TweetAnalyzer.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from tweepy import API\n",
    "from tweepy import Cursor\n",
    "from tweepy.streaming import StreamListener             \n",
    "from tweepy import OAuthHandler\n",
    "from tweepy import Stream\n",
    "from textblob import TextBlob\n",
    "import credentials\n",
    "import re\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "class TweetClient():\n",
    "    def __init__(self, tweet_user = None):\n",
    "        self.auth = TweetAuth().authenticate()\n",
    "        self.tweet_client = API(self.auth)\n",
    "        \n",
    "        self.tweet_user = tweet_user\n",
    "\n",
    "    def get_tweetclient(self):\n",
    "        return self.tweet_client\n",
    "\n",
    "    def get_tweets(self, no_tweets):\n",
    "        tweets = []\n",
    "        for i in Cursor(self.tweet_client.user_timeline, id = self.tweet_user).items(no_tweets):\n",
    "            tweets.append(i)\n",
    "        return tweets\n",
    "\n",
    "    def get_friend_list(self, no_friends):\n",
    "        friend_list = []\n",
    "        for j in Cursor(self.tweet_client.friends, id = self.tweet_user).items(no_friends):\n",
    "            friend_list,append(j)\n",
    "        return friend_list\n",
    "\n",
    "    def get_hometimeline_tweets(self, no_tweets):\n",
    "        hometimeline_tweets = []\n",
    "        for k in Cursor(self.tweets_client.home_timeline, id = self.tweet_user).items(no_tweets):\n",
    "            hometimeline_tweets.append(k)\n",
    "        return hometimeline_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "class TweetAuth():\n",
    "    def authenticate(self):\n",
    "          auth = OAuthHandler(credentials.CONSUMER_KEY, credentials.CONSUMER_SECRET)\n",
    "          auth.set_access_token(credentials.ACCESS_TOKEN, credentials.ACCESS_TOKEN_SECRET)\n",
    "          return auth"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "class TweetStream():\n",
    "    def __init__(self):\n",
    "        self.tweet_authenticator = TweetAuth()\n",
    "\n",
    "    def stream_tweets(self, fetched_tweet, hashtag_list):\n",
    "        catcher = CatchTweet(fetched_tweet)\n",
    "        auth = self.tweet_authenticator.authenticate()\n",
    "        stream = Stream(auth, catcher)\n",
    "\n",
    "        stream.filter(track=hashtag_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "class CatchTweet(StreamListener):\n",
    "    def __init__(self, fetched_tweet):\n",
    "        self.fetched_tweet = fetched_tweet\n",
    "\n",
    "    def on_data(self, data):\n",
    "        try:\n",
    "            print(data)\n",
    "            with open(self.fetched_tweet, 'a') as tf:\n",
    "                tf.write(data)\n",
    "            return True\n",
    "\n",
    "        except BaseException as e:\n",
    "            print(\"Error on_data: %s\" % str(e))\n",
    "        return True\n",
    "\n",
    "    def on_error(self, status):\n",
    "        if status == 420:\n",
    "            return False\n",
    "        print(status)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "class TweetAnalyzer():\n",
