1.accenture_data_set.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Preparing Data Set"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Import libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Load Data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "metadata": {},
   "outputs": [],
   "source": [
    "content = pd.read_csv('/Users/deborabastos/Documents/3.DataScience/accenture_data_analytics/data/Content (1).csv')\n",
    "reactions = pd.read_csv('/Users/deborabastos/Documents/3.DataScience/accenture_data_analytics/data/Reactions (1).csv')\n",
    "reaction_type = pd.read_csv('/Users/deborabastos/Documents/3.DataScience/accenture_data_analytics/data/ReactionTypes (1).csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Verify Data Content"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "metadata": {},
   "outputs": [
    {
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       "      <td>Studying</td>\n",
       "      <td>https://socialbuzz.cdn.com/content/storage/975...</td>\n",
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       "    <tr>\n",
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       "      <td>1</td>\n",
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       "      <td>2</td>\n",
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       "      <td>e206e31b-5f85-4964-b6ea-d7ee5324def1</td>\n",
       "      <td>video</td>\n",
       "      <td>food</td>\n",
       "      <td>https://socialbuzz.cdn.com/content/storage/01a...</td>\n",
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       "   Unnamed: 0                            Content ID  \\\n",
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       "\n",
       "                                User ID   Type        Category  \\\n",
       "0  8d3cd87d-8a31-4935-9a4f-b319bfe05f31  photo        Studying   \n",
       "1  beb1f34e-7870-46d6-9fc7-2e12eb83ce43  photo  healthy eating   \n",
       "2  a5c65404-5894-4b87-82f2-d787cbee86b4  photo  healthy eating   \n",
       "3  9fb4ce88-fac1-406c-8544-1a899cee7aaf  photo      technology   \n",
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       "\n",
       "                                                 URL  \n",
       "0  https://socialbuzz.cdn.com/content/storage/975...  \n",
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       "2  https://socialbuzz.cdn.com/content/storage/230...  \n",
       "3  https://socialbuzz.cdn.com/content/storage/356...  \n",
       "4  https://socialbuzz.cdn.com/content/storage/01a...  "
      ]
     },
     "execution_count": 162,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "content.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "metadata": {},
   "outputs": [
    {
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       "      <td>2021-04-22 15:17:15</td>\n",
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       "      <th>1</th>\n",
       "      <td>1</td>\n",
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       "      <td>5d454588-283d-459d-915d-c48a2cb4c27f</td>\n",
       "      <td>disgust</td>\n",
       "      <td>2020-11-07 09:43:50</td>\n",
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       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>97522e57-d9ab-4bd6-97bf-c24d952602d2</td>\n",
       "      <td>92b87fa5-f271-43e0-af66-84fac21052e6</td>\n",
       "      <td>dislike</td>\n",
       "      <td>2021-06-17 12:22:51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
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       "      <td>163daa38-8b77-48c9-9af6-37a6c1447ac2</td>\n",
       "      <td>scared</td>\n",
       "      <td>2021-04-18 05:13:58</td>\n",
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       "      <th>4</th>\n",
       "      <td>4</td>\n",
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       "      <td>34e8add9-0206-47fd-a501-037b994650a2</td>\n",
       "      <td>disgust</td>\n",
       "      <td>2021-01-06 19:13:01</td>\n",
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       "   Unnamed: 0                            Content ID  \\\n",
       "0           0  97522e57-d9ab-4bd6-97bf-c24d952602d2   \n",
