+OHPmzOHmm29uPfbee+/JPlSi29iXXYFLg0EpkYBsCuspsRGBHC6sbh7MHRfi7XCEEOKE3Bpk/OmnnzJv3rw2911zzTWsXr3aEzEJ0W4t428Gp8gKxp4Uc9Q4HCGE6M7cSnCioqL48ccf29z3zTffEB8f75GghGiv3YfKCTDqSE2Qwa+eFGI2EGjSYy2XBEcI0b251Yl+zz338Nvf/pazzjqLuLg48vPz2bx5M6+88oqn4xPilOwOF/tyKhiUEoFO51bOLjpIURQskc3jcOobHQTKOBwhRDfl1qfBBRdcwEcffUR6ejoAI0eO5OOPP2bSpEkeDU4IdxzMr6TJ7pT9p7qIJbK5m0pacYQQ3ZnbX7/69etHv379PBmLEB2y+9DP+08Jz7NE/ZzgyHo4Qojuyq0EZ926dfzpT3/i8OHDaJrW5tiePXs8EpgQ7tp9qAxVVejfK8LbofiFoAADIWYD1rI6NE2TaflCiG7JrQTn2WefZfz48TzzzDPo9dLnLroPTdPYfaictIRQzAEGnE6nt0PyC5ZIM5l5VdTW2wkxG70djhBCHMOtbCU3N5clS5ZgMBg8HY8Q7VJQWkd1XROTRiV5OxS/YokMIjOvCmu5TRIcIUS35NYg4+HDh7N3715PxyJEu+093Dz+ZlBvGX/TlWSgsRCiu3OrBSctLY1f//rXTJo0iaiotjNVHn30UY8EJoQ79mZXADAgRcbfdCWTUUd4iAlrmU3G4QghuiW3Epz6+nqmT58OQF1dnUcDEqI99h4uJzI0gJjwQG+H4nfiIs3sza6gsraRiJAAb4cjhBBtuD3I2NNWrVrFK6+8gqqqBAcH8+STT9KnTx8WLFjA4sWLcTqdnH322fz+97+XsUACAFuDnZyiasalx0sLghdYjiQ41nKbJDhCiG7H7WVfv/nmG2699VZmz55NSUkJzzzzDHa7vVOCaGho4L777uMvf/kLy5YtY8aMGTz++OOsWbOGDz/8kMWLF/PFF19QXl7OwoULO6VO0fMdyKnEpcFAGX/jFTERZhQFrGUyDkcI0f24leB88MEH/OlPf2LUqFHk5uai0+lYv349zz//fKcE4XQ6URSFqqoqAGw2GwEBAaxcuZKZM2cSEhKCTqfj6quvZunSpZ1Sp+j59mY3DzCWBMc7DHqV6LBAiitsuFzaqZ8ghBBdyK0uqoULF/LGG28wYMAA3n77bSIjI3nzzTeZM2dOpwwyDgoK4oknnuDXv/41kZGRNDY28q9//Yv58+czcuTI1sfFxcVRWFjYoTpcLpdfrZHScq6+fM57Dpej1ymkxAcf93w1zYXL5fJI3Zrm6lZ1tCzAqWma2/F0xjnERgRSUllPaaWN6OOMg9KOfIXy1OvQH17nxyPnLeftD0732upWglNRUdG6TUPLWIeYmJhO66Lat28ff/3rX/nkk09IS0tj+fLl3HLLLfTp0+eYsRUdHWuRmZnZGaH2OBkZGd4OwSM0TWP3wVIs4QZ272p7jjqdDgBFUVE9tPemojQXXFJSQkNj57wPfinYbAT6U1xcTGOTw63nWK1Wj5b/S3qan5eVU4yjwXTMcaNBBwxkx44dHksEwXdf56ci5+1f/PW8O8qtBGfIkCH885//5MYbb2y9b8mSJQwaNKhTgvj+++9JT08nLS0NgFmzZvHcc8/hdDrbXLCtVisJCQkdqqNv374EBwd3Srw9gdPpJCMjg/T09NYPfF+SX1xLfVM+owYlMmLEkNb7nU5n6/YhDfn7sTc2eaR+JdgM9G1O9B2e+eBu2ak7Njb2lHVomobVasVisbj9JaA95Z9IjEtjZ3YWNruOuLi4Y44b9M2J4LBhwzpU/qn4+uv8ROS85bz9QW1t7Wk1TriV4Pz+97/nxhtv5IMPPsBms3H55ZdTWFjIO++80+GKjzZkyBAWLlxIUVERcXFxbNy4EYfDwQ033MBLL73E3LlzCQ4OZtGiRUybNq1Ddaiq6lcvjBY6nc4nz3t/bvN4rUGpUSc+P00DPDQ25EiXUFe0ErlTR0vriKIoqG4G1J7yT0RVISYikOLyelwa6HVtC2qpw9OvQV99nZ+KnLd/8bfzdvdadiJuJTh9+/bliy++YPXq1RQUFGCxWJg8eTIhISGnVXmLcePGcfvttzNv3jwMBgNms5m///3vjBo1iuzsbK6++mocDgejRo3itttu65Q6Rc8mA4y7j7jIIIrKbJRW1hMXFeTtcIQQAnAzwQEwm82kpqbSu3dvoHlcTmclOABXX301V1999TH3z5s3j3nz5nVaPcI37MuuICosgJgIWeDP2yxRZjgARWU2SXCEEN3GSRMcu93OH//4RxISErjzzju58sorsdvtaJpGYGAgn332WYfHxAjRUbYGO9lF1YxPl9dedxARYsJk0FFUVgfEeDscIYQATrEOzptvvsmhQ4e47LLLADCZTOzZs4e9e/dy1llnyaJ7wiv251SgaTBQ9p/qFhRFIS7KTEVNI/WNHZuNJYQQne2kCc6KFSt4/PHHW1tpjp6dcdttt/Hdd995NjohjqNlg00Zf9N9xEc3d001t+IIIYT3nTTBKSgooH///q23W8bfAKSnp1NcXOy5yIQ4gb2Hy9HrVPokhXk7FHFEy9ibwlJJcIQQ3cNJExyj0djm9uLFi1v/39TURECAbLAnupamaezLrqBPUhgGvf9Ml+zuAk16IkJMFJbZcGmybYMQwvtOmuD079+fdevWHffYd999x+DBgz0SlBAnkl9SS229nQG9ZfxNdxMfHUST3UlFdYO3QxFCiJMnOFdeeSVPPPEEBw4caHN/dnY2zz77LNdcc41HgxPil/YelvE33VW8dFMJIbqRk04Tv/DCC9m7dy+zZ89mxIgRxMXFUVJSwubNm7nppps477zzuipOIQBZ4K87iw4PRK9TKSyrY2ifaG+HI4Twc6dc6O93v/sdF198MStXrsRqtdK7d28efvjhTtuHSoj2kAX+ui9VbZ4unl9cS6PdickgY6SEEN7j1krG/fr1a91NXAhvkQX+ur+E6CDyimspLK0jJT7U2+EIIfyYh7YJFKLzyQJ/3V9CTDDQPBhcCCG8SRIc0WPIAn/dX6BJT2RoAIWldbhcMl1cCOE9kuCIHkMW+OsZEmOCsDtclFTWezsUIYQfczvB0Y5avGvjxo3HTB0XwpNcLvcX+FNVydu9SbqphBDdgVufBGvWrGHixIlA8wacN910E3PmzGHJkiUeDU74JmcHui5aFvg7VfeUTqcjPT29+cZRe6eJrhMRYiLQpKdAEhwhhBe5NYvqtdde4+6778blcvHuu+/y2muvERMTw913392607gQ7tKpCktXZ2J3uNx+TmZeJQAV1Q38b9X+Ez5O01zU1VRx46VjJcHxEkVRSIwJIjOviqraRm+HI4TwU24lODk5OcyZM4cdO3bQ1NTEhAkT0Ol0lJaWejo+4aPsDhcOp/sJTnG5DYCIUNNJn+dyuWiyO047PnF6EmKCycyrIq9YWnGEEN7hVhdVUFAQubm5fPHFF4wZMwadTsfWrVuJiorydHxCAFBaVY/ZpMccYPB2KMINlkgzep1CrrXG26EIIfyUWy048+bNY+bMmbhcLhYuXMi2bdu48cYbeeSRRzwdnxA02Z1U1TaRbAnxdijCTXqdSkJ0MDnWGsqq6okKk5WnhRBdy60EZ9q0aUyaNAm9Xk9CQgLl5eW89957DB061NPxCUHZkd2po8MDvByJaI8kS3OC89POImZOSPV2OEIIP+NWF9Xs2bOJjIwkIaF5ifzIyEhJbkSXKTuynkq0tAL0KAnRwaiqwo87CrwdihDCD7mV4MTExJCTk+PpWIQ4rtLKBlRFISLU5O1QRDsY9CoJ0UHsPFgms6mEEF3OrS4qi8XClVdeSb9+/YiNjW1z7I033vBIYEJA8wKTpVX1RIaa0MkCfj1OL0sIecW1bNhVxNSxvb0djhDCj7iV4AwbNoxhw4Z5OhYhjlFd14Td4SIqXLqneqIkSwi6XUX8mFEoCY4Qoku5leDccccdno5DiOMqrToywFjG3/RIJoOOYX2j2ba/hNp6O8GBMs1fCNE13Grz1zSN9957jwsvvJCxY8dSUFDA7bffTk2NrHEhPKt1gLHMoOqxzhmRiMPpYp0MNhZCdCG3Epw33niDDz/8kN/+9re4XC5CQkKw2Ww8+eSTno5P+LnSynrMAbLAX0921rAE9DqVNVvzvB2KEMKPuJXgfPjhh/z973/nggsuQFEUQkJC+Mtf/sLatWs9HZ/wY012J1V1TdI91cMFBxoYMyiWjMxSyo+saSSEEJ7mVoJjs9mIjo4GmrurAMxmM4psZig8qGWBvyjpnurxJo1KwqXB99vyvR2KEMJPuJXgnHHGGbzwwgs4nc7WpOaNN95g1KhRHg1O+DdZ4M93nDE4jkCTTrqphBBdxq0E5w9/+AMbN25kzJgx1NbWMmHCBFauXMmjjz7q6fiEHyutbEBVFSJCpQWnpzMZdIwbGs/+nEoKSmWHcSGE57m90N+SJUvYuXMn+fn5WCwWhg0bhl7v1tOFaLe2C/xJV6gvmDQqiW8357Fmcx5XTx/o7XCEED7OrQxl48aNrf+Pjo7G6XSydetWDAYDERER9O4tC3iJztWywJ90T/mOEf1iiAgxsWpTLldOHYAqiasQwoPcSnAefvhhCgoKUFWViIgIKisrcTqd6HQ6HA4HvXv35o033iA1VXYMFp2jZYG/KElwfIZOpzJlTDJLvs0kI6uU4f1ivB2SEMKHuTUGZ+bMmcyZM4eNGzfy/fffs2nTJubOnctvfvMbtmzZwnnnncdTTz3l6ViFH5EF/nxTy3YNK9fL5r1CCM9yK8FZunQpjz32GGazGYCAgAAefPBB/ve//2E2m7nnnnvYsWOHRwMV/kUW+PNNiTHBDE6N5MeMAmptTd4ORwjhw9zeqiE3N7fNfbm5uTgcDgAaGhowGOSDSHQOWeDPt009szd2h4s1W2VNHCGE57g1Bufaa69l3rx5XHvttSQkJFBQUMD777/Ptddei9Vq5Z577mHq1KmejlX4ibIqWeDPl00YnsBbH+9g5YZsZk6QcXtCCM9wK8G59dZbiYuLY9myZRQVFREfH88DDzzABRdcwN69eznvvPO4/vrrPR2r8BOlVbLAny8LNOmZODKJL3/KZn9OBf17RXg7JCGED3J7IZtLLrmESy655Jj7Bw4cyMCBsqaF6DyllfWywJ+PmzkhlS9/ymb59we5/5rR3g5HCOGD3Epw9u3bxwsvvMDhw4dxuVxtjn399dceCUz4J03TKKtqkAX+fFxqQhhD0qL4fls+N84aQkSIJLNCiM7lVoLzxz/+kdjYWO655x5ZvVh4lCzw5z9mnZ3GroNlfPlTNldNHeDtcIQQPsatbOXAgQO8++67BATItyzhWaWt699IguPrxg2NIzosgBU/HmbOlH7odW5N6hRCCLe4dUVJS0vDarV6OhYhZAVjP6LTqfxqfCrl1Q38uKPA2+EIIXyMWy04EyZM4Ne//jUXXnghUVFRbY7NmzfPI4EJ/1RaWU9QgAFzgHSF+oPp43rzwar9LPk2k3NGJKIoMu5KCNE53PoU2bJlC8nJyWzfvr3N/YqidFqCc+DAAZ588klqampQVZU//vGPjBgxgmXLlvHWW2/hcDgYNGgQTz31FMHBwZ1Sp+heGu1Oquua6B0X4u1QRBcJCzYxbWwvPv3+EFv3lTBqYKy3QxJC+Ai3Epz33nvPo0E0NDRw44038thjjzFt2jRWr17Nvffey1tvvcXzzz/P0qVLsVgsPPfcc8yfP58nn3zSo/EI75DxN/5p9uS+rPjxMP/7er8kOEKITuP2qL69e/fypz/9idtvv52KigrefffdTgvi+++/JyYmhmnTpgEwadIk/v73v7Nq1SomTZqExWIBYO7cuSxfvvyYqerCN7QkODGS4PiV2Agzk0cnsetgGXsOlXs7HCGEj3ArwVm1ahXXX389DoeDn376iaamJt555x1ee+21Tgni0KFDxMbG8uijj3LppZfy61//mqamJgoLC4mPj299XFxcHDabjcrKyk6pV3QvpZX16HUKYcEmb4ciuthl5/ZDUWDxN/u9HYoQwke41UX117/+lb/97W+cccYZfP7551gsFhYsWMDNN9/MHXfccdpBOBwOfvjhBxYuXMhTTz3FmjVr+M1vfsOUKVOOO+iwIwMRXS4XTqfztGPtKVrOtTues06nQ9NcbVriXK7mBf6iwwMADZdL61DZmqYdfaPt7c50pNxfnkfnVuFyuw6tNR7N7XjaU35HaUe+Qp3qdZgQbeasofH8mFHInkOlbm/f0J1f554k5y3n7Q9O97rkVoJTWFjImDFjgJ+Tiz59+lBXV3dalbewWCykpKS01jFp0iT0ej0JCQkUFRW1Ps5qtRIUFERYWFi768jMzOyUWHuajIwMb4fQhqqqjBw5EqvVSpP95zdrTb0Tp0vDpHO2+Zt3RLC5uQXIZqujwVZ/WmWd0JEcu6SkhIZGu0eqCDYbgf4UFxfT2ORw6zntWc6hI+W3l9GgAwayY8eOU16sRvRysW4n/H3xJn59Xky76ulur/OuIuftX/z1vDvKrQSnT58+rFixggsuuKD1vm+//Za0tLROCWLixIk888wzbNu2jREjRrB582aampo4//zzueWWW7BarVgsFv7zn/9w/vnno6rtXxCsb9++fjX7yul0kpGRQXp6OjqdztvhHMNisWB3/PyBV51TCdhISYomLiqow+VqmkZdTSUAZnMQevX0zl3RXAQ5KwlxVGBy1WNwNaDTnOjqjZR+VU26w4HNGEpDQDS2gFg0tfOmtweamsuKjY1t87s6Hk3TWt8n7rZwtqf8jjLom9+rw4YNc+vx+6zb+XpTLkpQIsP7nTrJ6e6vc0+R85bz9ge1tbWn1Tjh1tX4wQcf5Oabb+bDDz+kvr6ee+65hx9//JHXX3+9wxUfLTo6mjfffJNnnnkGm82GTqfj1VdfZeDAga112+12UlNTee655zpUh6qqfvXCaKHT6brleSuKytF5all18wJ/MeHmDiWwLdq0EihKh7oz9a4moptysTRkE2YvRsdxPvwboXrjXpKPrlvRYQuMozo0jcrQftQE90JTDe0/idbw1dZ/T/UraTlvRVHc/v21p/yOaqnD3dfgNTMGsmZrPu+t2MvIAe4na931de5pct7+xd/O+3Q+C8DNBGfUqFF89tlnfPrpp/Tu3RuLxcL9999PcnLyqZ/sptGjR/O///3vmPtnzZrFrFmzOq0e0T2VVtYTFmw80qXhHSZnHb1su4lvyEKHCxcqlYZYqg3RVOsjadAFYVcCcCo6gswBzL7kHL78ehv6hnIC64sJqssnuC6XhKJ8EorW4tCZKA8fQlnkMKpC00DxnwtTR8VGmLlgQgqffHeQ77cXcM6IRG+HJIToodxuT4+Li+OWW24BYOPGjTQ0NHgsKOFf6hrs2Boc9Elq/9iqzqBz2UmzbSeh/gAqGtX6SPID+lFqSsahGo/7HIcuAH1oNHUhvXCYk34+oLkw2woJr84ksmIXsWVbiC3bQpM+iLLIYZRGjaAuKOm4ZYpmV5zXn6835PDO8l2cMchCgElWtRZCtJ9b7T9r1qxh4sSJALz55pvcdNNNzJkzhyVLlng0OOEfvLn+TXRjHmdWfEpS/X5q9JFsCzuXzeHTKQrsc8Lk5qQUFVtQIgXxk9g5+LdsG3ovuQlTcOoCiS9eR/qevzN09+tEl25FcXlmcHJPFxZsYu6MQZRW1rP4mwPeDkcI0UO59dXotdde4+6778blcvHPf/6T1157jZiYGO6++24uu+wyT8cofJw3VjBWNCd9a7eQ1HAAu2Jgb/CZFAb0gU7eC6khIJr8hPPIj59CkK2A2JINRJdvp+/hD+md9znF0WOwxoylyRTeqfW2K8bCLOweapE1mJpnarXXBeNT+Gp9Nh99m8l5Y5JJiPGfCQJCiM7hVgtOTk4Oc+bMYefOndjtdiZMmMCgQYMoLS31dHzCD5RW1mMy6AgO7PiA3PYwOm2MrPyapIYDVBhi2RBxIYWBfTs9uWlDUagLSuRQymy2DHuIw0kX4NAFklj0HSMzXqTPocUE1rs/xbtTaS7P/XRwHQudTuXWS4fhcLp48+MMz61nJITwWW614AQFBZGbm8sXX3zBmDFj0Ol0bN269ZidxYVoL4fDRUVNIwnRwV2yk3Sgo5oRVd8Q4LKREziIg0HD0RQPTSE6Aac+kKK4CRRZziK8+gDxRd8TU7aNmLJtVIQNoCBuIjUhKV0aU3c0JC2KKWOS+WZTLt9uzmPKmM6b1CCE8H1uJTjz5s1j5syZuFwuFi5cyLZt27jxxht55JFHPB2f8HFl1Q1oWteMvwl2VDC88lv0WiN7QsZRFNA56zh1mKJSGTaAyrABBNXmklC0lsjK3URU7aM6OIXi3tOAvt6N0ctuumgoW/YV89bHGYzoH0NkaIC3QxJC9BBuJTjXXXddm9WFy8vLee+99xg6dKin4xM+7ufxN5794Ap2VDCichU6zcmu0LMpNXWv1oC64GQO9L2GgIYSEorWEl22ldBdb1FQ+yPBQROoNPfydoheERpk5PY5w3l64Qb+tng7j954Zpe09Akhej632+YbGhpISEigrq6O//73v2zfvl129RanrbSyHlXBo9/MAx3VDK/8FlVzsiNscrdLbo7WEBDDwZRL2T70XspiRtOQs5uBu99k4P6FBNXmejs8rxg3NJ5JI5PYsLuIrzfmeDscIUQP4VaC8/bbb3PNNdcA8Kc//YkVK1awaNEi5s+f79HghG/TNI3SynoiQgPQ6TwzDsbotDG86lsMWiO7QydQYYzzSD2drdEUSW6/K0i+9RVKo0cSVp1F+t436HvwA4yNFd4Or8v9ZnY6UWEBvLE0g5yiam+HI4ToAdz6VFm6dCn//e9/aWxsZMWKFbz00ku8++67LF++3NPxCR9WXddEk8PlsfE3qsvBsOo1BLrq2BtyZrduuTkRQ2QCh/tcwfYhd1ERNoDo8h2M2PkyyXlfoXP6z2KboUFGHrh2DHaHi+ff20SDhzYHFUL4DrcSnJKSEvr378+GDRsICwtjwIABREREyGrG4rR4cv0bTdPoV7GWEEcFh8xDKQro0+l1dKWGwFj29buePf3mUR8QRWLRGoZnvERM6SbwkynUQ9KiuHbGQHKKanhrqUwdF0KcnFsJTmJiIp988gnvv/8+EyZMAOA///kPqampHg1O+LYSDyY4VeuWEmM7RIkxicPm9E4v31uqwvqSMfgOsnpfAij0ObyUQfvfIaChzNuhdYnLzu3HqIGxrNyQw+c/HPJ2OEKIbsytBOfhhx/mpZdeIisri7vuuosff/yR1157TaaJi9NSUlFPiNlAYCfvNRRpy6H82/9SZ4hgT8hZnl3AzxsUlZKYM9g+9B6sMWcQVnOQ4Xteo1/NFtCc3o7Oo1RV4YG5o0mIDuKtZTvZfqDE2yEJIboptz5Zxo0bx+rVq1tvR0VFsXbtWgyGrll5Vvieuno7tfV2+iR27gabBnst6dYVKEYTeyKn4HT67mvUqQ/kUO9LKI0cTtrhpaTXrKN272EOpl6KzZzg7fA8Jths5LGbxvK7V75j/r+3MO+8SG+HJITohtz+6vzTTz9htVpb+73tdjv79+/nD3/4g8eCE76ruMIGQExEJ3ZPaS76Zn+EyVlH9IV307ClBvxgIG5NSCrbBt1OROZn9K/dytA9b5CbOI1Cy3jo4lWau0pSbAgPXncGTyz4ife+LWXU8AZiIoO8HZYQohtxK8F54oknWLp0KSEhIWiahqIolJaWMnnyZA+HJ3xVcXlLgmPutDLjitcRUX2A/JAhpA2dCFs+67SyuztNNbA7dByNSWfS//BieuetIKz6AFmpl2M3+OZGlaMGxnL7nGG8+r/t/N+C9Tx/+9kEmzuwA7wQwie59fXuiy++YNGiRbz00kuMHTuWtWvXcscddxAaGurp+ISPslbYMAfoCQronPE3AQ0l9Mr7inpTJHtjzu2UMnuiOnMCGYNuxxo9hvDqTNJ3v0Zwbba3w/KY88Ykc/6IUHKKanhywXrqG2X6uBCimVsJjsPhYODAgfTp04c9e/YAcNNNN/HDDz94NDjhm6pqG6mqbSImIrBzlt3XXPQ5tARFc5LZ+1Kcqn9/i3fpjBxKmU1m6uXonA0M3vcPLMU/eTssj5kwKIRLJqax53A5T/zjJ0lyhBCAmwlOQkICWVlZREZGUlFRQW1tLS6XC5vN5un4hA/afah5SnNsJ3VPxVt/IKQul0LLeGqCe3dKmb6gNGoEOwfeSqMxgtSc5aRkf+KTs6wUReHXMwdx0cQ0dh0s48kFP9EgSY4Qfs+tBOeKK67gmmuuoaioiOnTpzNv3jxuuukmRo4c6en4hA/aebAlwTn9AcYBDaUk56+i3hRNbuLU0y6vJztea1i9OY6dg26lKiSNuJL1DDzwL59cAVlRFG6+aCizzkljZ1YZj775I9V1Td4OSwjhRW4lOHPnzuXNN98kMjKS3//+90ydOpUxY8bw5z//2dPxCR+0+2AZJqOOkNMdEKpppGYvQ9UcHEyZjab67pTwU1FVlfj4eFT12Le0U29mb78bsEafQXh1JoP3/gODvcYLUXqWoijccvFQLj+vH/uyK3j4b2spqaj3dlhCCC855QjPmpoacnJyGDRoEEZj8wfSb37zG48HJnyTrcHOwfwqkmJDTnv8TXT5dsJqDmKNHkNNSErnBNgNNRRmYT