    "    def tweetclean(self, tweet):\n",
    "        return ' '.join(re.sub(\"(@[A-Za-z0-9]+)|([^0-9A-Za-z \\t])|(\\w+:\\/\\/\\S+)\", \" \", tweet).split())    \n",
    "    def sentiment_analysis(self, tweet):\n",
    "        analysis = TextBlob(self.tweetclean(tweet))\n",
    "        \n",
    "        if analysis.sentiment.polarity > 0:\n",
    "            return 1\n",
    "        elif analysis.sentiment.polarity == 0:\n",
    "            return 0\n",
    "        else:\n",
    "            return -1\n",
    "    \n",
    "    def tweet2df(self, tweets):\n",
    "        data = pd.DataFrame(data = [tweet.text for tweet in tweets], columns = ['Tweets'])\n",
    "        data['ID'] = np.array([tweet.id for tweet in tweets])\n",
    "        data['Length'] = np.array([len(tweet.text) for tweet in tweets])\n",
    "        data['Date'] = np.array([tweet.created_at for tweet in tweets])\n",
    "        data['Source'] = np.array([tweet.source for tweet in tweets])\n",
    "        data['Likes'] = np.array([tweet.favorite_count for tweet in tweets])\n",
    "        data['Retweets'] = np.array([tweet.retweet_count for tweet in tweets])\n",
    "        \n",
    "        return data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Enter the Twitter Handle of User on which you want to perform Sentiment Analysis:-  GoogleIO201X\n",
      "                                               Tweets                   ID  \\\n",
      "0   335 days left until Google I/O 2020. There’s r...  1137128098812481537   \n",
      "1   342 days left until Google I/O 2020. I heard t...  1134505536639119360   \n",
      "2   349 days left until Google I/O 2020. \\n\\nStill...  1132119093249810432   \n",
      "3   358 days left until Google I/O 2020. \\n\\nIt wo...  1129421317252485121   \n",
      "4                365 days left until Google I/O 2020.  1126728574826713088   \n",
      "5   RT @sundarpichai: #io19 is a wrap and a big th...  1126712387581513730   \n",
      "6   RT @GooglePlayDev: 🎉 That's a wrap for #io19! ...  1126649285355790336   \n",
      "7   RT @Google: That's a wrap! Close out #io19 wit...  1126643875945205761   \n",
      "8   RT @Google: Count ‘em up! 100 things we announ...  1126643866239561728   \n",
      "9   As you can tell by the tweets, Google I/O 2019...  1126643016968445952   \n",
      "10  RT @gdg: 👏🏾Thank you to all our community lead...  1126642152207831040   \n",
      "11  RT @WomenTechmakers: 🎬✨That’s a wrap on #io19!...  1126641869314617344   \n",
      "12  RT @ActionsOnGoogle: We're about to wrap up #i...  1126641800679002112   \n",
      "13  RT @googledevs: 🙌Thank You 🙌\\n\\n#io19 is offic...  1126641585335062528   \n",
      "14  RT @googledevs: 🕺 Break it down 🕺\\n\\n@TensorFl...  1126603452572823552   \n",
      "15  RT @googledevs: At #io19 we announced new solu...  1126600276331204608   \n",
      "16  RT @googledevs: A huge shoutout to the 500+ #i...  1126585390628925440   \n",
      "17  RT @googledevs: Bounce, rock, and roller-skate...  1126570324940677120   \n",
      "18  RT @Android: Use your voice to control:\\nTempe...  1126531026589630464   \n",