       "1           1  97522e57-d9ab-4bd6-97bf-c24d952602d2   \n",
       "2           2  97522e57-d9ab-4bd6-97bf-c24d952602d2   \n",
       "3           3  97522e57-d9ab-4bd6-97bf-c24d952602d2   \n",
       "4           4  97522e57-d9ab-4bd6-97bf-c24d952602d2   \n",
       "\n",
       "                                User ID     Type             Datetime  \n",
       "0                                   NaN      NaN  2021-04-22 15:17:15  \n",
       "1  5d454588-283d-459d-915d-c48a2cb4c27f  disgust  2020-11-07 09:43:50  \n",
       "2  92b87fa5-f271-43e0-af66-84fac21052e6  dislike  2021-06-17 12:22:51  \n",
       "3  163daa38-8b77-48c9-9af6-37a6c1447ac2   scared  2021-04-18 05:13:58  \n",
       "4  34e8add9-0206-47fd-a501-037b994650a2  disgust  2021-01-06 19:13:01  "
      ]
     },
     "execution_count": 163,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "reactions.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>Type</th>\n",
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       "      <td>disgust</td>\n",
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       "      <th>3</th>\n",
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       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>interested</td>\n",
       "      <td>positive</td>\n",
       "      <td>30</td>\n",
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       "   Unnamed: 0        Type Sentiment  Score\n",
       "0           0       heart  positive     60\n",
       "1           1        want  positive     70\n",
       "2           2     disgust  negative      0\n",
       "3           3        hate  negative      5\n",
       "4           4  interested  positive     30"
      ]
     },
     "execution_count": 164,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "reaction_type.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Select columns of interest"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "metadata": {},
   "outputs": [],
   "source": [
    "my_content = content[['Content ID', 'User ID', 'Type', 'Category']]\n",
    "my_reactions = reactions[['Content ID', 'Type', 'Datetime']]\n",
    "my_reaction_type = reaction_type[['Type', 'Sentiment', 'Score']]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Adjusting Category strings (lower case and removing quotes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "metadata": {},
   "outputs": [],
   "source": [
    "my_content['Category'] = my_content['Category'].str.lower()\n",
    "my_content['Category'] = my_content['Category'].str.replace(r'\"', \"\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Count Content, Users, Type of Content and Category"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Content ID    1000\n",
       "User ID        446\n",
       "Type             4\n",
       "Category        16\n",
       "dtype: int64"
      ]
     },
     "execution_count": 167,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "my_content.nunique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### List content by categories"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Category\n",
       "animals            72\n",
       "cooking            61\n",
       "culture            67\n",
       "dogs               58\n",
       "education          59\n",
       "fitness            66\n",
       "food               64\n",
       "healthy eating     62\n",
       "public speaking    50\n",
       "science            68\n",
       "soccer             64\n",
       "studying           58\n",
       "technology         73\n",
       "tennis             59\n",
       "travel             69\n",
       "veganism           50\n",
       "Name: Content ID, dtype: int64"
      ]
     },
     "execution_count": 168,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "my_content.groupby('Category')[\"Content ID\"].count()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Merge Reactions and Content"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "metadata": {},
   "outputs": [
    {
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       "      <td>photo</td>\n",
       "      <td>studying</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>97522e57-d9ab-4bd6-97bf-c24d952602d2</td>\n",