/VtiiaRm1dHcFBQSdc2HC30p+6oCbS6rYzOOM19iXNAvp2fsBepCgK118wmLBgE/9YtpMHX/2OJ//feJItId4OTQjRxU7agrN582YmT57MZZddxvnnn8+uXbu6Ki7ho/YcLselQWzk6Y2/0Tls9M79HLs+iJyk6W2OdcrA5e5Ec53yR9NcaC4n2skeh0a2eQh7g88kwFXH4PyPaSrN8/bZecTFE/tw/zWjqKhp5KHX1rIvu9zbIQkhuthJE5yXX36Zu+66i61btzJnzhxeeumlropL+KhdR8bfWE5zgHGv/K8wOOrITr4Ap/7nslRVJSYm9rTK9nWFgX3ZFToBvbOBgvcew9zUsz/8mxPaY5PayaOTefTGsTQ5XPzhjR9Zv7PwtOpxumRzTyF6kpN2Ue3Zs4f33nsPgJtvvpmpU/17EKc4fTuzyjAH6AmszaG+3N6hMoIcFcSWb6LSEEturRHq9vx8UNOo16lwrm91vXS2ElMvMi1m+pd8Q3rDCraGnUedPtzbYXWIoijodCpLV2did7iOOX7uqGS+3ZzLUws3MLJ/DEPSotrdymfQq8yeLK8pIXqSk7bgtGzLABAUFITDIVMvRcc12p0cyK1gcGoUiqa51fVyzI/LSd+aTYDGgaBRgHZMV40vToX2hIqgFOIufxCdy87wqm8JcNZ6O6TTYne4cDiP/YkINTFtbC/Cgo1s3V/C2u35NDY5jvvYE/0cL3ESQnRvbic4Qpyu/dkVOJwaQ9KiOlxGVFM+kXYrRQFp1Bpkk8XTZe47mn1RkzC6GhhR+TVGp2+ubRVsNjL1zN4kxgSTXVjD1xtzZUFAIXzcSbuoNE1j9+7drYmO0+lscxtgyJAhno1Q+IyW9W+GpkWxIaf9z1c0J33rtuBAz0Hz8E6Ozn+VmVPZ11jHwNoNDK/6lq3h5+NQTd4Oq9MZ9CrnjEhgR2Ypuw+V8+VP2Zw9PIHo8E7c8FUI0W2cNMGpr6/n0ksvbXPf0bcVRWndukGIU9l9sAyjQUefpHA2dOD5ifUHMDtrOWgeTpNOPpQ6U2FgX/Sanb51WxletZptYVNw+uC6QoqiMLxfDGHBJjbsKuLrjTmMHBBLv+Rw35t9J4SfO2mCs3fv3q6KQ/g4h9PFnuxyBvaOwKB3a33JNgyuBlJsGdSrQeSaB3ggQpFrHoReayLFtov06u/YHjYZTdF5OyyPSIkPJSzIyPfbC9i8t5iSynrOHBzXodemEKJ7knez6BJZeZU0Njk7PP4mpS4Dg2YnK2gELqVzdiAXxzpkHkZeQD8i7FYG1GwAHx6HFxEawPRxvUmKDSanqIav1mdTVdvo7bCEEJ1EEhzRJXZmNY+/GZLa/gQnyFFJYkMmlfoYSky9Ojs0cTRF4UDwaEqNCcQ3HqJXvW93QRsNOs4ensCI/jHU2Jr4an02hwurvR2WEKITSIIjusSOrFL0OpUBKRHtfm5a3TYUNDKDR51wGwLRiRSV3SETqNWF06duG9GNud6OyKMURWFQSiRTxiRj0Kusyyhk0x4rTpdMDReiJ5MER3ic3eFi98EyBqZEEGBsX/dSmL2E6KYCrKZe1Bg6Pr1ctI9TNbAjbBJNSgCDq38k2N6zVzt2R2yEmenjUoiNMHMgt5JVG3KptcmO5EL0VJLgCI/bn1NBQ5OT4f1i2vdETSOtbhsuFA6Zh3kmOHFCjbogMsImAhrDqtf47Bo5Rws06Tl3dBKDUyMpr27gi5+yybX63s7rQvgDSXCEx+3ILAVgWN/odj0vsqmQcHsJRQFp1OtDPRGaOIVqQzR7Q8ZhctUzrHoNqub7i+OpavNU8smjklAVhe+3F7BhdxF2h6yQLURPIgmO8LgdmSUEGHX0S27H+BtNI822HScqh83pngtOnFJxQAqHzEMJcVTQv2ajT8+sOlp8dBAzzkohNiKQfdkVPPDqWgpKe/Z2FkL4E0lwhEc1NDnYe7iCwWlR7VpjJKYxhxBHBfmB/WnUnd7O4+L0HTant86sSmg44O1wuow5QM+5o5MZ1jeag/lV3PPSGtZuzfd2WEIIN0iCIzxq7+FyHE4Xw9vRPaVoLtJsO3AoenLMgz0YnXCborAnZDw2NZh+tVsItZd4O6Iu09Jl9affjMdk1DH/35v424fbabRLl5UQ3ZkkOMKjfh5/4/4A47iGg5idNeQGDsKuBngqNNFODtXIzrBz0FAYWv09Rle9t0MCQFW75jI2vH8Mf71vMsP7RfPFusP87pXvyCuWAchCdFeS4AiP2n6ghKBAA6mJYW49XtWcpNh20qSYyA0c6OHoRHvV6SPYGzIWk6ueIdXfo2gnXytG1ak4XZ4bs6PT6Rg+vOs2Xo0IDeCJ34xn7oyB5BRVc+9f1rB6s2+vEyRETyVr3guPqa23k5lbyZlD4tCp7i3Ql1B/gACXjQNBo3xys0dfUByQQqijjOT6ffSp20pm8OgTPlanquhUhaWrM7E7On/hPE1zUVtdyU2Xjev0sk9EpypcNXUAQ1KjeOE/m3jxv1vYkVnKb2ant3udJyGE50gLjvCYHQdKcGkwckCsW49XNQe9bLtpUAMpCOzn4ehOk5+vqJwVNJJKQwzJ9fuIacg+5ePtDhcOZ+f/2B0u7A7vTF1P7xvNK/edy8j+MazckMPvXvmOghKZZSVEdyFfN4THbN3fPBB1ZH/3EpzE+gOYtAb2B43B1d13sT6S4DQUZmFvaPBMFSHBQF+PlH26NEVlV8jZjKlYwcDa9dTqI/xyraLwEBP/d8tZfPjNAf7zxR7ue3kND1w3htEDLd4OTQi/Jy04wiM0TWPLvmLioszERwed8vE/t96YKQjo0wURdhLN5dmfbqxJF8ju0AnoNCdDq9f6xSKAx6OqClec35/HbzkLRVF44h8/8eE3B9D8ZL0gIborSXCERxSW1VFcbmtX641RayTbPAStu7feiFaVRgsHg4YR7KxiQM0Gv1kE8HhGDYjlpXsmkWwJ4d3PdvPCvzfT0OSfSZ8Q3UG3S3C2b9/O0KFDKSoqAmDZsmXMnDmT6dOnc88991BbK33cPcHWfUe6pwacenr40a03hQFpng5NdLKcwMGUGhOJazxMfEOWt8PxqvjoIP585zmclR7Pd9vyeejV7ymr6h7T6YXwN90qwSkrK+Pxxx/HbrcDcODAAZ5//nneeecdvvzyS+Li4pg/f76XoxTu2La/GFVVSHdj/Zuk+v3SetOTKQp7Qs6iXg2if+0mv9h5/GTMAQYevv4Mrpk+kIMFVfzur2tlw04hvKDbJDgOh4P77ruPBx54oPW+VatWMWnSJCyW5gF7c+fOZfny5bhc3Xtsgr9zOF3syCxlQK8IggNPPtVbp9lJtu2R1psezqEa2Rl6DgBDq9eidzV5OaLOpapKu9bzUVWFq6cN4N6rR1FR3cCDr65lz6GTJ36eXC9ICH/UbWZRzZ8/n7FjxzJhwoTW+woLC4mPj2+9HRcXh81mo7KyksjISG+EKdywP6cCW4ODkf1P3XrTMvZmX9AZ0nrTw9UaItkfPIaBtRsYVPMjGaGTvB1Sp1EVpcPr+UwalcR3W/N45PXvOWdEIsmWkGMeY9CrzJ7cPWfMCdFTdYsE59NPPyUnJ4dHHnnkmGPKcdYbOd59p+JyuXA6/WfvmJZz9cY5b9pjBWBYv+jj1q/T6UDTUJ1NJNt2U68GUWBK7ZRZJ5qmoaC03PDcTJaWcrtJHS3H2xWLB86hwJRGmL2Y+MbD9LLtpjRozJEqXB5peT06bk/V0VI2QJPd0e4EJyY8gMmjkli7rYA1W/IYPSiWPr9Y2VvTmhvT3X2/evP97U1y3v513qf7fu4WCc6SJUuwWq1ccsklrffddNNN/OpXv2odbAxgtVoJCgoiLMy9Zf+PlpmZ2Rmh9jgZGRldXufaLVYCTSq2ssNsq2i7CJxer2f48OHU2Wwk1+7EqDWxTTeQmrrOG4gZEtb8Ddlms9Fgs3VauUdTdEq3rKOurs6j5btjC4M4RykjzbadqsooAEpKSmhotHdaHUcLNhsBKC4uptFDs5aa6+h/WnUMSwkg47CNTXuKqaioIina2HrMaNABA9mxY0e7LureeH93B3Lewh3dIsFZuHBhm9sDBgxgwYIF1NTUcOONN2K1WrFYLPznP//h/PPP79Dmen379iU4OLizQu72nE4nGRkZpKenN7eYdJHyqgaKKvKYNDKRUaNGnvBxoQF6+lUdpF4NoiJsIMGd1D119Dd6s9mM3kMbMZrNQd2qDk3TqKurIygoyO0WTk+ew27HRMZUfcnQmnU4aq4hJibGQ1s1aNTVVAAQGxvrkToAAk36TqkjPs7B6i35ZBU1EhwSwsDeEUBzFxXAsGHD3CrHW+9vb5Pz9q/zrq2tPa3GiW6R4JxIv379ePDBB7n55pux2+2kpqby3HPPdagsVVX96oXRQqfTdel5bz3QvHv4mMFxJ6033rYPg9ZEVtAIUPV4ZOMDRelQd6a7ZXfHOpT2xOPBc6g3hLE3ZBxDq7+neOmLKPFzPbLr99GtHYqi4qmNxRVF7ZQ6ggKNnDcmmW8257L9QCkKCoNSI1vLb+97tavf392FnLd/ON1rRrdMcPbt29f6/1mzZjFr1iwvRiPaY9MeK6oCoweeeIE/V6ONxJqd1KtBFMnMKZ9VYupFYcgQ4nN3kej4iuzE6d4OqVsIMOmZMiaZbzblsu1ACXqdwqDUKG+HJYTP6TbTxEXPZ3c42ba/mAG9IwkxG0/4uKqNn2PQmjhsHoqmyEvQl+VGnokpsT/xhd8RUbHb2+F0GwFGPeeOTibEbGDT3mKy8iu9HZIQPkc+XUSn2X2wnPpGJ2cMPvFGg66GOqrWL6deF4I1ILULoxPeoCk6LJfej10fRJ/DSzA1lHk7pG4j0KTn3DHJBAXoWbejkI27i079JCGE2yTBEZ1m45Hp4WMGnTjBqdr4Ga6GWnJDhknrjZ/Qh0ZzqM8V6JyN9M96H8XlmdlUPVFQgIFzxyRjNOiY/94mMvMqvR2SED5DPmFEp9m0p4josABS4kOPe9xZX0vV+uXoI+IoNvegHcPFaasO709ewrkE1ReSkvOpt8PpVkLMRiaPTsLp0vjTgp8orvDMsgNC+BtJcESnyLXWkF9Sx5jBcSeckVO1YTmuRhsR51wB0nrjd/Ljz6UytC+W0k3ElG7xdjjdSmyEmfuuGUV5dSNP/uMn6uqllUuI0yWfMqJT/LSzEICzhsYf97jTVkPVhs8wRCUQPOTsrgxNdBeKSmbqFTQawkjJ+QSzTcacHO3s4YncMHMw2UU1PPfuRhxO2XNPiNMhCY7oFD/tLMQcoCe9b/Rxj1et/wStqZ6Ic65AUf1nHQfRlsMQxIE+V6FoTvpl/Redo8HbIXUrl57blxlnpbDtQAl/W