diff --git a/your-code/main.ipynb b/your-code/main.ipynb
index 31724c5..79240ed 100644
--- a/your-code/main.ipynb
+++ b/your-code/main.ipynb
@@ -9,10 +9,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 24,
    "metadata": {},
    "outputs": [],
-   "source": []
+   "source": [
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np"
+   ]
   },
   {
    "cell_type": "markdown",
@@ -23,10 +27,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [],
-   "source": []
+   "source": [
+    "import pymysql\n",
+    "from sqlalchemy import create_engine\n"
+   ]
   },
   {
    "cell_type": "markdown",
@@ -37,10 +44,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [],
-   "source": []
+   "source": [
+    "engine = create_engine('mysql+pymysql://guest:relational@relational.fit.cvut.cz')"
+   ]
   },
   {
    "cell_type": "markdown",
@@ -51,10 +60,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [],
-   "source": []
+   "source": [
+    "user_table = pd.read_sql_query('SELECT * FROM stats.users', engine)"
+   ]
   },
   {
    "cell_type": "markdown",
@@ -65,10 +76,38 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 5,
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "userId                                                             8\n",
+       "Reputation                                                      6764\n",
+       "CreationDate                                     2010-07-19 19:04:52\n",
+       "DisplayName                                              csgillespie\n",
+       "LastAccessDate                                   2014-09-09 21:15:08\n",
+       "WebsiteUrl                          http://www.mas.ncl.ac.uk/~ncsg3/\n",
+       "Location                                   Newcastle, United Kingdom\n",
+       "AboutMe            <p>I'm a statistics lecturer at Newcastle Univ...\n",
+       "Views                                                           1089\n",
+       "UpVotes                                                          604\n",
+       "DownVotes                                                         25\n",
+       "AccountId                                                      70002\n",
+       "Age                                                             36.0\n",
+       "ProfileImageUrl                                                 None\n",
+       "Name: 7, dtype: object"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "user_table.rename(columns = {'Id':'userId'}, inplace=True)\n",
+    "user_table.loc[7]"
+   ]
   },
   {
    "cell_type": "markdown",
@@ -79,10 +118,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [],
-   "source": []
+   "source": [
+    "post_table = pd.read_sql_query('SELECT * FROM stats.posts', engine)"
+   ]
   },
   {
    "cell_type": "markdown",
@@ -93,10 +134,24 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 7,
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "24.0"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "post_table.rename(columns = {'Id':'postId', \"OwnerUserId\":\"userId\" }, inplace=True)\n",
+    "post_table.loc[ 9, 'userId']"
+   ]
   },
   {
    "cell_type": "markdown",
@@ -109,10 +164,160 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 9,
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>postId</th>\n",
+       "      <th>Score</th>\n",
+       "      <th>userId</th>\n",
+       "      <th>ViewCount</th>\n",
+       "      <th>CommentCount</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>23</td>\n",
+       "      <td>8.0</td>\n",
+       "      <td>1278.0</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>22</td>\n",
+       "      <td>24.0</td>\n",
+       "      <td>8198.0</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>54</td>\n",
+       "      <td>18.0</td>\n",