      "19  RT @Google: Sessions, Sandboxes and so much mo...  1126530996197707777   \n",
      "20  RT @googledevs: The Final day of #io19 is abou...  1126524143300558848   \n",
      "21  Welcome back to Day 3. Although this is the la...  1126509631621279744   \n",
      "22  RT @Google: Eye-popping AR demos, inspiring ta...  1126396433907605506   \n",
      "23  Day 2 is over. That concert was fun, wasn’t it...  1126356489533136896   \n",
      "24  Alright, who’s ready to see The Flaming Lips p...  1126327392979628034   \n",
      "25  RT @googledevs: Day 2 of #io19 is over, but th...  1126310183163060229   \n",
      "26  RT @googledevs: Missed our biggest announcemen...  1126310156550180864   \n",
      "27  RT @googledevs: As we shared yesterday at #io1...  1126192573008113664   \n",
      "28  RT @Google: Back at it again, #io19! Let's go,...  1126189925748039680   \n",
      "29  RT @googledevs: ✨ And we're back! ✨\\n\\nDay 2 o...  1126166377239330817   \n",
      "30  Day 1 is over. Come back tomorrow for Day 2 to...  1126003802551664640   \n",
      "31  RT @madebygoogle: Storage? Unlimited. #pixel3a...  1125969839741214721   \n",
      "32  RT @Android: ⚡️ “#io19 - Android Highlights”\\n...  1125969774549200896   \n",
      "33  RT @Google: Kicking off with updates in Search...  1125968722001154049   \n",
      "34  RT @googledevs: 👏That’s a wrap! 👏\\n\\nDay 1 of ...  1125936874600591360   \n",
      "35  RT @Google: With federated learning, a new app...  1125920944445317120   \n",
      "36  RT @Google: So fast, you might've missed it. R...  1125920937524600833   \n",
      "37  RT @Google: #io19 attendees      BTS fans \\n  ...  1125920927462481920   \n",
      "38  RT @Google: Make your mark at the #io19 Landma...  1125920916649545728   \n",
      "39  RT @GoogleARVR: Today at #io19, we announced h...  1125920834420236288   \n",
      "40  RT @madebygoogle: Battery, you ask? #pixel3a h...  1125913660143034368   \n",
      "41  RT @madebygoogle: #Pixel3a has arrived and its...  1125877910244433920   \n",
      "42  RT @madebygoogle: New phone, new color. #pixel...  1125877898429132801   \n",
      "43  RT @madebygoogle: Here's a quick snapshot of #...  1125877886336913408   \n",
      "44  RT @AndroidDev: Protecting users in #AndroidQ,...  1125858144326828032   \n",
      "45  RT @Google: AR shark, doo doo doo doo doo doo....  1125855177892720641   \n",
      "46  RT @googledevs: 🔴[LIVE] Gather around, develop...  1125849124203483137   \n",
      "47  RT @AndroidDev: Announced at #io19: #AndroidQ ...  1125844823217336320   \n",
      "48  The developer keynote is about to begin shortl...  1125843516930777089   \n",
      "49  Hmm... Wonder what “Phone X” belongs to.\\n\\n#io19  1125837684461596674   \n",
      "\n",
      "    Length                Date              Source  Likes  Retweets  Sentiment  \n",
      "0       97 2019-06-07 22:44:00           TweetDeck     15         0         -1  \n",
      "1      140 2019-05-31 17:02:52           TweetDeck     71        11          0  \n",
      "2       55 2019-05-25 03:00:00           TweetDeck     67         5          0  \n",
