diff --git a/data/.DS_Store b/data/.DS_Store
index b0becff..1896f1a 100644
Binary files a/data/.DS_Store and b/data/.DS_Store differ
diff --git a/notebooks/eda.ipynb b/notebooks/eda.ipynb
index 061eef1..e73c164 100644
--- a/notebooks/eda.ipynb
+++ b/notebooks/eda.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 481,
+   "execution_count": 807,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -11,12 +11,24 @@
     "import datetime\n",
     "import re\n",
     "from collections import Counter\n",
-    "import seaborn as sns"
+    "import seaborn as sns\n",
+    "import numeritos as nitos\n",
+    "import matplotlib.pyplot as plt\n",
+    "from nltk.corpus import stopwords"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 425,
+   "execution_count": 808,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "pd.set_option('max_colwidth', None)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 809,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -26,7 +38,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 426,
+   "execution_count": 810,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -36,7 +48,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 427,
+   "execution_count": 811,
    "metadata": {},
    "outputs": [
     {
@@ -74,7 +86,7 @@
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td>1578613094191796224</td>\n",
-       "      <td>Gente muy agradable en @TheBridge_Tech , te ri...</td>\n",
+       "      <td>Gente muy agradable en @TheBridge_Tech , te ries mucho en el dia a dia. El tema es que pasas tanto tiempo trabajando aqui, que te quita la libido y tu vida sexual se va a la mierda, jjj. Tengo ganas de terminar mi Bootcamp para poder hacer una buena sesión de Shibari</td>\n",
        "      <td>1578095844569514011</td>\n",
        "      <td>2022-10-08 05:07:45</td>\n",
        "      <td>0</td>\n",
@@ -85,7 +97,7 @@
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>1577334577701453827</td>\n",
-       "      <td>Recordaros que la semana que viene tenemos la ...</td>\n",
+       "      <td>Recordaros que la semana que viene tenemos la primera quedada #CPS en Madrid, en @TheBridge_Tech, en el que tendremos la gran suerte de contar con @Recuenco para que nos dé una charla. Las plazas se han agotado, pero os podéis apuntar al grupo para próximas quedadas 🚀</td>\n",
        "      <td>1003872445</td>\n",
        "      <td>2022-10-04 16:27:23</td>\n",
        "      <td>2</td>\n",
@@ -96,7 +108,7 @@
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>1576902991507922944</td>\n",
-       "      <td>El desarrollador web es uno de los perfiles má...</td>\n",
+       "      <td>El desarrollador web es uno de los perfiles más demandados en el mercado laboral 📈  Descubre nuestro #bootcamp Desarrollo Web Full Stack de la mano de @TheBridge_Tech 💻  Toda la información aquí! 👇 https://t.co/LOoTu97aQq https://t.co/xpaAzxXSDX</td>\n",
        "      <td>2529499620</td>\n",
        "      <td>2022-10-03 11:52:25</td>\n",
        "      <td>3</td>\n",
@@ -118,7 +130,7 @@
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td>1575217357105946624</td>\n",
-       "      <td>Hoy por fin ve la luz mi primer Case Study púb...</td>\n",
+       "      <td>Hoy por fin ve la luz mi primer Case Study público. Un trabajo intensivo de fin de bootcamp realizado con un cliente real @emancipaTIC  y dos semanas para que las 5 verticales en @TheBridge_Tech hiciésemos realidad un MVP. Os invito a verlo y dar feedback. https://t.co/rkCjxulYS9 https://t.co/PqM0dvxj3X</td>\n",
        "      <td>604485175</td>\n",
        "      <td>2022-09-28 20:14:18</td>\n",
        "      <td>3</td>\n",
@@ -131,12 +143,19 @@
        "</div>"
       ],
       "text/plain": [
-       "                    id                                               text  \\\n",
-       "0  1578613094191796224  Gente muy agradable en @TheBridge_Tech , te ri...   \n",
-       "1  1577334577701453827  Recordaros que la semana que viene tenemos la ...   \n",
-       "2  1576902991507922944  El desarrollador web es uno de los perfiles má...   \n",
-       "3  1576856703349374976      @jorgegrev @TheBridge_Tech Enhorabuena crack!   \n",
-       "4  1575217357105946624  Hoy por fin ve la luz mi primer Case Study púb...   \n",
+       "                    id  \\\n",
+       "0  1578613094191796224   \n",
+       "1  1577334577701453827   \n",
+       "2  1576902991507922944   \n",
+       "3  1576856703349374976   \n",
+       "4  1575217357105946624   \n",
+       "\n",
+       "                                                                                                                                                                                                                                                                                                               text  \\\n",
+       "0                                       Gente muy agradable en @TheBridge_Tech , te ries mucho en el dia a dia. El tema es que pasas tanto tiempo trabajando aqui, que te quita la libido y tu vida sexual se va a la mierda, jjj. Tengo ganas de terminar mi Bootcamp para poder hacer una buena sesión de Shibari   \n",
+       "1                                      Recordaros que la semana que viene tenemos la primera quedada #CPS en Madrid, en @TheBridge_Tech, en el que tendremos la gran suerte de contar con @Recuenco para que nos dé una charla. Las plazas se han agotado, pero os podéis apuntar al grupo para próximas quedadas 🚀   \n",
+       "2                                                             El desarrollador web es uno de los perfiles más demandados en el mercado laboral 📈  Descubre nuestro #bootcamp Desarrollo Web Full Stack de la mano de @TheBridge_Tech 💻  Toda la información aquí! 👇 https://t.co/LOoTu97aQq https://t.co/xpaAzxXSDX   \n",
+       "3                                                                                                                                                                                                                                                                     @jorgegrev @TheBridge_Tech Enhorabuena crack!   \n",
+       "4  Hoy por fin ve la luz mi primer Case Study público. Un trabajo intensivo de fin de bootcamp realizado con un cliente real @emancipaTIC  y dos semanas para que las 5 verticales en @TheBridge_Tech hiciésemos realidad un MVP. Os invito a verlo y dar feedback. https://t.co/rkCjxulYS9 https://t.co/PqM0dvxj3X   \n",
        "\n",
        "             author_id          created_at  retweet_count  reply_count  \\\n",
        "0  1578095844569514011 2022-10-08 05:07:45              0            0   \n",
@@ -153,7 +172,7 @@
        "4           4            0  "
       ]
      },
-     "execution_count": 427,
+     "execution_count": 811,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -164,7 +183,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 428,
+   "execution_count": 812,
    "metadata": {},
    "outputs": [
     {
@@ -195,7 +214,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 429,
+   "execution_count": 813,
    "metadata": {},
    "outputs": [
     {
@@ -275,7 +294,7 @@
        "4      bertinha84  "
       ]
      },
-     "execution_count": 429,
+     "execution_count": 813,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -286,7 +305,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 430,
+   "execution_count": 814,
    "metadata": {},
    "outputs": [
     {
@@ -312,36 +331,102 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 431,
+   "execution_count": 815,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "The Bridge school has been mentioned a total of 154 times since 13th of June.\n"
+     ]
+    }
+   ],
+   "source": [
+    "print('The Bridge school has been mentioned a total of ' + str(len(df_tweets)) + ' times since 13th of June.')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 816,
    "metadata": {},
    "outputs": [],
    "source": [
-    "df_tweets['year'] = df_tweets['created_at'].dt.year\n",
-    "df_tweets['month'] = df_tweets['created_at'].dt.month\n",
-    "df_tweets['day'] = df_tweets['created_at'].dt.day\n",
-    "df_tweets['time'] = df_tweets['created_at'].dt.time"
+    "# The column social_repercussion contains the sum of the 4 metrics columns\n",
+    "df_tweets['total_interactions'] = df_tweets['retweet_count'] + df_tweets['reply_count'] + df_tweets['like_count'] + df_tweets['quote_count']"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 432,
+   "execution_count": 817,
    "metadata": {},
    "outputs": [
     {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "The Bridge school has been mentioned a total of 154 times since 13th of June.\n"
-     ]
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 720x360 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
     }
    ],
    "source": [
-    "print('The Bridge school has been mentioned a total of ' + str(len(df_tweets)) + ' times since 13th of June.')"
+    "def scatterplot(x, y, df):\n",
+    "    plt.figure(figsize=(10,5))\n",
+    "    plot = sns.scatterplot(x=x,y=y,data=df);\n",
+    "    plot.set(xticklabels=[]) \n",
+    "    plt.show()\n",
+    "\n",
+    "scatterplot('id', 'total_interactions', df_tweets)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 818,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def get_values(df, feature):\n",
+    "    return df[feature].values\n",
+    "\n",
+    "def get_usernames(user_df, df):\n",
+    "    id = df['author_id'].values\n",
+    "    return [user_df[user_df['id'] == elem]['name'].values[0] for elem in id]\n",
+    "\n",
+    "def most_repeated_value(df, feature):\n",
+    "    return df[feature].value_counts().idxmax()\n",
+    "\n",
+    "def count_repetiton_times(df, feature):\n",
+    "    id = get_values(df, feature)\n",
+    "    return [df[feature].value_counts()[elem] for elem in id]\n",
+    "\n",
+    "def get_dates(df):\n",
+    "    dates = get_values(df, 'created_at')\n",
+    "    dates_mod = [pd.to_datetime(str(date)) for date in dates]\n",
+    "    return [ts.strftime('%Y.%m.%d') for ts in dates_mod]\n",
+    "\n",
+    "def get_dict(user_df, df):\n",
+    "    return {'Text': get_values(df, 'text'),\n",
+    "            'Author name': get_usernames(user_df, df),\n",
+    "            'Date': get_dates(df),\n",
+    "            'Total interactions' : get_values(df, 'total_interactions'),\n",
+    "            'Retweet count': get_values(df, 'retweet_count'),\n",
+    "            'Reply count': get_values(df, 'reply_count'),\n",
+    "            'Like count': get_values(df, 'like_count'),\n",
+    "            'Quote count': get_values(df, 'quote_count'),\n",
+    "            'Total posts': count_repetiton_times(df, 'author_id')}\n",
+    "\n",
+    "def get_df(user_df, df):    \n",
+    "    return pd.DataFrame.from_dict(get_dict(user_df, df))"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 433,
+   "execution_count": 819,
    "metadata": {},
    "outputs": [
     {
@@ -365,135 +450,229 @@
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
-       "      <th>id</th>\n",
-       "      <th>text</th>\n",
-       "      <th>author_id</th>\n",
-       "      <th>created_at</th>\n",
-       "      <th>retweet_count</th>\n",
-       "      <th>reply_count</th>\n",
-       "      <th>like_count</th>\n",
-       "      <th>quote_count</th>\n",
-       "      <th>year</th>\n",
-       "      <th>month</th>\n",
-       "      <th>day</th>\n",
-       "      <th>time</th>\n",
-       "      <th>total_interactions</th>\n",
+       "      <th>Text</th>\n",
+       "      <th>Author name</th>\n",
+       "      <th>Date</th>\n",
+       "      <th>Total interactions</th>\n",