7zdc9uACOEHJMERp62sqp79OZWMGWRpXZH1aM66quap4dFJBA0a74UIRXdSG9yLnKRfEdhYRlr2Rz/viSVQFIVbZ6czemAsqzbmsHztQW+HJESPJQmOOG0/7Wzuajgr/fjdU5XrP0GzNxAx8UppvREAFMWeRVlEOlEVu4iz/ujtcLoVnU7lgWvHkBAdxDvLd7HroEytF6IjJMERp+2njEIMepVRA45dvdhRW0n1phUYY3sRNHCcF6IT3ZKikJUym/qAaHrlf0FIzWFvR9StBAUa+P0NZ6LXqzz3r42UVXXeZrRC+AtJcMRpqbU1kZFVyvB+MZgDDMccr/rpYzR7IxHnXNW6344QAC6dif19rkFT9PTP+i+mxnJvh9St9I4P5e4rRlJZ08jz/9rksY1EhfBV8okjTsvGPVacLo1xx5k95aipoHrzlxgtqZgHnOmF6ER3Vx9oITP1cvQOGwMOvCeDjn/hnJGJXDyxD3sOl/PO8p1tjnli81IhfIm8Q8Rp+X5bAaqqMG5o3DHHKtd9hOZoah5746kdt0WPVxExmJyk6Zgbiul3cBFoTm+H1OVUVcHpOv5g6xsuHMyQtCg+/f4Q327OBZp3lR45cmS7d5Y+UR1C+KJuuZu46BlqbU1s2WdleN9owoJNbY45qsuo2bISY1wfzP3GeClC0VMUWs4moKEUS+kmUnI/53CvWd4OqUupioJOVVi6OvO4XVGDUiI5mF/FK4u2ciCnkrBgA1arFYvF4nbXr0GvMnty384OXYhuS1pwRIetyyjE4dQ4Z0TiMccqf/wIzWkncpK03gg3KAqHe82iKiSNuOKfsBSv83ZEXmF3uHA4j/0x6FUmDIvHpWl8tzWP+kYHTXbnCR9/vB8ZwyP8jSQ4osPWbstHr1OOmR7uqCqheusqTAn9COwzykvRiZ5GU/Xs73M19aYoUnI+I7xyr7dD6lZiIsyk94mmqq6JrftLvB2OEN2eJDiiQyprGtmeWcrIAbEEm41tjlWsXQwuh4y9Ee3m1JvZ1+96HPpA+h1cJNPHf2FQaiSWSDMH86sprpL9qoQ4GUlwRIf8mFGAy6Ux8RfdU00ludTs+JaA3kMITBvhneBEj9YQEM3evtcDCgMy35M9q46iKs0tpiaDjv35DdTKppxCnJAkOKJD1m7Lx6hXOXNI29lT5av/C5qLyHOvldYb0WF1wcns6zsX1WVn4P6FmBpkNd8WgSY9Y4dacLqax8G5ZGaUEMclCY5ot+JyGzuzyjhjcFybxf0a8vZi27+BoIHjCEjs78UIhS+oDu1LZtoVGBx1DNq/EENTtbdD6jbio4JIjjZSXt3IjsxSb4cjRLckCY5ot2+OrMVx3hnJrfdpmkb5N/8GRSVi8jXeCk34mPKIoRzsfTEBTRUMOvBPdA6bt0PqNlIsRiJDA9hzuJzC0jpvhyNEtyMJjmgXl0vj6405RISY2uw9ZcvcTEPuHkJGnIcx6thp40J0VEnMGeQkTsdcb2Xw/nfQ2+XDHFrG48Rh0Kv8tLOQhkaHt0MSoluRBEe0y+5DZRSV2Th3dDI6XfPLR3M5Kf/2Pyh6IxHnXOHlCIUvKoifSG7CeQTZChm0fwF6e623Q+oWggMNjBlkoaHJyU+7itA0GY8jRAtJcES7fL3x2O6p2p3fYS/JIezMC9GHRHorNOHj8hOmkJ04naB6K0P2/UPG5ByREh9KakIohaV17Mup8HY4QnQbkuAIt9U3Ovh+ez79e4XTKy4UAJejifI1i1ADggk76xLvBih8XmH8RA4nzySwoYTB+/6BsanK2yF1C6MHWggxG9i+v4TyatmwVAiQBEe0ww/b82locnLeGb1a76ve+DnO6lLCJ1yGLiDIi9EJf1FkGc/BXhcR2FjG0P0LCLRXejskrzPoVcYPSwDgxx2FOGRbBiEkwRHu++zHw5iMOiaOTALAUVtBxfcfog+PJXTMDC9HJ/xJcexYslJmY2qqZGzuIhryZFuHyNAAhvWLocbWxOZ9xd4ORwivkwRHuGV/TgWZuZVMHpVEcGDz2jfl3/4HrameqPNvQNUbT1GCEJ2rJHoMe9OuRqfZKfz3/xFRtsPbIXndwN4RxEWZOZhfRU6RjFES/k0SHOGWz344BMDMCakANOQfoHbHtwSmDsPc/0xvhib8WEX4IDYkXoEaGEyfzPdJKFwDfjyTSFEUxg2Nx2TUsWG3VbZyEH5NEhxxSlW1jazdls/g1EhSE8LQNBdlXy0ARSVq6o2yJYPwqpoAC4nznsMWGEev/K9Iy16K4vLfNWECTXrGDYnD7nCx7siecUL4I0lwxCmt3JCD3eHigvHNrTe1Gd/RWHCA0DEzMMYkn+LZQniePjSavYP/H5Wh/Ygt3dw8w6rRf6dMJ8QEM6B3BKWVDew6KPt4Cf/kRwmO51sZnD7yTUlzOVv/73S6WPHjIcJDTIwfloCrsZ7yb95DDQwh4pwrvRilEG259AHs7XcdBXHnEFKXy7DdfyO8co+3w/Ka4f2iiQgxsetgGcXlssWF8D96bwfQVXQ6laWrM7F7aPqkQa8ye3Jfj5Td1RRVR8VPn6A57azLVSiu0HHpICc165dSf3AbzrpKAvufQdWWL9tfdkAIEaOneSBqIQBFR07SDKqDU+hz6EMGZv6bAsvZ5CZOQ1N1p118Q2EW9obOX2dGCTYDnXv90KnNU8e/WHeYdRmFXHh2WqeWL0R350ctOGB3uHA4PfPjqcTJWzQ0NA0+3adi0mmc10fDaauhMXcvuuAIjPF9OlyuEJ3r2NbZyvCBZAy+g5qgXiRYv2fwvrcxNZafflWayzM/Ls9cP0KDjIweZMHW6GDdzkLZykH4Fb9pwRHuc7o0IsddzKY9VvKqf+KSSX1InjyEovf/BJqL2Nn3EthryOlVIgOT/YOH/86qqhIbaznusSZTOLsH3Exy/koSrGsZtuuv5CZOoyh2HCj+890uLSGUorI6copq+GTtQS6e2LEvJ0L0NJLgiGPoVIX3/7uCr/Y0oShgL8rii9dXMqByO0Xmvnz/dSaQ2aGyA4ODuPzy8yXB8RdH/s6e6tpB06hXgXOP372jqTpykmdQGdaftOylpOR+RlR5Blmpl9IQENP58XRDiqJw5uA4KmsaWbh8F32TwhmSFuXtsITwOP/5GiPapbDCTqkNkkNcBLrqSK3aSJNi4kDgcOx2R4d/HA7nqSsXvsdDXTua5kJzo3unOjSNHYPvpDB2PMF1uQzb9Rrxhd+huPzj9WjQq0wamYRBrzL/vY1UyH5Vwg9IgiOOoWkaO60aoNEvykXf2q0YtUYOBI/GoZq8HZ4QHeLSGcnuNZNdA2+h0RRO7/wvSd/9GmFVB7wdWpcIDzFx5xUjKK9u5Pn3NuF0+ta4QSF+SRIccYyt+0ooqYPeYRq9tQLiGw9SZoin2NTb26EJcdpqg3uzY/Ad5CZMwdRUwaAD/6T/gfcIaCj1dmgeN3FkErPOSWPXwTLe/dx/p9AL/yBjcEQbLpfGu5/vRlVgSEQjA2vX41AM7As5U8bNCJ+hqQbyE86jJGo0vfK/JLp8B+HVByiKPYv8+Mk49YHeDtFj5l04hMzcSpauzmRg74jWXciF8DXSgiPa+GF7AQfzq+gbBcMaN2Fy1XMgaBSNuiBvhyZEp2syhZOZdiW7BtyCLdBCgvV7Rma8QGLBt6jORm+H5xEGvcpD148hPNjEy4u2kF0om3IK3+RXLTgNBQewNzZ5pGyDyQj090jZXaXJ7uRfK3ZjDtBzVkgO8VWHKDPGUxQgC4QJ31YTksLOQbcRXb6DpIKvSS5YRVzxj+THTcIaOxZfu1RGhQXy0PVjeOzNH3nynfW8dPdEwoJlfJ3wLf7VguPy0CJdHlyoqyst+eYARWU25pydRHr1WuyKkb3BY6VrSvgHRaU0agTbh9zDwd6X4FIMpOStYGTGi8QUrMXV5Fszj4b2iea2y4ZTXG7jmX9uwC4zHIWP8a8ER5xQYWkdi785QLIlmHGlH2HQGtkbMpYmndnboQnRpTRVR3HMGWxLv5fDyTMBjcTDn5Lz2q0kV21D7/JMK7A3TBvbm4sn9mH3oXL++sE2WelY+BTfancVHaJpGm8u3YHd4eK6/lXYd+2kMGgApSbZKVz4L001UGQZjzXmDBIqt5Na9gO9q7aQqOwgP6AfeeaBNKk9fzDyvFlDKCqrY/WWPGIiArn+gsHeDkmITiEtOILvtxWweW8xEwcEY9n9PoaYZA6FneHtsIToFjTVQFncOJJ/+xr7IifSqAbRu34P48qW0a9mIwHOWm+HeFp0qsLvrh3NgF4RLP76AJ//eMjbIQnRKbpNgvP+++8za9YsLrroIq688kp27NgBwIIFC5gxYwZTp07liSeewG63ezlS31JaWc/rS7YTajYwvXoxisGE5bIHcCnSuCfE0RRVR0lQXzZEXEBG6DnU6cNJajjA2PLlDKr+gSBHhbdD7LAAo57HbhpLfHQQb3y0g++25nk7JCFOW7dIcLZs2cJbb73Fu+++yyeffMKtt97Kb3/7W9asWcOHH37I4sWL+eKLLygvL2fhwoXeDtdnuFwaf3l/C7X1dq6N3kFwYwmxs+7EGJXo7dCE6L4UhVJTMpvDp7MtbAqVBgtxjdmcWbGCYVXfEt5khR44liUs2MSTvzmLiJAAXvrvFjbsKvJ2SEKclm6R4ISFhfGnP/2JyMhIAIYNG0ZZWRkrV65k5syZhISEoNPpuPrqq1m6dKmXo/UdH6/JYkdmKZPjaxhQu5Hw8bMJGjjW22EJ0TMoChXGOLaHT2Fj+AyKTb2IbCpiZNXXjKr8iujG3B6X6MRFBfHUreMJCjTw3L82smVfsbdDEqLDukU/RJ8+fejTpw8ALpeLZ555hsmTJ1NYWMjIkSNbHxcXF0dhYWHHK9I0z80SOFKu09k9plq2xHGieHZklvLu57uJC3ZxQcNyAvuNJvTsK3E6neh0Os/9rlrK9FD5mqahoHi0jpayu1MdLcfbFUs3O4eOFa+hHFnGQNNcuDy0XIOmuVr+c9zzqNFHsDNkAoHmGnrV7yWu4SDp1Wup04WSEziIIlNvNEV3sgpa63HnHI7+e7t7ztqRr7OnukYlRJv5v1vG8tibP/HUO+t56LrRjBlkcasOTzvVdc1X+et5n+77uVskOC1qa2t58MEHKS8v56233uLee+9tvXi1+OXt9qiz2Whs8MxaFqaAAAB27tyJw+HwSB0dkZGRccx9ZTUO3v7SikFxMU+3HF1YFAUp51KwYwd6vZ7hw4d77Hel6Jr/fjabjQabrdPLBwgJC/F4HV1xHh2po66uzqPlt1dX1BEcEgxASUkJDY2eGaMXbDYB/bHZ6miw1Z/wcbUolDAIkymVNMchUpyHGVS7npTa7RzUp3FY1