final_PRIDE++.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[nltk_data] Downloading package stopwords to\n",
      "[nltk_data]     C:\\Users\\KIIT\\AppData\\Roaming\\nltk_data...\n",
      "[nltk_data]   Package stopwords is already up-to-date!\n",
      "[nltk_data] Downloading package wordnet to\n",
      "[nltk_data]     C:\\Users\\KIIT\\AppData\\Roaming\\nltk_data...\n",
      "[nltk_data]   Package wordnet is already up-to-date!\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import re\n",
    "import nltk\n",
    "import string\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from textblob import TextBlob\n",
    "from wordcloud import WordCloud\n",
    "import matplotlib.pyplot as plt\n",
    "from nltk.corpus import stopwords\n",
    "from nltk.stem.porter import PorterStemmer\n",
    "from nltk.stem import WordNetLemmatizer\n",
    "nltk.download(\"stopwords\")\n",
    "nltk.download('wordnet')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def helper_remove_b(text):\n",
    "    if(text[:1] == 'b'):\n",
    "        text = text[1:]\n",
    "    return text\n",
    "\n",
    "def helper_regex(text):\n",
    "    text = re.sub(r'@[A-Za-z0-9]+', '', text)\n",
    "    text = re.sub(r'#', '', text)\n",
    "    text = re.sub(r'RT[\\s]+', '', text)\n",
    "    text = re.sub(r'b\\'', '', text)\n",
    "    text = re.sub(r'b\\\" ', '', text)\n",
    "    text = re.sub(\"\\$\", \"\", text)\n",
    "    text = re.sub(\"https?:\\/\\/.*[\\r\\n]*\", \"\", text)\n",
    "    text = re.sub(\"@\\S+\", \"\", text)\n",
    "    \n",
    "    text = re.sub(r'[^\\x00-\\x7f]',r'', text)  \n",
    "    text = text.translate({ord(i): None for i in '\\\\'})\n",
    "    return text\n",
    "\n",
    "def stop_words(text):\n",
    "    nltk.download(\"stopwords\")\n",
    "    stop_words = set(stopwords.words(\"english\"))\n",
    "    text = \" \".join([word for word in text.split() if word not in stop_words])\n",
    "    return text\n",
    "\n",
    "def encode_decode(text):\n",
    "    encode = text.encode(encoding=\"ascii\", errors=\"ignore\")\n",
    "    decode = encode.decode()\n",
    "    clean_text = \" \".join([word for word in decode.split()])\n",
    "    return clean_text\n",
    "\n",
    "def remove_punctuation(text):\n",
    "    punct = set(string.punctuation) \n",
    "    text = \"\".join([ch for ch in text if ch not in punct])\n",
    "    return text\n",
    "\n",
    "\n",
    "def lemm_stem(text):\n",
    "    stemmer = PorterStemmer()\n",
    "    text1 = \"\"\n",
    "    for word in text:\n",
    "        text1 += stemmer.stem(word)\n",
    "    \n",
    "    text2 = \"\"\n",
    "    lemmatizer = WordNetLemmatizer()\n",
    "    for word in text1:\n",
    "        text2 += lemmatizer.lemmatize(word)\n",
    "    \n",
    "    return text2\n",
    "\n",
    "def clean_text_full_power(text):\n",
    "    text = helper_remove_b(text)\n",
    "    text = helper_regex(text)\n",
    "    text = stop_words(text)\n",
    "    text = encode_decode(text)\n",
    "    text = remove_punctuation(text)\n",
    "    #text = lemm_stem(text)\n",
    "    return text"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(r'LGBTQ.csv')\n",
    "data = df[['tweet_text']].copy()\n",
    "my_data = pd.DataFrame(data.iloc[1::2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "my_data = my_data.reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "my_data = my_data.drop('index', axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .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>tweet_text</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>b'It\\xe2\\x80\\x99s always a great weekend when ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>b\"To our #UK-based friends and customers, here...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>b'Just a reminder:  It was not trump nor his p...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>b'Release Blitz: Concussion and Contentment by...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>b\"Outrage at the @thetimes article about #Ston...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                          tweet_text\n",
       "0  b'It\\xe2\\x80\\x99s always a great weekend when ...\n",
       "1  b\"To our #UK-based friends and customers, here...\n",
       "2  b'Just a reminder:  It was not trump nor his p...\n",
       "3  b'Release Blitz: Concussion and Contentment by...\n",
       "4  b\"Outrage at the @thetimes article about #Ston..."