+       "      <th>Retweet count</th>\n",
+       "      <th>Reply count</th>\n",
+       "      <th>Like count</th>\n",
+       "      <th>Quote count</th>\n",
+       "      <th>Total posts</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>6</th>\n",
-       "      <td>1573246948693651456</td>\n",
-       "      <td>Y seguimos con lo prometido:  Primera quedada ...</td>\n",
-       "      <td>1003872445</td>\n",
-       "      <td>2022-09-23 09:44:36</td>\n",
+       "      <th>0</th>\n",
+       "      <td>Y seguimos con lo prometido:  Primera quedada de la comunidad #CPS en Madrid 🚀: https://t.co/xnWjKu6fPi en un espacio cedido por @TheBridge_Tech.</td>\n",
+       "      <td>Pau Mugarra</td>\n",
+       "      <td>2022.09.23</td>\n",
+       "      <td>31</td>\n",
        "      <td>7</td>\n",
        "      <td>0</td>\n",
        "      <td>20</td>\n",
        "      <td>4</td>\n",
-       "      <td>2022</td>\n",
-       "      <td>9</td>\n",
-       "      <td>23</td>\n",
-       "      <td>09:44:36</td>\n",
-       "      <td>31</td>\n",
+       "      <td>1</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "text/plain": [
-       "                    id                                               text  \\\n",
-       "6  1573246948693651456  Y seguimos con lo prometido:  Primera quedada ...   \n",
+       "                                                                                                                                                Text  \\\n",
+       "0  Y seguimos con lo prometido:  Primera quedada de la comunidad #CPS en Madrid 🚀: https://t.co/xnWjKu6fPi en un espacio cedido por @TheBridge_Tech.   \n",
        "\n",
-       "    author_id          created_at  retweet_count  reply_count  like_count  \\\n",
-       "6  1003872445 2022-09-23 09:44:36              7            0          20   \n",
+       "   Author name        Date  Total interactions  Retweet count  Reply count  \\\n",
+       "0  Pau Mugarra  2022.09.23                  31              7            0   \n",
        "\n",
-       "   quote_count  year  month  day      time  total_interactions  \n",
-       "6            4  2022      9   23  09:44:36                  31  "
+       "   Like count  Quote count  Total posts  \n",
+       "0          20            4            1  "
       ]
      },
-     "execution_count": 433,
+     "execution_count": 819,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "# The column social_repercussion contains the sum of the 4 metrics columns\n",
-    "df_tweets['total_interactions'] = df_tweets['retweet_count'] + df_tweets['reply_count'] + df_tweets['like_count'] + df_tweets['quote_count']\n",
+    "df_max_interaction = df_tweets[df_tweets['total_interactions']==df_tweets['total_interactions'].max()]\n",
     "\n",
-    "# Row which contains tweet with most repercussion information\n",
-    "tweet_most_repercussion = df_tweets[df_tweets['total_interactions']==df_tweets['total_interactions'].max()]\n",
-    "tweet_most_repercussion"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 434,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "def printed_text(feature):\n",
-    "    return tweet_most_repercussion[feature].values[0]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 435,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "def get_user_name(id):\n",
-    "    return df_users[df_users['id'] == id]['name'].values[0]"
+    "max_interactions_tweet = get_df(df_users, df_max_interaction)\n",
+    "\n",
+    "max_interactions_tweet"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 436,
+   "execution_count": 820,
    "metadata": {},
    "outputs": [
     {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "The tweet with most social repercussion was:\n",
-      "Text:  Y seguimos con lo prometido:  Primera quedada de la comunidad #CPS en Madrid 🚀: https://t.co/xnWjKu6fPi en un espacio cedido por @TheBridge_Tech. \n",
-      "Author name:  Pau Mugarra \n",
-      "Date:  23 / 9 / 2022 \n",
-      "Total interactions:  31 \n",
-      "Retweet count:  7 \n",
-      "Reply count:  0 \n",
-      "Like count:  20 \n",
-      "Quote count:  4\n"
-     ]
+     "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>Text</th>\n",
+       "      <th>Author name</th>\n",
+       "      <th>Date</th>\n",
+       "      <th>Total interactions</th>\n",
+       "      <th>Retweet count</th>\n",
+       "      <th>Reply count</th>\n",
+       "      <th>Like count</th>\n",
+       "      <th>Quote count</th>\n",
+       "      <th>Total posts</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Y seguimos con lo prometido:  Primera quedada de la comunidad #CPS en Madrid 🚀: https://t.co/xnWjKu6fPi en un espacio cedido por @TheBridge_Tech.</td>\n",
+       "      <td>Pau Mugarra</td>\n",
+       "      <td>2022.09.23</td>\n",
+       "      <td>31</td>\n",
+       "      <td>7</td>\n",
+       "      <td>0</td>\n",
+       "      <td>20</td>\n",
+       "      <td>4</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>¿Quieres impulsar tu perfil profesional en el ámbito digital?  🔥¡Descubre los #bootcamps de @ENCamaraSevilla y @TheBridge_Tech y despega en el sector tecnológico!  🚀La formación más innovadora en #DesarrolloWeb #FullStack, #DataScience y #Ciberseguridad: https://t.co/dI7Go0yJsW https://t.co/598NsYg0Ud</td>\n",
+       "      <td>Cámara de Comercio de Sevilla</td>\n",
+       "      <td>2022.08.31</td>\n",
+       "      <td>24</td>\n",
+       "      <td>11</td>\n",
+       "      <td>0</td>\n",
+       "      <td>13</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Comienza la masterclass en @TheBridge_Tech de @uriondo hablando de cómo evitar ser #Periodista?!?! En serio?!?! jajaja con lo que mola el curso de @JotDownSpain,  verdad @imparsifal? https://t.co/EFVSpRN56s</td>\n",
+       "      <td>Loretogf</td>\n",
+       "      <td>2022.07.28</td>\n",
+       "      <td>25</td>\n",
+       "      <td>6</td>\n",
+       "      <td>2</td>\n",
+       "      <td>16</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>El próximo jueves 28 estaremos em @TheBridge_Tech con @uriondo que impartirá la masterclass «Evita el periodismo: una oda a la profesión». La asistencia es gratuita hasta completar aforo. Os esperamos. https://t.co/mHGMocUoP2</td>\n",
+       "      <td>Jot Down Magazine</td>\n",
+       "      <td>2022.07.24</td>\n",
+       "      <td>28</td>\n",
+       "      <td>10</td>\n",
+       "      <td>0</td>\n",
+       "      <td>15</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Esto me hace ilusión. El jueves a las 19 en @TheBridge_Tech hablaré de la profesión que amo y que ejercí locamente durante 20 años para el Programa superior de emprendimiento en periodismo de @JotDownSpain. Elige ¿streaming o aire acondicionado? https://t.co/yCk9MxVa0I</td>\n",
+       "      <td>Miguel Ángel Uriondo</td>\n",
+       "      <td>2022.07.19</td>\n",
+       "      <td>28</td>\n",
+       "      <td>7</td>\n",
+       "      <td>1</td>\n",
+       "      <td>17</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>El sentido de la vida ya no es 42 -- Light Mental edición especial @TheBridge_Tech https://t.co/z7hOVln8Bp</td>\n",
+       "      <td>Heavy Mental</td>\n",
+       "      <td>2022.06.29</td>\n",
+       "      <td>30</td>\n",
+       "      <td>3</td>\n",
+       "      <td>2</td>\n",
+       "      <td>22</td>\n",
+       "      <td>3</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>🕣 TIC, TAC: MAÑANA os vemos a todos a las 7.30pm en nuestro evento en directo en MADRID en @TheBridge_Tech   🚨Para los que no vayáis, TRANQUILOS, seguramente el martes lo emitamos para todos vosotros :D https://t.co/fqaYsbyxl7</td>\n",
+       "      <td>Heavy Mental</td>\n",
+       "      <td>2022.06.26</td>\n",
+       "      <td>30</td>\n",
+       "      <td>6</td>\n",
+       "      <td>6</td>\n",
+       "      <td>17</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                                                                                                                                                                                                                                                                                             Text  \\\n",
+       "0                                                                                                                                                               Y seguimos con lo prometido:  Primera quedada de la comunidad #CPS en Madrid 🚀: https://t.co/xnWjKu6fPi en un espacio cedido por @TheBridge_Tech.   \n",
+       "1  ¿Quieres impulsar tu perfil profesional en el ámbito digital?  🔥¡Descubre los #bootcamps de @ENCamaraSevilla y @TheBridge_Tech y despega en el sector tecnológico!  🚀La formación más innovadora en #DesarrolloWeb #FullStack, #DataScience y #Ciberseguridad: https://t.co/dI7Go0yJsW https://t.co/598NsYg0Ud   \n",
+       "2                                                                                                  Comienza la masterclass en @TheBridge_Tech de @uriondo hablando de cómo evitar ser #Periodista?!?! En serio?!?! jajaja con lo que mola el curso de @JotDownSpain,  verdad @imparsifal? https://t.co/EFVSpRN56s   \n",
+       "3                                                                               El próximo jueves 28 estaremos em @TheBridge_Tech con @uriondo que impartirá la masterclass «Evita el periodismo: una oda a la profesión». La asistencia es gratuita hasta completar aforo. Os esperamos. https://t.co/mHGMocUoP2   \n",
+       "4                                   Esto me hace ilusión. El jueves a las 19 en @TheBridge_Tech hablaré de la profesión que amo y que ejercí locamente durante 20 años para el Programa superior de emprendimiento en periodismo de @JotDownSpain. Elige ¿streaming o aire acondicionado? https://t.co/yCk9MxVa0I   \n",
+       "5                                                                                                                                                                                                      El sentido de la vida ya no es 42 -- Light Mental edición especial @TheBridge_Tech https://t.co/z7hOVln8Bp   \n",
+       "6                                                                              🕣 TIC, TAC: MAÑANA os vemos a todos a las 7.30pm en nuestro evento en directo en MADRID en @TheBridge_Tech   🚨Para los que no vayáis, TRANQUILOS, seguramente el martes lo emitamos para todos vosotros :D https://t.co/fqaYsbyxl7   \n",
+       "\n",
+       "                     Author name        Date  Total interactions  \\\n",
+       "0                    Pau Mugarra  2022.09.23                  31   \n",
+       "1  Cámara de Comercio de Sevilla  2022.08.31                  24   \n",
+       "2                       Loretogf  2022.07.28                  25   \n",
+       "3              Jot Down Magazine  2022.07.24                  28   \n",
+       "4           Miguel Ángel Uriondo  2022.07.19                  28   \n",
+       "5                   Heavy Mental  2022.06.29                  30   \n",
+       "6                   Heavy Mental  2022.06.26                  30   \n",
+       "\n",
+       "   Retweet count  Reply count  Like count  Quote count  Total posts  \n",
+       "0              7            0          20            4            1  \n",
+       "1             11            0          13            0            1  \n",
+       "2              6            2          16            1            1  \n",
+       "3             10            0          15            3            1  \n",
+       "4              7            1          17            3            1  \n",