       "      <td>disgust</td>\n",
       "      <td>2020-11-07 09:43:50</td>\n",
       "      <td>8d3cd87d-8a31-4935-9a4f-b319bfe05f31</td>\n",
       "      <td>photo</td>\n",
       "      <td>studying</td>\n",
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       "      <th>2</th>\n",
       "      <td>97522e57-d9ab-4bd6-97bf-c24d952602d2</td>\n",
       "      <td>dislike</td>\n",
       "      <td>2021-06-17 12:22:51</td>\n",
       "      <td>8d3cd87d-8a31-4935-9a4f-b319bfe05f31</td>\n",
       "      <td>photo</td>\n",
       "      <td>studying</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>97522e57-d9ab-4bd6-97bf-c24d952602d2</td>\n",
       "      <td>scared</td>\n",
       "      <td>2021-04-18 05:13:58</td>\n",
       "      <td>8d3cd87d-8a31-4935-9a4f-b319bfe05f31</td>\n",
       "      <td>photo</td>\n",
       "      <td>studying</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>97522e57-d9ab-4bd6-97bf-c24d952602d2</td>\n",
       "      <td>disgust</td>\n",
       "      <td>2021-01-06 19:13:01</td>\n",
       "      <td>8d3cd87d-8a31-4935-9a4f-b319bfe05f31</td>\n",
       "      <td>photo</td>\n",
       "      <td>studying</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                             Content ID   Type_x             Datetime  \\\n",
       "0  97522e57-d9ab-4bd6-97bf-c24d952602d2      NaN  2021-04-22 15:17:15   \n",
       "1  97522e57-d9ab-4bd6-97bf-c24d952602d2  disgust  2020-11-07 09:43:50   \n",
       "2  97522e57-d9ab-4bd6-97bf-c24d952602d2  dislike  2021-06-17 12:22:51   \n",
       "3  97522e57-d9ab-4bd6-97bf-c24d952602d2   scared  2021-04-18 05:13:58   \n",
       "4  97522e57-d9ab-4bd6-97bf-c24d952602d2  disgust  2021-01-06 19:13:01   \n",
       "\n",
       "                                User ID Type_y  Category  \n",
       "0  8d3cd87d-8a31-4935-9a4f-b319bfe05f31  photo  studying  \n",
       "1  8d3cd87d-8a31-4935-9a4f-b319bfe05f31  photo  studying  \n",
       "2  8d3cd87d-8a31-4935-9a4f-b319bfe05f31  photo  studying  \n",
       "3  8d3cd87d-8a31-4935-9a4f-b319bfe05f31  photo  studying  \n",
       "4  8d3cd87d-8a31-4935-9a4f-b319bfe05f31  photo  studying  "
      ]
     },
     "execution_count": 169,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "my_data = pd.merge(my_reactions, my_content, on='Content ID', how=\"left\")\n",
    "my_data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Rename columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 170,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Content ID</th>\n",
       "      <th>Reaction_Type</th>\n",
       "      <th>Datetime</th>\n",
       "      <th>User_ID_(Post_owner)</th>\n",
       "      <th>Content_Type</th>\n",
       "      <th>Category</th>\n",
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       "      <th>0</th>\n",
       "      <td>97522e57-d9ab-4bd6-97bf-c24d952602d2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2021-04-22 15:17:15</td>\n",
       "      <td>8d3cd87d-8a31-4935-9a4f-b319bfe05f31</td>\n",
       "      <td>photo</td>\n",
       "      <td>studying</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>97522e57-d9ab-4bd6-97bf-c24d952602d2</td>\n",
       "      <td>disgust</td>\n",
       "      <td>2020-11-07 09:43:50</td>\n",
       "      <td>8d3cd87d-8a31-4935-9a4f-b319bfe05f31</td>\n",
       "      <td>photo</td>\n",
       "      <td>studying</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>97522e57-d9ab-4bd6-97bf-c24d952602d2</td>\n",
       "      <td>dislike</td>\n",
       "      <td>2021-06-17 12:22:51</td>\n",
       "      <td>8d3cd87d-8a31-4935-9a4f-b319bfe05f31</td>\n",
       "      <td>photo</td>\n",
       "      <td>studying</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>97522e57-d9ab-4bd6-97bf-c24d952602d2</td>\n",
       "      <td>scared</td>\n",
       "      <td>2021-04-18 05:13:58</td>\n",
       "      <td>8d3cd87d-8a31-4935-9a4f-b319bfe05f31</td>\n",
       "      <td>photo</td>\n",
       "      <td>studying</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>97522e57-d9ab-4bd6-97bf-c24d952602d2</td>\n",
       "      <td>disgust</td>\n",
       "      <td>2021-01-06 19:13:01</td>\n",