+       "      <td>3613.0</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>13</td>\n",
+       "      <td>23.0</td>\n",
+       "      <td>5224.0</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>81</td>\n",
+       "      <td>23.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>91971</th>\n",
+       "      <td>115374</td>\n",
+       "      <td>2</td>\n",
+       "      <td>805.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>91972</th>\n",
+       "      <td>115375</td>\n",
+       "      <td>0</td>\n",
+       "      <td>49365.0</td>\n",
+       "      <td>9.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>91973</th>\n",
+       "      <td>115376</td>\n",
+       "      <td>1</td>\n",
+       "      <td>55746.0</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>91974</th>\n",
+       "      <td>115377</td>\n",
+       "      <td>0</td>\n",
+       "      <td>805.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>91975</th>\n",
+       "      <td>115378</td>\n",
+       "      <td>0</td>\n",
+       "      <td>7250.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>91976 rows × 5 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       postId  Score   userId  ViewCount  CommentCount\n",
+       "0           1     23      8.0     1278.0             1\n",
+       "1           2     22     24.0     8198.0             1\n",
+       "2           3     54     18.0     3613.0             4\n",
+       "3           4     13     23.0     5224.0             2\n",
+       "4           5     81     23.0        NaN             3\n",
+       "...       ...    ...      ...        ...           ...\n",
+       "91971  115374      2    805.0        NaN             2\n",
+       "91972  115375      0  49365.0        9.0             0\n",
+       "91973  115376      1  55746.0        5.0             2\n",
+       "91974  115377      0    805.0        NaN             0\n",
+       "91975  115378      0   7250.0        NaN             0\n",
+       "\n",
+       "[91976 rows x 5 columns]"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "user_df = user_table[[\"userId\", \"Reputation\", \"Views\", \"UpVotes\", \"DownVotes\"]]\n",
+    "posts_df = post_table[[\"postId\", \"Score\", \"userId\", \"ViewCount\", \"CommentCount\"]]\n",
+    "\n",
+    "user_df\n",
+    "posts_df"
+   ]
   },
   {
    "cell_type": "markdown",
@@ -126,8 +331,216 @@
    "cell_type": "code",
    "execution_count": 11,
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>postId</th>\n",
+       "      <th>Score</th>\n",
+       "      <th>userId</th>\n",
+       "      <th>ViewCount</th>\n",
+       "      <th>CommentCount</th>\n",
+       "      <th>Reputation</th>\n",
+       "      <th>Views</th>\n",
+       "      <th>UpVotes</th>\n",
+       "      <th>DownVotes</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>23</td>\n",
+       "      <td>8.0</td>\n",
+       "      <td>1278.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>6764</td>\n",
+       "      <td>1089</td>\n",
+       "      <td>604</td>\n",
+       "      <td>25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>16</td>\n",
+       "      <td>16</td>\n",
+       "      <td>8.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>3</td>\n",
+       "      <td>6764</td>\n",
+       "      <td>1089</td>\n",
+       "      <td>604</td>\n",
+       "      <td>25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>36</td>\n",
+       "      <td>41</td>\n",
+       "      <td>8.0</td>\n",
+       "      <td>67396.0</td>\n",
+       "      <td>7</td>\n",
+       "      <td>6764</td>\n",
+       "      <td>1089</td>\n",
+       "      <td>604</td>\n",
+       "      <td>25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>65</td>\n",
+       "      <td>14</td>\n",