+       "5              3            2          22            3            2  \n",
+       "6              6            6          17            1            2  "
+      ]
+     },
+     "execution_count": 820,
+     "metadata": {},
+     "output_type": "execute_result"
     }
    ],
    "source": [
-    "print('The tweet with most social repercussion was:\\nText: ', printed_text('text'),\n",
-    "      '\\nAuthor name: ', get_user_name(printed_text('author_id')),\n",
-    "      '\\nDate: ', printed_text('day'), '/', printed_text('month'), '/', printed_text('year'),\n",
-    "      '\\nTotal interactions: ', printed_text('total_interactions'),\n",
-    "      '\\nRetweet count: ', printed_text('retweet_count'),\n",
-    "      '\\nReply count: ', printed_text('reply_count'),\n",
-    "      '\\nLike count: ', printed_text('like_count'),\n",
-    "      '\\nQuote count: ', printed_text('quote_count'),)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 437,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# User with most tweets\n",
-    "most_repeated_user = df_tweets['author_id'].value_counts().idxmax()\n",
+    "df_max_interaction_mult = df_tweets.loc[df_tweets['total_interactions'] >= 20]\n",
     "\n",
-    "# Times this user posted\n",
-    "times_user_repeated = df_tweets['author_id'].value_counts()[most_repeated_user]"
+    "max_interactions_tweets = get_df(df_users, df_max_interaction_mult)\n",
+    "\n",
+    "max_interactions_tweets"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 438,
+   "execution_count": 821,
    "metadata": {},
    "outputs": [
     {
@@ -538,212 +717,557 @@
        "48  1255794072280842240  Heavy Mental  HeavyMental_es"
       ]
      },
-     "execution_count": 438,
+     "execution_count": 821,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "# Row which contains author information\n",
-    "df_users[df_users['id'] == most_repeated_user]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 439,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "The user with most tweets was:\n",
-      "Name:  Heavy Mental \n",
-      "Number of tweets:  12\n"
-     ]
-    }
-   ],
-   "source": [
-    "print('The user with most tweets was:\\nName: ', get_user_name(most_repeated_user),\n",
-    "      '\\nNumber of tweets: ', times_user_repeated)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 440,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "month_with_most_tweets = df_tweets['month'].value_counts().idxmax()\n",
+    "# User with most tweets\n",
+    "most_active_user_df = df_users[df_users['id'] == most_repeated_value(df_tweets, 'author_id')]\n",
     "\n",
-    "datetime_object = datetime.datetime.strptime(str(month_with_most_tweets), \"%m\")\n",
-    "month_name = datetime_object.strftime(\"%B\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 441,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Most of the tweets were done in June\n"
-     ]
-    }
-   ],
-   "source": [
-    "print('Most of the tweets were done in', month_name)"
+    "most_active_user_df"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 442,
+   "execution_count": 822,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "text/plain": [
-       "[('de', 172),\n",
-       " ('@TheBridge_Tech', 135),\n",
-       " ('en', 92),\n",
-       " ('la', 85),\n",
-       " ('y', 66),\n",
-       " ('@HeavyMental_es', 65),\n",
-       " ('el', 63),\n",
-       " ('a', 62),\n",
-       " ('que', 53),\n",
-       " ('@GuillermoDeHaro', 51),\n",
-       " ('@Recuenco', 50),\n",
-       " ('para', 39),\n",
-       " ('@_miki', 32),\n",
-       " ('@DavidAlayon', 30),\n",
-       " ('por', 28),\n",
-       " ('un', 26),\n",
-       " ('con', 25),\n",
-       " ('las', 22),\n",
-       " ('del', 21),\n",
-       " ('se', 19),\n",
-       " ('una', 18),\n",
-       " ('no', 18),\n",
-       " ('los', 17),\n",
-       " ('es', 15),\n",
-       " ('lo', 13),\n",
-       " ('nos', 12),\n",
-       " ('@Mulder01198676', 12),\n",
-       " ('más', 11),\n",
-       " ('pero', 10),\n",
-       " ('@Alienta', 10),\n",
-       " ('te', 9),\n",
-       " ('El', 9),\n",
-       " ('al', 9),\n",
-       " ('talento', 9),\n",
-       " ('convenio', 9),\n",
-       " ('formación', 9),\n",
-       " ('@uriondo', 9),\n",
-       " ('primera', 8),\n",
-       " ('@TheBridge_Tech,', 8),\n",
-       " ('si', 8),\n",
-       " ('La', 8),\n",
-       " ('ya', 8),\n",
-       " ('@JotDownSpain', 8),\n",
-       " ('vida', 7),\n",
-       " ('Si', 7),\n",
-       " ('gracias', 7),\n",
-       " ('ha', 7),\n",
-       " ('sobre', 7),\n",
-       " ('sus', 7),\n",
-       " ('the', 7),\n",
-       " ('Gracias', 7),\n",
-       " ('@moquintana', 7),\n",
-       " ('Hoy', 6),\n",
-       " ('o', 6),\n",
-       " ('Y', 6),\n",
-       " ('entre', 6),\n",
-       " ('and', 6),\n",
-       " ('profesionales', 6),\n",
-       " ('#ciberseguridad', 6),\n",
-       " ('No', 6),\n",
-       " ('@PauMugarra', 6),\n",
-       " ('va', 5),\n",
-       " ('hacer', 5),\n",
-       " ('tenemos', 5),\n",
-       " ('han', 5),\n",
-       " ('ser', 5),\n",
-       " ('nuestros', 5),\n",
-       " ('@TheBridge_Tech.', 5),\n",
-       " ('desde', 5),\n",
-       " ('todos', 5),\n",
-       " ('Data', 5),\n",
-       " ('demanda', 5),\n",
-       " ('unen', 5),\n",
-       " ('nuevo', 5),\n",
-       " ('firman', 5),\n",
-       " ('aceleradora', 5),\n",
-       " ('millones', 5),\n",
-       " ('euros', 5),\n",
-       " ('me', 5),\n",
-       " ('ronda', 5),\n",
-       " ('directo', 5),\n",
-       " ('Que', 5),\n",
-       " ('@joobid', 5),\n",
-       " ('@Atorrerus', 5),\n",
-       " ('@joansabater', 5),\n",
-       " ('@PesetJairo', 5),\n",
-       " ('@adriskou', 5),\n",
-       " ('@estodopornada', 5),\n",
-       " ('Bootcamp', 4),\n",
-       " ('buena', 4),\n",
-       " ('os', 4),\n",
-       " ('#bootcamp', 4),\n",
-       " ('Un', 4),\n",
-       " ('5', 4),\n",
-       " ('Os', 4),\n",
-       " ('nuestras', 4),\n",
-       " ('esta', 4),\n",
-       " ('colaboración', 4),\n",
-       " ('hemos', 4),\n",
-       " ('@IronhackMAD', 4)]"
+      "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>Text</th>\n",
+       "      <th>Author name</th>\n",
+       "      <th>Date</th>\n",
+       "      <th>Total interactions</th>\n",
+       "      <th>Retweet count</th>\n",
+       "      <th>Reply count</th>\n",
+       "      <th>Like count</th>\n",
+       "      <th>Quote count</th>\n",
+       "      <th>Total posts</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>@carlosmdh @UbaldoHervas @DavidAlayon @Recuenco @_miki @GuillermoDeHaro @TheBridge_Tech Yes!! ;) ;)</td>\n",
+       "      <td>Heavy Mental</td>\n",
+       "      <td>2022.06.29</td>\n",
+       "      <td>4</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0</td>\n",
+       "      <td>12</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>El sentido de la vida ya no es 42 -- Light Mental edición especial @TheBridge_Tech https://t.co/z7hOVln8Bp</td>\n",
+       "      <td>Heavy Mental</td>\n",
+       "      <td>2022.06.29</td>\n",
+       "      <td>30</td>\n",
+       "      <td>3</td>\n",
+       "      <td>2</td>\n",
+       "      <td>22</td>\n",
+       "      <td>3</td>\n",
+       "      <td>12</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>@Mulder01198676 @PauMugarra @DavidAlayon @Recuenco @_miki @GuillermoDeHaro @TheBridge_Tech Sí a todo</td>\n",
+       "      <td>Heavy Mental</td>\n",
+       "      <td>2022.06.28</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>12</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>@Bombabarros @Mulder01198676 @_miki @Recuenco @DavidAlayon @GuillermoDeHaro @moquintana @TheBridge_Tech Gracias por venir y buen viaje de vuelta… eres top!!</td>\n",
+       "      <td>Heavy Mental</td>\n",
+       "      <td>2022.06.27</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0</td>\n",
+       "      <td>12</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>@vmcasamayor @TheBridge_Tech @Recuenco @Alienta 🙄 @TheBridge_Tech</td>\n",
+       "      <td>Heavy Mental</td>\n",
+       "      <td>2022.06.27</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>12</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>@joobid @TheBridge_Tech @Recuenco @GuillermoDeHaro Si claro, Miki no tiene otra cosa que hacer</td>\n",
+       "      <td>Heavy Mental</td>\n",
+       "      <td>2022.06.27</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>12</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>@jatorrero @TheBridge_Tech Juan Antonio, te mandamos dm para que te vengas que hay hueco!</td>\n",
+       "      <td>Heavy Mental</td>\n",
+       "      <td>2022.06.27</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "      <td>12</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>@navarro_batista @TheBridge_Tech En orbyt ya si eso.</td>\n",
+       "      <td>Heavy Mental</td>\n",
+       "      <td>2022.06.27</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>12</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>@CarlosLGonzalez @TheBridge_Tech Yes, seguramente martes a la misma hora en todos lados :)</td>\n",
+       "      <td>Heavy Mental</td>\n",
+       "      <td>2022.06.26</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "      <td>12</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>@CarlosLGonzalez @TheBridge_Tech Sí, vida real se llama.</td>\n",
+       "      <td>Heavy Mental</td>\n",
+       "      <td>2022.06.26</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>12</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>🕣 TIC, TAC: MAÑANA os vemos a todos a las 7.30pm en nuestro evento en directo en MADRID en @TheBridge_Tech   🚨Para los que no vayáis, TRANQUILOS, seguramente el martes lo emitamos para todos vosotros :D https://t.co/fqaYsbyxl7</td>\n",
+       "      <td>Heavy Mental</td>\n",
+       "      <td>2022.06.26</td>\n",
+       "      <td>30</td>\n",
+       "      <td>6</td>\n",
+       "      <td>6</td>\n",
+       "      <td>17</td>\n",
+       "      <td>1</td>\n",
+       "      <td>12</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>Lo prometimos y han llegado gracias a @TheBridge_Tech ... últimas entradas para el podcast 27 en directo :D  cc @Atorrerus @Mulder01198676 @joansabater @PesetJairo @pelayoarbues @adriskou @estodopornada https://t.co/Aygpl489sQ</td>\n",
+       "      <td>Heavy Mental</td>\n",
+       "      <td>2022.06.13</td>\n",
+       "      <td>12</td>\n",
+       "      <td>2</td>\n",
+       "      <td>4</td>\n",
+       "      <td>6</td>\n",
+       "      <td>0</td>\n",
+       "      <td>12</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                                                                                                                                                                                                                  Text  \\\n",
+       "0                                                                                                                                  @carlosmdh @UbaldoHervas @DavidAlayon @Recuenco @_miki @GuillermoDeHaro @TheBridge_Tech Yes!! ;) ;)   \n",
+       "1                                                                                                                           El sentido de la vida ya no es 42 -- Light Mental edición especial @TheBridge_Tech https://t.co/z7hOVln8Bp   \n",
+       "2                                                                                                                                 @Mulder01198676 @PauMugarra @DavidAlayon @Recuenco @_miki @GuillermoDeHaro @TheBridge_Tech Sí a todo   \n",