       "      <td>8d3cd87d-8a31-4935-9a4f-b319bfe05f31</td>\n",
       "      <td>photo</td>\n",
       "      <td>studying</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                             Content ID Reaction_Type             Datetime  \\\n",
       "0  97522e57-d9ab-4bd6-97bf-c24d952602d2           NaN  2021-04-22 15:17:15   \n",
       "1  97522e57-d9ab-4bd6-97bf-c24d952602d2       disgust  2020-11-07 09:43:50   \n",
       "2  97522e57-d9ab-4bd6-97bf-c24d952602d2       dislike  2021-06-17 12:22:51   \n",
       "3  97522e57-d9ab-4bd6-97bf-c24d952602d2        scared  2021-04-18 05:13:58   \n",
       "4  97522e57-d9ab-4bd6-97bf-c24d952602d2       disgust  2021-01-06 19:13:01   \n",
       "\n",
       "                   User_ID_(Post_owner) Content_Type  Category  \n",
       "0  8d3cd87d-8a31-4935-9a4f-b319bfe05f31        photo  studying  \n",
       "1  8d3cd87d-8a31-4935-9a4f-b319bfe05f31        photo  studying  \n",
       "2  8d3cd87d-8a31-4935-9a4f-b319bfe05f31        photo  studying  \n",
       "3  8d3cd87d-8a31-4935-9a4f-b319bfe05f31        photo  studying  \n",
       "4  8d3cd87d-8a31-4935-9a4f-b319bfe05f31        photo  studying  "
      ]
     },
     "execution_count": 170,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "my_data.rename(columns = {'Type_x':'Reaction_Type', 'Type_x':'Reaction_Type', 'User ID':'User_ID_(Post_owner)', 'Type_y':'Content_Type'}, inplace = True)\n",
    "my_data.head()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Add Reactions Types"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 171,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>Content ID</th>\n",
       "      <th>Reaction_Type</th>\n",
       "      <th>Datetime</th>\n",
       "      <th>User_ID_(Post_owner)</th>\n",
       "      <th>Content_Type</th>\n",
       "      <th>Category</th>\n",
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       "      <th>0</th>\n",
       "      <td>97522e57-d9ab-4bd6-97bf-c24d952602d2</td>\n",
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       "      <td>2021-04-22 15:17:15</td>\n",
       "      <td>8d3cd87d-8a31-4935-9a4f-b319bfe05f31</td>\n",
       "      <td>photo</td>\n",
       "      <td>studying</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>97522e57-d9ab-4bd6-97bf-c24d952602d2</td>\n",
       "      <td>disgust</td>\n",
       "      <td>2020-11-07 09:43:50</td>\n",
       "      <td>8d3cd87d-8a31-4935-9a4f-b319bfe05f31</td>\n",
       "      <td>photo</td>\n",
       "      <td>studying</td>\n",
       "      <td>disgust</td>\n",
       "      <td>negative</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>97522e57-d9ab-4bd6-97bf-c24d952602d2</td>\n",
       "      <td>dislike</td>\n",
       "      <td>2021-06-17 12:22:51</td>\n",
       "      <td>8d3cd87d-8a31-4935-9a4f-b319bfe05f31</td>\n",
       "      <td>photo</td>\n",
       "      <td>studying</td>\n",
       "      <td>dislike</td>\n",
       "      <td>negative</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>97522e57-d9ab-4bd6-97bf-c24d952602d2</td>\n",
       "      <td>scared</td>\n",
       "      <td>2021-04-18 05:13:58</td>\n",
       "      <td>8d3cd87d-8a31-4935-9a4f-b319bfe05f31</td>\n",
       "      <td>photo</td>\n",
       "      <td>studying</td>\n",
       "      <td>scared</td>\n",
       "      <td>negative</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>97522e57-d9ab-4bd6-97bf-c24d952602d2</td>\n",
       "      <td>disgust</td>\n",
       "      <td>2021-01-06 19:13:01</td>\n",
       "      <td>8d3cd87d-8a31-4935-9a4f-b319bfe05f31</td>\n",
       "      <td>photo</td>\n",
       "      <td>studying</td>\n",
       "      <td>disgust</td>\n",
       "      <td>negative</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25548</th>\n",
       "      <td>75d6b589-7fae-4a6d-b0d0-752845150e56</td>\n",
       "      <td>dislike</td>\n",
       "      <td>2020-06-27 09:46:48</td>\n",
       "      <td>b8c653b5-0118-4d7e-9bde-07c2de90f0ff</td>\n",
       "      <td>audio</td>\n",
       "      <td>technology</td>\n",
       "      <td>dislike</td>\n",
       "      <td>negative</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25549</th>\n",