xvn8ca3HbmstfccrFar2481GnTAQHbs2OHWB8e1kyL417elPPPuRi6fEMWg5O4zY+x41zV/4K/n3VHdJsE5dOgQt912G8OGDeMvf/kLJpOJhISENm9gq9VKQkLH900JMpsx6D1zykajEYChQ4d6pPz2cjqdZGRkkJ6e3twic0RtvZ1//O0HGu0avwlZTWK4nrjrnkAfEtnm+Z76XZnNQUf+NaNXO7+H9Ohv156qo7lsz55He+vQNI26ujqCgoLc/hLQ3c6hI47+e8fExGB3eKYFJ9DU/F4wm4PQqydpiWkVTC7RFLiGk9iQSXL9PoY4dtPfeYD8gP7kBg7Arv68cnCQuXm9KXfPQdM0rFYrFovF7b+3Qd/8+x82bJhbjx8BDBpUzeNv/8TiH8r57WXpnH9GL7ee6yknuq75On8979raWjIzMzv8/G6R4BQUFDB37lxuuukmbrrpptb7p06dyvz585k7dy7BwcEsWrSIadOmdbwiRTmtFqBTlQ10uxefTqdrjamu3s6TC9aTV1zLJUFbGBpaRfw1f8IYHnPsEz31u2op05N/i6Pq8vTfu7vVobQnnm56Dh2vSsVDeRqKorb8p13n4dKZyA0aQr55IJaGQ/Sq30NK/S6S6veRH9ifXPNA7GpA6+/J3XNoaYFRFAXVzZNuOYf2XKP6JEXw3O1n8/hb63ht8Q4qa5q44vz+nn/vnsLR1zV/4m/n7e5r+0S6RYKzYMECqqur+eSTT/jkk09a73/rrbe47LLLuPrqq3E4HIwaNYrbbrvNi5H2XLYGO//39jr251QyLWg3U0IPEX/1Exijk7wdmhA+z6XoKAzsS2FAGrGNufS27aR3/e7WRKckYOSpC/GSpNgQ/nzXRJ54+yf+/cVeCsvquH3OcAx6//mgFT1Tt0hwHnvsMR577LHjHps3bx7z5s3r4oh8S2VNI08tXM++7ArOC9zDzJDdxF/1KKa4VG+HJoR/UVSKA3pTbOpFTFMuKXUZ9KrfQ2LefspWVqO3D8OhC/J2lMeIDA3g2dsnMP+9TXy9MZe84lp+f8OZRIYGeDs0IU6oW0wTF56TXVTN/X/9jn3ZFZwfuIuLI/eReO0TBCQN8HZoQvgvRaHE1IuNRxYNbNCHUbXhU4Ztm0/vnM8w2Gu8HeExzAEGHrtpHJed25d92RXc89Jqtu8v8XZYQpyQJDg+StM0Mg7bePhvP1JWUcdVQT9ySewhEq//E6b4NG+HJ0Sn8fZ4kNNyZNHAnQmzscx5iPrAWOKLf2RExov0yl2B3u7+rLiuoFMVbrhwCA9eO4aGJgePvfUj//p8Nw6nZwZ3C3E6ukUXlehc1XVNvP7hNn7YUU6IwcFNwV8ztFcwljnPoQ+N8nZ4QnSuI/lNQ2EWdg8tA6GEBAN9PVJ2cwUKQQPOZE9OGCFlu0gq+JoE6/dYSjZQFDuOwrhzcOjNnqu/nc4ZmUif5DD+/N4mFn99gM17i7nnqpGkJoR5OzQhWkmC40PsDief/XCY/63aR43NTnpAIVcFfIdl6BhiLrwd1WA6dSFC9FSaq/nHU2V3BUWhImIwFeEDiazcTVL+1yQWfUdc8U8UWsZTaDkbp757rEeTEB3M/Dsn8v5Xe1nybSb3/mUNc6b0Y855/QgwykeL8D55FfoAW4OdbzflsnRNFtZyG5GBGtcF/8go02Gizrue8DNn9uxmfCH8jaJSHjGU8vDBRFXsJKngG5IKVxNXvI5CywQKYs5qd5GqquB0aejUzrsWGPQq118wmPHpCbzywVY+WLWfbzblcuNFQ5gwLEGuO8KrJMHpoZxOFzuzyvgho4A1W/KwNTgIMqlcHJXJ2a71BMXEUzZgHqljpslFRoieSlEpixxGWcRQosp3kFTwDckF3xBv/ZFg83BqYqaC6l6Ljqoo6FSFpaszPbIg4oRhCVgizezMKuX5f21iQO8IrvvVIIb3O846W0J0AUlweoiq2kZyrTUcyK1k96Eydh0so8bWvKR7r+gAJsXnMKzyW0w6HeETryDkjAsp3rnLy1ELITqFolIWNYKyyHSiy7aTVPANQ2rWY9+5g8K4cyiKHYdL514XtN3h8tig4P69Irjj8hG8/9VevlqfzaNv/Eh6n2gum9KXUQNi5cuW6FKS4LSD0wU1TVDZoFDdqGBzgM2uYHeC3eViye+WNT9Qad7uUVFAp1MxGXSYjDpMBh0BRh0mo771tsmoI8CoR6cqOJyu1ouPw+nCVu+goqaBsqoGaut/3p9GVSAtMYwZQ1WGNGwmPPd7lCoIGnQWkVOuxRAR53ebsgnhFxQdpdGjKIlIx3hwDUPqt9Ir/yvird9TEDcRa8xYXDqjV0MMDzFx22XDmT25L4tW7mP15jwy3i4lJT6UX41PYeLIJIIDDV6NUfgHSXBOwWaHwloFa51CqU3Bpf38DURBI9AAAXoI1UNaajwALlfLTr/gcLlosjtpaHLS2OSk2mansbKexiYnjXYnJ9tgOdCkIyIkgN7xoSREB5FsCSE5zEVizW4ce5dhz8wBwNz/DCImXoEpTqZ/C+EPNEVHdtBgmlInYqnYRmLBanrnfUF80fcUxE/EGnMmmurdJCIuKoh7rhrFNdMH8sl3B/lq/WH+vmQHC5btZPywBKaO7cXQtGjUThwTJMTRJME5DpcGBTUK2VUKJTYFUFDQiDJrRAVqhAdohJk0AvU/b7VjMBq5/oYz21WPpmk0OVw0NjlxOl0Y9Cp6nYper6JTm/e8cTXW01hwgPrDO7Bl7aCpKIt6QA0IIvTMCwkbPQNDZHyn/w6EEN2fpuopjjmTkqhRxJZuIrFwNSm5n5NQtJb8+EkUR4/xeqITG2Hm5ouHMnfGQH7Yns/KDTms3pLH6i15WCLNnD08gXFD4+nfK8KtZKe5m8uzSVFnD8YW3iEJzlGcLsipUjhQoWKzNyc18cEayaEuYoM09J28LKKiKJgMOow6cNZWYy8poqmiCFuFFXullabibOyl+UBzM48aGEzQkLMJHnw25rQRKHpp5hVCNCc61thxFEePxlKykYTCNaTmfEpC4VoK4idRHD0ab1/uA016zj+zN+ef2Zu84hpWbcjh2815LPk2kyXfZhIRYuLMIXGMGxrPsL7RGA3H3+tKURR0OtVjg6UNepXZkz245pHoMpLg0NyVVFCrsKukObEx6jQGRjlJDdcwdeA35Gqsx1lXgbOuGmddFU5bFU5bNU5bNa76Gpz1NbhsR/6tr8HVaDtuOfqwWIIGjcMU35fA3kMxxqWiqO5vcHe6O7EKIXoWTTVQZBlPcfQYLCUbSCj6jtScT0go+g5r8hQ0Z4q3QwSaN/C84cIhXH/BYDLzKvlpZyHrMgr58qdsvvwpG6NBR3qfKEYPtDB6YCwJMcHHlOHJwdLCN/h9glPbBNuKVErrVfSqxpBoJ6kRbrTWaBoml40QRzlBjmqC6urIf/cnHBWFOOuqTvpURW9EDQxBZw7FEB7b/P+gcAwRFvQRcRgi4tCHx6Lqjx0s6G7TqU6nY+TI09ihWGY7CNFjuXRGCuPOxhpzBnHF64kv+o5eWR+R+8b3REWeQ3H4cLR2fFnyFFVV6N8rgv69Irj+gsHkWmvYuLuIzXuL2X6ghM17iwGIjwpi9MBYRvSPBg+02gjf5LcJjqZBVoXCnlIVp6aQEuZiULTrpC02JmcdkU2FRNiLCLeXYHLVtzlu10IwRMYTmDocfWgUqjkMnTkUXdCRf81hqIHBp7WisLvrWGiaC6vVisViQVHcb8kJNOmYdU4fSXCE8AEunal50HHsmSSVbSCx+HtSDy4hwbiKotjmlh6nvvvsCJ5sCSHZEsKl5/bD1mBnR2Ypm/cWs3mvlU9/OMSnPxxCr0L6lkZUVSEuykyI2SjTz8Vx+WWC0+CAzYUqJTaVIIPGyDgH0SfY5sXkrMPSeJiYxlxCHeVA84iYWl04pQGJVOujqNOHYQ+MYu6Nc7okfneaZl1HZm/ZHS7a01Nld0i3lhA9QXs+1J26AKxJUzjr8rn88MF7xBSto3feChILvqE4ZgxFseNpMoV7LtgOMAcYGDc0nnFD49E0jbziWjbuLmLNpoNkZJW1XgODAgwkxgbRyxJCdHigJDuild8lOCU2hU0FKo3O5labobGuY7qjFM1FdGMuCQ1ZRNiLUAC7YqDIlEKpMZFKowW72vZbj0H17toTQogerJ0fyqqqEh/f/tmTakAQhYlTyIudQHT5duKLfiDB+gPx1nWURwzGGjOW6pDUbteCqygKyZYQEqLNpIbXMmhwOq8v2U5ecS0FpXXsz6lkf04lZpOe5LgQellCiAoLkGTHz/lNgqNpGgdKNbYVqugVGBPvJCm07SI0OpedhIZMkur3EeCy4UKhxJhMUUAa5cY4NMX7fdZCCB905IPY7R3RNY3aujqCg4LcTkaUYDMtO6JrqoGS6DGURI0mrPoA8dYfiKrYSVTFTmwBMVhjx1IaObJbdV8dLcCkJyk2hLioIDRNo6KmkZyiGnKKatiXXcG+7AqCzQb6JIaRlhBGQEdmi4gez2/+6v9btZ9thRrBBhib5CTkqAYXnWYnsf4AvWy7MWhNNCoBHDQPoyCw7zEtNUII4TFu7oiuaRqay4mmuVDcXRPGdZxyFYWqsP5UhfUnoKGU2JINxJZuJjXnU3rlfUVZxFBKokdTE9y727XqtFAUhcjQACJDAxjeL5ry6gayi2o4XFDN9gOlZGSWkhgbTJ+kcOIizdKq40f8JsFZl1GIJRhGxzkxHmmIUTQXcQ0HSavbgVFroF4NIitoBEUBqdJaI4TwKw0B0eQkX0BewvlEVWRgKV5PbNkWYsu2UG+KoiR6FKVRI2kyhnk71BNSFIWosECiwgIZ3i+a/OJaMvOqyLXWkmutJcRsYGBKJKnxoeh0Mt7Q1/lNgnP9BYPI3J6B88iWTuFNVvrVbiLYWUWjEsC+4DMoDEjzqcRGvqkIIdrLpTNSEj2akujRBNZbiSndTEzZNnrlryQ5fxXVIamURaZTHj4EhyGoy+Nzd30vnarSKy6UXnGh1NiayMqrIjOvko27rezILGVArwj6JodjOsGCgqLn85sEZ9RACwd37ERxNdGnbisJDVk40XHYPIScwME4T3M5c1WndqvlvTs6CFEI4aM68IWnPtBCTvIF5CZOJ7xqHzFlWwivOkBYzUFScpZTHdKH0shhVIQPxqkPQFUVj14HdTodw4cPb/fzQsxGRvSPYUhaFFn5lezLrmBHZim7DpbRNzmcwSmRMk7HB/nNX1TTNKJth0itXI9Ja6DcYGFfyJk06EI6pXydqrq9Rk1HtaxR49ZAxA4MQgRQQoJpGYgohPAh7R3I/As2FAqMo9FFpRPdmIel8TAR1ZmEVx/AxVLKjAlUhfWDs+JZur7II