      "3      140 2019-05-17 16:20:00           TweetDeck     89         5          1  \n",
      "4       36 2019-05-10 06:00:00           TweetDeck    496        50          0  \n",
      "5      140 2019-05-10 04:55:41  Twitter for iPhone      0       362          1  \n",
      "6      140 2019-05-10 00:44:56  Twitter for iPhone      0        13          1  \n",
      "7      140 2019-05-10 00:23:26  Twitter for iPhone      0        62          0  \n",
      "8      108 2019-05-10 00:23:24  Twitter for iPhone      0       170          0  \n",
      "9      139 2019-05-10 00:20:01           TweetDeck     24         3          1  \n",
      "10     140 2019-05-10 00:16:35  Twitter for iPhone      0        60          0  \n",
      "11     140 2019-05-10 00:15:28  Twitter for iPhone      0       125          0  \n",
      "12     140 2019-05-10 00:15:11  Twitter for iPhone      0        13          0  \n",
      "13     140 2019-05-10 00:14:20  Twitter for iPhone      0       232          0  \n",
      "14     140 2019-05-09 21:42:49  Twitter for iPhone      0       174          1  \n",
      "15     140 2019-05-09 21:30:11  Twitter for iPhone      0        57          1  \n",
      "16     139 2019-05-09 20:31:02  Twitter for iPhone      0        45          1  \n",
      "17      86 2019-05-09 19:31:10  Twitter for iPhone      0        36          0  \n",
      "18     140 2019-05-09 16:55:01  Twitter for iPhone      0       113          1  \n",
      "19     133 2019-05-09 16:54:54  Twitter for iPhone      0        64          1  \n",
      "20     140 2019-05-09 16:27:40  Twitter for iPhone      0        44          1  \n",
      "21     140 2019-05-09 15:30:00           TweetDeck     10         3          1  \n",
      "22     140 2019-05-09 08:00:11  Twitter for iPhone      0        83          1  \n",
      "23     136 2019-05-09 05:21:28           TweetDeck     14         1          1  \n",
      "24     139 2019-05-09 03:25:51           TweetDeck     14         3          1  \n",
      "25     140 2019-05-09 02:17:28  Twitter for iPhone      0        16          1  \n",
      "26     140 2019-05-09 02:17:21  Twitter for iPhone      0        36         -1  \n",
      "27     140 2019-05-08 18:30:07  Twitter for iPhone      0        46          1  \n",
      "28     102 2019-05-08 18:19:36  Twitter for iPhone      0       136          0  \n",
      "29     139 2019-05-08 16:46:02  Twitter for iPhone      0        18         -1  \n",
      "30     129 2019-05-08 06:00:01           TweetDeck     22         3          1  \n",
      "31     139 2019-05-08 03:45:03  Twitter for iPhone      0       137          0  \n",
      "32      69 2019-05-08 03:44:48  Twitter for iPhone      0       130          0  \n",
      "33     140 2019-05-08 03:40:37  Twitter for iPhone      0       101          1  \n",
      "34     140 2019-05-08 01:34:04  Twitter for iPhone      0        48          1  \n",
      "35     140 2019-05-08 00:30:46  Twitter for iPhone      0       341          1  \n",
      "36     140 2019-05-08 00:30:44  Twitter for iPhone      0       348          1  \n",