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "my_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[nltk_data] Downloading package stopwords to\n",
      "[nltk_data]     C:\\Users\\KIIT\\AppData\\Roaming\\nltk_data...\n",
      "[nltk_data]   Package stopwords is already up-to-date!\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "'Fun long stream Gonna deep thinkin scheming Fun stuff works coulrophilia Clowngirl transgender LGBTQ ENVTuber VTuber Twitch GirlStreamer'"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clean_text_full_power(my_data['tweet_text'][10])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
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    {
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     ]
    }
   ],
   "source": [
    "clean_data = pd.DataFrame(my_data['tweet_text'].apply(lambda a: clean_text_full_power(a)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "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>tweet_text</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Itxe2x80x99s always great weekend boheme subda...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>To UKbased friends customers important message...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Just reminder It trump people responsible rapi...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Release Blitz Concussion Contentment Liz Farai...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Outrage article Stonewall veryinterestingxf0x9...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>Love tshirt marvel LGBTQ</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>We harassed intimidated back closet LGBTQ Mond...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>xf0x9fx8cx9f M O N D A Y xe2x8fxb0 9th August ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>WIN WIN WINxf0x9fx8fx86 Somewhere hidden pride...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>Hey all Heres post missed Read whyHouse Bill H...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>100 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                           tweet_text\n",
       "0   Itxe2x80x99s always great weekend boheme subda...\n",
       "1   To UKbased friends customers important message...\n",
       "2   Just reminder It trump people responsible rapi...\n",
       "3   Release Blitz Concussion Contentment Liz Farai...\n",
       "4   Outrage article Stonewall veryinterestingxf0x9...\n",
       "..                                                ...\n",
       "95                           Love tshirt marvel LGBTQ\n",
       "96  We harassed intimidated back closet LGBTQ Mond...\n",
       "97  xf0x9fx8cx9f M O N D A Y xe2x8fxb0 9th August ...\n",
       "98  WIN WIN WINxf0x9fx8fx86 Somewhere hidden pride...\n",
       "99  Hey all Heres post missed Read whyHouse Bill H...\n",
       "\n",
       "[100 rows x 1 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clean_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "def clean(text):\n",
    "    text = helper_remove_b(text)\n",
    "    text = helper_regex(text)\n",
    "    text = encode_decode(text)\n",
    "    return text"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "tweet_data = pd.DataFrame(my_data['tweet_text'].apply(lambda a: clean(a)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "tweet_data.columns = ['tweet_text']\n",
    "clean_data.columns = ['clean_text']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "final_data = tweet_data.join(clean_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Wordcloud plotting. Wordcloud was actually used to see the most popular word to make the image logo for our Project. \n",
    "allWords = ' '. join( [twts for twts in final_data['tweet_text']])\n",
    "wordCloud = WordCloud(width = 500, height = 300, random_state = 21, max_font_size = 119).generate(allWords)\n",
    "plt.imshow(wordCloud, interpolation = \"bilinear\")\n",
    "plt.axis('off')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "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>tweet_text</th>\n",
       "      <th>clean_text</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>'Itxe2x80x99s always a great weekend when bohe...</td>\n",
       "      <td>Itxe2x80x99s always great weekend boheme subda...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>\"To our UK-based friends and customers, here i...</td>\n",
       "      <td>To UKbased friends customers important message...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>'Just a reminder: It was not trump nor his peo...</td>\n",
       "      <td>Just reminder It trump people responsible rapi...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>'Release Blitz: Concussion and Contentment by ...</td>\n",