9dBTXNRW13JTZeN69DzDXqVgb0j6Z8cQY61hj2Hy9mXXUFmbiX9e0UwKCUCfaDMiPUVfpPglK18h4EVa7ArRvaEjKPI5JmpkJ5cPrx1jRo3BiJ2aBBiS9lCCN/l5kDmE3EqeqwBKVgDUtC7GolpzCW2MYfopnxiSvLIfvk7UoNTKA8bSHn4IJpMEZ0Wusvlwu5wnnY5qqqQEh9K77gQ8oprycgqZc/hcg7kVjAoJZILxqcQbJZEp6fzmwSnIXcP5YFp7DeP8MzMKBnvIoTwMw7VRGFgXwoD+2JwNZCglDA03IYrazuh1Vmk5H5GXWAcFeGDKA8fhM2ccFrXSlVViY21dFr8LevrJMUGk2OtYWdWGRlZZdz89EountSXi85JIyhQNjXuqfwmwbFc8Xt+WrEVe1OTZyo4zeZft6qQ7iMhRDdlVwMoCRlE3JXT+fe7nxBSc4joxjyiGvJJKvyWpMJvaVDNlBkTKTMlUmGMw6W08yNI06hXgXM79zqoKAq940JJtoSQZ63lYEEV//1yL598l8Wl5/Zl1tlpMkanB/Kbv5ghJLJrKjrN5t9Tli2EEN2cS9FRakyi1JiEEuwi1F5KdFMe0U35JDYcILHhAE50lBvjmhMeYyJNusBTlqtpGnjwMqgqCmmJYTxw7Wi+2ZTLolX7+dfne/jku4Ncfl4/ZpyVglFmXfUYfpPgCCGE6HqaolJljKXKGEsWowh0VBPdlE9UUz5RTQXENOUDUK2PpMyYSKkxkVp9hFe7/XU6laljezN5dDIrN2Tzwcr9vL1sJx+tzuTKqQM4/4xeGH65x4/odiTBEUII0WXq9aHk6kPJNQ9C72oisqmA6KZ8IpsKSLVlkGrLoFENpPRIy06F0dL+rqxOYtCrXDA+lfPO6MWKHw/z4Tf7ef3D7Sz55gDXTB/ApFHJ3WZpEHEsSXCEEEJ4hUM1UhyQQnFACormIsxe0tqyk9iQSWJDJk50VBjjKDUmUmqIp0lv7vI4TQYdl0zqw/RxvVm+9iAfrc7kL+9vZfHXB7hm+kAmDEtAlUSn25EERwghhNdpikql0UKl0XJMV1ZLKw80d2VVfOfCXBdDtSmuS7uyAk16rji/PxdMSOXjNZl88l0W89/bREp8KJdN6cc5wxNkC4huRBIcIYQQ3c7xurKaW3cKqVj7AYOBJkMIFWEDqYgYRFVIHzS1az7SggMNXDtjELPOTmPJt5ms+PEQL/5nM++t2MPsSX04/8xeBBjl49Xb5C8ghBCiW2vpyrKaeqPg4ppfDWHrqpWEVezFUroRS+lGHLpAyiMGUxaRTnVIGprq+dlOYcEmbpw1hDlT+vH5j4dYvvYgby7N4P2v9jFzQirTx/UmKuzUs8OEZ0iCI4QQosfQFJXAXkPI62XgcOIMAhpKiazYRVR5BrGlm4kt3YxdF0h5xBDKI9KpCk0FD2+iHBpk5KqpA7hkUh++3pDDR2uyeP+rfXywaj/jhsbxq7NSGNY3RsbpdDFJcIQQQvRYDQHRFMRPoiB+UnOyU55BVMVOLKWbsJRuwq43Ux4x5EjLTioonhsjE2DUM/PsNGaclcKG3VZW/HiIH3cU8uOOQhKig5g+LoVJoxKlVaeLSIIjhBCix1BOMqi4ISCagoRzKUg4l4D6YqIqdhJVnoGlZCOWko006YMpi0ynLHIYtUHJHhugrNOpnJUez1np8RSW1vHFusOs3JDDwk938c/PdjE0LZpJoxIZPyyBENnzymMkwRFCCNFzHMlJTrUtTj1QQTyZofGYzZXENmRjaTxMfPE64ovXUa8Gt24aatOHtz7PYDIC/Tst3PjoIObNGsLcGQPZtMfKmq15bNxtJSOrlDc+2sGI/rGcOSSOMwdbpGWnk0mCI4QQoudpx7Y4Nl0oh4PSOWweSrCjAkvjYSyN2aTYdpJi20mtLhxrQG+KTb1xGjyzrY/RoGP8sATGD0ugrt7OTzsLWbMlj637itm0x8rrQJ+kMM4YFMcZgy30SQxrM+VcVWX6eXtJgiOEEMI/KAq1hkhqDZFkBY0g3F6CpfEwMY259KnbTp+67VQbY6ncqCNk8AR0QWEeCSMo0MDk0Umcd0YvauvtbN1bzIbdRWzaY2XRyn0sWrkPc4CeIWlRDOsbw7C+0QwfPqLdg5SdLs2vV1qWBEcIIYT/OWphwf3BY4hsKsTSmE10Uz7lXy2g7KuFVIf1oTxqOBURQ3DpAzqt6kCTjlnn9GHp6kzsjuZWqGRLCIkxwZRU1lNYWktRmY1Ne6xs3G0FwKBTiIsOIj4qiJgIM+EhJtSTjCEy6FVmT+7cXdd7GklwhBBC+DVN0VFmSqLMlERwoIGZoyLYv/oLQqv2E1Z1gN7Kx1SED6Q0chiVYf3RVMNp1Wd3qEf+deFwtu1miwoLICosgKF9mo+XVNZjLasjv7iKPGstudZaoDmBiQoLICY8kOjwQKLCAmUD0F+QBEcIIYQ4wqUaCB5yDpmFFmisJbJiJ9FlO5rX2qnYiUNnojx8CGWRwz2+xo5Br5IQHURcZCCWEAeRUTGUVjVSWllPSWU9xRX1FJXZgOYJYeHBJmIimhOeuMggj8XVU0iCI4QQQhyHQ2+mOOZMimPO5P+3d+fBUVX5Ase/9/aapJOmO6GzKQQiiRGJloOCJCSUAmopJSUuWLFKEXWUGZ3FhQKZmXJjIDI1ilUiaFzABYwbQUVLSkBwQY3KzJt5IQxbIOmE7B3SSXe6+7w/GvvJE5+AJB0uv0/VrfQ9ye0+v/7d3P7VPbfvsQY7SW37J6lt2/G0foOn9RuC5iRa3YW0uscc/tp5/55BsVpMnOFxcIbHAUA4EqHdF6C5oyda9LT3UFvXQW1dBwBbttdTMNxNwQg3BTlucrKcp9U1OVLgCCGEED8jaHXizSjGm1GMvbeF1LbtpLX+I/a186A5iQ5nPu1DCuhMOYuIqf/vb2PSddIOD1EBKKU45O+juaOH1s5eAn0hPvmunk++i05UmmAzMepMF6POHEL+cBd5w1yG/mq6FDhCCCHEcei1p1GfdSn1mZeQ5G/A3f4vXJ01sTM7Ec2ML3kEHSmj6EzJpSchfUBmPdc0jeQkK8lJVvKGubh+ch5d/iA1e9v478NLbV07//hPS2ybNKedUcNc5A9zkTfcxVlnDCHBZozSwBhRCCGEEANN0+hOyqY7KZv9Z0zFFmjD1VGDq6OGlK7dDPHtBCBoduBLyaUzeSRdjmFgyRiwLiYnWrnwnAwuPCf6muFwhLqmLmrr2g8PZ7Wz7b+8fP5PLwC6Fv1G14hsJzkZKQzPTGFEVgruFPv/exfpwUgKHCGEEOIkCNjcNKZPoDF9Ano4QMqhvaT4duH07SKtbTtpbdsBCJkT8B48m8xAKr6EM/AnZtBndgzIWR6TSWdElpMRWU4uGx9t6wmE+M+BDmr3tVO7v52d+zvYVH3giO0cCZZosZOZwhnpyWSmJZGVlsTQIQlH3JBwMDklCpwtW7awZMkSAoEAmZmZLF68GI/HE+9uCSGEEEcVMdnocObT4cwHwNJ3iOSuvTi663B278e8959kh0NkH/77PnMS/oQM/IkZ+O0eAjY3vXY3QUtKv/c1wWZmTG4aY3LTYm2HevrY5/Wx1+uL/dxd38m/drcesa1J1/C4E/G4EnCn2KOL005qSkLssSvZhtXSvzO6H82gL3Da2tq47777WLlyJfn5+axcuZJ58+ZRUVER764JIYQQx6TP4qDNfS5t7nOxW81MnziM9es2Y+86QGJPI4k9TdHip2vXEdtFNDO91iH4SEQLpBGyJBO0JNNncRAyJxEy2wnrNsImO2GTDaWfnI91R4KF0SNTGT0yNdamlKK5vYcDzYdobO3G2xJdGlq62bm/A39v6Cefz2ox4Uiw4Ei0kGSP/oyuW0m0mbHbzNitJuxWMwk2M3abCbP20893LAZ9gbN161by8/PJz49WwTNnzqS8vJzm5maGDh0a594JIYQQx083W+lOHk5n4pn/26gi2ALtJPQexB5owxZoxx5oxdbbRlqwAXNr3c8+b0QzEzbZiJhs7P9PIprJjGYygcmMppvRTGbQTWi6CXQdTdNB10HTYo81TY9+5V3T0fTvH2touo5J0xmuaeRoOjh1lFNHHxXdLhDW6QjotPdCR69GR69Ge69GZy90B6E7GKTbH6S+Q9EdVIR/ZiqxTJeFX1+RfsLv8aAvcBobG8nMzIytW61WXC4XXq/3mAqcSCT6Dvb09OBITiDU1z8h2xJt+P1+HMl2Qtb+GY88ntdQKCxWE/YEGxrHPq7b33H09/MrFLrJNKhyMRCvcSL5HmwxnAij5Pt4n1/y3Y+5sEdjSLSECenHNpnncb+GRfvp17AOIZg8hOAPmpSC9vY2UlOSsIT9mEPRxRTqxRQJokcC6OG+6ONwED0SxBzpo8+u4z/UjdYXAdWLpiJoKoKOAiKAOo5Ph2OjA6mHlyPjOrz8IKYQJnqVhT5lJqjMBDERUqbYYz1pCJAe+xw/XppSSp3QlgNk+fLl7Nmzh0WLFsXaJk6cyLJlyzj33HN/dvvW1lb27t3bjz0UQgghRH/JyckhNfVHJdPPGvRncLKysvjiiy9i68FgkPb2drKyso5pe6fTSU5ODjabTaabF0IIIU4RkUiEQCCA03lis7oP+gKnqKiIRx99lNraWvLy8qisrOS8887D7XYf0/Zms/mEKj8hhBBCxJfD4TjhbQf9EBXAZ599xuOPP04gECA1NZVFixaRnZ398xsKIYQQ4rR0ShQ4QgghhBDHQy5KEUIIIYThSIEjhBBCCMORAkcIIYQQhiMFjhBCCCEMRwocIYQQQhiOFDhCCCGEMBwpcIQQQghhOIP+Tsa/xJYtW1iyZAmBQIDMzEwWL16Mx+OJd7f61RNPPEFzczOPPfYYAGvXrmXFihWEQiEKCgp49NFHf9GdIQeb1157jVdffRVN00hISODBBx+ksLCQiooKKisrCYfDFBcXM3/+fCwWS7y7e9K8+eabvPjiiwC4XC4eeughRowYYfi4v7d9+3bKysrYsGEDGRkZht/P582bx7Zt20hOTgZg+PDhLF261PD53rlzJw8//DBdXV3ous6f//xnzj//fEPnu7Kykpdffjm23t3dzYEDB/jwww/ZsGGDofO9YcMGnnzySXRdx+Fw8PDDD5Obm3vi+7kyqNbWVnXRRRepmpoapZRSL730krr11lvj3Kv+s3//fjVnzhxVWFio5s+fr5RSqra2Vl188cWqsbFRKaXUX//6V/WnP/0pnt08qaqrq9WkSZNUa2urUkqpjz/+WBUVFalNmzapyy+/XPl8PhUKhdQ999yjli9fHufenjy7du1SF198sWppaVFKKbVy5Up10003GT7u77W0tKirr75a5eXlKa/