Cleaned_Tweets.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import nltk\n",
    "import string"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(\"Concat_ML_Data/Election_2008.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tweet</th>\n",
       "      <th>replies_count</th>\n",
       "      <th>retweets_count</th>\n",
       "      <th>likes_count</th>\n",
       "      <th>candidate</th>\n",
       "      <th>tweet_length</th>\n",
       "      <th>Subjectivity</th>\n",
       "      <th>Polarity</th>\n",
       "      <th>Sentiment</th>\n",
       "      <th>year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Working on public service spots for Barack Oba...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Barack</td>\n",
       "      <td>12</td>\n",
       "      <td>0.533333</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>Positive</td>\n",
       "      <td>2008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>An lise candidatos precisam de pol tica regula...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Barack</td>\n",
       "      <td>16</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>2008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Barack Obama LIVE Barack and Joe in Fredricksb...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Barack</td>\n",
       "      <td>9</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.136364</td>\n",
       "      <td>Positive</td>\n",
       "      <td>2008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>kid keeps saying interchangeably my name is ba...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Barack</td>\n",
       "      <td>18</td>\n",
       "      <td>0.200000</td>\n",
       "      <td>-0.100000</td>\n",
       "      <td>Negative</td>\n",
       "      <td>2008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>The media darling Barack Obama</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Barack</td>\n",
       "      <td>5</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>2008</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                               tweet  replies_count  \\\n",
       "0  Working on public service spots for Barack Oba...              0   \n",
       "1  An lise candidatos precisam de pol tica regula...              0   \n",
       "2  Barack Obama LIVE Barack and Joe in Fredricksb...              0   \n",
       "3  kid keeps saying interchangeably my name is ba...              0   \n",
       "4                    The media darling Barack Obama               0   \n",
       "\n",
       "   retweets_count  likes_count candidate  tweet_length  Subjectivity  \\\n",
       "0               0            0    Barack            12      0.533333   \n",
       "1               0            0    Barack            16      0.000000   \n",
       "2               0            0    Barack             9      0.500000   \n",
       "3               0            0    Barack            18      0.200000   \n",
       "4               0            0    Barack             5      0.000000   \n",
       "\n",
       "   Polarity Sentiment  year  \n",
       "0  0.500000  Positive  2008  \n",
       "1  0.000000   Neutral  2008  \n",
       "2  0.136364  Positive  2008  \n",
       "3 -0.100000  Negative  2008  \n",
       "4  0.000000   Neutral  2008  "
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Keeping the tweet columns for both datasets\n",
    "# df=pd.DataFrame(df, columns=['tweet', 'candidate'])\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Creating Function to tokenize words in tweet columns\n",
    "def tokenized_words(row):\n",
    "    tweet = row['tweet']\n",
    "    tokens = nltk.word_tokenize(tweet)\n",
    "    token_wds = [word for word in tokens if word.isalpha()]\n",
    "    return token_wds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tweet</th>\n",
       "      <th>replies_count</th>\n",
       "      <th>retweets_count</th>\n",
       "      <th>likes_count</th>\n",
       "      <th>candidate</th>\n",
       "      <th>tweet_length</th>\n",
       "      <th>Subjectivity</th>\n",
       "      <th>Polarity</th>\n",
       "      <th>Sentiment</th>\n",
       "      <th>year</th>\n",
       "      <th>t_words</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Working on public service spots for Barack Oba...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Barack</td>\n",
       "      <td>12</td>\n",
       "      <td>0.533333</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>Positive</td>\n",
       "      <td>2008</td>\n",
       "      <td>[Working, on, public, service, spots, for, Bar...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>An lise candidatos precisam de pol tica regula...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Barack</td>\n",
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       "      <td>0.000000</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>2008</td>\n",
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       "      <th>2</th>\n",
       "      <td>Barack Obama LIVE Barack and Joe in Fredricksb...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Barack</td>\n",
       "      <td>9</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.136364</td>\n",
       "      <td>Positive</td>\n",
       "      <td>2008</td>\n",
       "      <td>[Barack, Obama, LIVE, Barack, and, Joe, in, Fr...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>kid keeps saying interchangeably my name is ba...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Barack</td>\n",
       "      <td>18</td>\n",
       "      <td>0.200000</td>\n",
       "      <td>-0.100000</td>\n",
       "      <td>Negative</td>\n",
       "      <td>2008</td>\n",
       "      <td>[kid, keeps, saying, interchangeably, my, name...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>The media darling Barack Obama</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Barack</td>\n",
       "      <td>5</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>2008</td>\n",
       "      <td>[The, media, darling, Barack, Obama]</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                               tweet  replies_count  \\\n",
       "0  Working on public service spots for Barack Oba...              0   \n",
       "1  An lise candidatos precisam de pol tica regula...              0   \n",
       "2  Barack Obama LIVE Barack and Joe in Fredricksb...              0   \n",
       "3  kid keeps saying interchangeably my name is ba...              0   \n",
       "4                    The media darling Barack Obama               0   \n",
       "\n",
       "   retweets_count  likes_count candidate  tweet_length  Subjectivity  \\\n",
       "0               0            0    Barack            12      0.533333   \n",
       "1               0            0    Barack            16      0.000000   \n",
       "2               0            0    Barack             9      0.500000   \n",