+       "      <td>8.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>3</td>\n",
+       "      <td>6764</td>\n",
+       "      <td>1089</td>\n",
+       "      <td>604</td>\n",
+       "      <td>25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>78</td>\n",
+       "      <td>33</td>\n",
+       "      <td>8.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>4</td>\n",
+       "      <td>6764</td>\n",
+       "      <td>1089</td>\n",
+       "      <td>604</td>\n",
+       "      <td>25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>90579</th>\n",
+       "      <td>115366</td>\n",
+       "      <td>1</td>\n",
+       "      <td>55742.0</td>\n",
+       "      <td>17.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>6</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>90580</th>\n",
+       "      <td>115370</td>\n",
+       "      <td>1</td>\n",
+       "      <td>55744.0</td>\n",
+       "      <td>13.0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>6</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>90581</th>\n",
+       "      <td>115371</td>\n",
+       "      <td>0</td>\n",
+       "      <td>35801.0</td>\n",
+       "      <td>19.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>90582</th>\n",
+       "      <td>115375</td>\n",
+       "      <td>0</td>\n",
+       "      <td>49365.0</td>\n",
+       "      <td>9.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>90583</th>\n",
+       "      <td>115376</td>\n",
+       "      <td>1</td>\n",
+       "      <td>55746.0</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>106</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>90584 rows × 9 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       postId  Score   userId  ViewCount  CommentCount  Reputation  Views  \\\n",
+       "0           1     23      8.0     1278.0             1        6764   1089   \n",
+       "1          16     16      8.0        NaN             3        6764   1089   \n",
+       "2          36     41      8.0    67396.0             7        6764   1089   \n",
+       "3          65     14      8.0        NaN             3        6764   1089   \n",
+       "4          78     33      8.0        NaN             4        6764   1089   \n",
+       "...       ...    ...      ...        ...           ...         ...    ...   \n",
+       "90579  115366      1  55742.0       17.0             0           6      0   \n",
+       "90580  115370      1  55744.0       13.0             2           6      1   \n",
+       "90581  115371      0  35801.0       19.0             0           1      1   \n",
+       "90582  115375      0  49365.0        9.0             0           1      0   \n",
+       "90583  115376      1  55746.0        5.0             2         106      1   \n",
+       "\n",
+       "       UpVotes  DownVotes  \n",
+       "0          604         25  \n",
+       "1          604         25  \n",
+       "2          604         25  \n",
+       "3          604         25  \n",
+       "4          604         25  \n",
+       "...        ...        ...  \n",
+       "90579        0          0  \n",
+       "90580        0          0  \n",
+       "90581        0          0  \n",
+       "90582        0          0  \n",
+       "90583        0          0  \n",
+       "\n",
+       "[90584 rows x 9 columns]"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "combined_merge = pd.merge(right=user_df, left=posts_df, on=\"userId\")\n",
+    "combined_merge\n"
+   ]
   },
   {
    "cell_type": "markdown",
@@ -138,10 +551,33 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 12,
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "postId              0\n",
+       "Score               0\n",
+       "userId              0\n",
+       "ViewCount       48396\n",
+       "CommentCount        0\n",