       "      <td>Release Blitz Concussion Contentment Liz Farai...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>\"Outrage at the article about Stonewall is ver...</td>\n",
       "      <td>Outrage article Stonewall veryinterestingxf0x9...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>'Love this tshirt from marvel LGBTQ</td>\n",
       "      <td>Love tshirt marvel LGBTQ</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>'We will not be harassed or intimidated back i...</td>\n",
       "      <td>We harassed intimidated back closet LGBTQ Mond...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>\"xf0x9fx8cx9f M O N D A Y xe2x8fxb0 9th August...</td>\n",
       "      <td>xf0x9fx8cx9f M O N D A Y xe2x8fxb0 9th August ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>'WIN, WIN, WINxf0x9fx8fx86 Somewhere hidden in...</td>\n",
       "      <td>WIN WIN WINxf0x9fx8fx86 Somewhere hidden pride...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>'Hey all! Here's a post you've missed! Read ab...</td>\n",
       "      <td>Hey all Heres post missed Read whyHouse Bill H...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>100 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                           tweet_text  \\\n",
       "0   'Itxe2x80x99s always a great weekend when bohe...   \n",
       "1   \"To our UK-based friends and customers, here i...   \n",
       "2   'Just a reminder: It was not trump nor his peo...   \n",
       "3   'Release Blitz: Concussion and Contentment by ...   \n",
       "4   \"Outrage at the article about Stonewall is ver...   \n",
       "..                                                ...   \n",
       "95                'Love this tshirt from marvel LGBTQ   \n",
       "96  'We will not be harassed or intimidated back i...   \n",
       "97  \"xf0x9fx8cx9f M O N D A Y xe2x8fxb0 9th August...   \n",
       "98  'WIN, WIN, WINxf0x9fx8fx86 Somewhere hidden in...   \n",
       "99  'Hey all! Here's a post you've missed! Read ab...   \n",
       "\n",
       "                                           clean_text  \n",
       "0   Itxe2x80x99s always great weekend boheme subda...  \n",
       "1   To UKbased friends customers important message...  \n",
       "2   Just reminder It trump people responsible rapi...  \n",
       "3   Release Blitz Concussion Contentment Liz Farai...  \n",
       "4   Outrage article Stonewall veryinterestingxf0x9...  \n",
       "..                                                ...  \n",
       "95                           Love tshirt marvel LGBTQ  \n",
       "96  We harassed intimidated back closet LGBTQ Mond...  \n",
       "97  xf0x9fx8cx9f M O N D A Y xe2x8fxb0 9th August ...  \n",
       "98  WIN WIN WINxf0x9fx8fx86 Somewhere hidden pride...  \n",
       "99  Hey all Heres post missed Read whyHouse Bill H...  \n",
       "\n",
       "[100 rows x 2 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "final_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "text_data = final_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "def getSubjectivity(text):\n",
    "    return TextBlob(text).sentiment.subjectivity\n",
    "\n",
    "def getPolarity(text):\n",
    "    return TextBlob(text).sentiment.polarity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "text_data['Subjectivity'] = text_data['clean_text'].apply(getSubjectivity)\n",
    "text_data['Polarity'] = text_data['clean_text'].apply(getPolarity)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tweet_text</th>\n",
       "      <th>clean_text</th>\n",
       "      <th>Subjectivity</th>\n",
       "      <th>Polarity</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>'Itxe2x80x99s always a great weekend when bohe...</td>\n",
       "      <td>Itxe2x80x99s always great weekend boheme subda...</td>\n",
       "      <td>0.750000</td>\n",
       "      <td>0.800000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>\"To our UK-based friends and customers, here i...</td>\n",
       "      <td>To UKbased friends customers important message...</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.400000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>'Just a reminder: It was not trump nor his peo...</td>\n",
       "      <td>Just reminder It trump people responsible rapi...</td>\n",
       "      <td>0.275000</td>\n",
       "      <td>0.100000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>'Release Blitz: Concussion and Contentment by ...</td>\n",
       "      <td>Release Blitz Concussion Contentment Liz Farai...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>\"Outrage at the article about Stonewall is ver...</td>\n",
       "      <td>Outrage article Stonewall veryinterestingxf0x9...</td>\n",
