tweet_analysis (4).ipynb

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    "def analize_sentiment(tweet):\n",
    "    analysis = TextBlob(tweet)\n",
    "    if analysis.sentiment.polarity > 0:\n",
    "        return 1\n",
    "    elif analysis.sentiment.polarity == 0:\n",
    "        return 0\n",
    "    else:\n",
    "        return -1\n",
    "data['sentiment'] = np.array([ analize_sentiment(tweet) for tweet in data['Tweets_Cln']])\n",
    "display(data.head(2))\n",
    "\n",
    "positive=data.loc[data.sentiment==1,'Tweets'].count()\n",
    "negative=data.loc[data.sentiment==-1,'Tweets'].count()\n",
    "neutral=data.loc[data.sentiment==0,'Tweets'].count()\n",
    "\n",
    "#Let's plot\n",
    "labels='Postive', 'Negative', 'Neutral'\n",
    "sizes=[positive, negative, neutral]\n",
    "explode=(0, 0.1, 0)\n",
    "fig1, ax1 = plt.subplots()\n",
    "ax1.pie(sizes, explode=explode, labels=labels, autopct='%1.1f%%',\n",
    "        shadow=True, startangle=0)\n",
    "ax1.axis('equal') \n",
    "plt.show()"
   ]
  }
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