+       "Reputation          0\n",
+       "Views               0\n",
+       "UpVotes             0\n",
+       "DownVotes           0\n",
+       "dtype: int64"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "null_cols = combined_merge.isnull().sum()\n",
+    "null_cols "
+   ]
   },
   {
    "cell_type": "markdown",
@@ -153,10 +589,37 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 13,
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "Int64Index: 90584 entries, 0 to 90583\n",
+      "Data columns (total 8 columns):\n",
+      " #   Column        Non-Null Count  Dtype  \n",
+      "---  ------        --------------  -----  \n",
+      " 0   postId        90584 non-null  int64  \n",
+      " 1   Score         90584 non-null  int64  \n",
+      " 2   userId        90584 non-null  float64\n",
+      " 3   CommentCount  90584 non-null  int64  \n",
+      " 4   Reputation    90584 non-null  int64  \n",
+      " 5   Views         90584 non-null  int64  \n",
+      " 6   UpVotes       90584 non-null  int64  \n",
+      " 7   DownVotes     90584 non-null  int64  \n",
+      "dtypes: float64(1), int64(7)\n",
+      "memory usage: 6.2 MB\n"
+     ]
+    }
+   ],
+   "source": [
+    "combined_merge[\"ViewCount\"].isnull().mean()* 100\n",
+    "## 53% de los datos son nulos la opción viable es elimanrr\n",
+    "cleaned_data = combined_merge.drop(['ViewCount'], axis=1)\n",
+    "cleaned_data.info()"
+   ]
   },
   {
    "cell_type": "markdown",
@@ -167,10 +630,206 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 15,
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>postId</th>\n",
+       "      <th>Score</th>\n",
+       "      <th>userId</th>\n",
+       "      <th>CommentCount</th>\n",
+       "      <th>Reputation</th>\n",
+       "      <th>Views</th>\n",
+       "      <th>UpVotes</th>\n",
+       "      <th>DownVotes</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>23</td>\n",
+       "      <td>8</td>\n",
+       "      <td>1</td>\n",
+       "      <td>6764</td>\n",
+       "      <td>1089</td>\n",
+       "      <td>604</td>\n",
+       "      <td>25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>16</td>\n",
+       "      <td>16</td>\n",
+       "      <td>8</td>\n",
+       "      <td>3</td>\n",
+       "      <td>6764</td>\n",
+       "      <td>1089</td>\n",
+       "      <td>604</td>\n",
+       "      <td>25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>36</td>\n",
+       "      <td>41</td>\n",
+       "      <td>8</td>\n",
+       "      <td>7</td>\n",
+       "      <td>6764</td>\n",
+       "      <td>1089</td>\n",
+       "      <td>604</td>\n",
+       "      <td>25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>65</td>\n",
+       "      <td>14</td>\n",
+       "      <td>8</td>\n",
+       "      <td>3</td>\n",
+       "      <td>6764</td>\n",
+       "      <td>1089</td>\n",
+       "      <td>604</td>\n",
+       "      <td>25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>78</td>\n",
+       "      <td>33</td>\n",
+       "      <td>8</td>\n",
+       "      <td>4</td>\n",
+       "      <td>6764</td>\n",
+       "      <td>1089</td>\n",
+       "      <td>604</td>\n",
+       "      <td>25</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",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>90579</th>\n",
+       "      <td>115366</td>\n",
+       "      <td>1</td>\n",
+       "      <td>55742</td>\n",
+       "      <td>0</td>\n",
+       "      <td>6</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>90580</th>\n",
+       "      <td>115370</td>\n",
+       "      <td>1</td>\n",
+       "      <td>55744</td>\n",
+       "      <td>2</td>\n",
+       "      <td>6</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>90581</th>\n",