       "      <td>75d6b589-7fae-4a6d-b0d0-752845150e56</td>\n",
       "      <td>intrigued</td>\n",
       "      <td>2021-02-16 17:17:02</td>\n",
       "      <td>b8c653b5-0118-4d7e-9bde-07c2de90f0ff</td>\n",
       "      <td>audio</td>\n",
       "      <td>technology</td>\n",
       "      <td>intrigued</td>\n",
       "      <td>positive</td>\n",
       "      <td>45.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25550</th>\n",
       "      <td>75d6b589-7fae-4a6d-b0d0-752845150e56</td>\n",
       "      <td>interested</td>\n",
       "      <td>2020-09-12 03:54:58</td>\n",
       "      <td>b8c653b5-0118-4d7e-9bde-07c2de90f0ff</td>\n",
       "      <td>audio</td>\n",
       "      <td>technology</td>\n",
       "      <td>interested</td>\n",
       "      <td>positive</td>\n",
       "      <td>30.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25551</th>\n",
       "      <td>75d6b589-7fae-4a6d-b0d0-752845150e56</td>\n",
       "      <td>worried</td>\n",
       "      <td>2020-11-04 20:08:31</td>\n",
       "      <td>b8c653b5-0118-4d7e-9bde-07c2de90f0ff</td>\n",
       "      <td>audio</td>\n",
       "      <td>technology</td>\n",
       "      <td>worried</td>\n",
       "      <td>negative</td>\n",
       "      <td>12.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25552</th>\n",
       "      <td>75d6b589-7fae-4a6d-b0d0-752845150e56</td>\n",
       "      <td>cherish</td>\n",
       "      <td>2021-01-04 04:55:11</td>\n",
       "      <td>b8c653b5-0118-4d7e-9bde-07c2de90f0ff</td>\n",
       "      <td>audio</td>\n",
       "      <td>technology</td>\n",
       "      <td>cherish</td>\n",
       "      <td>positive</td>\n",
       "      <td>70.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>25553 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                 Content ID Reaction_Type  \\\n",
       "0      97522e57-d9ab-4bd6-97bf-c24d952602d2           NaN   \n",
       "1      97522e57-d9ab-4bd6-97bf-c24d952602d2       disgust   \n",
       "2      97522e57-d9ab-4bd6-97bf-c24d952602d2       dislike   \n",
       "3      97522e57-d9ab-4bd6-97bf-c24d952602d2        scared   \n",
       "4      97522e57-d9ab-4bd6-97bf-c24d952602d2       disgust   \n",
       "...                                     ...           ...   \n",
       "25548  75d6b589-7fae-4a6d-b0d0-752845150e56       dislike   \n",
       "25549  75d6b589-7fae-4a6d-b0d0-752845150e56     intrigued   \n",
       "25550  75d6b589-7fae-4a6d-b0d0-752845150e56    interested   \n",
       "25551  75d6b589-7fae-4a6d-b0d0-752845150e56       worried   \n",
       "25552  75d6b589-7fae-4a6d-b0d0-752845150e56       cherish   \n",
       "\n",
       "                  Datetime                  User_ID_(Post_owner) Content_Type  \\\n",
       "0      2021-04-22 15:17:15  8d3cd87d-8a31-4935-9a4f-b319bfe05f31        photo   \n",
       "1      2020-11-07 09:43:50  8d3cd87d-8a31-4935-9a4f-b319bfe05f31        photo   \n",
       "2      2021-06-17 12:22:51  8d3cd87d-8a31-4935-9a4f-b319bfe05f31        photo   \n",
       "3      2021-04-18 05:13:58  8d3cd87d-8a31-4935-9a4f-b319bfe05f31        photo   \n",
       "4      2021-01-06 19:13:01  8d3cd87d-8a31-4935-9a4f-b319bfe05f31        photo   \n",
       "...                    ...                                   ...          ...   \n",
       "25548  2020-06-27 09:46:48  b8c653b5-0118-4d7e-9bde-07c2de90f0ff        audio   \n",
       "25549  2021-02-16 17:17:02  b8c653b5-0118-4d7e-9bde-07c2de90f0ff        audio   \n",
       "25550  2020-09-12 03:54:58  b8c653b5-0118-4d7e-9bde-07c2de90f0ff        audio   \n",
       "25551  2020-11-04 20:08:31  b8c653b5-0118-4d7e-9bde-07c2de90f0ff        audio   \n",
       "25552  2021-01-04 04:55:11  b8c653b5-0118-4d7e-9bde-07c2de90f0ff        audio   \n",
       "\n",
       "         Category        Type Sentiment  Score  \n",
       "0        studying         NaN       NaN    NaN  \n",
       "1        studying     disgust  negative    0.0  \n",
       "2        studying     dislike  negative   10.0  \n",
       "3        studying      scared  negative   15.0  \n",
       "4        studying     disgust  negative    0.0  \n",