       "3               0            0    Barack            18      0.200000   \n",
       "4               0            0    Barack             5      0.000000   \n",
       "\n",
       "   Polarity Sentiment  year                                            t_words  \n",
       "0  0.500000  Positive  2008  [Working, on, public, service, spots, for, Bar...  \n",
       "1  0.000000   Neutral  2008  [An, lise, candidatos, precisam, de, pol, tica...  \n",
       "2  0.136364  Positive  2008  [Barack, Obama, LIVE, Barack, and, Joe, in, Fr...  \n",
       "3 -0.100000  Negative  2008  [kid, keeps, saying, interchangeably, my, name...  \n",
       "4  0.000000   Neutral  2008               [The, media, darling, Barack, Obama]  "
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['t_words']=df.apply(tokenized_words, axis=1)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "from nltk.corpus import stopwords\n",
    "stops = set(stopwords.words(\"english\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Creating Function to remove stop words in tweet column\n",
    "def remove_stop_wds(row):\n",
    "    t_words=row['t_words']\n",
    "    meaningful_words = [word for word in t_words if not word in stops]\n",
    "    return (meaningful_words)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tweet</th>\n",
       "      <th>replies_count</th>\n",
       "      <th>retweets_count</th>\n",
       "      <th>likes_count</th>\n",
       "      <th>candidate</th>\n",
       "      <th>tweet_length</th>\n",
       "      <th>Subjectivity</th>\n",
       "      <th>Polarity</th>\n",
       "      <th>Sentiment</th>\n",
       "      <th>year</th>\n",
       "      <th>t_words</th>\n",
       "      <th>final_wds</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Working on public service spots for Barack Oba...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Barack</td>\n",
       "      <td>12</td>\n",
       "      <td>0.533333</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>Positive</td>\n",
       "      <td>2008</td>\n",
       "      <td>[Working, on, public, service, spots, for, Bar...</td>\n",
       "      <td>[Working, public, service, spots, Barack, Obam...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>An lise candidatos precisam de pol tica regula...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Barack</td>\n",
       "      <td>16</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>2008</td>\n",
       "      <td>[An, lise, candidatos, precisam, de, pol, tica...</td>\n",
       "      <td>[An, lise, candidatos, precisam, de, pol, tica...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Barack Obama LIVE Barack and Joe in Fredricksb...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Barack</td>\n",
       "      <td>9</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.136364</td>\n",
       "      <td>Positive</td>\n",
       "      <td>2008</td>\n",
       "      <td>[Barack, Obama, LIVE, Barack, and, Joe, in, Fr...</td>\n",
       "      <td>[Barack, Obama, LIVE, Barack, Joe, Fredricksbu...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>kid keeps saying interchangeably my name is ba...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Barack</td>\n",
       "      <td>18</td>\n",
       "      <td>0.200000</td>\n",
       "      <td>-0.100000</td>\n",
       "      <td>Negative</td>\n",
       "      <td>2008</td>\n",
       "      <td>[kid, keeps, saying, interchangeably, my, name...</td>\n",
       "      <td>[kid, keeps, saying, interchangeably, name, ba...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>The media darling Barack Obama</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Barack</td>\n",
       "      <td>5</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>2008</td>\n",
       "      <td>[The, media, darling, Barack, Obama]</td>\n",
       "      <td>[The, media, darling, Barack, Obama]</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                               tweet  replies_count  \\\n",
       "0  Working on public service spots for Barack Oba...              0   \n",
       "1  An lise candidatos precisam de pol tica regula...              0   \n",
       "2  Barack Obama LIVE Barack and Joe in Fredricksb...              0   \n",
       "3  kid keeps saying interchangeably my name is ba...              0   \n",
       "4                    The media darling Barack Obama               0   \n",
       "\n",
       "   retweets_count  likes_count candidate  tweet_length  Subjectivity  \\\n",
       "0               0            0    Barack            12      0.533333   \n",
       "1               0            0    Barack            16      0.000000   \n",
       "2               0            0    Barack             9      0.500000   \n",
       "3               0            0    Barack            18      0.200000   \n",
       "4               0            0    Barack             5      0.000000   \n",
       "\n",
       "   Polarity Sentiment  year  \\\n",
       "0  0.500000  Positive  2008   \n",
       "1  0.000000   Neutral  2008   \n",
       "2  0.136364  Positive  2008   \n",
       "3 -0.100000  Negative  2008   \n",
       "4  0.000000   Neutral  2008   \n",
       "\n",
       "                                             t_words  \\\n",
       "0  [Working, on, public, service, spots, for, Bar...   \n",
       "1  [An, lise, candidatos, precisam, de, pol, tica...   \n",
       "2  [Barack, Obama, LIVE, Barack, and, Joe, in, Fr...   \n",
       "3  [kid, keeps, saying, interchangeably, my, name...   \n",
       "4               [The, media, darling, Barack, Obama]   \n",
       "\n",
       "                                           final_wds  \n",
       "0  [Working, public, service, spots, Barack, Obam...  \n",
       "1  [An, lise, candidatos, precisam, de, pol, tica...  \n",
       "2  [Barack, Obama, LIVE, Barack, Joe, Fredricksbu...  \n",
       "3  [kid, keeps, saying, interchangeably, name, ba...  \n",
       "4               [The, media, darling, Barack, Obama]  "
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Applying remove_stop_wds function to dataset\n",
    "df['final_wds']=df.apply(remove_stop_wds, axis=1)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tweet             5550\n",
       "replies_count     5550\n",
       "retweets_count    5550\n",
       "likes_count       5550\n",
       "candidate         5550\n",
       "tweet_length      5550\n",
       "Subjectivity      5550\n",
       "Polarity          5550\n",
       "Sentiment         5550\n",
       "year              5550\n",
       "t_words           5550\n",
       "final_wds         5550\n",
       "dtype: int64"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.to_csv(r'C:\\Users\\Greg\\Documents\\Analysis_Projects\\US_Election_NLP\\US_Election_NLP\\Concat_ML_Data\\wordcloud_2008.csv', index = False, header=True)"
   ]
  }
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