      "37     124 2019-05-08 00:30:42  Twitter for iPhone      0     25345          0  \n",
      "38     140 2019-05-08 00:30:39  Twitter for iPhone      0       153          1  \n",
      "39     140 2019-05-08 00:30:20  Twitter for iPhone      0        66          1  \n",
      "40     140 2019-05-08 00:01:49  Twitter for iPhone      0        65          1  \n",
      "41     140 2019-05-07 21:39:46  Twitter for iPhone      0       158          1  \n",
      "42     139 2019-05-07 21:39:43  Twitter for iPhone      0        83          1  \n",
      "43     140 2019-05-07 21:39:40  Twitter for iPhone      0        90          1  \n",
      "44     140 2019-05-07 20:21:13  Twitter for iPhone      0       153          1  \n",
      "45      77 2019-05-07 20:09:26  Twitter for iPhone      0       573          0  \n",
      "46     140 2019-05-07 19:45:23  Twitter for iPhone      0        49          1  \n",
      "47     140 2019-05-07 19:28:17  Twitter for iPhone      0       132          0  \n",
      "48      82 2019-05-07 19:23:06           TweetDeck     10         5          0  \n",
      "49      47 2019-05-07 18:59:55           TweetDeck     53         9          0  \n"
     ]
    }
   ],
   "source": [
    "if __name__ == \"__main__\":\n",
    "\n",
    "    tweet_client = TweetClient()\n",
    "    tweet_analyzer = TweetAnalyzer()\n",
    "    api = tweet_client.get_tweetclient()\n",
    "    \n",
    "    x = input(\"Enter the Twitter Handle of User on which you want to perform Sentiment Analysis:-  \")\n",
    "    tweets = api.user_timeline(screen_name = x, count = 200)\n",
    "    #print(dir(tweets[0]))\n",
    "    #print(tweets[0].id)\n",
    "    #print(tweets[0].retweet_count)\n",
    "    data = tweet_analyzer.tweet2df(tweets)\n",
    "    data['Sentiment'] = np.array([tweet_analyzer.sentiment_analysis(tweet) for tweet in data['Tweets']])\n",
    "    print(data.head(50))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Visualizing The Data & Sentiments"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "115.04\n"
     ]
    }
   ],
   "source": [
    "print(np.mean(data['Length']))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "496\n"
     ]
    }
   ],
   "source": [
    "print(np.max(data['Likes']))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "25345\n"
     ]
    }
   ],
   "source": [
    "print(np.max(data['Retweets']))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'No. Of Likes')"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1152x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "like_Series = pd.Series(data = data['Likes'].values, index = data['Date'])\n",
    "like_Series.plot(figsize = (16,4), color = 'r')\n",
    "plt.xlabel('Date')\n",
    "plt.ylabel('No. Of Likes')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'No. Of Retweets')"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1152x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "retweet_Series = pd.Series(data = data['Retweets'].values, index = data['Date'])\n",
    "retweet_Series.plot(figsize = (16,4), color = 'r')\n",
    "plt.xlabel('Date')\n",