+       "3                                                                         @Bombabarros @Mulder01198676 @_miki @Recuenco @DavidAlayon @GuillermoDeHaro @moquintana @TheBridge_Tech Gracias por venir y buen viaje de vuelta… eres top!!   \n",
+       "4                                                                                                                                                                    @vmcasamayor @TheBridge_Tech @Recuenco @Alienta 🙄 @TheBridge_Tech   \n",
+       "5                                                                                                                                       @joobid @TheBridge_Tech @Recuenco @GuillermoDeHaro Si claro, Miki no tiene otra cosa que hacer   \n",
+       "6                                                                                                                                            @jatorrero @TheBridge_Tech Juan Antonio, te mandamos dm para que te vengas que hay hueco!   \n",
+       "7                                                                                                                                                                                 @navarro_batista @TheBridge_Tech En orbyt ya si eso.   \n",
+       "8                                                                                                                                           @CarlosLGonzalez @TheBridge_Tech Yes, seguramente martes a la misma hora en todos lados :)   \n",
+       "9                                                                                                                                                                             @CarlosLGonzalez @TheBridge_Tech Sí, vida real se llama.   \n",
+       "10  🕣 TIC, TAC: MAÑANA os vemos a todos a las 7.30pm en nuestro evento en directo en MADRID en @TheBridge_Tech   🚨Para los que no vayáis, TRANQUILOS, seguramente el martes lo emitamos para todos vosotros :D https://t.co/fqaYsbyxl7   \n",
+       "11  Lo prometimos y han llegado gracias a @TheBridge_Tech ... últimas entradas para el podcast 27 en directo :D  cc @Atorrerus @Mulder01198676 @joansabater @PesetJairo @pelayoarbues @adriskou @estodopornada https://t.co/Aygpl489sQ   \n",
+       "\n",
+       "     Author name        Date  Total interactions  Retweet count  Reply count  \\\n",
+       "0   Heavy Mental  2022.06.29                   4              0            1   \n",
+       "1   Heavy Mental  2022.06.29                  30              3            2   \n",
+       "2   Heavy Mental  2022.06.28                   2              0            1   \n",
+       "3   Heavy Mental  2022.06.27                   3              0            0   \n",
+       "4   Heavy Mental  2022.06.27                   1              0            0   \n",
+       "5   Heavy Mental  2022.06.27                   2              0            1   \n",
+       "6   Heavy Mental  2022.06.27                   3              0            1   \n",
+       "7   Heavy Mental  2022.06.27                   2              0            1   \n",
+       "8   Heavy Mental  2022.06.26                   2              0            0   \n",
+       "9   Heavy Mental  2022.06.26                   2              0            1   \n",
+       "10  Heavy Mental  2022.06.26                  30              6            6   \n",
+       "11  Heavy Mental  2022.06.13                  12              2            4   \n",
+       "\n",
+       "    Like count  Quote count  Total posts  \n",
+       "0            3            0           12  \n",
+       "1           22            3           12  \n",
+       "2            1            0           12  \n",
+       "3            3            0           12  \n",
+       "4            1            0           12  \n",
+       "5            1            0           12  \n",
+       "6            2            0           12  \n",
+       "7            1            0           12  \n",
+       "8            2            0           12  \n",
+       "9            1            0           12  \n",
+       "10          17            1           12  \n",
+       "11           6            0           12  "
       ]
      },
-     "execution_count": 442,
+     "execution_count": 822,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "Counter(\" \".join(df_tweets[\"text\"]).split()).most_common(100)"
+    "tweets_by_most_active_user = df_tweets[df_tweets['author_id'] == most_repeated_value(df_tweets, 'author_id')]\n",
+    "\n",
+    "tweets_by_most_active_user = get_df(df_users, tweets_by_most_active_user)\n",
+    "\n",
+    "tweets_by_most_active_user"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 823,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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nBEVHZgVKI+Op014fqKlygqQ6belq0IqmuunnK5pq1RLyk6oDABeRzgNK4IcvDOrezz932g18/TVVWtFYqxXNdXrV8obpAKnLWbaGCZIAYCkjnQeUwGeeeElt4YDuf+2G6UCpNRxQFTfwBYCyRToPKDJrrZ56cUjvvnGN3nD5crerAwBYJNz2BSiynJWslUJ+/mcBAC/hti9AkU1NaMvwJgDwFgaWA4sskc5qV99JbTs0qu2HR7X90KgkKegryf8sAIASYWA5sAhSmZz++pH9evrFYe05FlUml/9fYXVrSDevb9eVKxsZDwUAHsMgDWARPH88qn/84UvavLxB9920Rld2N+mK7ka1hJn0EgC8inQeMI9EOquxibRGxlManXAe4ymNOtvGJlIamUhrbCKl/mhCkvTh123UdWtaXK45AKAUSOeh4hwentCOvjEnIDoVGJ0KlPLrE6nsvOeIBGrUGPKpuc6vpjq/1raF1dkQ1OVdjaVrCADAVaTz4HnZnNV/HR7V958f0KPP9+vAQPy0/Q21PjXV+dQU8qs9EtT6jvrp5011/tPXQz411vrlr2GQOABUOtJ58LRP/uCA/umpVzQynlJNldHVq5r1lqu79DMXt6o9ElBDrU811QREAIDzRzoPnmWt1T8+8ZJWtYT0kZ+/VK9Z16aGWp/b1QIAeAQ9UfCc/mhCD+0+ru/uPqFYIqM3XbVCP7/lIrerBQDwGHqi4AknTib00E+P67u7j6v30KisldZ3RPSh29fpniuZnwkAsPgYWI6ydfzkpB7afWI6cJKkDcvygdNdmzt1cXvY5RoCALzMTN3Xq1R6enpsb29vSctEebHWKjqZ0WA8oYFoUoPx5PRyMJbUQCyh/mhSB51v2W1YFtHrNnfqrss6tbaNwAkAsHiMMdustT1z7SOdh5I7NjapvceiM4KjM4OlVCZ3xnH+miq1RwJqjwS0ti2kN15+ke7a3Kk1BE4AABcwsBwlMRBL6Lu7jutbu45rm5N6m9JU51N7JKi2SEDXrg6pLRKYfkxtb4sEVB+skTHGpRYAAHA6eqJQVE8eGNKnHjuop18elrX51Nvv/tx63bC2RR31QbWGA0xcCQAoSwwsR1GcOJnQn35nr76z67iWN9bqN2+9RK+/rFOXdETcrhoAAIuCdB4W3TMvDevez/cqmc3pQ7ev03tes0ZBX7Xb1QIAYFGRzsOievLAkO79wnNa3lirz77zaq1qDbldJQAAioJ0HhbVXz28Xx31QX31PderJRxwuzoAABQN6TwUJJ3N6fhYQn2jE+obm1Tf6KT6Rif0Qn9Mt2/sIIACAHge6TzMayie1L7jMfWNTujojEDp6OikTkQTys0Ih42RltUHtamzXm+8gvvUAQC8j54onCGbs/rsky/prx9+QUln0ssqI3U21Gp5U62uW9uiFY21WtFUpxVN+eWyhiBTFQAAKgo9UTjNQCyhd39hm3YeGdPtGzv0669epS4nSPJVEyQBADCFgeU4zRd+fEi7+8b0t790uX5+y0XMEA4AwDxK0rVgrd1qre2x1va0tbWVokgUYDKV1bd2HdPVq5r1hsuXE0ABAHAWJQmijDH3GWN6jTG9g4ODpSgS5ymRzup3v7ZTh0cm9N9vudjt6gAAsOSRzqtwx8Ym9cVnDulLzx7RyHhK99+5QTeto7cQAIBz4dt5Fex/fm2nvr79qKy1um1jh371hlW6YW2L29UCAKAs8O28CjWezOirvX26Y1OH/vC/bVJXc53bVQIAoKwwsLxCnYgmJEk/u6mDAAoAgAIwsLxCbT80KknavKLB5ZoAAFCemD2xQh0ciMtfU6V17RG3qwIAQFkinVeBMtlcPoiqrlJVFXNBAQBQCNJ5FWYgltBbH3hGj+4b0K9cv9Lt6gAAULaYJ6rC/PlD+7XzyJj+5i1bdPcVK9yuDgAAZYt0XoU5NDyuK7obCaAAALhApPMqTDyZUX3Q53Y1AAAoe/REVRhrJe4rDADAhaMnqsJYWRkRRQEAcKGYJ6rC0BMFAMDiIJ1XYawIogAAWAyk8yrMycm0wgFmtgAA4ELRE1VBsjmroXhSy+qDblcFAICyd9YuCWPMPWfbb619cCGFGGPuk3SfJHV3dy+4clhc6WxO1kpBf7XbVQEAoOydK6/zemfZLukGST9wnt8i6ceSFhREYWnYffSkJKmzgZ4oAAAu1FmDKGvtr0mSMeZhSZustced552SPrfQQqy1WyVtlaSenh5baGVxYb7y3BFFAjX6uUuXuV0VAADK3kLHRHVNBVCOfkkLzssxsNx91lo9+/KIfubiVtX5GVgOAMCFWuhf00eNMd+T9CXn+Vskfb84VcJistbqB/sG9IlHXtDhkQnde+Nqt6sEAIAnGGsXll1zBpnf6Dx9wlr774UU2NPTY3t7ews5FOcpkc7qVz77jJ57ZVTdzXX6wG2X6O4rlqu6iomiAABYCGPMNmttz1z7FpzXcb6JV9BAcr6d545dfSf13Cuj+tDt6/T+W9bKV80E9QAALJaz/lU1xjzpLGPGmOiMR8wYE11oIcwT5Y6R8ZQk6fZN7QRQAAAssnN9O+/VzjJyIYXQE+WO0Yl8ENUc8rtcEwAAvIfuCQ+b6olqqiOIAgBgsXHbFw8bHU+pzl+toI8ZygEAWGzcgNjDRiZS9EIBAFAkpPM8bDCWVEuYIAoAgGIgnedhh4Yn1N1c53Y1AADwJNJ5HpXK5NQ3OqE1rSG3qwIAgCfRE+VRfaMTyllpZQtBFAAAxUBPlEeNTqQliTFRAAAUCQPLPWoylZUk1TK9AQAARUE6z6Nyzo2ludkwAADFQTrPo6yzNIYgCgCAYqAnyqOmeqLoiAIAoDjoifIo6wRR9EQBAFAcDCz3KCeGoicKAIAiIZ3nUTkniDIiigIAoBhI53lUbjqd53JFAADwKNJ5HnUqnUcUBQBAMZDO8yhLTxQAAEVFOs+jYsmMJCnkr3G5JgAAeBM9UR41GEtKktrrAy7XBAAAb6InyqMmUhlVVxkFuXceAABFwcByj0qmcwrU8OMFAKBYSOd5VDJDEAUAQDGRzvOoZCarQA2pPAAAioWuCo9KZnIK+PjxAgBQLKTzPIoxUQAAFBfpPI86Mjqh9kjQ7WoAAOBZ9ER50GQqq+ePR3Vld6PbVQEAwLPoifKgoXhSOSt1Nde5XRUAADyLQTMeNDKekiQ1h/wu1wQAAO8inedBIxP5IKqxjiAKAIBiIZ3nQZOprCQpFGCeKAAAioWeKA/K5KwkqabKuFwTAAC8i54oD8o5QVR1FUPeAAAoFv7KetBUT1S1oScKAIBiIZ3nQdlcTpJUXU0QBQBAsZDO86BsPoZiTBQAAEVEOs9jsjmr7+05IV+1UShQ43Z1AADwLNJ5HvP3PzigH74wqD96/aUKE0QBAFA0pPM85qmDQ7qyu1Fvv26l21UBAMDT6InymFTWKhz0uV0NAAA8j54oj8lkc/IxoBwAgKJjYLmHWGs1FE+qvpaeKAAAio10noccHZtUfzSpy7sa3a4KAACeRzrPQ7YdGpUkXbWyyeWaAADgfaTzPGTv8aj81VXasCzidlUAAPA80nkeksrkFPBVqaaa2BgAgGIjnechuZxVFTcdBgCgJOiJ8pCstapmegMAAEqCnigPyeZETxQAACXC4BkPyeZyqqEnCgCAkiCd5yGT6Zxq/dVuVwMAgIpAOs9DJlNZBX0EUQAAlAI9UR6SSGdVR08UAAAlQU+Uh0yms6qlJwoAgJJgYLmHkM4DAKB0SOd5yEQqw8ByAABKhHSeR2SyOR0bS+iihqDbVQEAoCKQzvOIgVhSqWxOK1tCblcFAICKQDrPIzJZK0ny1xAXAwBQCqTzPCJn80EUE5YDAFAa9ER5RNYJorgBMQAApUFPlEdYJ4gy3IAYAICSYACNR/SNTkqSGmt9LtcEAIDKQDrPIx7bN6BaX7WuWd3sdlUAAKgIpPM8Ymg8pYsag8xYDgBAiZDOAwAAKADpPK+wblcAAIDKQjrPQ/hmHgAApUNPlEdMpDJMtAkAQAnRE+UBQ/Gknjo4rBvWtrpdFQAAKgYDyz3gqYNDSmVz+oUrV7hdFQAAKgbpPA8YiCYlSd0tdS7XBACAykE6zwP2Ho+qLRJQfbDG7aoAAFAx6InygF19Y7qiq5Fv5wEAUEL0RHlAPJlRc8jvdjUAAKgoDCz3gEQ6p0ANP0oAAEqJdF6Zs9ZqMp3lnnkAAJQY6bwyd2RkUqlMTitbQm5XBQCAikIOqMy9OBiXJK1fFna5JgAAVBbSeWXu5GRakuSvJp0HAEApkc4rY72vjOh/f+OnWt5Yq9VtpPMAACgleqLK1Oh4Sr/6z8+pNRzQV997vcIBJtoEAKCU6IkqU//y9CHFkxl9+u1XaXljrdvVAQCg4jCwvEz96OCQLu9q1PplEberAgBARSKdV6ZSmZzqa31uVwMAgIpFOq9MpbM5+au5Vx4AAG4hnVem0tmcfNX8+AAAcAvpvDKVyhBEAQDgJtJ5ZSqdtQRRAAC4iJ6oMpXK5uSvYUwUAABuKckMjcaY+yTdJ0nd3d2lKNJTrLUaT2U1FEtqKJ5/jCcz9EQBAOAiprl20Xgyo6F4UoNOcDQYT02vD8WSGoxPrac0mc6ecXx3c50LtQYAAFKJgihr7VZJWyWpp6fHlqLMpeiF/pg+/cMX1fvKqAZjyTkDI2Ok5jq/WsMBtUb8uqq7yVkPqM1Ztob9aosE1B4JutAKAAAgkc4riZ1HxvTJxw7qkb39qvVV69aN7eqsDzoBUUBtU4FROKDmkF81pOkAAFjy6Ikqsof3nNB7/mWb6oM+ffC2S/TOG1apOeR3u1oAAOAC0RNVoFzOajyVUTSRUXQyrehkWrFERtHEqfWTk2l98ZnDumx5g/7l3msVCXKbFgAAvKJiB5ZnsrnpoCc2FQgl0opOOoGQs21mYBRNZBSbCpKSGdlz9KnV+au1bllEn3nHVQRQAAB4TMWl8557ZUR/9I092ns8es7XRoI1qg/68stan5Y31qq+NqL6oE/1zrap19TX+k57bSRYwxQEAAB4WMWk82KJtP74W3v1tW19Wt5Yqw/edoka63zTAdCpYCgfBIX9NaqqYjJLAAAwt4pJ52194iU9uL1P77t5rX7z1otV56+YpgMAgCKoiNu+7D0W1bd3HdcV3U26/84NBFAAAOCCeTqdt+3QqD712EH9YN+AwoEa3X/n+pKVDQAAvM2zA8t/+MKg3vlPz6qpzqffuWOd3nH9KjXU8Q05AACwODzbE/Wpxw7qooagHvnt1ygUIH0HAAAWlye/g5/K5PTsyyO658oVBFAAAKAoPDmwfOrGvg21pO8AAEBxlCSIMsbcZ4zpNcb0Dg4OFr287YdHJUmXdISLXhYAAKhMnkznPfPSiHzVRtetaXG7KgAAwKM8mc4bGU+qOeRX0Fdd9LIAAEBl8mQ6L5HOqZYACgAAFJEne6Jy1qrKcN87AABQPJ7sibKSiKEAAEAxeXJgubVWhigKAAAUkSfTedmcFSEUAAAoJs+l83I5q51HTmpNW6io5QAAgMrmuZ6onX1jOhFN6OcuXVbUcgAAQGXz3A2IN3bW6zPv6NE1q5uLWg4AAKhsxlpb0gJ7enpsb29vScsEAAAohDFmm7W2Z659nvx2HgAAQLERRAEAABSAIAoAAKAABFEAAAAFIIgCAAAoAEEUAABAAQiiAAAACkAQBQAAUACCKAAAgAIQRAEAABSg5Ld9McYMSjpU0kLP1CppyOU6LDWVeE0qsc2FqLTrVGntLVQlXqdKbPNCeP26rLTWts21o+RB1FJgjOmd7z44laoSr0kltrkQlXadKq29harE61SJbV6ISr4upPMAAAAKQBAFAABQgEoNora6XYElqBKvSSW2uRCVdp0qrb2FqsTrVIltXoiKvS4VOSYKAADgQlVqTxQAAMCFsda6+pDUJekxSXsl7ZH0QWd7s6RHJB1wlk3O9rdJ2iVpt6QfS9pytvPMU+adkvZLOijp92ZsN5I+KukFSc9L+sA8x/+Gc6yV1Dpj+82STkra4Tz+0CPX5Ucz2nRM0n/Mc/xqSc84x39Fkt/ZfpOk7ZIykt7ksTYX/b2wxK/Tbc7PdoekJyVdPM/xVznlH5T0dzrVC/5mp+ycpB4Ptfejko5Iis/a/quSBme8L+716PviVuc6/VTS5yXVzHO8lz4zFtrmon5muHRN/knSgKSfzto+Z5mL/T5w8+F+BaROSVc66xHlA5hNkv5i6g0q6fck/bmzfsOMH/5rJT1ztvPMUV61pBclrZHkl7Rz6nWSfk3SFyRVOc/b56nzFZJWSXpljl+Cb3vtusx63dclvWOeOn9V0i8565+W9D5nfZWky5xre7YPxHJsc9HfC0v5OjnHbHTW3y/pc/PU+VlJ1yn/j8pDkl7rbN8oab2kxzV/EFWO7b3OKW+uIOqTXn5fKJ/hOCJpnfO6P5H0rnnq7InPjPNsc1E/M0p9TZz9N0m6UmcGUXOWudjvAzcfrldgjov5DUl3KB/pd874Ye6f47VNko6e7TxzbL9e0vdmPP99Sb/vrD+ref6znKeMovwSLLXrMmNbvaRRSfVzHG+Un2ytZq7zOds+dz6/CEu9zW69F5bSdXLKvHbG9j+b4/hOSftmPP9lSf846zWPa54gqtzaO+tcJQuilsp1ktQm6cUZ22+U9N05jvfMZ8ZC2zzrXK+oBJ8Zxb4mM/av0plB1ELKXPT3QSkfS2pMlDFmlfJR+jOSOqy1x51dJyR1zHHIu5T/r/Zs55ltufL/MUzpc7ZJ0lpJbzHG9BpjHjLGXFJAM643xux0jr+0gOPPsASuy5Q3SnrUWhud4/gWSWPW2sxZjl+wMmnzuSz6e2G2JXCd7pX0XWNMn6RfkfTxeY7vm+f481Im7T2XXzDG7DLGfM0Y01XA8efk8nUaklRjjJmafPFNyqeGZvPSZ8ZC23wui/qZUaJrcjYLKXNR3weltmSCKGNMWPm0yW/N/oNl86GonfX6W5T/gd+/0PMsQEBSwuZnXv2M8nne87Fd+enht0j6e0n/cZ7Hn2GJXJcpvyzpSwUeu2AeafOivxdmWyLX6UOS7rLWrpD0z5I+cZ7HL5hH2vstSaustZcpP0bk8+d5/Dm5fZ2cMn5J0t8YY56VFJOULaApC+aRNi/qZ4bb12S2ucr0giURRBljfMr/kL5orX3Q2dxvjOl09ncqP2ht6vWXSXpA0hustcNnO48xpssYs8N5vFfSUZ3+H8IKZ5uUj4Cnyv935XOxMsZ8zzn+gbO1w1obtdbGnfXvSvIZY1rP83JMW0LXRU47rpH0nRnbZl6XYUmNxpiauY73aJvntdjvhdmWwnUyxrQpPwh16r/Tr0i6wRhTPeP4P3GOXzH7eA+3d17W2mFrbdJ5+oDyA+4XzVK4Tk47f2KtvdFae42kJ5QfT+Ppz4wFtnlei/mZUeJrcjZzllmM94FrCskBLuZD+XzoFyT931nb/1KnD0j7C2e9W/kR/Dcs5DxzlFcj6SXlvw0wNTDwUmffxyX9urN+s6TnznGuV3R6TnuZTn3r6BpJh6eel/N1cfa/V9Lnz3GOf9PpgwPfP2v/53T2QaJl1+ZSvBeW6nVytg/p1GDad0n6+jznmD2w/K5Z+x/X/APLy669M841e0xU54z1uyU9vRjviaV0nZx97c4yIOlRSbfOcw7PfGYstM0zzvWKivCZUeprMuP1q3TmmKg5y1zs94GbD/crIL1a+S6+XTr11c67lM+TPqr8VyO/L6nZef0Dyg/0nXpt79nOM0+Zdyn/X8KLkj48Y3uj8r0OuyX9RM5XPec4/gPK91pllP/6+wPO9t9Q/qugOyU9PftNWa7Xxdn3uKQ7z1HnNcr/sTzo/FIEnO1XO9drXPn/OvZ4qM1Ffy8s5eukfCCw22nn45LWzHN8j/Jf/X5R0id16o/F3c71S0rq16wBpWXc3r9w2pVzlh9xtn9sxvviMUkbPPq++Evlp4nZr3wayPOfGefR5qJ+Zrh0Tb4k6biktNO2dznb5yxzsd8Hbj6YsRwAAKAAS2JMFAAAQLkhiAIAACgAQRQAAEABCKIAAAAKQBAFAABQAIIoAACAAhBEASg7xpibjTE3FHDcK4XMAm2M+YPzPQaA9xFEAXDVjNs9nI+bJZ13EHUBCKIAnKGQDy8AOC/GmHdI+h86NQNyVlJC+TvDP2WM+ZSkT0lqkzQh6d3W2n3GmNdL+l/K32JjWNLbJNUqf0uerDHm7ZJ+U9I+5W8X0e0U+VvW2qeMMS3Kz6a8XPm7EJhz1PM/lL83WlDS31prtxpjPi6p1hizQ/kZk9924VcEgBcwYzmAojLGXKr8Db1vsNYOGWOaJX1CUqvyNzzNGmMelfRea+0BY8y1kj5mrb3VGNMkacxaa40x90raaK39HWPMR5S/L91fOWX8q6R/sNY+aYzpVv72MRuNMX8nacha+yfGmNdJ+rakNmvt0Dx1bbbWjhhjaiU9J+k11tphY0zcWhsu5nUCUH7oiQJQbLdK+repwMUJUuRsyxpjwsqn5v7N2S7lb+Iq5e/o/hXnDvB+SS/PU8btkjbNOL7eOe9Nku5xyv2OMWb0HHX9gDHmbme9S9IlyveAAcAZCKIAuGXcWVYp39t0+Ryv+XtJn7DWftMYc7Okj8xzripJ11lrEzM3zgiqzsk5/+2SrrfWThhjHlc+rQcAc2JgOYBi+4GkNzvjk+Sk86ZZa6OSXjbGvNnZb4wxW5zdDZKOOuvvnHFYTFJkxvOHlR8bJecclzurT0h6q7PttZKazlLPBkmjTgC1QdJ1M/aljTG+c7QTQIUhiAJQVNbaPZI+KumHxpidyo+Hmu1tkt7l7N8j6Q3O9o8on+bbJmnmOKZvSbrbGLPDGHOjpA9I6jHG7DLG7FV+4Lkk/bGkm4wxe5RP6x0+S1X/U1KNMeZ5SR+X9PSMfVsl7TLGfHGh7QbgfQwsBwAAKAA9UQAAAAVgYDmAiuKMzXp0jl23WWv5Jh6ABSOdBwAAUADSeQAAAAUgiAIAACgAQRQAAEABCKIAAAAKQBAFAABQgP8P+FO7oMfyhGUAAAAASUVORK5CYII=",
+      "text/plain": [
+       "<Figure size 720x360 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "def lineplot(x, y, df):\n",
+    "    plt.figure(figsize=(10,5))\n",
+    "    plot = sns.lineplot(data=df, x=x, y=y)\n",
+    "    plot.set(yticklabels=[]) \n",
+    "    plt.show()\n",
+    "\n",
+    "lineplot('created_at', 'id', df_tweets)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 824,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "June\n"
+     ]
+    }
+   ],
+   "source": [
+    "month_with_most_tweets = df_tweets['created_at'].dt.month.value_counts().idxmax()\n",
+    "\n",
+    "datetime_object = datetime.datetime.strptime(str(month_with_most_tweets), \"%m\")\n",
+    "\n",
+    "month_name = datetime_object.strftime(\"%B\")\n",
+    "\n",
+    "print(month_name)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 825,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Most of the tweets were done in June\n"
+     ]
+    }
+   ],
+   "source": [
+    "print('Most of the tweets were done in', month_name)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 443,
+   "execution_count": 826,
    "metadata": {},
    "outputs": [],
    "source": [
-    "from nltk.corpus import stopwords\n",
-    "stop = stopwords.words('spanish')\n",
-    "df_tweets['text_without_stopwords'] = df_tweets['text'].apply(lambda x: ' '.join([word for word in x.split() if word not in (stop)]))"
+    "df_tweets_month = df_tweets.copy()\n",
+    "df_tweets_month['month'] = df_tweets_month['created_at'].dt.month"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 827,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "month\n",
+       "6     88\n",
+       "7     27\n",
+       "8     10\n",
+       "9     25\n",
+       "10     4\n",
+       "Name: text, dtype: int64"
+      ]
+     },
+     "execution_count": 827,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_tweets_month_text = df_tweets_month.groupby(['month']).count()\n",
+    "df_tweets_month_text['text']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 828,
+   "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>retweet_count</th>\n",
+       "      <th>reply_count</th>\n",
+       "      <th>like_count</th>\n",
+       "      <th>quote_count</th>\n",
+       "      <th>total_interactions</th>\n",
+       "      <th>tweet_count</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>month</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>29</td>\n",
+       "      <td>47</td>\n",
+       "      <td>292</td>\n",
+       "      <td>9</td>\n",
+       "      <td>377</td>\n",
+       "      <td>88</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>40</td>\n",
+       "      <td>8</td>\n",
+       "      <td>92</td>\n",
+       "      <td>10</td>\n",
+       "      <td>150</td>\n",
+       "      <td>27</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>31</td>\n",
+       "      <td>0</td>\n",
+       "      <td>40</td>\n",
+       "      <td>2</td>\n",
+       "      <td>73</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>23</td>\n",
+       "      <td>8</td>\n",
+       "      <td>76</td>\n",
+       "      <td>7</td>\n",
+       "      <td>114</td>\n",
+       "      <td>25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>5</td>\n",
+       "      <td>0</td>\n",
+       "      <td>16</td>\n",
+       "      <td>0</td>\n",
+       "      <td>21</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       retweet_count  reply_count  like_count  quote_count  \\\n",
+       "month                                                        \n",
+       "6                 29           47         292            9   \n",
+       "7                 40            8          92           10   \n",
+       "8                 31            0          40            2   \n",
+       "9                 23            8          76            7   \n",
+       "10                 5            0          16            0   \n",
+       "\n",
+       "       total_interactions  tweet_count  \n",
+       "month                                   \n",
+       "6                     377           88  \n",
+       "7                     150           27  \n",
+       "8                      73           10  \n",
+       "9                     114           25  \n",
+       "10                     21            4  "
+      ]
+     },
+     "execution_count": 828,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_tweets_month_intractions = df_tweets_month.groupby(['month']).sum()\n",
+    "df_tweets_month_intractions['tweet_count'] = df_tweets_month_text['text']\n",
+    "df_tweets_month_intractions"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 829,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 720x360 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "def lineplot_mult(df):\n",
+    "    plt.figure(figsize=(10,5))\n",
+    "    plot = sns.lineplot(data=df)\n",
+    "    plot.set(yticklabels=[]) \n",
+    "    plt.show()\n",
+    "\n",
+    "lineplot_mult(df_tweets_month_intractions)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 444,
+   "execution_count": 830,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "[('@TheBridge_Tech', 135),\n",
+       "[('de', 172),\n",
+       " ('@TheBridge_Tech', 135),\n",
+       " ('en', 92),\n",
+       " ('la', 85),\n",
+       " ('y', 66),\n",
        " ('@HeavyMental_es', 65),\n",
+       " ('el', 63),\n",
+       " ('a', 62),\n",
+       " ('que', 53),\n",
        " ('@GuillermoDeHaro', 51),\n",
        " ('@Recuenco', 50),\n",
+       " ('para', 39),\n",
        " ('@_miki', 32),\n",
        " ('@DavidAlayon', 30),\n",
+       " ('por', 28),\n",
+       " ('un', 26),\n",
+       " ('con', 25),\n",
+       " ('las', 22),\n",
+       " ('del', 21),\n",
+       " ('se', 19),\n",
+       " ('una', 18),\n",
+       " ('no', 18),\n",
+       " ('los', 17),\n",
+       " ('es', 15),\n",
+       " ('lo', 13),\n",
+       " ('nos', 12),\n",
        " ('@Mulder01198676', 12),\n",
+       " ('más', 11),\n",
+       " ('pero', 10),\n",
        " ('@Alienta', 10),\n",
+       " ('te', 9),\n",
        " ('El', 9),\n",
+       " ('al', 9),\n",
        " ('talento', 9),\n",
        " ('convenio', 9),\n",
        " ('formación', 9),\n",
@@ -752,15 +1276,21 @@
        " ('@TheBridge_Tech,', 8),\n",
        " ('si', 8),\n",
        " ('La', 8),\n",
+       " ('ya', 8),\n",
        " ('@JotDownSpain', 8),\n",
        " ('vida', 7),\n",
        " ('Si', 7),\n",
        " ('gracias', 7),\n",
+       " ('ha', 7),\n",
+       " ('sobre', 7),\n",
+       " ('sus', 7),\n",
        " ('the', 7),\n",
        " ('Gracias', 7),\n",
        " ('@moquintana', 7),\n",
        " ('Hoy', 6),\n",
+       " ('o', 6),\n",
        " ('Y', 6),\n",
+       " ('entre', 6),\n",
        " ('and', 6),\n",
        " ('profesionales', 6),\n",
        " ('#ciberseguridad', 6),\n",
@@ -768,8 +1298,13 @@
        " ('@PauMugarra', 6),\n",
        " ('va', 5),\n",
        " ('hacer', 5),\n",
+       " ('tenemos', 5),\n",
+       " ('han', 5),\n",
        " ('ser', 5),\n",
+       " ('nuestros', 5),\n",
        " ('@TheBridge_Tech.', 5),\n",
+       " ('desde', 5),\n",
+       " ('todos', 5),\n",
        " ('Data', 5),\n",
        " ('demanda', 5),\n",
        " ('unen', 5),\n",
@@ -778,6 +1313,7 @@
        " ('aceleradora', 5),\n",
        " ('millones', 5),\n",
        " ('euros', 5),\n",
+       " ('me', 5),\n",
        " ('ronda', 5),\n",
        " ('directo', 5),\n",
        " ('Que', 5),\n",
@@ -789,209 +1325,571 @@
        " ('@estodopornada', 5),\n",
        " ('Bootcamp', 4),\n",
        " ('buena', 4),\n",
+       " ('os', 4),\n",
        " ('#bootcamp', 4),\n",
        " ('Un', 4),\n",
        " ('5', 4),\n",
        " ('Os', 4),\n",
+       " ('nuestras', 4),\n",
+       " ('esta', 4),\n",
        " ('colaboración', 4),\n",
-       " ('@IronhackMAD', 4),\n",
-       " ('@ISDICoders', 4),\n",
-       " ('@Ubiqum', 4),\n",
-       " ('@4GeeksAcademyES', 4),\n",
-       " ('@hackaboss_', 4),\n",
-       " ('@KeepCoding_', 4),\n",
-       " ('@uxerschool', 4),\n",
-       " ('@CraftCodeTech', 4),\n",
-       " ('@CodenotchMAD', 4),\n",
-       " ('@NeolandStudio', 4),\n",
-       " ('@Adalab_Digital', 4),\n",
-       " ('@IEuniversity', 4),\n",
-       " ('@lemoncoders', 4),\n",
-       " ('@Fujitsu_ES', 4),\n",
-       " ('hoy', 4),\n",
-       " ('#talento', 4),\n",
-       " ('En', 4),\n",
-       " ('🤝🏼', 4),\n",
-       " ('@ceeivalencia', 4),\n",
-       " ('digital,', 4),\n",
-       " ('colaboración:', 4),\n",
-       " ('https://t.co/8neFc4j8i4', 4),\n",
-       " ('🎯', 4),\n",
-       " ('Complementar', 4),\n",
-       " ('técnica', 4),\n",
-       " ('talento,', 4),\n",
-       " ('principales', 4),\n",
-       " ('objetivos.', 4),\n",
-       " ('@Google', 4),\n",
-       " ('@UbaldoHervas', 4),\n",
-       " ('@pelayoarbues', 4),\n",
-       " ('trabajando', 3),\n",
-       " ('web', 3),\n",
-       " ('Full', 3),\n",
-       " ('mano', 3),\n",
-       " ('👇', 3),\n",
-       " ('primer', 3),\n",
-       " ('bootcamp', 3),\n",
-       " ('quieres', 3),\n",
-       " ('futuros', 3),\n",
-       " ('@valerybriz', 3)]"
+       " ('hemos', 4),\n",
+       " ('@IronhackMAD', 4)]"
       ]
      },
-     "execution_count": 444,
+     "execution_count": 830,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "Counter(\" \".join(df_tweets[\"text_without_stopwords\"]).split()).most_common(100)"