       "...           ...         ...       ...    ...  \n",
       "25548  technology     dislike  negative   10.0  \n",
       "25549  technology   intrigued  positive   45.0  \n",
       "25550  technology  interested  positive   30.0  \n",
       "25551  technology     worried  negative   12.0  \n",
       "25552  technology     cherish  positive   70.0  \n",
       "\n",
       "[25553 rows x 9 columns]"
      ]
     },
     "execution_count": 171,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "my_data = pd.merge(my_data, my_reaction_type, left_on=\"Reaction_Type\", right_on=\"Type\", how=\"left\")\n",
    "my_data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Delete duplicated column (Type)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>Content ID</th>\n",
       "      <th>Reaction_Type</th>\n",
       "      <th>Datetime</th>\n",
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       "      <th>0</th>\n",
       "      <td>97522e57-d9ab-4bd6-97bf-c24d952602d2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2021-04-22 15:17:15</td>\n",
       "      <td>8d3cd87d-8a31-4935-9a4f-b319bfe05f31</td>\n",
       "      <td>photo</td>\n",
       "      <td>studying</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>97522e57-d9ab-4bd6-97bf-c24d952602d2</td>\n",
       "      <td>disgust</td>\n",
       "      <td>2020-11-07 09:43:50</td>\n",
       "      <td>8d3cd87d-8a31-4935-9a4f-b319bfe05f31</td>\n",
       "      <td>photo</td>\n",
       "      <td>studying</td>\n",
       "      <td>negative</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>97522e57-d9ab-4bd6-97bf-c24d952602d2</td>\n",
       "      <td>dislike</td>\n",
       "      <td>2021-06-17 12:22:51</td>\n",
       "      <td>8d3cd87d-8a31-4935-9a4f-b319bfe05f31</td>\n",
       "      <td>photo</td>\n",
       "      <td>studying</td>\n",
       "      <td>negative</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>97522e57-d9ab-4bd6-97bf-c24d952602d2</td>\n",
       "      <td>scared</td>\n",
       "      <td>2021-04-18 05:13:58</td>\n",
       "      <td>8d3cd87d-8a31-4935-9a4f-b319bfe05f31</td>\n",
       "      <td>photo</td>\n",
       "      <td>studying</td>\n",
       "      <td>negative</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>97522e57-d9ab-4bd6-97bf-c24d952602d2</td>\n",
       "      <td>disgust</td>\n",
       "      <td>2021-01-06 19:13:01</td>\n",
       "      <td>8d3cd87d-8a31-4935-9a4f-b319bfe05f31</td>\n",
       "      <td>photo</td>\n",
       "      <td>studying</td>\n",
       "      <td>negative</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                             Content ID Reaction_Type             Datetime  \\\n",
       "0  97522e57-d9ab-4bd6-97bf-c24d952602d2           NaN  2021-04-22 15:17:15   \n",
       "1  97522e57-d9ab-4bd6-97bf-c24d952602d2       disgust  2020-11-07 09:43:50   \n",
       "2  97522e57-d9ab-4bd6-97bf-c24d952602d2       dislike  2021-06-17 12:22:51   \n",
       "3  97522e57-d9ab-4bd6-97bf-c24d952602d2        scared  2021-04-18 05:13:58   \n",
       "4  97522e57-d9ab-4bd6-97bf-c24d952602d2       disgust  2021-01-06 19:13:01   \n",
       "\n",
       "                   User_ID_(Post_owner) Content_Type  Category Sentiment  \\\n",
       "0  8d3cd87d-8a31-4935-9a4f-b319bfe05f31        photo  studying       NaN   \n",
       "1  8d3cd87d-8a31-4935-9a4f-b319bfe05f31        photo  studying  negative   \n",
       "2  8d3cd87d-8a31-4935-9a4f-b319bfe05f31        photo  studying  negative   \n",
       "3  8d3cd87d-8a31-4935-9a4f-b319bfe05f31        photo  studying  negative   \n",
       "4  8d3cd87d-8a31-4935-9a4f-b319bfe05f31        photo  studying  negative   \n",
       "\n",
       "   Score  \n",
       "0    NaN  \n",
       "1    0.0  \n",
       "2   10.0  \n",
       "3   15.0  \n",
       "4    0.0  "
      ]
     },
     "execution_count": 172,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "my_data = my_data.drop('Type', 1)\n",
    "my_data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Clear data (delete invalid values)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Content ID                0\n",
       "Reaction_Type           980\n",