Xa/j9XCmlpkyZonbs2HFEm9Hz3dPTo4qLi9WHH36olFJq48aNatKkSadFvr8XCoXUTTfdpJ577rnTIt9jxoxRO3fuVEpFj2tlZWW/KG7DDlFt3bqV/Px88vPzAZg5cybbtm2jubk5zj3rH2vWrGHChAnMmjUr1rZhwwZKS0tJT08HoKysjHXr1p3w1PODjdPp5JFHHonNS1ZYWEhraysfffQRV155JcnJyZhMJm688UbefvvtOPf25Bk5ciSbN28mNTWVUChEQ0MDLpfL8HEDhEIh/vjHP3L//ffH2oy+n7e0tNDQ0MDSpUuZNm0ad999N/X19YbP99atWxk6dChTp04FoLS0lGXLlhk+3z/04osvYjKZuPXWWw2f73A4jKZpdHZ2AuD3+7Hb7b8obsMWOI2NjWRmZsbWrVYrLpcLr9cbx171n3vvvZeysjJMJlOszev1HvEeZGRk4Pf76ejoiEMPT77c3FyKi4uB6KyzCxcuZNKkSUeN22h5t1gsfP3115SWlrJmzRpmzZp1WsRdXl7OuHHjKCoqirUZfT8/ePAgxcXFzJs3j6qqKgoLC7nzzjupr683dL737NmDx+NhwYIFXHPNNdx8880Eg0HD5/t7Pp+P5cuXs2DBAjRNM/z/d1JSEg899BA333wzJSUlPP/889x///2/KG7DFjhKKTRN+1G7rhs25KM62ntwtLZT2aFDh/jtb39LfX09ixcvBn4co9FiBhg7diyffvop5eXl3HHHHYCx43733Xepq6vjrrvu+tHvjLyfn3POOTzzzDNkZ2ejaRq33XYb9fX16Lpu6HyHQiE+/fRTpk+fzltvvcXs2bO54447CIVChs73915//XUmTJjAWWedFWszcr537NjB0qVLqaqq4pNPPmHBggXcfvvtRCKRE47bsJ/2WVlZNDU1xdaDwSDt7e1kZWXFsVcD6/++B01NTSQlJeF0OuPYq5Nrz549XHvttTgcDl566SVSUlKOGreR8n7gwAE+//zz2PrkyZOxWCxEIhFDx/3mm29SV1fH9OnTufrqqwGYPXs2Ho/H0Pv5t99+ywcffHBEm1KKvr4+Q+c7PT2dnJwcxo4dC0SHqMxm82lxXAN4//33mTFjRmzd6Me1rVu3MmbMGEaOHAnAtGnTCIfDhMPhE47bsAVOUVER//73v6mtrQWiV6afd955ses1TgeXXnopmzdvju0cr7zyCpMnTzbMWayGhgbKysq47rrrKC8vx2azATBlyhTee+89fD4fkUiE1atXx8bxjaCzs5Pf//73NDY2ArB582Z0XeeWW24xdNwvvPAC77//PmvXrmXt2rUAVFRUcNlllxl6Pw8GgzzyyCMcPHgQgFWrVpGbm8vs2bMNne+SkhK8Xi/fffcdANXV1QSDQSZPnmzofAN0dXVRW1vLhRdeGGsz+nFt9OjRVFdXx45rX331FaFQ6Bcd1wz7NXG3283f//535s6dSyAQIDU1lfLy8nh3a0CNGjWKBx54gNtuu42+vj5GjBjBokWL4t2tk6aiogKfz0dVVRVVVVWx9hUrVjBjxgxuvPFGQqEQF1xwwVGHNU5Vo0ePZu7cudx+++3ouk5KSgrPPvssBQUF7N6927Bx/xSj7+fjxo1jzpw5zJo1i3A4TFZWFk8++STZ2dmGzndaWhrLly9n4cKF+P1+TCYTTz31FGeffbah8w2wd+9e3G43drs91lZSUsKuXbsMm+/x48fzm9/8hlmzZmGxWEhMTGTZsmVccMEF7Nu374Ti1pRSqp/7LYQQQggxoIxzTk8IIYQQ4jApcIQQQghhOFLgCCGEEMJwpMARQgghhOFIgSOEEEIIw5ECRwghhBCGIwWOEEIIIQxHChwhxKC2ePFi8vPzqa6ujndXhBCnELnRnxBi0AoEApSUlDBlyhR8Ph9Lly6Nd5eEEKcIOYMjhBi01q9fT3Z2NnfffTcbN26koaEh9rvKykouueQSxo0bx4IFC5g5cyZvvfUWEJ2va968eRQXFzNx4kQee+wxAoFAvMIQQsSBFDhCiEFr9erVXH/99aSnp1NaWsrLL78MRCfiW7hwIeXl5WzZsoWMjAy+/fbb2HZz586lu7ub9evXs3btWmpra/nb3/4WrzCEEHEgBY4QYlCqqalh586dTJs2DYCysjLeeOMNenp6eOedd5g2bRpjx47FarUyZ84cPB4PAC0tLWzcuJH58+eTnJyM2+3mD3/4A5WVlfEMRwgxwAw7m7gQ4tT22muvEQgEmDp1aqyts7OTt99+m8bGRsaOHRtr13WdzMxMgNgw1lVXXXXE84VCIVpaWkhLSxuA3gsh4k0KHCHEoNPd3c26det4+umnKSgoiLWvXr2aVatW8atf/Qqv1xtrV0rR2NgIQHp6OpqmsWnTJhwOBwA9PT0cPHiQ1NTUgQ1ECBE3MkQlhBh0qqqqcLvdlJSUMHTo0Nhyww03sG/fPs4880zeffddvvnmG0KhEBUVFTQ1NQHRAqeoqIiFCxdy6NAh/H4/f/nLX7jnnnvQNC3OkQkhBooUOEKIQWfNmjWxa29+yOPxUFJSwpdffsl9993H7373O4qKiti/fz9ZWVlYLBYAHn/8ccLhMJdffjmlpaV0dnby9NNPD3QYQog4kvvgCCFOObt378ZsNjNs2LBY2/jx41myZAnFxcVx7JkQYrCQMzhCiFNOTU0Ns2fPpqmpiUgkwqpVqwiHw5x//vnx7poQYpCQi4yFEKecK664gh07djBjxgy6u7vJy8tjxYoVsYuKhRBChqiEEEIIYTgyRCWEEEIIw5ECRwghhBCGIwWOEEIIIQxHChwhhBBCGI4UOEIIIYQwHClwhBBCCGE4/wMMXfKlTxhn8QAAAABJRU5ErkJggg==",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
-    "# your code here"
+    "plt.figure(figsize=(8, 6))\n",
+    "sns.histplot(data=titanic, x=\"Age\", hue=\"Gender\", kde=True, bins=20, color='skyblue')\n",
+    "\n",
+    "plt.xlabel(\"Age\")\n",
+    "plt.ylabel(\"Passengers Gender\")\n",
+    "plt.title(\"Age Distribution by Gender\")\n",
+    "\n",
+    "plt.show()"
    ]
   }
  ],
@@ -318,7 +839,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.12"
+   "version": "3.11.5"
   },
   "nbTranslate": {
    "displayLangs": [
diff --git a/your-code/main.ipynb b/your-code/main.ipynb
new file mode 100644
index 0000000..ab83cdd
--- /dev/null
+++ b/your-code/main.ipynb
@@ -0,0 +1,503 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Lab | Matplotlib & Seaborn\n",
+    "\n",
+    "#### Import all the necessary libraries here:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Libraries\n",
+    "import numpy as np\n",
+    "# Your Code Here"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Challenge \n",
+    "#### Import the `Fitbit2` dataset and store it in a variable called `fitbit`. You can find the dataset in Ironhack's database:\n",
+    "* db: `fitbit`\n",
+    "* table: `fitbit2`"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# your code here"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### From the Fitbit data, we want to visually understand:\n",
+    "\n",
+    "How the average number of steps change by month. Use the appropriate visualization to show the median steps by month. Is Fitbitter more active on weekend or workdays?\n",
+    "**Hints**:\n",
+    "\n",
+    "* Use Months_encoded and Week_or Weekend columns.\n",
+    "* Set your size figure to 12,4\n",
+    "* Explore plt.sca\n",
+    "* Explore plt.xticks\n",
+    "* Save your figures in a folder called `figures` in your repo. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# AVERAGE STEPS BY MONTH_ENCODED\n",
+    "# your code here"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# AVERAGE STEPS BY WORK_OR_WEEKEND\n",
+    "# your code here"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Write a loop to plot 3 scatter plots of the following features:\n",
+    "\n",
+    "* Minutes Lightly Active vs Steps    \n",
+    "* Minutes Very Active vs Steps    \n",
+    "* Minutes Sedentary vs Steps  "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# your code here"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Challenge \n",
+    "\n",