+    "Counter(\" \".join(df_tweets[\"text\"]).split()).most_common(100)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 831,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def remove_links(text):\n",
+    "    return \" \".join([' ' if ('http') in word else word for word in text.split()])\n",
+    "\n",
+    "df_tweets['text_mod'] = df_tweets['text'].apply(lambda x: remove_links(x))"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 445,
+   "execution_count": 832,
    "metadata": {},
    "outputs": [],
    "source": [
-    "df_tweets['text_without_articles'] = df_tweets['text_without_stopwords'].apply(lambda x: x.lower())"
+    "def remove_stopwords(text, language):\n",
+    "    stop = stopwords.words(language)\n",
+    "    return ' '.join([word for word in text.split() if word not in (stop)])\n",
+    "\n",
+    "df_tweets['text_mod'] = df_tweets['text_mod'].apply(lambda x: remove_stopwords(x, 'spanish'))"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 463,
+   "execution_count": 833,
    "metadata": {},
    "outputs": [],
    "source": [
-    "def removearticles(text):\n",
-    "  text = re.sub('\\s+(la|el|si|y|the|and|que|.|#)(\\s+)', '\\2', text)\n",
-    "  return text"
+    "def remove_metions(text):\n",
+    "    return re.sub(r\"\\@\\w+[,]|\\@\\w+|[,]\\@\\w+\", \" \", text)\n",
+    "\n",
+    "df_tweets['text_mod'] = df_tweets['text_mod'].apply(lambda x: remove_metions(x))"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 464,
+   "execution_count": 834,
    "metadata": {},
    "outputs": [],
    "source": [
-    "def process_string(text):\n",
-    "    text = re.sub(r\"\\@\\w+[,]|\\@\\w+|[,]\\@\\w+\", \"\", text)\n",
-    "    return text"
+    "def signs_tweets(text, signs):\n",
+    "    return signs.sub(' ', text.lower())\n",
+    "\n",
+    "signs = re.compile(\"(\\.)|(\\;)|(\\:)|(\\!)|(\\?)|(\\¿)|(\\@)|(\\,)|(\\\")|(\\()|(\\))|(\\[)|(\\])|(\\d+)|(\\¡)\")\n",
+    "\n",
+    "df_tweets['text_mod'] = df_tweets['text_mod'].apply(lambda x: signs_tweets(x, signs))"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 465,
+   "execution_count": 835,
    "metadata": {},
    "outputs": [],
    "source": [
-    "df_tweets['text_without_articles'] = df_tweets['text_without_articles'].apply(lambda x: removearticles(x))\n",
-    "df_tweets['text_without_articles'] = df_tweets['text_without_articles'].apply(lambda x: process_string(x))"
+    "def remove_hash(text):\n",
+    "    return re.sub(r\"\\#\\w+[,]|\\#\\w+|[,]\\#\\w+\", \" \", text)\n",
+    "\n",
+    "df_tweets['text_mod'] = df_tweets['text_mod'].apply(lambda x: remove_hash(x))"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 478,
+   "execution_count": 836,
    "metadata": {},
    "outputs": [],
    "source": [
-    "most_repeated = Counter(\" \".join(df_tweets[\"text_without_articles\"]).split()).most_common(100)"
+    "def remove_aux_words(text, articles):\n",
+    "  return articles.sub(' ', text.lower())\n",
+    "\n",
+    "articles = re.compile('\\s+(la|el|y|the|and|que|si|no|.|#)(\\s+)')\n",
+    "\n",
+    "df_tweets['text_mod'] = df_tweets['text_mod'].apply(lambda x: remove_aux_words(x, articles))"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 479,
+   "execution_count": 837,
    "metadata": {},
    "outputs": [],
    "source": [
-    "most_repeated = most_repeated[:10]"
+    "df_tweets['text_mod'] = df_tweets['text_mod'].apply(lambda x: nitos.clean_emoji(x))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 838,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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+       "      <th>id</th>\n",
+       "      <th>text</th>\n",
+       "      <th>author_id</th>\n",
+       "      <th>created_at</th>\n",
+       "      <th>retweet_count</th>\n",
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+       "      <th>like_count</th>\n",
+       "      <th>quote_count</th>\n",
+       "      <th>total_interactions</th>\n",
+       "      <th>text_mod</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1578613094191796224</td>\n",
+       "      <td>Gente muy agradable en @TheBridge_Tech , te ries mucho en el dia a dia. El tema es que pasas tanto tiempo trabajando aqui, que te quita la libido y tu vida sexual se va a la mierda, jjj. Tengo ganas de terminar mi Bootcamp para poder hacer una buena sesión de Shibari</td>\n",
+       "      <td>1578095844569514011</td>\n",
+       "      <td>2022-10-08 05:07:45</td>\n",
+       "      <td>0</td>\n",
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+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
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+       "      <td>gente agradable ries dia dia tema pasas tiempo trabajando aqui  quita libido vida sexual va mierda  jjj  tengo ganas terminar bootcamp poder hacer buena sesión shibari</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1577334577701453827</td>\n",
+       "      <td>Recordaros que la semana que viene tenemos la primera quedada #CPS en Madrid, en @TheBridge_Tech, en el que tendremos la gran suerte de contar con @Recuenco para que nos dé una charla. Las plazas se han agotado, pero os podéis apuntar al grupo para próximas quedadas 🚀</td>\n",
+       "      <td>1003872445</td>\n",
+       "      <td>2022-10-04 16:27:23</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "      <td>12</td>\n",
+       "      <td>0</td>\n",
+       "      <td>14</td>\n",
+       "      <td>recordaros semana viene primera quedada madrid gran suerte contar dé charla  las plazas agotado  podéis apuntar grupo próximas quedadas</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1576902991507922944</td>\n",
+       "      <td>El desarrollador web es uno de los perfiles más demandados en el mercado laboral 📈  Descubre nuestro #bootcamp Desarrollo Web Full Stack de la mano de @TheBridge_Tech 💻  Toda la información aquí! 👇 https://t.co/LOoTu97aQq https://t.co/xpaAzxXSDX</td>\n",
+       "      <td>2529499620</td>\n",
+       "      <td>2022-10-03 11:52:25</td>\n",
+       "      <td>3</td>\n",
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+       "      <td>0</td>\n",
+       "      <td>6</td>\n",
+       "      <td>el desarrollador web perfiles demandados mercado laboral descubre desarrollo web full stack mano toda información aquí</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>1576856703349374976</td>\n",
+       "      <td>@jorgegrev @TheBridge_Tech Enhorabuena crack!</td>\n",
+       "      <td>706520411551494145</td>\n",
+       "      <td>2022-10-03 08:48:29</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>enhorabuena crack</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>1575217357105946624</td>\n",
+       "      <td>Hoy por fin ve la luz mi primer Case Study público. Un trabajo intensivo de fin de bootcamp realizado con un cliente real @emancipaTIC  y dos semanas para que las 5 verticales en @TheBridge_Tech hiciésemos realidad un MVP. Os invito a verlo y dar feedback. https://t.co/rkCjxulYS9 https://t.co/PqM0dvxj3X</td>\n",
+       "      <td>604485175</td>\n",
+       "      <td>2022-09-28 20:14:18</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0</td>\n",
+       "      <td>4</td>\n",
+       "      <td>0</td>\n",
+       "      <td>7</td>\n",
+       "      <td>hoy fin ve luz primer case study público  un trabajo intensivo fin bootcamp realizado cliente real dos semanas verticales hiciésemos realidad mvp  os invito verlo dar feedback</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
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+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
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+       "    <tr>\n",
+       "      <th>149</th>\n",
+       "      <td>1536313018321190912</td>\n",
+       "      <td>Lo conseguí!!! Gracias @TheBridge_Tech  @HeavyMental_es https://t.co/SOccLkT3dG</td>\n",
+       "      <td>18955785</td>\n",
+       "      <td>2022-06-13 11:42:21</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>lo conseguí gracias</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>150</th>\n",
+       "      <td>1536311923423203331</td>\n",
+       "      <td>@TheBridge_Tech @HeavyMental_es @Alienta ¡Y yo! Que buena forma de empezar la semana.</td>\n",
+       "      <td>15521945</td>\n",
+       "      <td>2022-06-13 11:38:00</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>yo buena forma empezar semana</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>151</th>\n",
+       "      <td>1536310998319210496</td>\n",
+       "      <td>@TheBridge_Tech @HeavyMental_es @Alienta ¡La tengo!</td>\n",
+       "      <td>10614452</td>\n",
+       "      <td>2022-06-13 11:34:19</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>tengo</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>152</th>\n",
+       "      <td>1536310702876549123</td>\n",
+       "      <td>Lo prometimos y han llegado gracias a @TheBridge_Tech ... últimas entradas para el podcast 27 en directo :D  cc @Atorrerus @Mulder01198676 @joansabater @PesetJairo @pelayoarbues @adriskou @estodopornada https://t.co/Aygpl489sQ</td>\n",
+       "      <td>1255794072280842240</td>\n",
+       "      <td>2022-06-13 11:33:09</td>\n",
+       "      <td>2</td>\n",
+       "      <td>4</td>\n",
+       "      <td>6</td>\n",
+       "      <td>0</td>\n",
+       "      <td>12</td>\n",
+       "      <td>lo prometimos llegado gracias últimas entradas podcast directo cc</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>153</th>\n",
+       "      <td>1536267654717132801</td>\n",
+       "      <td>@HeavyMental_es @PesetJairo @TheBridge_Tech @GuillermoDeHaro @Recuenco @Alienta Inocente de mi, que lo daba por hecho...</td>\n",
+       "      <td>1434890317640126469</td>\n",
+       "      <td>2022-06-13 08:42:06</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>inocente mi  daba hecho</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>154 rows × 10 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                      id  \\\n",
+       "0    1578613094191796224   \n",
+       "1    1577334577701453827   \n",
+       "2    1576902991507922944   \n",
+       "3    1576856703349374976   \n",
+       "4    1575217357105946624   \n",
+       "..                   ...   \n",
+       "149  1536313018321190912   \n",
+       "150  1536311923423203331   \n",
+       "151  1536310998319210496   \n",
+       "152  1536310702876549123   \n",
+       "153  1536267654717132801   \n",
+       "\n",
+       "                                                                                                                                                                                                                                                                                                                 text  \\\n",
+       "0                                         Gente muy agradable en @TheBridge_Tech , te ries mucho en el dia a dia. El tema es que pasas tanto tiempo trabajando aqui, que te quita la libido y tu vida sexual se va a la mierda, jjj. Tengo ganas de terminar mi Bootcamp para poder hacer una buena sesión de Shibari   \n",
+       "1                                        Recordaros que la semana que viene tenemos la primera quedada #CPS en Madrid, en @TheBridge_Tech, en el que tendremos la gran suerte de contar con @Recuenco para que nos dé una charla. Las plazas se han agotado, pero os podéis apuntar al grupo para próximas quedadas 🚀   \n",
+       "2                                                               El desarrollador web es uno de los perfiles más demandados en el mercado laboral 📈  Descubre nuestro #bootcamp Desarrollo Web Full Stack de la mano de @TheBridge_Tech 💻  Toda la información aquí! 👇 https://t.co/LOoTu97aQq https://t.co/xpaAzxXSDX   \n",