    "plt.ylabel('No. Of Retweets')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1152x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "like_Series = pd.Series(data = data['Likes'].values, index = data['Date'])\n",
    "like_Series.plot(figsize = (16,4), label = 'Likes', legend = True)\n",
    "retweet_Series = pd.Series(data = data['Retweets'].values, index = data['Date'])\n",
    "retweet_Series.plot(figsize = (16,4), label = 'Retweets', legend = True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fa7675739b0>"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYgAAAEKCAYAAAAIO8L1AAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDMuMC4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvOIA7rQAADxBJREFUeJzt3X2QXXV9x/H3BwJVVAYwq2JCDW1TbdQOwg4VGFsKTketPJSC1ak1IDPpH4hPtZXajvTJKUypQKm1kxEkdBwMg7ZAx2nLUKitSupGqTwNJaUUI5Es9QFtKwh++8c9mezEX8jNsnfP3dz3a+bO3Xv23Hu+sJO8c86952yqCkmSdrVf3wNIksaTgZAkNRkISVKTgZAkNRkISVKTgZAkNRkISVKTgZAkNRkISVLTsr4HeCaWL19eq1at6nsMSVpSNm/e/GhVTe1pvSUdiFWrVjEzM9P3GJK0pCT5r2HW8xCTJKnJQEiSmgyEJKnJQEiSmgyEJKnJQEiSmgyEJKnJQEiSmgyEJKlpSZ9JLWn8nXDFCX2PMBE+d/7nFvw13YOQJDUZCElSk4GQJDUZCElSk4GQJDUZCElSk4GQJDUZCElSk4GQJDUZCElSk4GQJDUZCElSk4GQJDUZCElSk4GQJDUZCElSk4GQJDUZCElSk4GQJDUZCElS08gCkeSqJNuT3DVn2WFJbk5yf3d/aLc8Sf4syZYkX0ly9KjmkiQNZ5R7EFcDr9tl2QXALVW1GrilewzwemB1d1sHfHSEc0mShjCyQFTVZ4Fv7LL4NGBD9/UG4PQ5y6+pgduBQ5IcPqrZJEl7ttjvQbywqrYBdPcv6JavAL46Z72t3TJJUk/G5U3qNJZVc8VkXZKZJDOzs7MjHkuSJtdiB+KRHYeOuvvt3fKtwBFz1lsJPNx6gapaX1XTVTU9NTU10mElaZItdiBuBNZ2X68Fbpiz/G3dp5leDXx7x6EoSVI/lo3qhZNcC5wILE+yFbgQuAi4Lsm5wEPAWd3qnwHeAGwB/hc4Z1RzSZKGM7JAVNVbdvOtkxvrFnDeqGaRJO29cXmTWpI0ZgyEJKnJQEiSmgyEJKnJQEiSmgyEJKnJQEiSmgyEJKnJQEiSmgyEJKnJQEiSmgyEJKnJQEiSmgyEJKnJQEiSmgyEJKnJQEiSmgyEJKnJQEiSmgyEJKnJQEiSmgyEJKnJQEiSmgyEJKnJQEiSmgyEJKnJQEiSmgyEJKmpl0AkeU+Su5PcleTaJM9KcmSSTUnuT7IxyYF9zCZJGlj0QCRZAbwTmK6qVwD7A28GLgYurarVwDeBcxd7NknSTn0dYloGPDvJMuAgYBtwEnB99/0NwOk9zSZJoodAVNXXgEuAhxiE4dvAZuBbVfVkt9pWYEXr+UnWJZlJMjM7O7sYI0vSROrjENOhwGnAkcCLgecAr2+sWq3nV9X6qpququmpqanRDSpJE66PQ0yvBf6zqmar6vvAp4HjgUO6Q04AK4GHe5hNktTpIxAPAa9OclCSACcD9wC3Amd266wFbuhhNklSp4/3IDYxeDP6S8Cd3QzrgfcD702yBXg+cOVizyZJ2mnZnldZeFV1IXDhLosfAI7tYRxJUoNnUkuSmgyEJKnJQEiSmgyEJKnJQEiSmgyEJKnJQEiSmgyEJKnJQEiSmgyEJKnJQEiSmgyEJKnJQEiSmnq5mqu0tx76g1f2PcI+70c/eGffI2jMuAchSWoyEJKkJgMhSWoyEJKkJgMhSWoaKhBJbhlmmSRp3/G0H3NN8izgIGB5kkOBdN86GHjxiGeTJPVoT+dB/DrwbgYx2MzOQDwGfGSEc0mSeva0gaiqy4HLk5xfVVcs0kySpDEw1JnUVXVFkuOBVXOfU1XXjGguSVLPhgpEkr8Cfhy4A3iqW1yAgZCkfdSw12KaBtZUVY1yGEnS+Bj2PIi7gBeNchBJ0ngZdg9iOXBPkn8FHt+xsKpOnc9GkxwCfAx4BYNDVW8H7gM2Mnif40HgTVX1zfm8viTpmRs2EL+3wNu9HPi7qjozyYEMzrX4AHBLVV2U5ALgAuD9C7xdSdKQhv0U0z8t1AaTHAz8LHB299pPAE8kOQ04sVttA3AbBkKSejPspTa+k+Sx7va9JE8leWye2/wxYBb4eJIvJ/lYkucAL6yqbQDd/Qvm+fqSpAUwVCCq6nlVdXB3exbwy8Cfz3Oby4CjgY9W1auA/2FwOGkoSdYlmUkyMzs7O88RJEl7Mq+ruVbV3wAnzXObW4GtVbWpe3w9g2A8kuRwgO5++262vb6qpqtqempqap4jSJL2ZNgT5c6Y83A/BudFzOuciKr6epKvJnlpVd0HnAzc093WAhd19zfM5/UlSQtj2E8xnTLn6ycZfAz1tGew3fOBT3SfYHoAOIdBeK5Lci7wEHDWM3h9SdIzNOynmM5ZyI1W1R0M9kJ2dfJCbkeSNH/DfoppZZK/TrI9ySNJPpVk5aiHkyT1Z9g3qT8O3Mjg90KsAG7qlkmS9lHDBmKqqj5eVU92t6sBP0IkSfuwYQPxaJK3Jtm/u70V+O9RDiZJ6tewgXg78Cbg68A24EwGnzySJO2jhv2Y6x8Ca3dcXTXJYcAlDMIhSdoHDbsH8dNzL71dVd8AXjWakSRJ42DYQOyX5NAdD7o9iGH3PiRJS9Cwf8n/KfD5JNczuMTGm4APjWwqSVLvhj2T+pokMwwu0BfgjKq6Z6STSZJ6NfRhoi4IRkGSJsS8LvctSdr3GQhJUpOBkCQ1GQhJUpOBkCQ1GQhJUpOBkCQ1GQhJUpOBkCQ1GQhJUpOBkCQ1GQhJUpOBkCQ1GQhJUpOBkCQ1GQhJUlNvgUiyf5IvJ/nb7vGRSTYluT/JxiQH9jWbJKnfPYh3AffOeXwxcGlVrQa+CZzby1SSJKCnQCRZCfwi8LHucRj8vuvru1U2AKf3MZskaaCvPYjLgN8CftA9fj7wrap6snu8FVjRx2CSpIFFD0SSNwLbq2rz3MWNVWs3z1+XZCbJzOzs7EhmlCT1swdxAnBqkgeBTzI4tHQZcEiSZd06K4GHW0+uqvVVNV1V01NTU4sxryRNpEUPRFX9dlWtrKpVwJuBf6yqXwVuBc7sVlsL3LDYs0mSdhqn8yDeD7w3yRYG70lc2fM8kjTRlu15ldGpqtuA27qvHwCO7XMeSdJO47QHIUkaIwZCktRkICRJTQZCktRkICRJTQZCktRkICRJTQZCktRkICRJTQZCktRkICRJTQZCktRkICRJTQZCktRkICRJTQZCktRkICRJTQZCktRkICRJTQZCktRkICRJTQZCktRkICRJTQZCktRkICRJTQZCktRkICRJTQZCktS06IFIckSSW5Pcm+TuJO/qlh+W5OYk93f3hy72bJKknfrYg3gS+I2q+ing1cB5SdYAFwC3VNVq4JbusSSpJ4seiKraVlVf6r7+DnAvsAI4DdjQrbYBOH2xZ5Mk7dTrexBJVgGvAjYBL6yqbTCICPCC3TxnXZKZJDOzs7OLNaokTZzeApHkucCngHdX1WPDPq+q1lfVdFVNT01NjW5ASZpwvQQiyQEM4vCJqvp0t/iRJId33z8c2N7HbJKkgT4+xRTgSuDeqvrwnG/dCKztvl4L3LDYs0mSdlrWwzZPAH4NuDPJHd2yDwAXAdclORd4CDirh9kkSZ1FD0RV/QuQ3Xz75MWcRZK0e55JLUlqMhCSpKY+3oPoxTG/eU3fI0yEzX/ytr5HkLRA3IOQJDUZCElSk4GQJDUZCElSk4GQJDUZCElSk4GQJDUZCElSk4GQJDUZCElSk4GQJDUZCElSk4GQJDUZCElSk4GQJDUZCElSk4GQJDUZCElSk4GQJDUZCElSk4GQJDUZCElSk4GQJDUZCElS01gFIsnrktyXZEuSC/qeR5Im2dgEIsn+wEeA1wNrgLckWdPvVJI0ucYmEMCxwJaqeqCqngA+CZzW80ySNLHGKRArgK/Oeby1WyZJ6sGyvgeYI41l9UMrJeuAdd3D7ya5b6RT9Ws58GjfQ+yNXLK27xHGxZL72XFh64/gxFpyP7+8c69+fi8ZZqVxCsRW4Ig5j1cCD++6UlWtB9Yv1lB9SjJTVdN9z6G9589uafPnNzBOh5i+CKxOcmSSA4E3Azf2PJMkTayx2YOoqieTvAP4e2B/4KqqurvnsSRpYo1NIACq6jPAZ/qeY4xMxKG0fZQ/u6XNnx+Qqh96H1iSpLF6D0KSNEYMxBhK8rIkX0jyeJL39T2P9o6XjFm6klyVZHuSu/qeZRwYiPH0DeCdwCV9D6K94yVjlryrgdf1PcS4MBBjqKq2V9UXge/3PYv2mpeMWcKq6rMM/oEmDIS00LxkjPYZBkJaWENdMkZaCgzEmEhyXpI7utuL+55H8zbUJWOkpcBAjImq+khVHdXd/Atl6fKSMdpneKLcGEryImAGOBj4AfBdYE1VPdbrYBpKkjcAl7HzkjEf6nkkDSnJtcCJDK7m+ghwYVVd2etQPTIQkqQmDzFJkpoMhCSpyUBIkpoMhCSpyUBIkpoMhCZSkt9JcneSr3QnJ/7MPF7jqO4jrTsenzrqq7cmOTHJ8aPchrTDWP1GOWkxJDkOeCNwdFU9nmQ5cOA8XuooYJrutyBW1Y2M/qS4ExmcF/P5EW9H8jwITZ4kZwDnVNUpuyw/Bvgw8FzgUeDsqtqW5DZgE/DzwCHAud3jLcCzga8Bf9x9PV1V70hyNfB/wMuAlwDnAGuB44BNVXV2t81fAH4f+BHgP7q5vpvkQWADcApwAHAW8D3gduApYBY4v6r+eWH/70g7eYhJk+gfgCOS/HuSv0jyc0kOAK4AzqyqY4CrgLlnQC+rqmOBdzM4u/YJ4IPAxu7yKBsb2zkUOAl4D3ATcCnwcuCV3eGp5cDvAq+tqqMZnD3/3jnPf7Rb/lHgfVX1IPCXwKXdNo2DRspDTJo43b/QjwFew2CvYCPwR8ArgJuTwOAyGdvmPO3T3f1mYNWQm7qpqirJncAjVXUnQJK7u9dYyeCXCn2u2+aBwBd2s80zhv8vlBaGgdBEqqqngNuA27q/wM8D7q6q43bzlMe7+6cY/s/Njuf8YM7XOx4v617r5qp6ywJuU1owHmLSxEny0iSr5yw6CrgXmOrewCbJAUlevoeX+g7wvGcwyu3ACUl+otvmQUl+csTblIZmIDSJngtsSHJPkq8wOMzzQeBM4OIk/wbcAezp46S3Amu6j8n+yt4OUVWzwNnAtd0ctzN4U/vp3AT8UrfN1+ztNqW94aeYJElN7kFIkpoMhCSpyUBIkpoMhCSpyUBIkpoMhCSpyUBIkpoMhCSp6f8BxciA04HO9ksAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(data['Sentiment'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Sentiments')"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1152x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sentiment_Series = pd.Series(data = data['Sentiment'].values, index = data['Date'])\n",
    "sentiment_Series.plot(figsize = (16, 4), color = 'g')\n",
    "plt.xlabel('Date')\n",
    "plt.ylabel('Sentiments')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}