       "Datetime                  0\n",
       "User_ID_(Post_owner)      0\n",
       "Content_Type              0\n",
       "Category                  0\n",
       "Sentiment               980\n",
       "Score                   980\n",
       "dtype: int64"
      ]
     },
     "execution_count": 173,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check for invalid value\n",
    "my_data.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Delete NaN\n",
    "my_data.dropna(subset = [\"Score\"], inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Content ID              0\n",
       "Reaction_Type           0\n",
       "Datetime                0\n",
       "User_ID_(Post_owner)    0\n",
       "Content_Type            0\n",
       "Category                0\n",
       "Sentiment               0\n",
       "Score                   0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 175,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check if all invalid value was deleted\n",
    "my_data.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Check final DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "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>Content ID</th>\n",
       "      <th>Reaction_Type</th>\n",
       "      <th>Datetime</th>\n",
       "      <th>User_ID_(Post_owner)</th>\n",
       "      <th>Content_Type</th>\n",
       "      <th>Category</th>\n",
       "      <th>Sentiment</th>\n",
       "      <th>Score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>97522e57-d9ab-4bd6-97bf-c24d952602d2</td>\n",
       "      <td>disgust</td>\n",
       "      <td>2020-11-07 09:43:50</td>\n",
       "      <td>8d3cd87d-8a31-4935-9a4f-b319bfe05f31</td>\n",
       "      <td>photo</td>\n",
       "      <td>studying</td>\n",
       "      <td>negative</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>97522e57-d9ab-4bd6-97bf-c24d952602d2</td>\n",
       "      <td>dislike</td>\n",
       "      <td>2021-06-17 12:22:51</td>\n",
       "      <td>8d3cd87d-8a31-4935-9a4f-b319bfe05f31</td>\n",
       "      <td>photo</td>\n",
       "      <td>studying</td>\n",
       "      <td>negative</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>97522e57-d9ab-4bd6-97bf-c24d952602d2</td>\n",
       "      <td>scared</td>\n",
       "      <td>2021-04-18 05:13:58</td>\n",
       "      <td>8d3cd87d-8a31-4935-9a4f-b319bfe05f31</td>\n",
       "      <td>photo</td>\n",
       "      <td>studying</td>\n",
       "      <td>negative</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>97522e57-d9ab-4bd6-97bf-c24d952602d2</td>\n",
       "      <td>disgust</td>\n",
       "      <td>2021-01-06 19:13:01</td>\n",
       "      <td>8d3cd87d-8a31-4935-9a4f-b319bfe05f31</td>\n",
       "      <td>photo</td>\n",
       "      <td>studying</td>\n",
       "      <td>negative</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>97522e57-d9ab-4bd6-97bf-c24d952602d2</td>\n",
       "      <td>interested</td>\n",
       "      <td>2020-08-23 12:25:58</td>\n",
       "      <td>8d3cd87d-8a31-4935-9a4f-b319bfe05f31</td>\n",
       "      <td>photo</td>\n",
       "      <td>studying</td>\n",
       "      <td>positive</td>\n",
       "      <td>30.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25548</th>\n",
       "      <td>75d6b589-7fae-4a6d-b0d0-752845150e56</td>\n",
       "      <td>dislike</td>\n",
       "      <td>2020-06-27 09:46:48</td>\n",
       "      <td>b8c653b5-0118-4d7e-9bde-07c2de90f0ff</td>\n",
       "      <td>audio</td>\n",
       "      <td>technology</td>\n",
       "      <td>negative</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25549</th>\n",
       "      <td>75d6b589-7fae-4a6d-b0d0-752845150e56</td>\n",
       "      <td>intrigued</td>\n",
       "      <td>2021-02-16 17:17:02</td>\n",
       "      <td>b8c653b5-0118-4d7e-9bde-07c2de90f0ff</td>\n",
       "      <td>audio</td>\n",
       "      <td>technology</td>\n",
       "      <td>positive</td>\n",
       "      <td>45.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25550</th>\n",
       "      <td>75d6b589-7fae-4a6d-b0d0-752845150e56</td>\n",
       "      <td>interested</td>\n",
       "      <td>2020-09-12 03:54:58</td>\n",