+       "3                                                                                                                                                                                                                                                                       @jorgegrev @TheBridge_Tech Enhorabuena crack!   \n",
+       "4    Hoy por fin ve la luz mi primer Case Study público. Un trabajo intensivo de fin de bootcamp realizado con un cliente real @emancipaTIC  y dos semanas para que las 5 verticales en @TheBridge_Tech hiciésemos realidad un MVP. Os invito a verlo y dar feedback. https://t.co/rkCjxulYS9 https://t.co/PqM0dvxj3X   \n",
+       "..                                                                                                                                                                                                                                                                                                                ...   \n",
+       "149                                                                                                                                                                                                                                   Lo conseguí!!! Gracias @TheBridge_Tech  @HeavyMental_es https://t.co/SOccLkT3dG   \n",
+       "150                                                                                                                                                                                                                             @TheBridge_Tech @HeavyMental_es @Alienta ¡Y yo! Que buena forma de empezar la semana.   \n",
+       "151                                                                                                                                                                                                                                                               @TheBridge_Tech @HeavyMental_es @Alienta ¡La tengo!   \n",
+       "152                                                                                Lo prometimos y han llegado gracias a @TheBridge_Tech ... últimas entradas para el podcast 27 en directo :D  cc @Atorrerus @Mulder01198676 @joansabater @PesetJairo @pelayoarbues @adriskou @estodopornada https://t.co/Aygpl489sQ   \n",
+       "153                                                                                                                                                                                          @HeavyMental_es @PesetJairo @TheBridge_Tech @GuillermoDeHaro @Recuenco @Alienta Inocente de mi, que lo daba por hecho...   \n",
+       "\n",
+       "               author_id          created_at  retweet_count  reply_count  \\\n",
+       "0    1578095844569514011 2022-10-08 05:07:45              0            0   \n",
+       "1             1003872445 2022-10-04 16:27:23              2            0   \n",
+       "2             2529499620 2022-10-03 11:52:25              3            0   \n",
+       "3     706520411551494145 2022-10-03 08:48:29              0            0   \n",
+       "4              604485175 2022-09-28 20:14:18              3            0   \n",
+       "..                   ...                 ...            ...          ...   \n",
+       "149             18955785 2022-06-13 11:42:21              0            0   \n",
+       "150             15521945 2022-06-13 11:38:00              0            0   \n",
+       "151             10614452 2022-06-13 11:34:19              0            0   \n",
+       "152  1255794072280842240 2022-06-13 11:33:09              2            4   \n",
+       "153  1434890317640126469 2022-06-13 08:42:06              0            0   \n",
+       "\n",
+       "     like_count  quote_count  total_interactions  \\\n",
+       "0             0            0                   0   \n",
+       "1            12            0                  14   \n",
+       "2             3            0                   6   \n",
+       "3             1            0                   1   \n",
+       "4             4            0                   7   \n",
+       "..          ...          ...                 ...   \n",
+       "149           1            0                   1   \n",
+       "150           1            0                   1   \n",
+       "151           2            0                   2   \n",
+       "152           6            0                  12   \n",
+       "153           2            0                   2   \n",
+       "\n",
+       "                                                                                                                                                                             text_mod  \n",
+       "0             gente agradable ries dia dia tema pasas tiempo trabajando aqui  quita libido vida sexual va mierda  jjj  tengo ganas terminar bootcamp poder hacer buena sesión shibari  \n",
+       "1                                            recordaros semana viene primera quedada madrid gran suerte contar dé charla  las plazas agotado  podéis apuntar grupo próximas quedadas   \n",
+       "2                                                            el desarrollador web perfiles demandados mercado laboral descubre desarrollo web full stack mano toda información aquí    \n",
+       "3                                                                                                                                                                  enhorabuena crack   \n",
+       "4    hoy fin ve luz primer case study público  un trabajo intensivo fin bootcamp realizado cliente real dos semanas verticales hiciésemos realidad mvp  os invito verlo dar feedback   \n",
+       "..                                                                                                                                                                                ...  \n",
+       "149                                                                                                                                                              lo conseguí gracias   \n",
+       "150                                                                                                                                                    yo buena forma empezar semana   \n",
+       "151                                                                                                                                                                            tengo   \n",
+       "152                                                                                                                lo prometimos llegado gracias últimas entradas podcast directo cc   \n",
+       "153                                                                                                                                                          inocente mi  daba hecho   \n",
+       "\n",
+       "[154 rows x 10 columns]"
+      ]
+     },
+     "execution_count": 838,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_tweets"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 480,
+   "execution_count": 839,
    "metadata": {},
    "outputs": [
     {
      "data": {
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+       "      <td>15</td>\n",
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+       "      <th>2</th>\n",
+       "      <td>primera</td>\n",
+       "      <td>11</td>\n",
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+       "      <th>3</th>\n",
+       "      <td>hoy</td>\n",
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+       "      <td>9</td>\n",
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+       "      <th>8</th>\n",
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+       "      <td>8</td>\n",
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+       "      <th>9</th>\n",
+       "      <td>bootcamp</td>\n",
+       "      <td>7</td>\n",
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       "text/plain": [
-       "[('gracias', 11),\n",
-       " ('talento', 10),\n",
-       " ('hoy', 9),\n",
-       " ('convenio', 9),\n",
-       " ('formación', 9),\n",
-       " ('vida', 7),\n",
-       " ('bootcamp', 7),\n",
-       " ('primera', 6),\n",
-       " ('data', 6),\n",
-       " ('profesionales', 6)]"
+       "           Word  Times\n",
+       "0       gracias     15\n",
+       "1       talento     14\n",
+       "2       primera     11\n",
+       "3           hoy     10\n",
+       "4     formación     10\n",
+       "5          vida      9\n",
+       "6      convenio      9\n",
+       "7  colaboración      8\n",
+       "8       digital      8\n",
+       "9      bootcamp      7"
       ]
      },
-     "execution_count": 480,
+     "execution_count": 839,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "most_repeated"
+    "most_repeated = Counter(\" \".join(df_tweets[\"text_mod\"]).split()).most_common(100)\n",
+    "\n",
+    "most_repeated = most_repeated[:10]\n",
+    "\n",
+    "df = pd.DataFrame(most_repeated, columns =['Word', 'Times'])\n",
+    "\n",
+    "df"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 486,
+   "execution_count": 840,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<seaborn.axisgrid.PairGrid at 0x7fa153731e10>"
+       "<seaborn.axisgrid.PairGrid at 0x7f9ced51e6d0>"
       ]
      },
-     "execution_count": 486,
+     "execution_count": 840,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
-       "<Figure size 1000x1000 with 20 Axes>"
+       "<Figure size 900x900 with 30 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     }
    ],
    "source": [
-    "sns.pairplot(df_tweets[['retweet_count', 'reply_count', 'like_count', 'quote_count']])"
+    "sns.pairplot(df_tweets)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 487,
+   "execution_count": 841,
    "metadata": {},
    "outputs": [
     {
      "data": {
+      "image/png": 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",
       "text/plain": [
-       "<AxesSubplot:>"
+       "<Figure size 720x360 with 2 Axes>"
       ]
      },
-     "execution_count": 487,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "def heatmap(df):\n",
+    "    plt.figure(figsize=(10,5))\n",
+    "    plot = sns.heatmap(df.corr(), annot=True)\n",
+    "    plt.show()\n",
+    "\n",
+    "heatmap(df_tweets)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 842,
+   "metadata": {},
+   "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
-       "<Figure size 640x480 with 2 Axes>"
+       "<Figure size 720x360 with 2 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     }
    ],
    "source": [
-    "sns.heatmap(df_tweets[['retweet_count', 'reply_count', 'like_count', 'quote_count']].corr(), annot=True)"
+    "heatmap(df_tweets_month_intractions)"
    ]
   },
   {
@@ -999,20 +1897,7 @@
    "execution_count": null,
    "metadata": {},
    "outputs": [],
-   "source": [
-    "def sql_query(query):\n",
-    "\n",
-    "    # Ejecuta la query\n",
-    "    crsr.execute(query)\n",
-    "\n",
-    "    # Almacena los datos de la query \n",
-    "    ans = crsr.fetchall()\n",
-    "\n",
-    "    # Obtenemos los nombres de las columnas de la tabla\n",
-    "    names = [description[0] for description in crsr.description]\n",
-    "\n",
-    "    return pd.DataFrame(ans,columns=names)"
-   ]
+   "source": []
   }
  ],
  "metadata": {
diff --git a/notebooks/predictions.ipynb b/notebooks/predictions.ipynb
index 51a39a9..92ed0e0 100644
--- a/notebooks/predictions.ipynb
+++ b/notebooks/predictions.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 73,
+   "execution_count": 433,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -12,12 +12,14 @@