+       "      <td>115371</td>\n",
+       "      <td>0</td>\n",
+       "      <td>35801</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>90582</th>\n",
+       "      <td>115375</td>\n",
+       "      <td>0</td>\n",
+       "      <td>49365</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>90583</th>\n",
+       "      <td>115376</td>\n",
+       "      <td>1</td>\n",
+       "      <td>55746</td>\n",
+       "      <td>2</td>\n",
+       "      <td>106</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>90584 rows × 8 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       postId  Score  userId  CommentCount  Reputation  Views  UpVotes  \\\n",
+       "0           1     23       8             1        6764   1089      604   \n",
+       "1          16     16       8             3        6764   1089      604   \n",
+       "2          36     41       8             7        6764   1089      604   \n",
+       "3          65     14       8             3        6764   1089      604   \n",
+       "4          78     33       8             4        6764   1089      604   \n",
+       "...       ...    ...     ...           ...         ...    ...      ...   \n",
+       "90579  115366      1   55742             0           6      0        0   \n",
+       "90580  115370      1   55744             2           6      1        0   \n",
+       "90581  115371      0   35801             0           1      1        0   \n",
+       "90582  115375      0   49365             0           1      0        0   \n",
+       "90583  115376      1   55746             2         106      1        0   \n",
+       "\n",
+       "       DownVotes  \n",
+       "0             25  \n",
+       "1             25  \n",
+       "2             25  \n",
+       "3             25  \n",
+       "4             25  \n",
+       "...          ...  \n",
+       "90579          0  \n",
+       "90580          0  \n",
+       "90581          0  \n",
+       "90582          0  \n",
+       "90583          0  \n",
+       "\n",
+       "[90584 rows x 8 columns]"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cleaned_data['userId'] = pd.to_numeric(cleaned_data[\"userId\"], downcast=\"integer\")\n",
+    "cleaned_data"
+   ]
   },
   {
    "cell_type": "markdown",
@@ -178,11 +837,329 @@
    "source": [
     "#### Bonus: Identify extreme values in your merged dataframe as you have learned in class, create a dataframe called outliers with the same columns as our data set and calculate the bounds. The values of the outliers dataframe will be the values of the merged_df that fall outside that bounds. You will need to save your outliers dataframe to a csv file on your-code folder."
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "AxesSubplot(0.125,0.125;0.775x0.755)\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYkAAAD6CAYAAABUHLtmAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/YYfK9AAAACXBIWXMAAAsTAAALEwEAmpwYAAASNElEQVR4nO3dbZCd5X3f8e+vksE4qQGbHepIuKuplQcZx429g0k94/FYLQjjWiRDHEgnqC5jTWrcpmknsWhfKPXDjDzJlIaJTUaNVITjsUyoO2gsOYqCnWaSDJjFJGAhE7Y8RNJgs7FAuCV+kPPvi71kny57adk90lmBvp+ZM3vf/+u6r/u69eL8dD+cc1JVSJI0l7+31BOQJJ2+DAlJUpchIUnqMiQkSV2GhCSpy5CQJHXNGxJJtid5KslXBmq/keSrSR5I8j+TnDfQdmOSqSQPJ7l8oL6u1aaSbBqor0pyT6t/JslZrX52W59q7eMn66AlSS9M5vucRJK3Af8HuK2qLm61y4AvVNWxJB8DqKoPJlkDfBq4BPgR4I+AH21D/RXwz4BDwL3AtVX1UJLbgc9W1c4kvwP8ZVXdkuT9wE9W1S8luQb4mar6+fkO6IILLqjx8fEF/jNI0pntvvvu+5uqGptdXz7fhlX1J7P/F19VfziwejdwdVteD+ysqm8DjyWZYiYwAKaq6lGAJDuB9UkOAO8AfqH12QH8OnBLG+vXW/0O4LeTpOZJtfHxcSYnJ+c7LEnSgCRPzFU/Gfck/hXw+ba8Ajg40Hao1Xr1VwPPVNWxWfX/b6zWfrT1f54kG5NMJpmcnp4e+oAkSTOGCokk/wk4Bnzq5Exncapqa1VNVNXE2NjzzpYkSYs07+WmniT/EngXsHbgEtBh4KKBbitbjU79G8B5SZa3s4XB/sfHOpRkOXBu6y9JGpFFnUkkWQf8GvDuqnpuoGkXcE17MmkVsBr4EjM3qle3J5nOAq4BdrVw+SI/uKexAbhzYKwNbflqZm6U+22EkjRC855