       "      <td>b8c653b5-0118-4d7e-9bde-07c2de90f0ff</td>\n",
       "      <td>audio</td>\n",
       "      <td>technology</td>\n",
       "      <td>positive</td>\n",
       "      <td>30.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25551</th>\n",
       "      <td>75d6b589-7fae-4a6d-b0d0-752845150e56</td>\n",
       "      <td>worried</td>\n",
       "      <td>2020-11-04 20:08:31</td>\n",
       "      <td>b8c653b5-0118-4d7e-9bde-07c2de90f0ff</td>\n",
       "      <td>audio</td>\n",
       "      <td>technology</td>\n",
       "      <td>negative</td>\n",
       "      <td>12.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25552</th>\n",
       "      <td>75d6b589-7fae-4a6d-b0d0-752845150e56</td>\n",
       "      <td>cherish</td>\n",
       "      <td>2021-01-04 04:55:11</td>\n",
       "      <td>b8c653b5-0118-4d7e-9bde-07c2de90f0ff</td>\n",
       "      <td>audio</td>\n",
       "      <td>technology</td>\n",
       "      <td>positive</td>\n",
       "      <td>70.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>24573 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                 Content ID Reaction_Type  \\\n",
       "1      97522e57-d9ab-4bd6-97bf-c24d952602d2       disgust   \n",
       "2      97522e57-d9ab-4bd6-97bf-c24d952602d2       dislike   \n",
       "3      97522e57-d9ab-4bd6-97bf-c24d952602d2        scared   \n",
       "4      97522e57-d9ab-4bd6-97bf-c24d952602d2       disgust   \n",
       "5      97522e57-d9ab-4bd6-97bf-c24d952602d2    interested   \n",
       "...                                     ...           ...   \n",
       "25548  75d6b589-7fae-4a6d-b0d0-752845150e56       dislike   \n",
       "25549  75d6b589-7fae-4a6d-b0d0-752845150e56     intrigued   \n",
       "25550  75d6b589-7fae-4a6d-b0d0-752845150e56    interested   \n",
       "25551  75d6b589-7fae-4a6d-b0d0-752845150e56       worried   \n",
       "25552  75d6b589-7fae-4a6d-b0d0-752845150e56       cherish   \n",
       "\n",
       "                  Datetime                  User_ID_(Post_owner) Content_Type  \\\n",
       "1      2020-11-07 09:43:50  8d3cd87d-8a31-4935-9a4f-b319bfe05f31        photo   \n",
       "2      2021-06-17 12:22:51  8d3cd87d-8a31-4935-9a4f-b319bfe05f31        photo   \n",
       "3      2021-04-18 05:13:58  8d3cd87d-8a31-4935-9a4f-b319bfe05f31        photo   \n",
       "4      2021-01-06 19:13:01  8d3cd87d-8a31-4935-9a4f-b319bfe05f31        photo   \n",
       "5      2020-08-23 12:25:58  8d3cd87d-8a31-4935-9a4f-b319bfe05f31        photo   \n",
       "...                    ...                                   ...          ...   \n",
       "25548  2020-06-27 09:46:48  b8c653b5-0118-4d7e-9bde-07c2de90f0ff        audio   \n",
       "25549  2021-02-16 17:17:02  b8c653b5-0118-4d7e-9bde-07c2de90f0ff        audio   \n",
       "25550  2020-09-12 03:54:58  b8c653b5-0118-4d7e-9bde-07c2de90f0ff        audio   \n",
       "25551  2020-11-04 20:08:31  b8c653b5-0118-4d7e-9bde-07c2de90f0ff        audio   \n",
       "25552  2021-01-04 04:55:11  b8c653b5-0118-4d7e-9bde-07c2de90f0ff        audio   \n",
       "\n",
       "         Category Sentiment  Score  \n",
       "1        studying  negative    0.0  \n",
       "2        studying  negative   10.0  \n",
       "3        studying  negative   15.0  \n",
       "4        studying  negative    0.0  \n",
       "5        studying  positive   30.0  \n",
       "...           ...       ...    ...  \n",
       "25548  technology  negative   10.0  \n",
       "25549  technology  positive   45.0  \n",
       "25550  technology  positive   30.0  \n",
       "25551  technology  negative   12.0  \n",
       "25552  technology  positive   70.0  \n",
       "\n",
       "[24573 rows x 8 columns]"
      ]
     },
     "execution_count": 176,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "my_data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Export Dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 177,
   "metadata": {},
   "outputs": [],
   "source": [
    "my_data.to_csv('/Users/deborabastos/Documents/3.DataScience/accenture_data_analytics/data/my_data.csv', index=False)"
   ]
  }
 ],
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