+    "#### Import the `titanic` dataset and store it in a variable called `titanic`. You can find the dataset in Ironhack's database:\n",
+    "* db: `titanic`\n",
+    "* table: `titanic`"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": [
+    "# your code here"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Explore the titanic dataset using Pandas dtypes."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# your code here"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### What are your numerical variables? What are your categorical variables?\n",
+    "**Hint**: Use Pandas select_dtypes."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# NUMERICAL VARIABLES\n",
+    "# your code here"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# CATEGORICAL VARIABLES\n",
+    "# your code here"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Set the plot style to classic and the figure size to (12,6).\n",
+    "**Hint**: To set the style you can use matplotlib or seaborn functions. Do some research on the matter."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# your code here"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Use the right visulalization to show the distribution of column `Age`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# your code here"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Use subplots and plot the distribution of the `Age`  with bins equal to 10, 20 and 50."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# your code here"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### How does the bin size affect your plot?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\"\"\"\n",
+    "your comments here\n",
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Use seaborn to show the distribution of column `Age`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# your code here"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Use the right plot to visualize column `Gender`. There are 2 ways of doing it. Do it both ways.\n",
+    "**Hint**: Use matplotlib and seaborn."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Method 1 - matplotlib\n",
+    "# your code here"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Method 2 - seaborn\n",
+    "# your code here"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Use the right plot to visualize the column `Pclass`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# your code here"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### We would like to have in one single plot the summary statistics of the feature `Age`. What kind of plot would you use? Plot it. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# your code here"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\"\"\"\n",
+    "your comments here\n",
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### What does the last plot tell you about the feature `Age`?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\"\"\"\n",
+    "your comments here\n",
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Now in addition to the summary statistics, we want to have in the same plot the distribution of `Age`. What kind of plot would you use? Plot it. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# your code here"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### What additional information does the last plot provide about feature `Age`?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\"\"\"\n",
+    "your comments here\n",
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### We suspect that there is a linear relationship between `Fare` and `Age`. Use the right plot to show the relationship between these 2 features. There are 2 ways, please do it both ways.\n",
+    "**Hint**: Use matplotlib and seaborn."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Method 1 - matplotlib\n",
+    "# your code here"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Method 2 - seaborn\n",
+    "# your code here"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Plot the correlation matrix using seaborn."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# your code here"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### What are the most correlated features?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\"\"\"\n",
+    "your comments here\n",
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Use the most appropriate plot to display the summary statistics of `Age` depending on `Pclass`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": [
+    "# your code here"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Use seaborn to plot the distribution of `Age` based on the `Gender`.\n",
+    "**Hint**: Use Facetgrid."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# your code here"
+   ]
+  }
+ ],
+ "metadata": {
+  "anaconda-cloud": {},
+  "kernelspec": {
+   "display_name": "ironhack",
+   "language": "python",
+   "name": "ironhack"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.5"
+  },
+  "toc": {
+   "base_numbering": 1,
+   "nav_menu": {},
+   "number_sections": true,
+   "sideBar": true,
+   "skip_h1_title": true,
+   "title_cell": "Table of Contents",
+   "title_sidebar": "Contents",
+   "toc_cell": false,
+   "toc_position": {},
+   "toc_section_display": true,
+   "toc_window_display": false
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}