       "      <td>0.066667</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>'Love this tshirt from marvel LGBTQ</td>\n",
       "      <td>Love tshirt marvel LGBTQ</td>\n",
       "      <td>0.600000</td>\n",
       "      <td>0.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>'We will not be harassed or intimidated back i...</td>\n",
       "      <td>We harassed intimidated back closet LGBTQ Mond...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>\"xf0x9fx8cx9f M O N D A Y xe2x8fxb0 9th August...</td>\n",
       "      <td>xf0x9fx8cx9f M O N D A Y xe2x8fxb0 9th August ...</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>'WIN, WIN, WINxf0x9fx8fx86 Somewhere hidden in...</td>\n",
       "      <td>WIN WIN WINxf0x9fx8fx86 Somewhere hidden pride...</td>\n",
       "      <td>0.377778</td>\n",
       "      <td>0.477778</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>'Hey all! Here's a post you've missed! Read ab...</td>\n",
       "      <td>Hey all Heres post missed Read whyHouse Bill H...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>100 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                           tweet_text  \\\n",
       "0   'Itxe2x80x99s always a great weekend when bohe...   \n",
       "1   \"To our UK-based friends and customers, here i...   \n",
       "2   'Just a reminder: It was not trump nor his peo...   \n",
       "3   'Release Blitz: Concussion and Contentment by ...   \n",
       "4   \"Outrage at the article about Stonewall is ver...   \n",
       "..                                                ...   \n",
       "95                'Love this tshirt from marvel LGBTQ   \n",
       "96  'We will not be harassed or intimidated back i...   \n",
       "97  \"xf0x9fx8cx9f M O N D A Y xe2x8fxb0 9th August...   \n",
       "98  'WIN, WIN, WINxf0x9fx8fx86 Somewhere hidden in...   \n",
       "99  'Hey all! Here's a post you've missed! Read ab...   \n",
       "\n",
       "                                           clean_text  Subjectivity  Polarity  \n",
       "0   Itxe2x80x99s always great weekend boheme subda...      0.750000  0.800000  \n",
       "1   To UKbased friends customers important message...      1.000000  0.400000  \n",
       "2   Just reminder It trump people responsible rapi...      0.275000  0.100000  \n",
       "3   Release Blitz Concussion Contentment Liz Farai...      0.000000  0.000000  \n",
       "4   Outrage article Stonewall veryinterestingxf0x9...      0.066667  0.000000  \n",
       "..                                                ...           ...       ...  \n",
       "95                           Love tshirt marvel LGBTQ      0.600000  0.500000  \n",
       "96  We harassed intimidated back closet LGBTQ Mond...      0.000000  0.000000  \n",
       "97  xf0x9fx8cx9f M O N D A Y xe2x8fxb0 9th August ...      0.500000  0.000000  \n",
       "98  WIN WIN WINxf0x9fx8fx86 Somewhere hidden pride...      0.377778  0.477778  \n",
       "99  Hey all Heres post missed Read whyHouse Bill H...      0.000000  0.000000  \n",
       "\n",
       "[100 rows x 4 columns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "text_data\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
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       "      <th></th>\n",
       "      <th>tweet_text</th>\n",
       "      <th>clean_text</th>\n",
       "      <th>Subjectivity</th>\n",
       "      <th>Polarity</th>\n",
       "      <th>Analysis</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>'Itxe2x80x99s always a great weekend when bohe...</td>\n",
       "      <td>Itxe2x80x99s always great weekend boheme subda...</td>\n",
       "      <td>0.750000</td>\n",
       "      <td>0.800000</td>\n",
       "      <td>Positive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>\"To our UK-based friends and customers, here i...</td>\n",
       "      <td>To UKbased friends customers important message...</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.400000</td>\n",
       "      <td>Positive</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>'Just a reminder: It was not trump nor his peo...</td>\n",
       "      <td>Just reminder It trump people responsible rapi...</td>\n",
       "      <td>0.275000</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>Positive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>'Release Blitz: Concussion and Contentment by ...</td>\n",
       "      <td>Release Blitz Concussion Contentment Liz Farai...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>Neutral</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>\"Outrage at the article about Stonewall is ver...</td>\n",
       "      <td>Outrage article Stonewall veryinterestingxf0x9...</td>\n",
       "      <td>0.066667</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>Neutral</td>\n",
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       "      <th>...</th>\n",
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       "      <td>'Love this tshirt from marvel LGBTQ</td>\n",
       "      <td>Love tshirt marvel LGBTQ</td>\n",
       "      <td>0.600000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>Positive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>'We will not be harassed or intimidated back i...</td>\n",
       "      <td>We harassed intimidated back closet LGBTQ Mond...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>Neutral</td>\n",
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       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>\"xf0x9fx8cx9f M O N D A Y xe2x8fxb0 9th August...</td>\n",
       "      <td>xf0x9fx8cx9f M O N D A Y xe2x8fxb0 9th August ...</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>Neutral</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>'WIN, WIN, WINxf0x9fx8fx86 Somewhere hidden in...</td>\n",
       "      <td>WIN WIN WINxf0x9fx8fx86 Somewhere hidden pride...</td>\n",
       "      <td>0.377778</td>\n",
       "      <td>0.477778</td>\n",
       "      <td>Positive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>'Hey all! Here's a post you've missed! Read ab...</td>\n",
       "      <td>Hey all Heres post missed Read whyHouse Bill H...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>Neutral</td>\n",
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       "</table>\n",
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      ],
      "text/plain": [
       "                                           tweet_text  \\\n",
       "0   'Itxe2x80x99s always a great weekend when bohe...   \n",
       "1   \"To our UK-based friends and customers, here i...   \n",
       "2   'Just a reminder: It was not trump nor his peo...   \n",
       "3   'Release Blitz: Concussion and Contentment by ...   \n",
       "4   \"Outrage at the article about Stonewall is ver...   \n",
       "..                                                ...   \n",
       "95                'Love this tshirt from marvel LGBTQ   \n",
       "96  'We will not be harassed or intimidated back i...   \n",
       "97  \"xf0x9fx8cx9f M O N D A Y xe2x8fxb0 9th August...   \n",
       "98  'WIN, WIN, WINxf0x9fx8fx86 Somewhere hidden in...   \n",
       "99  'Hey all! Here's a post you've missed! Read ab...   \n",
       "\n",
       "                                           clean_text  Subjectivity  Polarity  \\\n",
       "0   Itxe2x80x99s always great weekend boheme subda...      0.750000  0.800000   \n",
       "1   To UKbased friends customers important message...      1.000000  0.400000   \n",
       "2   Just reminder It trump people responsible rapi...      0.275000  0.100000   \n",
       "3   Release Blitz Concussion Contentment Liz Farai...      0.000000  0.000000   \n",
       "4   Outrage article Stonewall veryinterestingxf0x9...      0.066667  0.000000   \n",
       "..                                                ...           ...       ...   \n",
       "95                           Love tshirt marvel LGBTQ      0.600000  0.500000   \n",
       "96  We harassed intimidated back closet LGBTQ Mond...      0.000000  0.000000   \n",
       "97  xf0x9fx8cx9f M O N D A Y xe2x8fxb0 9th August ...      0.500000  0.000000   \n",
       "98  WIN WIN WINxf0x9fx8fx86 Somewhere hidden pride...      0.377778  0.477778   \n",
       "99  Hey all Heres post missed Read whyHouse Bill H...      0.000000  0.000000   \n",
       "\n",
       "    Analysis  \n",
       "0   Positive  \n",
       "1   Positive  \n",
       "2   Positive  \n",
       "3    Neutral  \n",
       "4    Neutral  \n",
       "..       ...  \n",
       "95  Positive  \n",
       "96   Neutral  \n",
       "97   Neutral  \n",
       "98  Positive  \n",
       "99   Neutral  \n",
       "\n",
       "[100 rows x 5 columns]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#compute the -ve, neutral or positive analysis\n",
    "def getAnalysis(score):\n",
    "    if score<0:\n",
    "        return 'Negative'\n",
    "    elif score ==0:\n",
    "        return 'Neutral'\n",
    "    else:\n",
    "        return 'Positive'\n",
    "    \n",
    "text_data['Analysis'] = text_data['Polarity'].apply(getAnalysis)\n",
    "text_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "positive_tweets = text_data[text_data['Analysis'] == 'Positive']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "positive_tweets.to_csv('finallgbtmodified.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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