JJPk08HbggiSHgM3AjcDZwL4kAHdX1S9V1f72tNJDzFyGuqGqvtfG+QCwF1gGbK+q/W0XHwR2JvkIcD+wrdW3AZ9sN7+PMBMskqQRmvcR2BebiYmJ8ukmSVqYJPdV1cTsup+4liR1GRKSpK5FP90knenGN+0eyX4e33LlSPYjzcWQkBZpoW/e45t2+4avFx0vN0mSugwJSVKXISFJ6jIkJEldhoQkqcuQkCR1GRKSpC5DQpLUZUhIkroMCUlSlyEhSeoyJCRJXYaEJKnLkJAkdRkSkqQuQ0KS1GVISJK6DAlJUpchIUnqMiQkSV2GhCSpa96QSLI9yVNJvjJQe1WSfUkeaX/Pb/UkuTnJVJIHkrxpYJsNrf8jSTYM1N+c5MG2zc1JcqJ9SJJG54WcSdwKrJtV2wTcVVWrgbvaOsAVwOr22gjcAjNv+MBm4C3AJcDmgTf9W4D3DWy3bp59SJJGZN6QqKo/AY7MKq8HdrTlHcBVA/XbasbdwHlJXgNcDuyrqiNV9TSwD1jX2l5ZVXdXVQG3zRprrn1IkkZksfckLqyqJ9vy14AL2/IK4OBAv0OtdqL6oTnqJ9qHJGlEhr5x3c4A6iTMZdH7SLIxyWSSyenp6VM5FUk6oyw2JL7eLhXR/j7V6oeBiwb6rWy1E9VXzlE/0T6ep6q2VtVEVU2MjY0t8pAkSbMtNiR2AcefUNoA3DlQv6495XQpcLRdMtoLXJbk/HbD+jJgb2t7Nsml7amm62aNNdc+JEkjsny+Dkk+DbwduCDJIWaeUtoC3J7keuAJ4D2t+x7gncAU8BzwXoCqOpLkw8C9rd+Hqur4zfD3M/ME1TnA59uLE+xDkjQi84ZEVV3baVo7R98CbuiMsx3YPkd9Erh4jvo35tqHJGl0/MS1JKnLkJAkdRkSkqQuQ0KS1GVISJK6DAlJUpchIUnqMiQkSV2GhCSpy5CQJHUZEpKkLkNCktRlSEiSugwJSVKXISFJ6jIkJEldhoQkqcuQkCR1zfvzpdKZ4I3/+Q85+rffPeX7Gd+0+5SOf+45L+MvN192SvehM4shIQFH//a7PL7lyqWextBOdQjpzOPlJklSlyEhSeoyJCRJXYaEJKnLkJAkdRkSkqSuoUIiya8k2Z/kK0k+neTlSVYluSfJVJLPJDmr9T27rU+19vGBcW5s9YeTXD5QX9dqU0k2DTNXSdLCLTokkqwA/i0wUVUXA8uAa4CPATdV1euAp4Hr2ybXA0+3+k2tH0nWtO1eD6wDPpFkWZJlwMeBK4A1wLWtryRpRIa93LQcOCfJcuAVwJPAO4A7WvsO4Kq2vL6t09rXJkmr76yqb1fVY8AUcEl7TVXVo1X1HWBn6ytJGpFFh0RVHQZ+E/hrZsLhKHAf8ExVHWvdDgEr2vIK4GDb9ljr/+rB+qxtevXnSbIxyWSSyenp6cUekiRplmEuN53PzP/sVwE/AvwQM5eLRq6qtlbVRFVNjI2NLcUUJOklaZjLTf8UeKyqpqvqu8BngbcC57XLTwArgcNt+TBwEUBrPxf4xmB91ja9uiRpRIYJib8GLk3yinZvYS3wEPBF4OrWZwNwZ1ve1dZp7V+oqmr1a9rTT6uA1cCXgHuB1e1pqbOYubm9a4j5SpIWaNHfAltV9yS5A/gycAy4H9gK7AZ2JvlIq21rm2wDPplkCjjCzJs+VbU/ye3MBMwx4Iaq+h5Akg8Ae5l5cmp7Ve1f7HwlSQs31FeFV9VmYPOs8qPMPJk0u++3gJ/rjPNR4KNz1PcAe4aZoyRp8fzEtSSpy5CQJHUZEpKkLkNCktRlSEiSugwJSVKXISFJ6jIkJEldhoQkqcuQkCR1GRKSpC5DQpLUZUhIkroMCUlSlyEhSeoyJCRJXYaEJKnLkJAkdRkSkqQuQ0KS1GVISJK6DAlJUpchIUnqMiQkSV2GhCSpa6iQSHJekjuSfDXJgSQ/neRVSfYleaT9Pb/1TZKbk0wleSDJmwbG2dD6P5Jkw0D9zUkebNvcnCTDzFeStDDDnkn8FvAHVfXjwBuBA8Am4K6qWg3c1dYBrgBWt9dG4BaAJK8CNgNvAS4BNh8PltbnfQPbrRtyvpKkBVh0SCQ5F3gbsA2gqr5TVc8A64EdrdsO4Kq2vB64rWbcDZyX5DXA5cC+qjpSVU8D+4B1re2VVXV3VRVw28BYkqQRGOZMYhUwDfz3JPcn+d0kPwRcWFVPtj5fAy5syyuAgwPbH2q1E9UPzVF/niQbk0wmmZyenh7ikCRJg4YJieXAm4BbquqngP/LDy4tAdDOAGqIfbwgVbW1qiaqamJsbOxU706SzhjDhMQh4FBV3dPW72AmNL7eLhXR/j7V2g8DFw1sv7LVTlRfOUddkjQiiw6JqvoacDDJj7XSWuAhYBdw/AmlDcCdbXkXcF17yulS4Gi7LLUXuCzJ+e2G9WXA3tb2bJJL21NN1w2MJUkageVDbv9vgE8lOQt4FHgvM8Fze5LrgSeA97S+e4B3AlPAc60vVXUkyYeBe1u/D1XVkbb8fuBW4Bzg8+0lSRqRzNw2eOmYmJioycnJpZ6GXmTesOMNSz2Fk+bBDQ8u9RT0IpTkvqqamF0f9kxCekn45oEtPL7lyqWextDGN+1e6inoJcav5ZAkdRkSkqQuQ0KS1GVISJK6DAlJUpchIUnqMiQkSV2GhCSpy5CQJHUZEpKkLkNCktRlSEiSugwJSVKXISFJ6jIkJEldhoQkqcuQkCR1GRKSpC5DQpLUZUhIkroMCUlSlyEhSeoyJCRJXYaEJKlr6JBIsizJ/Uk+19ZXJbknyVSSzyQ5q9XPbutTrX18YIwbW/3hJJcP1Ne12lSSTcPOVZK0MCfjTOKXgQMD6x8Dbqqq1wFPA9e3+vXA061+U+tHkjXANcDrgXXAJ1rwLAM+DlwBrAGubX0lSSMyVEgkWQlcCfxuWw/wDuCO1mUHcFVbXt/Wae1rW//1wM6q+nZVPQZMAZe011RVPVpV3wF2tr6SpBEZ9kzivwK/BvxdW3818ExVHWvrh4AVbXkFcBCgtR9t/b9fn7VNr/48STYmmUwyOT09PeQhSZKOW3RIJHkX8FRV3XcS57MoVbW1qiaqamJsbGyppyNJLxnLh9j2rcC7k7wTeDnwSuC3gPOSLG9nCyuBw63/YeAi4FCS5cC5wDcG6scNbtOrS5JGYNFnElV1Y1WtrKpxZm48f6Gq/gXwReDq1m0DcGdb3tXWae1fqKpq9Wva00+rgNXAl4B7gdXtaamz2j52LXa+kqSFG+ZMoueDwM4kHwHuB7a1+jbgk0mmgCPMvOlTVfuT3A48BBwDbqiq7wEk+QCwF1gGbK+q/adgvpKkjpMSElX1x8Aft+VHmXkyaXafbwE/19n+o8BH56jvAfacjDlKkhbOT1xLkroMCUlSlyEhSeoyJCRJXYaEJKnLkJAkdRkSkqQuQ0KS1GVISJK6DAlJUpchIUnqMiQkSV2GhCSpy5CQJHUZEpKkLkNCktRlSEiSugwJSVLXqfiNa+lFaXzT7qWewtDOPedlSz0FvcQYEhLw+JYrT/k+xjftHsl+pJPJy02SpC5DQpLUZUhIkroMCUlSlyEhSeoyJCRJXYsOiSQXJflikoeS7E/yy63+qiT7kjzS/p7f6klyc5KpJA8kedPAWBta/0eSbBiovznJg22bm5NkmIOVJC3MMGcSx4D/UFVrgEuBG5KsATYBd1XVauCutg5wBbC6vTYCt8BMqACbgbcAlwCbjwdL6/O+ge3WDTFfSdICLTokqurJqvpyW/4mcABYAawHdrRuO4Cr2vJ64LaacTdwXpLXAJcD+6rqSFU9DewD1rW2V1bV3VVVwG0DY0mSRuCk3JNIMg78FHAPcGFVPdmavgZc2JZXAAcHNjvUaieqH5qjPtf+NyaZTDI5PT093MFIkr5v6JBI8sPA/wD+XVU9O9jWzgBq2H3Mp6q2VtVEVU2MjY2d6t1J0hljqJBI8jJmAuJTVfXZVv56u1RE+/tUqx8GLhrYfGWrnai+co66JGlEhnm6KcA24EBV/ZeBpl3A8SeUNgB3DtSva085XQocbZel9gKXJTm/3bC+DNjb2p5Ncmnb13UDY0mSRmCYb4F9K/CLwINJ/qLV/iOwBbg9yfXAE8B7Wtse4J3AFPAc8F6AqjqS5MPAva3fh6rqSFt+P3ArcA7w+faSJI3IokOiqv4U6H1uYe0c/Qu4oTPWdmD7HPVJ4OLFzlGSNBw/cS1J6jIkJEldhoQkqcuQkCR1GRKSpC5DQpLUZUhIkroMCUlSlyEhSeoyJCRJXYaEJKnLkJAkdRkSkqQuQ0KS1GVISJK6DAlJUpchIUnqMiQkSV2GhCSpy5CQJHUZEpKkLkNCktRlSEiSugwJSVKXISFJ6jrtQyLJuiQPJ5lKsmmp5yNJZ5LTOiSSLAM+DlwBrAGuTbJmaWclSWeO0zokgEuAqap6tKq+A+wE1i/xnCTpjLF8qScwjxXAwYH1Q8BbZndKshHYCPDa1752NDPTGW980+6RbPP4lisXvI10spzuIfGCVNVWYCvAxMRELfF0dIbwzVtngtP9ctNh4KKB9ZWtJkkagdM9JO4FVidZleQs4Bpg1xLPSZLOGKf15aaqOpbkA8BeYBmwvar2L/G0JOmMcVqHBEBV7QH2LPU8JOlMdLpfbpIkLSFDQpLUZUhIkroMCUlSV6peWp89SzINPLHU85DmcAHwN0s9CanjH1bV2OziSy4kpNNVksmqmljqeUgL4eUmSVKXISFJ6jIkpNHZutQTkBbKexKSpC7PJCRJXYaEJKnLkJCWQJKrBn+vPcmtSa6eo9/bk3xutLOTfsCQkJbGVcCa+TpJS82QkBYoyXiSryb5VJIDSe5I8ooka5Pcn+TBJNuTnN36b0nyUJIHkvxmkn8CvBv4jSR/keQfzRp/XRv/y8DPLsEhSt9nSEiL82PAJ6rqJ4BngX8P3Ar8fFW9gZnfavnXSV4N/Azw+qr6SeAjVfXnzPzC4q9W1T+uqv99fNAkLwf+G/DPgTcD/2CExyQ9jyEhLc7Bqvqztvx7wFrgsar6q1bbAbwNOAp8C9iW5GeB5+YZ98fbOI/UzPPpv3fypy69cIaEtDizP2D0zJydqo4BlwB3AO8C/uDUTks6uQwJaXFem+Sn2/IvAJPAeJLXtdovAv8ryQ8D57af4f0V4I2t/ZvA359j3K+2cY7fp7j2lMxeeoEMCWlxHgZuSHIAOB+4CXgv8PtJHgT+DvgdZoLgc0keAP6UmXsXADuBX203ur9/47qqvgVsBHa3G9dPjeqApLn4tRzSAiUZBz5XVRcv9VykU80zCUlSl2cSkqQuzyQkSV2GhCSpy5CQJHUZEpKkLkNCktT1/wAiMSiktCeDMgAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "--------------------------------------------------------------------------------\n",
+      "AxesSubplot(0.125,0.125;0.775x0.755)\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "--------------------------------------------------------------------------------\n",
+      "AxesSubplot(0.125,0.125;0.775x0.755)\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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g74FlwBnA31bVPUneB/xO224OsLpr//OAzwAXAd8G5g3mzKTeDANpakaBC6vqlSTzW+2vgQeq6o9a7dEk/97a3g68taoOtIA57E+Al6vqzUneCnxtMMOXevM2kTQ1jwOfT/IHdK4OAFYAo0keAx4CzgIWt7btVXWgx35+HfgcQFU93vYrzRjDQOrtED///8dZ7f0q4HY63/h3tGcBAX63qi5ur8VVtbv1/++BjVg6DoaB1NvzwBuTvCHJq4F30/n/ZVFVPQh8BDiHzvOAbcCfJglAkrf1sf+vAr/X+i8D3nriT0Hqn88MpB6q6qdJbgIeBfbSecg7B/hcknPoXA3cVlUvJLkZ+CTweJJXAd+lEx5HcwfwmSS7gd3Azuk5E6k//jkKSZK3iSRJhoEkCcNAkoRhIEnCMJAkYRhIkjAMJEnA/wIYj1Pe/KwTjwAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "--------------------------------------------------------------------------------\n",
+      "AxesSubplot(0.125,0.125;0.775x0.755)\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "--------------------------------------------------------------------------------\n",
+      "AxesSubplot(0.125,0.125;0.775x0.755)\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "--------------------------------------------------------------------------------\n",
+      "AxesSubplot(0.125,0.125;0.775x0.755)\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "--------------------------------------------------------------------------------\n",
+      "AxesSubplot(0.125,0.125;0.775x0.755)\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "--------------------------------------------------------------------------------\n",
+      "AxesSubplot(0.125,0.125;0.775x0.755)\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "--------------------------------------------------------------------------------\n"
+     ]
+    }
+   ],
+   "source": [
+    "caja_de_bigotes = cleaned_data.copy()\n",
+    "\n",
+    "\n",
+    "for column in caja_de_bigotes:\n",
+    "    print(caja_de_bigotes[column].plot.box())\n",
+    "    plt.show()\n",