     "import pandas as pd\n",
     "import re\n",
     "import numpy as np\n",
-    "import matplotlib.pyplot as plt"
+    "import matplotlib.pyplot as plt\n",
+    "from nltk.corpus import stopwords\n",
+    "from nltk.stem.snowball import SnowballStemmer"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 74,
+   "execution_count": 434,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -27,7 +29,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 75,
+   "execution_count": 435,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -37,7 +39,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 76,
+   "execution_count": 436,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -46,27 +48,92 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 77,
+   "execution_count": 437,
    "metadata": {},
    "outputs": [],
    "source": [
-    "def process_string(text):\n",
-    "    text = re.sub(r\"\\@\\w+[,]|\\@\\w+|[,]\\@\\w+\", \"\", text)\n",
-    "    return text"
+    "def remove_links(text):\n",
+    "    return \" \".join([' ' if ('http') in word else word for word in text.split()])\n",
+    "\n",
+    "df_tweets['text'] = df_tweets['text'].apply(lambda x: remove_links(x))"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 78,
+   "execution_count": 438,
    "metadata": {},
    "outputs": [],
    "source": [
-    "df_tweets['text'] = df_tweets['text'].apply(lambda x: process_string(x))"
+    "def remove_stopwords(text, language):\n",
+    "    stop = stopwords.words(language)\n",
+    "    return ' '.join([word for word in text.split() if word not in (stop)])\n",
+    "\n",
+    "df_tweets['text'] = df_tweets['text'].apply(lambda x: remove_stopwords(x, 'spanish'))"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 79,
+   "execution_count": 439,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def remove_metions(text):\n",
+    "    return re.sub(r\"\\@\\w+[,]|\\@\\w+|[,]\\@\\w+\", \" \", text)\n",
+    "\n",
+    "df_tweets['text'] = df_tweets['text'].apply(lambda x: remove_metions(x))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 440,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def signs_tweets(text, signs):\n",
+    "    return signs.sub(' ', text.lower())\n",
+    "\n",
+    "signs = re.compile(\"(\\.)|(\\;)|(\\:)|(\\!)|(\\?)|(\\¿)|(\\@)|(\\,)|(\\\")|(\\()|(\\))|(\\[)|(\\])|(\\d+)|(\\¡)\")\n",
+    "\n",
+    "df_tweets['text'] = df_tweets['text'].apply(lambda x: signs_tweets(x, signs))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 441,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def remove_hash(text):\n",
+    "    return re.sub(r\"\\#\\w+[,]|\\#\\w+|[,]\\#\\w+\", \"\", text)\n",
+    "\n",
+    "df_tweets['text'] = df_tweets['text'].apply(lambda x: remove_hash(x))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 442,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def spanish_stemmer(x):\n",
+    "    stemmer = SnowballStemmer('spanish')\n",
+    "    return \" \".join([stemmer.stem(word) for word in x.split()])\n",
+    "\n",
+    "df_tweets['text'] = df_tweets['text'].apply(lambda x: spanish_stemmer(x))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 443,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df_tweets['text'] = df_tweets['text'].apply(lambda x: nitos.clean_emoji(x))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 444,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -76,7 +143,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 80,
+   "execution_count": 445,
    "metadata": {},
    "outputs": [
     {
@@ -88,7 +155,7 @@
        "                ('cls', LogisticRegression(C=0.5))])"
       ]
      },
-     "execution_count": 80,
+     "execution_count": 445,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -99,7 +166,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 81,
+   "execution_count": 446,
    "metadata": {},
    "outputs": [
     {
@@ -108,7 +175,7 @@
        "1000"
       ]
      },
-     "execution_count": 81,
+     "execution_count": 446,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -119,7 +186,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 82,
+   "execution_count": 447,
    "metadata": {},
    "outputs": [
     {
@@ -139,7 +206,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 91,
+   "execution_count": 448,
    "metadata": {},
    "outputs": [
     {
@@ -1147,7 +1214,7 @@
        " 'zp']"
       ]
      },
-     "execution_count": 91,
+     "execution_count": 448,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1158,7 +1225,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 83,
+   "execution_count": 449,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1167,7 +1234,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 84,
+   "execution_count": 450,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1176,7 +1243,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 85,
+   "execution_count": 451,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1185,7 +1252,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 86,
+   "execution_count": 452,
    "metadata": {},
    "outputs": [
     {
@@ -1194,7 +1261,7 @@
        "<AxesSubplot:title={'center':'Feature Importance'}>"
       ]
      },
-     "execution_count": 86,
+     "execution_count": 452,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -1217,7 +1284,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 87,
+   "execution_count": 453,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1226,7 +1293,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 88,
+   "execution_count": 454,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1236,7 +1303,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 89,
+   "execution_count": 455,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1246,7 +1313,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 90,
+   "execution_count": 456,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df_tweets['sentiment'] = predictions\n",
+    "df_tweets['sentiment1'] = sentiment1\n",
+    "df_tweets['sentiment2'] = sentiment2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 457,
    "metadata": {},
    "outputs": [
     {
@@ -1287,49 +1365,49 @@
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td>1578613094191796224</td>\n",
-       "      <td>Gente muy agradable en  , te ries mucho en el ...</td>\n",
+       "      <td>gent agrad ries dia dia el tem pas tiemp traba...</td>\n",
        "      <td>1578095844569514011</td>\n",
        "      <td>2022-10-08 05:07:45</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0.416938</td>\n",
-       "      <td>0.583062</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.982208</td>\n",
+       "      <td>0.017792</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>1577334577701453827</td>\n",
-       "      <td>Recordaros que la semana que viene tenemos la ...</td>\n",
+       "      <td>recordar seman vien primer qued madr gran suer...</td>\n",
        "      <td>1003872445</td>\n",
        "      <td>2022-10-04 16:27:23</td>\n",
        "      <td>2</td>\n",
        "      <td>0</td>\n",
        "      <td>12</td>\n",
        "      <td>0</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0.353377</td>\n",
-       "      <td>0.646623</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.919747</td>\n",
+       "      <td>0.080253</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>1576902991507922944</td>\n",
-       "      <td>El desarrollador web es uno de los perfiles má...</td>\n",
+       "      <td>el desarroll web perfil demand merc laboral de...</td>\n",
        "      <td>2529499620</td>\n",
        "      <td>2022-10-03 11:52:25</td>\n",
        "      <td>3</td>\n",
        "      <td>0</td>\n",
        "      <td>3</td>\n",
        "      <td>0</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0.288251</td>\n",
-       "      <td>0.711749</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.705893</td>\n",
+       "      <td>0.294107</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>1576856703349374976</td>\n",
-       "      <td>Enhorabuena crack!</td>\n",
+       "      <td>enhorabuen crack</td>\n",
        "      <td>706520411551494145</td>\n",
        "      <td>2022-10-03 08:48:29</td>\n",
        "      <td>0</td>\n",
@@ -1337,13 +1415,13 @@
        "      <td>1</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
-       "      <td>0.547459</td>\n",
-       "      <td>0.452541</td>\n",
+       "      <td>0.884458</td>\n",
+       "      <td>0.115542</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td>1575217357105946624</td>\n",
-       "      <td>Hoy por fin ve la luz mi primer Case Study púb...</td>\n",
+       "      <td>hoy fin ve luz prim cas study public un trabaj...</td>\n",
        "      <td>604485175</td>\n",
        "      <td>2022-09-28 20:14:18</td>\n",
        "      <td>3</td>\n",
@@ -1351,8 +1429,8 @@
        "      <td>4</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
-       "      <td>0.692391</td>\n",
-       "      <td>0.307609</td>\n",
+       "      <td>0.529245</td>\n",
+       "      <td>0.470755</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -1360,11 +1438,11 @@
       ],
       "text/plain": [
        "                    id                                               text  \\\n",
-       "0  1578613094191796224  Gente muy agradable en  , te ries mucho en el ...   \n",
-       "1  1577334577701453827  Recordaros que la semana que viene tenemos la ...   \n",
-       "2  1576902991507922944  El desarrollador web es uno de los perfiles má...   \n",
-       "3  1576856703349374976                                 Enhorabuena crack!   \n",
-       "4  1575217357105946624  Hoy por fin ve la luz mi primer Case Study púb...   \n",
+       "0  1578613094191796224  gent agrad ries dia dia el tem pas tiemp traba...   \n",
+       "1  1577334577701453827  recordar seman vien primer qued madr gran suer...   \n",
+       "2  1576902991507922944  el desarroll web perfil demand merc laboral de...   \n",
+       "3  1576856703349374976                                   enhorabuen crack   \n",
+       "4  1575217357105946624  hoy fin ve luz prim cas study public un trabaj...   \n",
        "\n",
        "             author_id          created_at  retweet_count  reply_count  \\\n",
        "0  1578095844569514011 2022-10-08 05:07:45              0            0   \n",
@@ -1374,24 +1452,28 @@
        "4            604485175 2022-09-28 20:14:18              3            0   \n",
        "\n",
        "   like_count  quote_count  sentiment  sentiment1  sentiment2  \n",
-       "0           0            0          1    0.416938    0.583062  \n",
-       "1          12            0          1    0.353377    0.646623  \n",
-       "2           3            0          1    0.288251    0.711749  \n",
-       "3           1            0          0    0.547459    0.452541  \n",
-       "4           4            0          0    0.692391    0.307609  "
+       "0           0            0          0    0.982208    0.017792  \n",
+       "1          12            0          0    0.919747    0.080253  \n",
+       "2           3            0          0    0.705893    0.294107  \n",
+       "3           1            0          0    0.884458    0.115542  \n",
+       "4           4            0          0    0.529245    0.470755  "
       ]
      },
-     "execution_count": 90,
+     "execution_count": 457,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "df_tweets['sentiment'] = predictions\n",
-    "df_tweets['sentiment1'] = sentiment1\n",
-    "df_tweets['sentiment2'] = sentiment2\n",
     "df_tweets.head()"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {