{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "66b45bb9",
   "metadata": {},
   "source": [
    "# Final Project"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6e07d13e",
   "metadata": {},
   "source": [
    "I love watching TV series and movies, most recently Ted Lasso seems to be the talk of the town. I loved the first season and can't wait to watch the second season. I also have an interest in the Emmy's, I watch it every year. The reason for this analysis is to determine if Twitter has any influence on the Emmy winner of Best Comedy Series. I first pulled Tweets that mention Ted Lasso or #tedlasso along with blackish or #blackish. Once I got a reasonable amount of Tweets i used the VADER toolkit(?) to determine the positive and negative sentiments of the Tweets that i pulled. Using VADER i can measure the sentiment of the Tweets to then compare the two shows. Once i got the sentiments of each show i created a histogram of the negative, positive, neutral, and compound of the tweets. This allowed me to get a visual of each sentiment and see which had more weight to it. Looking at these graphs comparatively, I can estimate that Ted Lasso has more positive Tweets than blackish. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "195ca0a5",
   "metadata": {},
   "outputs": [],
   "source": [
    "import requests\n",
    "import pandas as pd\n",
    "import urllib\n",
    "import json"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "2b330167",
   "metadata": {},
   "outputs": [],
   "source": [
    "bearer_token = pd.read_csv('bearer_token.txt', header = 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ec5074d7",
   "metadata": {},
   "outputs": [],
   "source": [
    "bearer_token"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3d0ca646",
   "metadata": {},
   "outputs": [],
   "source": [
    "bearer_token['bearer_token'].iloc[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "cf977181",
   "metadata": {},
   "outputs": [],
   "source": [
    "header = {'Authorization' : 'Bearer {}'.format(bearer_token['bearer_token'].iloc[0])}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "9902fd9a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['bearer_token'], dtype='object')"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bearer_token.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "716041a7",
   "metadata": {},
   "outputs": [],
   "source": [
    "endpoint_url = 'https://api.twitter.com/2/tweets/search/recent'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "f8e99bb4",
   "metadata": {},
   "outputs": [],
   "source": [
    "query = urllib.parse.quote('(#TedLasso OR Ted Lasso lang:en)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "ee6288bf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'%28%23TedLasso%20OR%20Ted%20Lasso%20lang%3Aen%29'"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "query"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "cf53e4d4",
   "metadata": {},
   "outputs": [],
   "source": [
    "my_api_url = endpoint_url + '?query={}'.format(query)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "3324a2c4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'https://api.twitter.com/2/tweets/search/recent?query=%28%23TedLasso%20OR%20Ted%20Lasso%20lang%3Aen%29'"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "my_api_url"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "7b6fa438",
   "metadata": {},
   "outputs": [],
   "source": [
    "tweet_fields = 'public_metrics,created_at,author_id,lang'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "8cd30266",
   "metadata": {},
   "outputs": [],
   "source": [
    "my_api_url = endpoint_url + '?query={}&tweet.fields={}'.format(query, tweet_fields)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "50081342",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'https://api.twitter.com/2/tweets/search/recent?query=%28%23TedLasso%20OR%20Ted%20Lasso%20lang%3Aen%29&tweet.fields=public_metrics,created_at,author_id,lang'"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "my_api_url"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "03ffca74",
   "metadata": {},
   "outputs": [],
   "source": [
    "expansions = 'author_id'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "8e639e27",
   "metadata": {},
   "outputs": [],
   "source": [
    "url = endpoint_url + '?query={}&max_results=10&tweet.fields{}'.format(query, tweet_fields)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "99ed4b2a",
   "metadata": {},
   "outputs": [],
   "source": [
    "response = requests.request(\"GET\", url, headers = header)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "968f6c08",
   "metadata": {},
   "outputs": [],
   "source": [
    "url_expansions = endpoint_url + '?query={}&max_results=100&tweet.fields={}&expansions={}&user.fields={}'.format(query, tweet_fields, expansions, 'username')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "3639f51e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'https://api.twitter.com/2/tweets/search/recent?query=%28%23TedLasso%20OR%20Ted%20Lasso%20lang%3Aen%29&max_results=100&tweet.fields=public_metrics,created_at,author_id,lang&expansions=author_id&user.fields=username'"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "url_expansions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "409787d5",
   "metadata": {},
   "outputs": [],
   "source": [
    "first_response = requests.request(\"GET\", url_expansions, headers = header)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "76e895f8",
   "metadata": {},
   "outputs": [],
   "source": [
    "first_response.text"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "6818c993",
   "metadata": {},
   "outputs": [],
   "source": [
    "first_dict = json.loads(first_response.text)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "69052a8c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_keys(['data', 'includes', 'meta'])"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "first_dict.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "aafd8903",
   "metadata": {},
   "outputs": [],
   "source": [
    "my_df = pd.DataFrame(first_dict['data'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "3b0c179e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "    }\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>author_id</th>\n",
       "      <th>text</th>\n",
       "      <th>created_at</th>\n",
       "      <th>id</th>\n",
       "      <th>public_metrics</th>\n",
       "      <th>lang</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1855042940</td>\n",
       "      <td>RT @goldenglobes: The #GoldenGlobes nominees f...</td>\n",
       "      <td>2021-12-13T23:40:21.000Z</td>\n",
       "      <td>1470539115343011846</td>\n",
       "      <td>{'retweet_count': 48, 'reply_count': 0, 'like_...</td>\n",
       "      <td>en</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1322320427507765248</td>\n",
       "      <td>RT @JarettSays: My heart feels so full when I ...</td>\n",
       "      <td>2021-12-13T23:40:06.000Z</td>\n",
       "      <td>1470539054353629189</td>\n",
       "      <td>{'retweet_count': 43, 'reply_count': 0, 'like_...</td>\n",
       "      <td>en</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>152531825</td>\n",
       "      <td>RT @QUEERLASSO: I dont think we talk about thi...</td>\n",
       "      <td>2021-12-13T23:39:52.000Z</td>\n",
       "      <td>1470538993666301952</td>\n",
       "      <td>{'retweet_count': 154, 'reply_count': 0, 'like...</td>\n",
       "      <td>en</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>25866804</td>\n",
       "      <td>late to ted lasso but woowee that nate charact...</td>\n",
       "      <td>2021-12-13T23:39:37.000Z</td>\n",
       "      <td>1470538932492324864</td>\n",
       "      <td>{'retweet_count': 0, 'reply_count': 0, 'like_c...</td>\n",
       "      <td>en</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1060508317204791296</td>\n",
       "      <td>RT @QUEERLASSO: I dont think we talk about thi...</td>\n",
       "      <td>2021-12-13T23:39:06.000Z</td>\n",
       "      <td>1470538802523430912</td>\n",
       "      <td>{'retweet_count': 154, 'reply_count': 0, 'like...</td>\n",
       "      <td>en</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>294151373</td>\n",
       "      <td>RT @goldenglobes: The #GoldenGlobes nominees f...</td>\n",
       "      <td>2021-12-13T23:12:34.000Z</td>\n",
       "      <td>1470532126265204736</td>\n",
       "      <td>{'retweet_count': 48, 'reply_count': 0, 'like_...</td>\n",
       "      <td>en</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>1909483010</td>\n",
       "      <td>RT @WestLondonFS: The @goldenglobes nomination...</td>\n",
       "      <td>2021-12-13T23:11:56.000Z</td>\n",
       "      <td>1470531964050370561</td>\n",
       "      <td>{'retweet_count': 34, 'reply_count': 0, 'like_...</td>\n",
       "      <td>en</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>1392853644840685570</td>\n",
       "      <td>📸 | jason sudeikis, the cast of ted lasso and ...</td>\n",
       "      <td>2021-12-13T23:11:13.000Z</td>\n",
       "      <td>1470531785352228867</td>\n",
       "      <td>{'retweet_count': 9, 'reply_count': 0, 'like_c...</td>\n",
       "      <td>en</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>828768590392389632</td>\n",
       "      <td>RT @DiscussingFilm: The #GoldenGlobes nominees...</td>\n",
       "      <td>2021-12-13T23:11:05.000Z</td>\n",
       "      <td>1470531751131086848</td>\n",
       "      <td>{'retweet_count': 216, 'reply_count': 0, 'like...</td>\n",
       "      <td>en</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>1076748693490016256</td>\n",
       "      <td>RT @DiscussingFilm: The #GoldenGlobes nominees...</td>\n",
       "      <td>2021-12-13T23:10:09.000Z</td>\n",
       "      <td>1470531518502158336</td>\n",
       "      <td>{'retweet_count': 332, 'reply_count': 0, 'like...</td>\n",
       "      <td>en</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>100 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              author_id                                               text  \\\n",
       "0            1855042940  RT @goldenglobes: The #GoldenGlobes nominees f...   \n",
       "1   1322320427507765248  RT @JarettSays: My heart feels so full when I ...   \n",
       "2             152531825  RT @QUEERLASSO: I dont think we talk about thi...   \n",
       "3              25866804  late to ted lasso but woowee that nate charact...   \n",
       "4   1060508317204791296  RT @QUEERLASSO: I dont think we talk about thi...   \n",
       "..                  ...                                                ...   \n",
       "95            294151373  RT @goldenglobes: The #GoldenGlobes nominees f...   \n",
       "96           1909483010  RT @WestLondonFS: The @goldenglobes nomination...   \n",
       "97  1392853644840685570  📸 | jason sudeikis, the cast of ted lasso and ...   \n",
       "98   828768590392389632  RT @DiscussingFilm: The #GoldenGlobes nominees...   \n",
       "99  1076748693490016256  RT @DiscussingFilm: The #GoldenGlobes nominees...   \n",
       "\n",
       "                  created_at                   id  \\\n",
       "0   2021-12-13T23:40:21.000Z  1470539115343011846   \n",
       "1   2021-12-13T23:40:06.000Z  1470539054353629189   \n",
       "2   2021-12-13T23:39:52.000Z  1470538993666301952   \n",
       "3   2021-12-13T23:39:37.000Z  1470538932492324864   \n",
       "4   2021-12-13T23:39:06.000Z  1470538802523430912   \n",
       "..                       ...                  ...   \n",
       "95  2021-12-13T23:12:34.000Z  1470532126265204736   \n",
       "96  2021-12-13T23:11:56.000Z  1470531964050370561   \n",
       "97  2021-12-13T23:11:13.000Z  1470531785352228867   \n",
       "98  2021-12-13T23:11:05.000Z  1470531751131086848   \n",
       "99  2021-12-13T23:10:09.000Z  1470531518502158336   \n",
       "\n",
       "                                       public_metrics lang  \n",
       "0   {'retweet_count': 48, 'reply_count': 0, 'like_...   en  \n",
       "1   {'retweet_count': 43, 'reply_count': 0, 'like_...   en  \n",
       "2   {'retweet_count': 154, 'reply_count': 0, 'like...   en  \n",
       "3   {'retweet_count': 0, 'reply_count': 0, 'like_c...   en  \n",
       "4   {'retweet_count': 154, 'reply_count': 0, 'like...   en  \n",
       "..                                                ...  ...  \n",
       "95  {'retweet_count': 48, 'reply_count': 0, 'like_...   en  \n",
       "96  {'retweet_count': 34, 'reply_count': 0, 'like_...   en  \n",
       "97  {'retweet_count': 9, 'reply_count': 0, 'like_c...   en  \n",
       "98  {'retweet_count': 216, 'reply_count': 0, 'like...   en  \n",
       "99  {'retweet_count': 332, 'reply_count': 0, 'like...   en  \n",
       "\n",
       "[100 rows x 6 columns]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "my_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "e1cb02d8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'newest_id': '1470539115343011846',\n",
       " 'oldest_id': '1470531518502158336',\n",
       " 'result_count': 100,\n",
       " 'next_token': 'b26v89c19zqg8o3fpe15ccn9w787zzmkvi2jx3avr9tvh'}"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "first_dict['meta']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "e06be4fb",
   "metadata": {},
   "outputs": [],
   "source": [
    "my_api_url2 = my_api_url + '&next_token={}&max_results=100'.format(first_dict['meta']['next_token'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "d72a6a71",
   "metadata": {},
   "outputs": [],
   "source": [
    "second_response = requests.request(\"GET\", my_api_url2, headers = header)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "152b9c26",
   "metadata": {},
   "outputs": [],
   "source": [
    "second_response.text"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "92966f5b",
   "metadata": {},
   "outputs": [],
   "source": [
    "my_df = my_df.append(pd.DataFrame(json.loads(second_response.text)['data']), ignore_index= True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "5de67674",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .dataframe tbody tr th {\n",
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       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>author_id</th>\n",
       "      <th>text</th>\n",
       "      <th>created_at</th>\n",
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       "      <th>public_metrics</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1855042940</td>\n",
       "      <td>RT @goldenglobes: The #GoldenGlobes nominees f...</td>\n",
       "      <td>2021-12-13T23:40:21.000Z</td>\n",
       "      <td>1470539115343011846</td>\n",
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       "      <td>en</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1322320427507765248</td>\n",
       "      <td>RT @JarettSays: My heart feels so full when I ...</td>\n",
       "      <td>2021-12-13T23:40:06.000Z</td>\n",
       "      <td>1470539054353629189</td>\n",
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       "      <th>2</th>\n",
       "      <td>152531825</td>\n",
       "      <td>RT @QUEERLASSO: I dont think we talk about thi...</td>\n",
       "      <td>2021-12-13T23:39:52.000Z</td>\n",
       "      <td>1470538993666301952</td>\n",
       "      <td>{'retweet_count': 154, 'reply_count': 0, 'like...</td>\n",
       "      <td>en</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>25866804</td>\n",
       "      <td>late to ted lasso but woowee that nate charact...</td>\n",
       "      <td>2021-12-13T23:39:37.000Z</td>\n",
       "      <td>1470538932492324864</td>\n",
       "      <td>{'retweet_count': 0, 'reply_count': 0, 'like_c...</td>\n",
       "      <td>en</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1060508317204791296</td>\n",
       "      <td>RT @QUEERLASSO: I dont think we talk about thi...</td>\n",
       "      <td>2021-12-13T23:39:06.000Z</td>\n",
       "      <td>1470538802523430912</td>\n",
       "      <td>{'retweet_count': 154, 'reply_count': 0, 'like...</td>\n",
       "      <td>en</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>195</th>\n",
       "      <td>1575603678</td>\n",
       "      <td>RT @BatatinhaGeek: As indicadas a 'Melhor Atri...</td>\n",
       "      <td>2021-12-13T22:35:03.000Z</td>\n",
       "      <td>1470522682773061635</td>\n",
       "      <td>{'retweet_count': 1, 'reply_count': 0, 'like_c...</td>\n",
       "      <td>en</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196</th>\n",
       "      <td>1575603678</td>\n",
       "      <td>RT @BatatinhaGeek: Os indicados a 'Melhor Ator...</td>\n",
       "      <td>2021-12-13T22:35:01.000Z</td>\n",
       "      <td>1470522675860754434</td>\n",
       "      <td>{'retweet_count': 2, 'reply_count': 0, 'like_c...</td>\n",
       "      <td>en</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>363940693</td>\n",
       "      <td>In honor of the holiday season and the upcomin...</td>\n",
       "      <td>2021-12-13T22:34:33.000Z</td>\n",
       "      <td>1470522556549668869</td>\n",
       "      <td>{'retweet_count': 0, 'reply_count': 1, 'like_c...</td>\n",
       "      <td>en</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>198</th>\n",
       "      <td>471528838</td>\n",
       "      <td>I miss Ted Lasso Twitter https://t.co/N5dQWP14hd</td>\n",
       "      <td>2021-12-13T22:34:04.000Z</td>\n",
       "      <td>1470522434923089924</td>\n",
       "      <td>{'retweet_count': 0, 'reply_count': 0, 'like_c...</td>\n",
       "      <td>en</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>199</th>\n",
       "      <td>1409283084520890370</td>\n",
       "      <td>RT @manvillebea: if there’s one thing the ted ...</td>\n",
       "      <td>2021-12-13T22:33:52.000Z</td>\n",
       "      <td>1470522384541052928</td>\n",
       "      <td>{'retweet_count': 3, 'reply_count': 0, 'like_c...</td>\n",
       "      <td>en</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>200 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               author_id                                               text  \\\n",
       "0             1855042940  RT @goldenglobes: The #GoldenGlobes nominees f...   \n",
       "1    1322320427507765248  RT @JarettSays: My heart feels so full when I ...   \n",
       "2              152531825  RT @QUEERLASSO: I dont think we talk about thi...   \n",
       "3               25866804  late to ted lasso but woowee that nate charact...   \n",
       "4    1060508317204791296  RT @QUEERLASSO: I dont think we talk about thi...   \n",
       "..                   ...                                                ...   \n",
       "195           1575603678  RT @BatatinhaGeek: As indicadas a 'Melhor Atri...   \n",
       "196           1575603678  RT @BatatinhaGeek: Os indicados a 'Melhor Ator...   \n",
       "197            363940693  In honor of the holiday season and the upcomin...   \n",
       "198            471528838   I miss Ted Lasso Twitter https://t.co/N5dQWP14hd   \n",
       "199  1409283084520890370  RT @manvillebea: if there’s one thing the ted ...   \n",
       "\n",
       "                   created_at                   id  \\\n",
       "0    2021-12-13T23:40:21.000Z  1470539115343011846   \n",
       "1    2021-12-13T23:40:06.000Z  1470539054353629189   \n",
       "2    2021-12-13T23:39:52.000Z  1470538993666301952   \n",
       "3    2021-12-13T23:39:37.000Z  1470538932492324864   \n",
       "4    2021-12-13T23:39:06.000Z  1470538802523430912   \n",
       "..                        ...                  ...   \n",
       "195  2021-12-13T22:35:03.000Z  1470522682773061635   \n",
       "196  2021-12-13T22:35:01.000Z  1470522675860754434   \n",
       "197  2021-12-13T22:34:33.000Z  1470522556549668869   \n",
       "198  2021-12-13T22:34:04.000Z  1470522434923089924   \n",
       "199  2021-12-13T22:33:52.000Z  1470522384541052928   \n",
       "\n",
       "                                        public_metrics lang  \n",
       "0    {'retweet_count': 48, 'reply_count': 0, 'like_...   en  \n",
       "1    {'retweet_count': 43, 'reply_count': 0, 'like_...   en  \n",
       "2    {'retweet_count': 154, 'reply_count': 0, 'like...   en  \n",
       "3    {'retweet_count': 0, 'reply_count': 0, 'like_c...   en  \n",
       "4    {'retweet_count': 154, 'reply_count': 0, 'like...   en  \n",
       "..                                                 ...  ...  \n",
       "195  {'retweet_count': 1, 'reply_count': 0, 'like_c...   en  \n",
       "196  {'retweet_count': 2, 'reply_count': 0, 'like_c...   en  \n",
       "197  {'retweet_count': 0, 'reply_count': 1, 'like_c...   en  \n",
       "198  {'retweet_count': 0, 'reply_count': 0, 'like_c...   en  \n",
       "199  {'retweet_count': 3, 'reply_count': 0, 'like_c...   en  \n",
       "\n",
       "[200 rows x 6 columns]"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "my_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "7e9cf994",
   "metadata": {},
   "outputs": [],
   "source": [
    "my_df.to_csv('tedLassoAnalysis.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "02dc20bd",
   "metadata": {},
   "outputs": [],
   "source": [
    "lasso = pd.read_csv('tedLassoAnalysis.csv', encoding = 'utf-8')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cb1055a2",
   "metadata": {},
   "outputs": [],
   "source": [
    "lasso.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "780f500e",
   "metadata": {},
   "outputs": [],
   "source": [
    "lasso['lang'].astype('category')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "2afc8d16",
   "metadata": {},
   "outputs": [],
   "source": [
    "lasso_posts = lasso[(lasso['lang']) == 'en']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b36f8783",
   "metadata": {},
   "outputs": [],
   "source": [
    "lasso_posts['lang'].astype('category')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "67c06948",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      RT @goldenglobes: The #GoldenGlobes nominees f...\n",
       "1      RT @JarettSays: My heart feels so full when I ...\n",
       "2      RT @QUEERLASSO: I dont think we talk about thi...\n",
       "3      late to ted lasso but woowee that nate charact...\n",
       "4      RT @QUEERLASSO: I dont think we talk about thi...\n",
       "                             ...                        \n",
       "195    RT @BatatinhaGeek: As indicadas a 'Melhor Atri...\n",
       "196    RT @BatatinhaGeek: Os indicados a 'Melhor Ator...\n",
       "197    In honor of the holiday season and the upcomin...\n",
       "198     I miss Ted Lasso Twitter https://t.co/N5dQWP14hd\n",
       "199    RT @manvillebea: if there’s one thing the ted ...\n",
       "Name: text, Length: 193, dtype: object"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lasso_posts['text']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9393daca",
   "metadata": {},
   "outputs": [],
   "source": [
    "lasso_posts['text'].iloc[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5585ac33",
   "metadata": {},
   "outputs": [],
   "source": [
    "lasso_posts['text'].iloc[0].lower()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "ecddcab6",
   "metadata": {},
   "outputs": [],
   "source": [
    "lowercase = [x.lower() for x in lasso_posts['text']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d28a9ec7",
   "metadata": {},
   "outputs": [],
   "source": [
    "lowercase[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "992444ef",
   "metadata": {},
   "outputs": [],
   "source": [
    "from vaderSentiment.vaderSentiment import SentimentIntensityAnalyzer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "155f0d1e",
   "metadata": {},
   "outputs": [],
   "source": [
    "analyze= SentimentIntensityAnalyzer()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "3ab109c2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'neg': 0.0, 'neu': 1.0, 'pos': 0.0, 'compound': 0.0}\n"
     ]
    }
   ],
   "source": [
    "print(analyze.polarity_scores(lasso_posts['text'].iloc[3]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "c33c826e",
   "metadata": {},
   "outputs": [],
   "source": [
    "senti = analyze.polarity_scores(lasso_posts['text'].iloc[3])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "152322f4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.0"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "senti['neu']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "312a3dbd",
   "metadata": {},
   "outputs": [],
   "source": [
    "all_sents = [analyze.polarity_scores(x) for x in lasso_posts['text']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d0e80f6c",
   "metadata": {},
   "outputs": [],
   "source": [
    "all_sents"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "21ddc335",
   "metadata": {},
   "source": [
    "## Ted Lasso histogram"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d645644e",
   "metadata": {},
   "source": [
    "In this section I created all of the individual tweets sentiments into a dataframe so that it is easier to analyze. Although the dataframe does not give me much information so i visualized it by making a histogram for the positive and negative sentiment."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "847ae783",
   "metadata": {},
   "outputs": [],
   "source": [
    "sents_df = pd.DataFrame(all_sents)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "6e8ddd6c",
   "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>neg</th>\n",
       "      <th>neu</th>\n",
       "      <th>pos</th>\n",
       "      <th>compound</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.000</td>\n",
       "      <td>0.729</td>\n",
       "      <td>0.271</td>\n",
       "      <td>0.7717</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.000</td>\n",
       "      <td>0.769</td>\n",
       "      <td>0.231</td>\n",
       "      <td>0.6369</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0000</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>188</th>\n",
       "      <td>0.091</td>\n",
       "      <td>0.785</td>\n",
       "      <td>0.124</td>\n",
       "      <td>0.2023</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>189</th>\n",
       "      <td>0.087</td>\n",
       "      <td>0.794</td>\n",
       "      <td>0.119</td>\n",
       "      <td>0.2023</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>190</th>\n",
       "      <td>0.000</td>\n",
       "      <td>0.730</td>\n",
       "      <td>0.270</td>\n",
       "      <td>0.9551</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>191</th>\n",
       "      <td>0.242</td>\n",
       "      <td>0.758</td>\n",
       "      <td>0.000</td>\n",
       "      <td>-0.1531</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>192</th>\n",
       "      <td>0.095</td>\n",
       "      <td>0.905</td>\n",
       "      <td>0.000</td>\n",
       "      <td>-0.3182</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>193 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       neg    neu    pos  compound\n",
       "0    0.000  0.729  0.271    0.7717\n",
       "1    0.000  0.769  0.231    0.6369\n",
       "2    0.000  1.000  0.000    0.0000\n",
       "3    0.000  1.000  0.000    0.0000\n",
       "4    0.000  1.000  0.000    0.0000\n",
       "..     ...    ...    ...       ...\n",
       "188  0.091  0.785  0.124    0.2023\n",
       "189  0.087  0.794  0.119    0.2023\n",
       "190  0.000  0.730  0.270    0.9551\n",
       "191  0.242  0.758  0.000   -0.1531\n",
       "192  0.095  0.905  0.000   -0.3182\n",
       "\n",
       "[193 rows x 4 columns]"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sents_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "bfc815e5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    193.000000\n",
       "mean       0.130731\n",
       "std        0.142610\n",
       "min        0.000000\n",
       "25%        0.000000\n",
       "50%        0.087000\n",
       "75%        0.258000\n",
       "max        0.463000\n",
       "Name: pos, dtype: float64"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sents_df['pos'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "7a99d402",
   "metadata": {},
   "outputs": [],
   "source": [
    "from matplotlib import pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "48dcd388",
   "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": [
    "fig0, ax0 = plt.subplots()\n",
    "ax0.hist(sents_df['pos'])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "8b7d74b4",
   "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": [
    "fig1, ax1 = plt.subplots()\n",
    "ax1.hist(sents_df['neg'])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b4d28b44",
   "metadata": {},
   "source": [
    "## Ted Lasso complete histogram"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7b2a0333",
   "metadata": {},
   "source": [
    "Here I visualized each sentiment into its own histogram. Here you can see there are few negative tweets but looks like there are more positive tweets than negative."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "7317e581",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig4, ax4 = plt.subplots(1, 4, figsize = (10, 5))\n",
    "ax4[0].hist(sents_df['neg'], bins =  8, color = 'red')\n",
    "ax4[1].hist(sents_df['pos'], bins =  8, color = 'blue')\n",
    "ax4[2].hist(sents_df['neu'], bins =  8, color = 'green')\n",
    "ax4[3].hist(sents_df['compound'], bins =  8, color = 'yellow')\n",
    "\n",
    "ax4[0].set_xlabel(\"Negative\")\n",
    "ax4[1].set_xlabel(\"Positive\")\n",
    "ax4[2].set_xlabel(\"Neutrual\")\n",
    "ax4[3].set_xlabel(\"Compound\")\n",
    "\n",
    "fig4.suptitle(\"Ted Lasso Sentiments\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "6353eb90",
   "metadata": {},
   "outputs": [],
   "source": [
    "endpoint_url2 = 'https://api.twitter.com/2/tweets/search/recent'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "ba424e52",
   "metadata": {},
   "outputs": [],
   "source": [
    "query2 = urllib.parse.quote('(#blackish OR blackish lang:en)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "c242b3e8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'%28%23blackish%20OR%20blackish%20lang%3Aen%29'"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "query2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "a83fca19",
   "metadata": {},
   "outputs": [],
   "source": [
    "my_api_url3 = endpoint_url2 + '?query={}'.format(query2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "f72983e4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'https://api.twitter.com/2/tweets/search/recent?query=%28%23blackish%20OR%20blackish%20lang%3Aen%29'"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "my_api_url3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "a6d858ae",
   "metadata": {},
   "outputs": [],
   "source": [
    "tweet_fields2 = 'public_metrics,created_at,author_id,lang'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "a56866f5",
   "metadata": {},
   "outputs": [],
   "source": [
    "my_api_url2 = endpoint_url2 + '?query={}&tweet.fields={}'.format(query2, tweet_fields2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "81dbbf46",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'https://api.twitter.com/2/tweets/search/recent?query=%28%23blackish%20OR%20blackish%20lang%3Aen%29&tweet.fields=public_metrics,created_at,author_id,lang'"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "my_api_url2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "70fcbe65",
   "metadata": {},
   "outputs": [],
   "source": [
    "expansions2 = 'author_id'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "bd22ec33",
   "metadata": {},
   "outputs": [],
   "source": [
    "url2 = endpoint_url2 + '?query={}&max_results=10&tweet.fields{}'.format(query2, tweet_fields2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "91da7b72",
   "metadata": {},
   "outputs": [],
   "source": [
    "response2 = requests.request(\"GET\", url, headers = header)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "ef92bf7e",
   "metadata": {},
   "outputs": [],
   "source": [
    "url_expansions2 = endpoint_url2 + '?query={}&max_results=100&tweet.fields={}&expansions={}&user.fields={}'.format(query2, tweet_fields2, expansions2, 'username')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "6cd03ca2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'https://api.twitter.com/2/tweets/search/recent?query=%28%23blackish%20OR%20blackish%20lang%3Aen%29&max_results=100&tweet.fields=public_metrics,created_at,author_id,lang&expansions=author_id&user.fields=username'"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "url_expansions2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "cc34f186",
   "metadata": {},
   "outputs": [],
   "source": [
    "blackish_response = requests.request(\"GET\", url_expansions2, headers = header)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f0de62ef",
   "metadata": {},
   "outputs": [],
   "source": [
    "blackish_response.text"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "b7317061",
   "metadata": {},
   "outputs": [],
   "source": [
    "blackish_dict = json.loads(blackish_response.text)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "8928cedb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_keys(['data', 'includes', 'meta'])"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "blackish_dict.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "dbc0b86c",
   "metadata": {},
   "outputs": [],
   "source": [
    "blackish_df = pd.DataFrame(blackish_dict['data'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "58d15055",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>blackish-grey ossel hitch</td>\n",
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       "      <td>796444880675438592</td>\n",
       "      <td>en</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1470539014117765122</td>\n",
       "      <td>{'retweet_count': 2, 'reply_count': 0, 'like_c...</td>\n",
       "      <td>RT @IamW4TC: Congratulations @IssaRae and @Tra...</td>\n",
       "      <td>2021-12-13T23:39:56.000Z</td>\n",
       "      <td>957821109444972545</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1470527694148452358</td>\n",
       "      <td>{'retweet_count': 0, 'reply_count': 0, 'like_c...</td>\n",
       "      <td>And I really feel like they nominate Blackish ...</td>\n",
       "      <td>2021-12-13T22:54:58.000Z</td>\n",
       "      <td>26905493</td>\n",
       "      <td>en</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1470527263489802240</td>\n",
       "      <td>{'retweet_count': 0, 'reply_count': 1, 'like_c...</td>\n",
       "      <td>@Chemicalboyy Banshee\\nVikings\\nElites\\nBlacki...</td>\n",
       "      <td>2021-12-13T22:53:15.000Z</td>\n",
       "      <td>1080035996027273217</td>\n",
       "      <td>en</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1470520951964065796</td>\n",
       "      <td>{'retweet_count': 0, 'reply_count': 0, 'like_c...</td>\n",
       "      <td>3) Mejor actor principal en comedia #GlobosDeO...</td>\n",
       "      <td>2021-12-13T22:28:10.000Z</td>\n",
       "      <td>1863836348</td>\n",
       "      <td>es</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
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       "      <td>1470204422399610884</td>\n",
       "      <td>{'retweet_count': 0, 'reply_count': 0, 'like_c...</td>\n",
       "      <td>Blackish be so inspiring like I wanna be succe...</td>\n",
       "      <td>2021-12-13T01:30:24.000Z</td>\n",
       "      <td>2398245080</td>\n",
       "      <td>en</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>1470203673200537601</td>\n",
       "      <td>{'retweet_count': 2, 'reply_count': 0, 'like_c...</td>\n",
       "      <td>RT @johnrfisher1: Been kinda snowbound of late...</td>\n",
       "      <td>2021-12-13T01:27:25.000Z</td>\n",
       "      <td>1463583253714059269</td>\n",
       "      <td>en</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>1470202539828289537</td>\n",
       "      <td>{'retweet_count': 3, 'reply_count': 0, 'like_c...</td>\n",
       "      <td>RT @ChastyRaunchSub: A third item from the AC ...</td>\n",
       "      <td>2021-12-13T01:22:55.000Z</td>\n",
       "      <td>1328506635397046273</td>\n",
       "      <td>en</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>1470193554962145282</td>\n",
       "      <td>{'retweet_count': 0, 'reply_count': 0, 'like_c...</td>\n",
       "      <td>The tv show Blackish is racist, unless there i...</td>\n",
       "      <td>2021-12-13T00:47:13.000Z</td>\n",
       "      <td>1319384189968461826</td>\n",
       "      <td>en</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>1470192856186990595</td>\n",
       "      <td>{'retweet_count': 0, 'reply_count': 0, 'like_c...</td>\n",
       "      <td>Blackish is ending? A show I swore I'd never w...</td>\n",
       "      <td>2021-12-13T00:44:26.000Z</td>\n",
       "      <td>242948954</td>\n",
       "      <td>en</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>100 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                     id                                     public_metrics  \\\n",
       "0   1470539115921870855  {'retweet_count': 0, 'reply_count': 0, 'like_c...   \n",
       "1   1470539014117765122  {'retweet_count': 2, 'reply_count': 0, 'like_c...   \n",
       "2   1470527694148452358  {'retweet_count': 0, 'reply_count': 0, 'like_c...   \n",
       "3   1470527263489802240  {'retweet_count': 0, 'reply_count': 1, 'like_c...   \n",
       "4   1470520951964065796  {'retweet_count': 0, 'reply_count': 0, 'like_c...   \n",
       "..                  ...                                                ...   \n",
       "95  1470204422399610884  {'retweet_count': 0, 'reply_count': 0, 'like_c...   \n",
       "96  1470203673200537601  {'retweet_count': 2, 'reply_count': 0, 'like_c...   \n",
       "97  1470202539828289537  {'retweet_count': 3, 'reply_count': 0, 'like_c...   \n",
       "98  1470193554962145282  {'retweet_count': 0, 'reply_count': 0, 'like_c...   \n",
       "99  1470192856186990595  {'retweet_count': 0, 'reply_count': 0, 'like_c...   \n",
       "\n",
       "                                                 text  \\\n",
       "0                           blackish-grey ossel hitch   \n",
       "1   RT @IamW4TC: Congratulations @IssaRae and @Tra...   \n",
       "2   And I really feel like they nominate Blackish ...   \n",
       "3   @Chemicalboyy Banshee\\nVikings\\nElites\\nBlacki...   \n",
       "4   3) Mejor actor principal en comedia #GlobosDeO...   \n",
       "..                                                ...   \n",
       "95  Blackish be so inspiring like I wanna be succe...   \n",
       "96  RT @johnrfisher1: Been kinda snowbound of late...   \n",
       "97  RT @ChastyRaunchSub: A third item from the AC ...   \n",
       "98  The tv show Blackish is racist, unless there i...   \n",
       "99  Blackish is ending? A show I swore I'd never w...   \n",
       "\n",
       "                  created_at            author_id lang  \n",
       "0   2021-12-13T23:40:21.000Z   796444880675438592   en  \n",
       "1   2021-12-13T23:39:56.000Z   957821109444972545   en  \n",
       "2   2021-12-13T22:54:58.000Z             26905493   en  \n",
       "3   2021-12-13T22:53:15.000Z  1080035996027273217   en  \n",
       "4   2021-12-13T22:28:10.000Z           1863836348   es  \n",
       "..                       ...                  ...  ...  \n",
       "95  2021-12-13T01:30:24.000Z           2398245080   en  \n",
       "96  2021-12-13T01:27:25.000Z  1463583253714059269   en  \n",
       "97  2021-12-13T01:22:55.000Z  1328506635397046273   en  \n",
       "98  2021-12-13T00:47:13.000Z  1319384189968461826   en  \n",
       "99  2021-12-13T00:44:26.000Z            242948954   en  \n",
       "\n",
       "[100 rows x 6 columns]"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "blackish_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "fabba9b0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'newest_id': '1470539115921870855',\n",
       " 'oldest_id': '1470192856186990595',\n",
       " 'result_count': 100,\n",
       " 'next_token': 'b26v89c19zqg8o3fpe15c4662ywe1xnmve7tuh31tur25'}"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "blackish_dict['meta']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "8f9b5d7f",
   "metadata": {},
   "outputs": [],
   "source": [
    "my_api_url4 = my_api_url2 + '&next_token={}&max_results=100'.format(blackish_dict['meta']['next_token'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "12502066",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'https://api.twitter.com/2/tweets/search/recent?query=%28%23blackish%20OR%20blackish%20lang%3Aen%29&tweet.fields=public_metrics,created_at,author_id,lang&next_token=b26v89c19zqg8o3fpe15c4662ywe1xnmve7tuh31tur25&max_results=100'"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "my_api_url4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "c1565190",
   "metadata": {},
   "outputs": [],
   "source": [
    "blackish2_response = requests.request(\"GET\", my_api_url4, headers = header)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cee7f0af",
   "metadata": {},
   "outputs": [],
   "source": [
    "blackish2_response.text"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "7ae3d759",
   "metadata": {},
   "outputs": [],
   "source": [
    "blackish_df = blackish_df.append(pd.DataFrame(json.loads(blackish2_response.text)['data']), ignore_index= True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "2b7642d5",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>public_metrics</th>\n",
       "      <th>text</th>\n",
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       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1470539115921870855</td>\n",
       "      <td>{'retweet_count': 0, 'reply_count': 0, 'like_c...</td>\n",
       "      <td>blackish-grey ossel hitch</td>\n",
       "      <td>2021-12-13T23:40:21.000Z</td>\n",
       "      <td>796444880675438592</td>\n",
       "      <td>en</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1470539014117765122</td>\n",
       "      <td>{'retweet_count': 2, 'reply_count': 0, 'like_c...</td>\n",
       "      <td>RT @IamW4TC: Congratulations @IssaRae and @Tra...</td>\n",
       "      <td>2021-12-13T23:39:56.000Z</td>\n",
       "      <td>957821109444972545</td>\n",
       "      <td>en</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1470527694148452358</td>\n",
       "      <td>{'retweet_count': 0, 'reply_count': 0, 'like_c...</td>\n",
       "      <td>And I really feel like they nominate Blackish ...</td>\n",
       "      <td>2021-12-13T22:54:58.000Z</td>\n",
       "      <td>26905493</td>\n",
       "      <td>en</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1470527263489802240</td>\n",
       "      <td>{'retweet_count': 0, 'reply_count': 1, 'like_c...</td>\n",
       "      <td>@Chemicalboyy Banshee\\nVikings\\nElites\\nBlacki...</td>\n",
       "      <td>2021-12-13T22:53:15.000Z</td>\n",
       "      <td>1080035996027273217</td>\n",
       "      <td>en</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1470520951964065796</td>\n",
       "      <td>{'retweet_count': 0, 'reply_count': 0, 'like_c...</td>\n",
       "      <td>3) Mejor actor principal en comedia #GlobosDeO...</td>\n",
       "      <td>2021-12-13T22:28:10.000Z</td>\n",
       "      <td>1863836348</td>\n",
       "      <td>es</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>195</th>\n",
       "      <td>1469655354086760451</td>\n",
       "      <td>{'retweet_count': 1, 'reply_count': 0, 'like_c...</td>\n",
       "      <td>That girl from Blackish... https://t.co/JNoPuq...</td>\n",
       "      <td>2021-12-11T13:08:35.000Z</td>\n",
       "      <td>984971006245769216</td>\n",
       "      <td>en</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196</th>\n",
       "      <td>1469651840207884288</td>\n",
       "      <td>{'retweet_count': 15, 'reply_count': 0, 'like_...</td>\n",
       "      <td>RT @_myvpl_: @NCares17 @jessicawhitIly Yh it w...</td>\n",
       "      <td>2021-12-11T12:54:38.000Z</td>\n",
       "      <td>387132443</td>\n",
       "      <td>en</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>1469648138906763267</td>\n",
       "      <td>{'retweet_count': 15, 'reply_count': 0, 'like_...</td>\n",
       "      <td>RT @_myvpl_: @NCares17 @jessicawhitIly Yh it w...</td>\n",
       "      <td>2021-12-11T12:39:55.000Z</td>\n",
       "      <td>452280828</td>\n",
       "      <td>en</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>198</th>\n",
       "      <td>1469624514417991681</td>\n",
       "      <td>{'retweet_count': 195, 'reply_count': 0, 'like...</td>\n",
       "      <td>RT @VasuBharat09: It's a ray.\\nLight and warmt...</td>\n",
       "      <td>2021-12-11T11:06:03.000Z</td>\n",
       "      <td>813312379509506049</td>\n",
       "      <td>en</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>199</th>\n",
       "      <td>1469622812642091010</td>\n",
       "      <td>{'retweet_count': 6, 'reply_count': 0, 'like_c...</td>\n",
       "      <td>RT @TvBoxSA: اعلنت @ABCNetwork تجديد المسلسل ا...</td>\n",
       "      <td>2021-12-11T10:59:17.000Z</td>\n",
       "      <td>1067634457</td>\n",
       "      <td>ar</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>200 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                      id                                     public_metrics  \\\n",
       "0    1470539115921870855  {'retweet_count': 0, 'reply_count': 0, 'like_c...   \n",
       "1    1470539014117765122  {'retweet_count': 2, 'reply_count': 0, 'like_c...   \n",
       "2    1470527694148452358  {'retweet_count': 0, 'reply_count': 0, 'like_c...   \n",
       "3    1470527263489802240  {'retweet_count': 0, 'reply_count': 1, 'like_c...   \n",
       "4    1470520951964065796  {'retweet_count': 0, 'reply_count': 0, 'like_c...   \n",
       "..                   ...                                                ...   \n",
       "195  1469655354086760451  {'retweet_count': 1, 'reply_count': 0, 'like_c...   \n",
       "196  1469651840207884288  {'retweet_count': 15, 'reply_count': 0, 'like_...   \n",
       "197  1469648138906763267  {'retweet_count': 15, 'reply_count': 0, 'like_...   \n",
       "198  1469624514417991681  {'retweet_count': 195, 'reply_count': 0, 'like...   \n",
       "199  1469622812642091010  {'retweet_count': 6, 'reply_count': 0, 'like_c...   \n",
       "\n",
       "                                                  text  \\\n",
       "0                            blackish-grey ossel hitch   \n",
       "1    RT @IamW4TC: Congratulations @IssaRae and @Tra...   \n",
       "2    And I really feel like they nominate Blackish ...   \n",
       "3    @Chemicalboyy Banshee\\nVikings\\nElites\\nBlacki...   \n",
       "4    3) Mejor actor principal en comedia #GlobosDeO...   \n",
       "..                                                 ...   \n",
       "195  That girl from Blackish... https://t.co/JNoPuq...   \n",
       "196  RT @_myvpl_: @NCares17 @jessicawhitIly Yh it w...   \n",
       "197  RT @_myvpl_: @NCares17 @jessicawhitIly Yh it w...   \n",
       "198  RT @VasuBharat09: It's a ray.\\nLight and warmt...   \n",
       "199  RT @TvBoxSA: اعلنت @ABCNetwork تجديد المسلسل ا...   \n",
       "\n",
       "                   created_at            author_id lang  \n",
       "0    2021-12-13T23:40:21.000Z   796444880675438592   en  \n",
       "1    2021-12-13T23:39:56.000Z   957821109444972545   en  \n",
       "2    2021-12-13T22:54:58.000Z             26905493   en  \n",
       "3    2021-12-13T22:53:15.000Z  1080035996027273217   en  \n",
       "4    2021-12-13T22:28:10.000Z           1863836348   es  \n",
       "..                        ...                  ...  ...  \n",
       "195  2021-12-11T13:08:35.000Z   984971006245769216   en  \n",
       "196  2021-12-11T12:54:38.000Z            387132443   en  \n",
       "197  2021-12-11T12:39:55.000Z            452280828   en  \n",
       "198  2021-12-11T11:06:03.000Z   813312379509506049   en  \n",
       "199  2021-12-11T10:59:17.000Z           1067634457   ar  \n",
       "\n",
       "[200 rows x 6 columns]"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "blackish_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "4d77e082",
   "metadata": {},
   "outputs": [],
   "source": [
    "blackish_df.to_csv('blackishAnalysis.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "d1bdeeb3",
   "metadata": {},
   "outputs": [],
   "source": [
    "blackish = pd.read_csv('blackishAnalysis.csv', encoding = 'utf-8')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "406aef93",
   "metadata": {},
   "outputs": [],
   "source": [
    "blackish.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "02fc8c20",
   "metadata": {},
   "outputs": [],
   "source": [
    "blackish['lang'].astype('category')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "id": "1d99ca98",
   "metadata": {},
   "outputs": [],
   "source": [
    "blackish_posts = blackish[(blackish['lang']) == 'en']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9b52f249",
   "metadata": {},
   "outputs": [],
   "source": [
    "blackish_posts['lang'].astype('category')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "id": "03e00c7c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0                              blackish-grey ossel hitch\n",
       "1      RT @IamW4TC: Congratulations @IssaRae and @Tra...\n",
       "2      And I really feel like they nominate Blackish ...\n",
       "3      @Chemicalboyy Banshee\\nVikings\\nElites\\nBlacki...\n",
       "5      2) Mejor actriz principal en comedia #GlobosDe...\n",
       "                             ...                        \n",
       "194           RT @hetros2022: That girl from Blackish...\n",
       "195    That girl from Blackish... https://t.co/JNoPuq...\n",
       "196    RT @_myvpl_: @NCares17 @jessicawhitIly Yh it w...\n",
       "197    RT @_myvpl_: @NCares17 @jessicawhitIly Yh it w...\n",
       "198    RT @VasuBharat09: It's a ray.\\nLight and warmt...\n",
       "Name: text, Length: 193, dtype: object"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "blackish_posts['text']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "472008f3",
   "metadata": {},
   "outputs": [],
   "source": [
    "blackish_posts['text'].iloc[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "2fce1128",
   "metadata": {},
   "outputs": [],
   "source": [
    "blackish_lowercase = [x.lower() for x in blackish_posts['text']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f7dcc9ad",
   "metadata": {},
   "outputs": [],
   "source": [
    "blackish_lowercase[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "fe5dff36",
   "metadata": {},
   "outputs": [],
   "source": [
    "blackish_analyze= SentimentIntensityAnalyzer()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "e9d1ccc1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'neg': 0.0, 'neu': 1.0, 'pos': 0.0, 'compound': 0.0}\n"
     ]
    }
   ],
   "source": [
    "print(blackish_analyze.polarity_scores(blackish_posts['text'].iloc[0]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "id": "e3797a28",
   "metadata": {},
   "outputs": [],
   "source": [
    "blackish_senti = blackish_analyze.polarity_scores(blackish_posts['text'].iloc[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "id": "a30df947",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "blackish_senti['neg']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "id": "4c866fad",
   "metadata": {},
   "outputs": [],
   "source": [
    "all_bsenti = [blackish_analyze.polarity_scores(x) for x in blackish_posts['text']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "id": "bb4b5546",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'neg': 0.0, 'neu': 1.0, 'pos': 0.0, 'compound': 0.0},\n",
       " {'neg': 0.0, 'neu': 0.69, 'pos': 0.31, 'compound': 0.8442},\n",
       " {'neg': 0.207, 'neu': 0.692, 'pos': 0.101, 'compound': -0.4441},\n",
       " {'neg': 0.0, 'neu': 1.0, 'pos': 0.0, 'compound': 0.0},\n",
       " {'neg': 0.102, 'neu': 0.8, 'pos': 0.098, 'compound': -0.0258},\n",
       " {'neg': 0.0, 'neu': 0.633, 'pos': 0.367, 'compound': 0.4404},\n",
       " {'neg': 0.0, 'neu': 0.873, 'pos': 0.127, 'compound': 0.7506},\n",
       " {'neg': 0.0, 'neu': 0.344, 'pos': 0.656, 'compound': 0.9855},\n",
       " {'neg': 0.0, 'neu': 0.676, 'pos': 0.324, 'compound': 0.8016},\n",
       " {'neg': 0.099, 'neu': 0.734, 'pos': 0.166, 'compound': 0.3155},\n",
       " {'neg': 0.281, 'neu': 0.514, 'pos': 0.206, 'compound': -0.7136},\n",
       " {'neg': 0.153, 'neu': 0.625, 'pos': 0.222, 'compound': 0.25},\n",
       " {'neg': 0.06, 'neu': 0.94, 'pos': 0.0, 'compound': -0.3736},\n",
       " {'neg': 0.096, 'neu': 0.814, 'pos': 0.09, 'compound': -0.0931},\n",
       " {'neg': 0.0, 'neu': 1.0, 'pos': 0.0, 'compound': 0.0},\n",
       " {'neg': 0.216, 'neu': 0.607, 'pos': 0.177, 'compound': -0.0711},\n",
       " {'neg': 0.024, 'neu': 0.726, 'pos': 0.25, 'compound': 0.9459},\n",
       " {'neg': 0.041, 'neu': 0.865, 'pos': 0.094, 'compound': 0.2846},\n",
       " {'neg': 0.0, 'neu': 0.902, 'pos': 0.098, 'compound': 0.0772},\n",
       " {'neg': 0.282, 'neu': 0.718, 'pos': 0.0, 'compound': -0.6249},\n",
       " {'neg': 0.0, 'neu': 0.69, 'pos': 0.31, 'compound': 0.8442},\n",
       " {'neg': 0.0, 'neu': 0.353, 'pos': 0.647, 'compound': 0.6705},\n",
       " {'neg': 0.034, 'neu': 0.966, 'pos': 0.0, 'compound': -0.0516},\n",
       " {'neg': 0.211, 'neu': 0.789, 'pos': 0.0, 'compound': -0.34},\n",
       " {'neg': 0.131, 'neu': 0.802, 'pos': 0.067, 'compound': -0.5994},\n",
       " {'neg': 0.0, 'neu': 0.913, 'pos': 0.087, 'compound': 0.4501},\n",
       " {'neg': 0.09, 'neu': 0.581, 'pos': 0.328, 'compound': 0.8974},\n",
       " {'neg': 0.211, 'neu': 0.789, 'pos': 0.0, 'compound': -0.34},\n",
       " {'neg': 0.0, 'neu': 0.508, 'pos': 0.492, 'compound': 0.7003},\n",
       " {'neg': 0.0, 'neu': 0.947, 'pos': 0.053, 'compound': 0.34},\n",
       " {'neg': 0.0, 'neu': 1.0, 'pos': 0.0, 'compound': 0.0},\n",
       " {'neg': 0.0, 'neu': 0.822, 'pos': 0.178, 'compound': 0.3818},\n",
       " {'neg': 0.0, 'neu': 0.375, 'pos': 0.625, 'compound': 0.875},\n",
       " {'neg': 0.211, 'neu': 0.789, 'pos': 0.0, 'compound': -0.34},\n",
       " {'neg': 0.245, 'neu': 0.682, 'pos': 0.073, 'compound': -0.8902},\n",
       " {'neg': 0.081, 'neu': 0.605, 'pos': 0.314, 'compound': 0.8439},\n",
       " {'neg': 0.0, 'neu': 0.525, 'pos': 0.475, 'compound': 0.9517},\n",
       " {'neg': 0.0, 'neu': 0.624, 'pos': 0.376, 'compound': 0.9524},\n",
       " {'neg': 0.0, 'neu': 0.691, 'pos': 0.309, 'compound': 0.7399},\n",
       " {'neg': 0.0, 'neu': 0.857, 'pos': 0.143, 'compound': 0.3612},\n",
       " {'neg': 0.29, 'neu': 0.588, 'pos': 0.122, 'compound': -0.6124},\n",
       " {'neg': 0.0, 'neu': 0.82, 'pos': 0.18, 'compound': 0.5106},\n",
       " {'neg': 0.0, 'neu': 0.712, 'pos': 0.288, 'compound': 0.7708},\n",
       " {'neg': 0.138, 'neu': 0.623, 'pos': 0.239, 'compound': 0.5046},\n",
       " {'neg': 0.056, 'neu': 0.944, 'pos': 0.0, 'compound': -0.1655},\n",
       " {'neg': 0.231, 'neu': 0.769, 'pos': 0.0, 'compound': -0.4019},\n",
       " {'neg': 0.088, 'neu': 0.912, 'pos': 0.0, 'compound': -0.34},\n",
       " {'neg': 0.211, 'neu': 0.789, 'pos': 0.0, 'compound': -0.34},\n",
       " {'neg': 0.0, 'neu': 1.0, 'pos': 0.0, 'compound': 0.0},\n",
       " {'neg': 0.211, 'neu': 0.789, 'pos': 0.0, 'compound': -0.34},\n",
       " {'neg': 0.211, 'neu': 0.789, 'pos': 0.0, 'compound': -0.34},\n",
       " {'neg': 0.211, 'neu': 0.789, 'pos': 0.0, 'compound': -0.34},\n",
       " {'neg': 0.211, 'neu': 0.789, 'pos': 0.0, 'compound': -0.34},\n",
       " {'neg': 0.211, 'neu': 0.789, 'pos': 0.0, 'compound': -0.34},\n",
       " {'neg': 0.0, 'neu': 0.753, 'pos': 0.247, 'compound': 0.5574},\n",
       " {'neg': 0.1, 'neu': 0.588, 'pos': 0.311, 'compound': 0.7269},\n",
       " {'neg': 0.208, 'neu': 0.708, 'pos': 0.085, 'compound': -0.3541},\n",
       " {'neg': 0.211, 'neu': 0.789, 'pos': 0.0, 'compound': -0.34},\n",
       " {'neg': 0.211, 'neu': 0.789, 'pos': 0.0, 'compound': -0.34},\n",
       " {'neg': 0.211, 'neu': 0.789, 'pos': 0.0, 'compound': -0.34},\n",
       " {'neg': 0.211, 'neu': 0.789, 'pos': 0.0, 'compound': -0.34},\n",
       " {'neg': 0.211, 'neu': 0.789, 'pos': 0.0, 'compound': -0.34},\n",
       " {'neg': 0.211, 'neu': 0.789, 'pos': 0.0, 'compound': -0.34},\n",
       " {'neg': 0.211, 'neu': 0.789, 'pos': 0.0, 'compound': -0.34},\n",
       " {'neg': 0.211, 'neu': 0.789, 'pos': 0.0, 'compound': -0.34},\n",
       " {'neg': 0.211, 'neu': 0.789, 'pos': 0.0, 'compound': -0.34},\n",
       " {'neg': 0.255, 'neu': 0.745, 'pos': 0.0, 'compound': -0.34},\n",
       " {'neg': 0.0, 'neu': 1.0, 'pos': 0.0, 'compound': 0.0},\n",
       " {'neg': 0.0, 'neu': 1.0, 'pos': 0.0, 'compound': 0.0},\n",
       " {'neg': 0.0, 'neu': 1.0, 'pos': 0.0, 'compound': 0.0},\n",
       " {'neg': 0.0, 'neu': 1.0, 'pos': 0.0, 'compound': 0.0},\n",
       " {'neg': 0.0, 'neu': 1.0, 'pos': 0.0, 'compound': 0.0},\n",
       " {'neg': 0.0, 'neu': 0.543, 'pos': 0.457, 'compound': 0.6369},\n",
       " {'neg': 0.0, 'neu': 0.679, 'pos': 0.321, 'compound': 0.6369},\n",
       " {'neg': 0.203, 'neu': 0.482, 'pos': 0.315, 'compound': 0.7998},\n",
       " {'neg': 0.0, 'neu': 1.0, 'pos': 0.0, 'compound': 0.0},\n",
       " {'neg': 0.0, 'neu': 1.0, 'pos': 0.0, 'compound': 0.0},\n",
       " {'neg': 0.0, 'neu': 1.0, 'pos': 0.0, 'compound': 0.0},\n",
       " {'neg': 0.0, 'neu': 0.904, 'pos': 0.096, 'compound': 0.3716},\n",
       " {'neg': 0.048, 'neu': 0.783, 'pos': 0.169, 'compound': 0.7156},\n",
       " {'neg': 0.0, 'neu': 1.0, 'pos': 0.0, 'compound': 0.0},\n",
       " {'neg': 0.385, 'neu': 0.615, 'pos': 0.0, 'compound': -0.3612},\n",
       " {'neg': 0.0, 'neu': 1.0, 'pos': 0.0, 'compound': 0.0},\n",
       " {'neg': 0.0, 'neu': 0.891, 'pos': 0.109, 'compound': 0.4019},\n",
       " {'neg': 0.0, 'neu': 1.0, 'pos': 0.0, 'compound': 0.0},\n",
       " {'neg': 0.127, 'neu': 0.574, 'pos': 0.299, 'compound': 0.4939},\n",
       " {'neg': 0.196, 'neu': 0.804, 'pos': 0.0, 'compound': -0.296},\n",
       " {'neg': 0.0, 'neu': 0.779, 'pos': 0.221, 'compound': 0.6597},\n",
       " {'neg': 0.0, 'neu': 1.0, 'pos': 0.0, 'compound': 0.0},\n",
       " {'neg': 0.0, 'neu': 0.832, 'pos': 0.168, 'compound': 0.872},\n",
       " {'neg': 0.0, 'neu': 0.519, 'pos': 0.481, 'compound': 0.8805},\n",
       " {'neg': 0.0, 'neu': 1.0, 'pos': 0.0, 'compound': 0.0},\n",
       " {'neg': 0.0, 'neu': 0.909, 'pos': 0.091, 'compound': 0.2732},\n",
       " {'neg': 0.248, 'neu': 0.752, 'pos': 0.0, 'compound': -0.6476},\n",
       " {'neg': 0.0, 'neu': 0.813, 'pos': 0.187, 'compound': 0.5704},\n",
       " {'neg': 0.0, 'neu': 0.429, 'pos': 0.571, 'compound': 0.8402},\n",
       " {'neg': 0.0, 'neu': 0.909, 'pos': 0.091, 'compound': 0.2732},\n",
       " {'neg': 0.04, 'neu': 0.907, 'pos': 0.053, 'compound': 0.1779},\n",
       " {'neg': 0.068, 'neu': 0.738, 'pos': 0.194, 'compound': 0.7184},\n",
       " {'neg': 0.0, 'neu': 0.905, 'pos': 0.095, 'compound': 0.4767},\n",
       " {'neg': 0.0, 'neu': 0.909, 'pos': 0.091, 'compound': 0.2732},\n",
       " {'neg': 0.231, 'neu': 0.769, 'pos': 0.0, 'compound': -0.7518},\n",
       " {'neg': 0.0, 'neu': 0.933, 'pos': 0.067, 'compound': 0.3182},\n",
       " {'neg': 0.0, 'neu': 1.0, 'pos': 0.0, 'compound': 0.0},\n",
       " {'neg': 0.0, 'neu': 1.0, 'pos': 0.0, 'compound': 0.0},\n",
       " {'neg': 0.085, 'neu': 0.813, 'pos': 0.102, 'compound': -0.2846},\n",
       " {'neg': 0.0, 'neu': 0.854, 'pos': 0.146, 'compound': 0.627},\n",
       " {'neg': 0.0, 'neu': 0.852, 'pos': 0.148, 'compound': 0.8388},\n",
       " {'neg': 0.127, 'neu': 0.728, 'pos': 0.144, 'compound': 0.34},\n",
       " {'neg': 0.0, 'neu': 0.853, 'pos': 0.147, 'compound': 0.6369},\n",
       " {'neg': 0.0, 'neu': 0.911, 'pos': 0.089, 'compound': 0.5106},\n",
       " {'neg': 0.0, 'neu': 0.798, 'pos': 0.202, 'compound': 0.6486},\n",
       " {'neg': 0.0, 'neu': 0.843, 'pos': 0.157, 'compound': 0.7515},\n",
       " {'neg': 0.0, 'neu': 0.924, 'pos': 0.076, 'compound': 0.34},\n",
       " {'neg': 0.03, 'neu': 0.913, 'pos': 0.057, 'compound': 0.0772},\n",
       " {'neg': 0.0, 'neu': 0.798, 'pos': 0.202, 'compound': 0.5106},\n",
       " {'neg': 0.0, 'neu': 0.769, 'pos': 0.231, 'compound': 0.5106},\n",
       " {'neg': 0.0, 'neu': 1.0, 'pos': 0.0, 'compound': 0.0},\n",
       " {'neg': 0.0, 'neu': 1.0, 'pos': 0.0, 'compound': 0.0},\n",
       " {'neg': 0.0, 'neu': 0.816, 'pos': 0.184, 'compound': 0.8399},\n",
       " {'neg': 0.215, 'neu': 0.545, 'pos': 0.24, 'compound': 0.1436},\n",
       " {'neg': 0.0, 'neu': 0.779, 'pos': 0.221, 'compound': 0.6588},\n",
       " {'neg': 0.0, 'neu': 1.0, 'pos': 0.0, 'compound': 0.0},\n",
       " {'neg': 0.0, 'neu': 0.444, 'pos': 0.556, 'compound': 0.3612},\n",
       " {'neg': 0.0, 'neu': 0.621, 'pos': 0.379, 'compound': 0.6705},\n",
       " {'neg': 0.0, 'neu': 0.899, 'pos': 0.101, 'compound': 0.4003},\n",
       " {'neg': 0.0, 'neu': 1.0, 'pos': 0.0, 'compound': 0.0},\n",
       " {'neg': 0.0, 'neu': 0.444, 'pos': 0.556, 'compound': 0.3612},\n",
       " {'neg': 0.0, 'neu': 0.445, 'pos': 0.555, 'compound': 0.5777},\n",
       " {'neg': 0.0, 'neu': 0.535, 'pos': 0.465, 'compound': 0.787},\n",
       " {'neg': 0.0, 'neu': 1.0, 'pos': 0.0, 'compound': 0.0},\n",
       " {'neg': 0.0, 'neu': 1.0, 'pos': 0.0, 'compound': 0.0},\n",
       " {'neg': 0.0, 'neu': 1.0, 'pos': 0.0, 'compound': 0.0},\n",
       " {'neg': 0.169, 'neu': 0.535, 'pos': 0.296, 'compound': 0.908},\n",
       " {'neg': 0.086, 'neu': 0.624, 'pos': 0.289, 'compound': 0.7063},\n",
       " {'neg': 0.092, 'neu': 0.596, 'pos': 0.311, 'compound': 0.7063},\n",
       " {'neg': 0.028, 'neu': 0.866, 'pos': 0.107, 'compound': 0.7622},\n",
       " {'neg': 0.0, 'neu': 1.0, 'pos': 0.0, 'compound': 0.0},\n",
       " {'neg': 0.338, 'neu': 0.662, 'pos': 0.0, 'compound': -0.5574},\n",
       " {'neg': 0.351, 'neu': 0.649, 'pos': 0.0, 'compound': -0.4019},\n",
       " {'neg': 0.0, 'neu': 0.633, 'pos': 0.367, 'compound': 0.4404},\n",
       " {'neg': 0.0, 'neu': 0.643, 'pos': 0.357, 'compound': 0.7273},\n",
       " {'neg': 0.0, 'neu': 1.0, 'pos': 0.0, 'compound': 0.0},\n",
       " {'neg': 0.112, 'neu': 0.77, 'pos': 0.119, 'compound': -0.2865},\n",
       " {'neg': 0.0, 'neu': 0.815, 'pos': 0.185, 'compound': 0.3612},\n",
       " {'neg': 0.0, 'neu': 0.828, 'pos': 0.172, 'compound': 0.3612},\n",
       " {'neg': 0.209, 'neu': 0.791, 'pos': 0.0, 'compound': -0.5719},\n",
       " {'neg': 0.155, 'neu': 0.845, 'pos': 0.0, 'compound': -0.6486},\n",
       " {'neg': 0.0, 'neu': 0.867, 'pos': 0.133, 'compound': 0.3818},\n",
       " {'neg': 0.086, 'neu': 0.667, 'pos': 0.247, 'compound': 0.7579},\n",
       " {'neg': 0.201, 'neu': 0.625, 'pos': 0.174, 'compound': -0.1531},\n",
       " {'neg': 0.0, 'neu': 0.767, 'pos': 0.233, 'compound': 0.743},\n",
       " {'neg': 0.0, 'neu': 1.0, 'pos': 0.0, 'compound': 0.0},\n",
       " {'neg': 0.0, 'neu': 1.0, 'pos': 0.0, 'compound': 0.0},\n",
       " {'neg': 0.0, 'neu': 1.0, 'pos': 0.0, 'compound': 0.0},\n",
       " {'neg': 0.204, 'neu': 0.389, 'pos': 0.408, 'compound': 0.969},\n",
       " {'neg': 0.0, 'neu': 1.0, 'pos': 0.0, 'compound': 0.0},\n",
       " {'neg': 0.0, 'neu': 1.0, 'pos': 0.0, 'compound': 0.0},\n",
       " {'neg': 0.0, 'neu': 1.0, 'pos': 0.0, 'compound': 0.0},\n",
       " {'neg': 0.0, 'neu': 1.0, 'pos': 0.0, 'compound': 0.0},\n",
       " {'neg': 0.0, 'neu': 1.0, 'pos': 0.0, 'compound': 0.0},\n",
       " {'neg': 0.0, 'neu': 0.947, 'pos': 0.053, 'compound': 0.4173},\n",
       " {'neg': 0.08, 'neu': 0.92, 'pos': 0.0, 'compound': -0.0772},\n",
       " {'neg': 0.0, 'neu': 1.0, 'pos': 0.0, 'compound': 0.0},\n",
       " {'neg': 0.445, 'neu': 0.555, 'pos': 0.0, 'compound': -0.9436},\n",
       " {'neg': 0.0, 'neu': 1.0, 'pos': 0.0, 'compound': 0.0},\n",
       " {'neg': 0.0, 'neu': 1.0, 'pos': 0.0, 'compound': 0.0},\n",
       " {'neg': 0.053, 'neu': 0.825, 'pos': 0.121, 'compound': 0.4215},\n",
       " {'neg': 0.0, 'neu': 1.0, 'pos': 0.0, 'compound': 0.0},\n",
       " {'neg': 0.0, 'neu': 0.741, 'pos': 0.259, 'compound': 0.4199},\n",
       " {'neg': 0.0, 'neu': 0.905, 'pos': 0.095, 'compound': 0.2975},\n",
       " {'neg': 0.136, 'neu': 0.864, 'pos': 0.0, 'compound': -0.296},\n",
       " {'neg': 0.0, 'neu': 1.0, 'pos': 0.0, 'compound': 0.0},\n",
       " {'neg': 0.0, 'neu': 1.0, 'pos': 0.0, 'compound': 0.0},\n",
       " {'neg': 0.262, 'neu': 0.738, 'pos': 0.0, 'compound': -0.4939},\n",
       " {'neg': 0.0, 'neu': 0.588, 'pos': 0.412, 'compound': 0.8885},\n",
       " {'neg': 0.0, 'neu': 0.798, 'pos': 0.202, 'compound': 0.6486},\n",
       " {'neg': 0.0, 'neu': 0.798, 'pos': 0.202, 'compound': 0.6486},\n",
       " {'neg': 0.187, 'neu': 0.813, 'pos': 0.0, 'compound': -0.6486},\n",
       " {'neg': 0.0, 'neu': 1.0, 'pos': 0.0, 'compound': 0.0},\n",
       " {'neg': 0.187, 'neu': 0.813, 'pos': 0.0, 'compound': -0.6486},\n",
       " {'neg': 0.052, 'neu': 0.708, 'pos': 0.24, 'compound': 0.7845},\n",
       " {'neg': 0.0, 'neu': 0.496, 'pos': 0.504, 'compound': 0.7269},\n",
       " {'neg': 0.157, 'neu': 0.843, 'pos': 0.0, 'compound': -0.68},\n",
       " {'neg': 0.0, 'neu': 0.8, 'pos': 0.2, 'compound': 0.3612},\n",
       " {'neg': 0.029, 'neu': 0.912, 'pos': 0.059, 'compound': 0.3519},\n",
       " {'neg': 0.0, 'neu': 1.0, 'pos': 0.0, 'compound': 0.0},\n",
       " {'neg': 0.385, 'neu': 0.615, 'pos': 0.0, 'compound': -0.3612},\n",
       " {'neg': 0.0, 'neu': 1.0, 'pos': 0.0, 'compound': 0.0},\n",
       " {'neg': 0.0, 'neu': 1.0, 'pos': 0.0, 'compound': 0.0},\n",
       " {'neg': 0.0, 'neu': 0.798, 'pos': 0.202, 'compound': 0.6486},\n",
       " {'neg': 0.0, 'neu': 0.798, 'pos': 0.202, 'compound': 0.6486},\n",
       " {'neg': 0.087, 'neu': 0.758, 'pos': 0.155, 'compound': 0.3182}]"
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_bsenti"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "id": "ec451bd5",
   "metadata": {},
   "outputs": [],
   "source": [
    "blacksents_df = pd.DataFrame(all_bsenti)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e3bdbb09",
   "metadata": {},
   "source": [
    "## black-ish histogram"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b7e674b5",
   "metadata": {},
   "source": [
    "Here I created a dataframe for the blackish sentiment scores. This allows me to better analyze the data and to visualize it. I then made a histogram with the positive sentiments and it visualizes it for me/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "id": "e6720a3a",
   "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>neg</th>\n",
       "      <th>neu</th>\n",
       "      <th>pos</th>\n",
       "      <th>compound</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.000</td>\n",
       "      <td>0.690</td>\n",
       "      <td>0.310</td>\n",
       "      <td>0.8442</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.207</td>\n",
       "      <td>0.692</td>\n",
       "      <td>0.101</td>\n",
       "      <td>-0.4441</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.102</td>\n",
       "      <td>0.800</td>\n",
       "      <td>0.098</td>\n",
       "      <td>-0.0258</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>188</th>\n",
       "      <td>0.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>189</th>\n",
       "      <td>0.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>190</th>\n",
       "      <td>0.000</td>\n",
       "      <td>0.798</td>\n",
       "      <td>0.202</td>\n",
       "      <td>0.6486</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>191</th>\n",
       "      <td>0.000</td>\n",
       "      <td>0.798</td>\n",
       "      <td>0.202</td>\n",
       "      <td>0.6486</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>192</th>\n",
       "      <td>0.087</td>\n",
       "      <td>0.758</td>\n",
       "      <td>0.155</td>\n",
       "      <td>0.3182</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>193 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       neg    neu    pos  compound\n",
       "0    0.000  1.000  0.000    0.0000\n",
       "1    0.000  0.690  0.310    0.8442\n",
       "2    0.207  0.692  0.101   -0.4441\n",
       "3    0.000  1.000  0.000    0.0000\n",
       "4    0.102  0.800  0.098   -0.0258\n",
       "..     ...    ...    ...       ...\n",
       "188  0.000  1.000  0.000    0.0000\n",
       "189  0.000  1.000  0.000    0.0000\n",
       "190  0.000  0.798  0.202    0.6486\n",
       "191  0.000  0.798  0.202    0.6486\n",
       "192  0.087  0.758  0.155    0.3182\n",
       "\n",
       "[193 rows x 4 columns]"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "blacksents_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "id": "4af5a4e6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    193.000000\n",
       "mean       0.127321\n",
       "std        0.160015\n",
       "min        0.000000\n",
       "25%        0.000000\n",
       "50%        0.076000\n",
       "75%        0.202000\n",
       "max        0.656000\n",
       "Name: pos, dtype: float64"
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "blacksents_df['pos'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "id": "5cab6097",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    193.00000\n",
       "mean       0.06943\n",
       "std        0.10193\n",
       "min        0.00000\n",
       "25%        0.00000\n",
       "50%        0.00000\n",
       "75%        0.13600\n",
       "max        0.44500\n",
       "Name: neg, dtype: float64"
      ]
     },
     "execution_count": 103,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "blacksents_df['neg'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "id": "0a43d131",
   "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": [
    "fig2, ax2 = plt.subplots()\n",
    "ax2.hist(blacksents_df['pos'])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3af04b42",
   "metadata": {},
   "source": [
    "## black-ish complete histogram"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "db4ef8f2",
   "metadata": {},
   "source": [
    "Here I have the blackish histograms with each sentiment in a histogram. Interpreting this data I can look at it and say that overall the tweets seem to be neutral. Next I will compare the two shows by each sentiment."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "id": "1cb499ba",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig3, ax3 = plt.subplots(1, 4, figsize = (10,5))\n",
    "ax3[0].hist(blacksents_df['neg'], bins =  8, color = 'red')\n",
    "ax3[1].hist(blacksents_df['pos'], bins = 8, color = 'blue')\n",
    "ax3[2].hist(blacksents_df['neu'], bins = 8, color = 'green')\n",
    "ax3[3].hist(blacksents_df['compound'], bins = 8, color = 'yellow')\n",
    "\n",
    "ax3[0].set_xlabel('Negative')\n",
    "ax3[1].set_xlabel('Positive')\n",
    "ax3[2].set_xlabel('Neutral')\n",
    "ax3[3].set_xlabel('Compound')\n",
    "\n",
    "fig3.suptitle(\"black-ish sentiments\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "010cb382",
   "metadata": {},
   "source": [
    "# Comparing Ted Lasso tweets vs. black-ish tweets"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5fd1be2b",
   "metadata": {},
   "source": [
    "Here I combined the two shows sentiment scores which allow me to look at each shows sentiment scores next to each other. The first histogram I am just putting the sentiment scores next to each other. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "id": "50b85a87",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 8 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig5, ax5 = plt.subplots(2, 4, figsize = (10, 8))\n",
    "ax5[0,0].hist(sents_df['neg'], bins =  10, color = 'red')\n",
    "ax5[0,1].hist(sents_df['pos'], bins =  10, color = 'blue')\n",
    "ax5[0,2].hist(sents_df['neu'], bins =  10, color = 'green')\n",
    "ax5[0,3].hist(sents_df['compound'], bins =  10, color = 'yellow')\n",
    "\n",
    "ax5[0,0].set_xlabel(\"Negative\")\n",
    "ax5[0,1].set_xlabel(\"Positive\")\n",
    "ax5[0,2].set_xlabel(\"Neutral\")\n",
    "ax5[0,3].set_xlabel(\"Compound\")\n",
    "ax5[0,0].set_ylabel(\"Ted Lasso\")\n",
    "ax5[0,0].set_ylim(0,140)\n",
    "ax5[0,1].set_ylim(0,140)\n",
    "ax5[0,2].set_ylim(0,140)\n",
    "ax5[0,3].set_ylim(0,140)\n",
    "\n",
    "ax5[1,0].hist(blacksents_df['neg'], bins =  10, color = 'red')\n",
    "ax5[1,1].hist(blacksents_df['pos'], bins = 10, color = 'blue')\n",
    "ax5[1,2].hist(blacksents_df['neu'], bins = 10, color = 'green')\n",
    "ax5[1,3].hist(blacksents_df['compound'], bins = 10, color = 'yellow')\n",
    "\n",
    "ax5[1,0].set_xlabel('Negative')\n",
    "ax5[1,1].set_xlabel('Positive')\n",
    "ax5[1,2].set_xlabel('Neutral')\n",
    "ax5[1,3].set_xlabel('Compound')\n",
    "ax5[1,0].set_ylabel(\"black-ish\")\n",
    "ax5[1,0].set_ylim(0,140)\n",
    "ax5[1,1].set_ylim(0,140)\n",
    "ax5[1,2].set_ylim(0,140)\n",
    "ax5[1,3].set_ylim(0,140)\n",
    "\n",
    "fig5.suptitle(\"Ted Lasso Sentiments vs. black-ish sentiments\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e18f724f",
   "metadata": {},
   "source": [
    "As for these histograms I overlapped the two shows data in order to get a more clear comparison of them. This is a better visualization because it can support my hypothesis. Ted Lasso is red and blackish is blue."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "id": "63cf61a0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig6, ax6 = plt.subplots(1, 4, figsize = (10, 8))\n",
    "ax6[0].hist(sents_df['neg'], bins =  10, color = 'red', alpha = .5)\n",
    "ax6[0].hist(blacksents_df['neg'], bins =  10, color = 'blue', alpha = .5)\n",
    "\n",
    "ax6[1].hist(sents_df['pos'], bins =  10, color = 'red', alpha = .5)\n",
    "ax6[1].hist(blacksents_df['pos'], bins =  10, color = 'blue', alpha = .5)\n",
    "\n",
    "ax6[2].hist(sents_df['neu'], bins =  10, color = 'red', alpha = .5)\n",
    "ax6[2].hist(blacksents_df['neu'], bins =  10, color = 'blue', alpha = .5)\n",
    "\n",
    "ax6[3].hist(sents_df['compound'], bins =  10, color = 'red', alpha = .5)\n",
    "ax6[3].hist(blacksents_df['compound'], bins =  10, color = 'blue', alpha = .5)\n",
    "\n",
    "ax6[0].set_ylim(0,180)\n",
    "ax6[1].set_ylim(0,180)\n",
    "ax6[2].set_ylim(0,180)\n",
    "ax6[3].set_ylim(0,180)\n",
    "\n",
    "ax6[0].set_xlim(0,1)\n",
    "ax6[1].set_xlim(0,1)\n",
    "ax6[2].set_xlim(0,1)\n",
    "ax6[3].set_xlim(0,1)\n",
    "\n",
    "ax6[0].set_xlabel(\"Negative\")\n",
    "ax6[1].set_xlabel(\"Positive\")\n",
    "ax6[2].set_xlabel(\"Neutral\")\n",
    "ax6[3].set_xlabel(\"Compound\")\n",
    "\n",
    "fig6.suptitle(\"Ted Lasso Sentiments vs. black-ish Sentiments\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4afccff3",
   "metadata": {},
   "source": [
    "## Conclusion"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d9e2e1d7",
   "metadata": {},
   "source": [
    "Overall, I believe that my hypothesis was right to some extent. Looking at the compound graph Ted Lasso seems to have a higher positive score than blackish. Even if you look at the graph above that one, you can see that Ted Lasso is more positive than negative. This has some limitations to it because I am just guessing by looking at the graphs, that Ted Lasso is more positive. If someone else were to look at the graphs they might say that blackish is more positive. Right now it is pretty bias to say that Ted Lasso is more positive. Another limitation I ran into was that I only have 200 Tweets for each show, I think collecting more Tweets would've help for my hypothesis. In the future I hope to get approved for the academic account for the Twitter API so that I can get Tweets from before the Emmy winners were announced."
   ]
  }
 ],
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