+    "    print('--------' * 10)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>count</th>\n",
+       "      <th>mean</th>\n",
+       "      <th>std</th>\n",
+       "      <th>min</th>\n",
+       "      <th>25%</th>\n",
+       "      <th>50%</th>\n",
+       "      <th>75%</th>\n",
+       "      <th>max</th>\n",
+       "      <th>IQR</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>postId</th>\n",
+       "      <td>90584.0</td>\n",
+       "      <td>56539.080522</td>\n",
+       "      <td>33840.307529</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>26051.75</td>\n",
+       "      <td>57225.5</td>\n",
+       "      <td>86145.25</td>\n",
+       "      <td>115378.0</td>\n",
+       "      <td>60093.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Score</th>\n",
+       "      <td>90584.0</td>\n",
+       "      <td>2.780767</td>\n",
+       "      <td>4.948922</td>\n",
+       "      <td>-19.0</td>\n",
+       "      <td>1.00</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>3.00</td>\n",
+       "      <td>192.0</td>\n",
+       "      <td>2.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>userId</th>\n",
+       "      <td>90584.0</td>\n",
+       "      <td>16546.764727</td>\n",
+       "      <td>15273.367108</td>\n",
+       "      <td>-1.0</td>\n",
+       "      <td>3437.00</td>\n",
+       "      <td>11032.0</td>\n",
+       "      <td>27700.00</td>\n",
+       "      <td>55746.0</td>\n",
+       "      <td>24263.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>CommentCount</th>\n",
+       "      <td>90584.0</td>\n",
+       "      <td>1.894650</td>\n",
+       "      <td>2.638704</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>3.00</td>\n",
+       "      <td>45.0</td>\n",
+       "      <td>3.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Reputation</th>\n",
+       "      <td>90584.0</td>\n",
+       "      <td>6282.395412</td>\n",
+       "      <td>15102.268670</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>60.00</td>\n",
+       "      <td>396.0</td>\n",
+       "      <td>4460.00</td>\n",
+       "      <td>87393.0</td>\n",
+       "      <td>4400.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                count          mean           std   min       25%      50%  \\\n",
+       "postId        90584.0  56539.080522  33840.307529   1.0  26051.75  57225.5   \n",
+       "Score         90584.0      2.780767      4.948922 -19.0      1.00      2.0   \n",
+       "userId        90584.0  16546.764727  15273.367108  -1.0   3437.00  11032.0   \n",
+       "CommentCount  90584.0      1.894650      2.638704   0.0      0.00      1.0   \n",
+       "Reputation    90584.0   6282.395412  15102.268670   1.0     60.00    396.0   \n",
+       "\n",
+       "                   75%       max      IQR  \n",
+       "postId        86145.25  115378.0  60093.5  \n",
+       "Score             3.00     192.0      2.0  \n",
+       "userId        27700.00   55746.0  24263.0  \n",
+       "CommentCount      3.00      45.0      3.0  \n",
+       "Reputation     4460.00   87393.0   4400.0  "
+      ]
+     },
+     "execution_count": 32,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "stats = caja_de_bigotes.describe().transpose()\n",
+    "stats['IQR'] = stats['75%'] - stats['25%']\n",
+    "stats.head(5)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -196,7 +1173,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.5"
+   "version": "3.8.9"
   }
  },
  "nbformat": 4,
diff --git a/your-code/weather.ipynb b/your-code/weather.ipynb
index 4fc40ab..d1bccf9 100644
--- a/your-code/weather.ipynb
+++ b/your-code/weather.ipynb
@@ -47,7 +47,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -61,7 +61,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.5"
+   "version": "3.8.9"
   }
  },
  "nbformat": 4,