Twitter_English_sentiment.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Track Trending Topic on Twitter"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Download Tweets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import tweepy\n",
    "from tweepy import OAuthHandler\n",
    "import json\n",
    "import pandas as pd\n",
    "import datetime\n",
    " \n",
    "consumer_key = 'xxxx'\n",
    "consumer_secret = 'xxxx'\n",
    "access_token = 'xxxx'\n",
    "access_secret = 'xxxx'\n",
    " \n",
    "auth = OAuthHandler(consumer_key, consumer_secret)\n",
    "auth.set_access_token(access_token, access_secret)\n",
    "api = tweepy.API(auth, wait_on_rate_limit=True)\n",
    " \n",
    "message,favorite_count,retweet_count,created_at,user_name,screen_name,favourites_count,description,friends_count,followers_count,location=[],[],[],[],[],[],[],[],[],[],[]\n",
    "\n",
    "for status in tweepy.Cursor(api.search, q='North Korea -filter:retweets').items(5000): #search by keyword, filter retweet\n",
    "    message.append(status.text)\n",
    "    favorite_count.append(status.favorite_count)\n",
    "    retweet_count.append(status.retweet_count)\n",
    "    created_at.append(status.created_at)\n",
    "    user_name.append(status.user.name)\n",
    "    screen_name.append(status.user.screen_name)\n",
    "    favourites_count.append(status.user.favourites_count)\n",
    "    description.append(status.user.description)\n",
    "    friends_count.append(status.user.friends_count)\n",
    "    followers_count.append(status.user.followers_count)\n",
    "    location.append(status.user.location)\n",
    "    \n",
    "df4=pd.DataFrame({'Message':message,\n",
    "                'Tweet Favorite Count':favorite_count,\n",
    "                'Retweet Count':retweet_count,\n",
    "                'Created At':created_at,\n",
    "                'Username':user_name,\n",
    "                'Handle':screen_name,\n",
    "                'Likes':favourites_count,\n",
    "                'User Description':description,\n",
    "                'Following':friends_count,\n",
    "                'Followers':followers_count,\n",
    "                'Location':location})\n",
    "pd.DataFrame(df4).to_excel('North Korea.xlsx', header=True, index=True)\n",
    "display(df4) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "df4 = pd.read_excel('North Korea.xlsx') #load the data from saved file"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# North Korea"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Text Cleaning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "df4['tweets_clean'] = df4['Message'].apply(lambda x: \" \".join(x.lower() for x in str(x).split())) #lower case\n",
    "df4['tweets_clean'] = df4['tweets_clean'].str.replace('[^\\w\\s]','') #removes punctuation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "df4['word_count'] = df4['tweets_clean'].apply(lambda x: len(str(x).split(\" \"))) #descriptive stats to understand data - returns word count\n",
    "df4['unique word_count'] = df4['tweets_clean'].apply(lambda x: len(set(str(x).split(\" \")))) #unique word count\n",
    "df4['char_count'] = df4['tweets_clean'].str.len() #character count by tweet"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### TextBlob Sentiment Analysis - Subjectivity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from textblob import TextBlob\n",
    "\n",
    "def sentiment_subjectivity(text):\n",
    "    try:\n",
    "        return TextBlob(text).sentiment.subjectivity\n",
    "    except:\n",
    "        return None\n",
    "    \n",
    "df4['subjectivity'] = df4['tweets_clean'].map(lambda text: TextBlob(text).sentiment.subjectivity)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### TextBlob Sentiment Analysis - Polarity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "from textblob import TextBlob\n",
    "\n",
    "def sentiment_polarity(text):\n",
    "    try:\n",
    "        return TextBlob(text).sentiment.polarity\n",
    "    except:\n",
    "        return None\n",
    "    \n",
    "df4['polarity'] = df4['tweets_clean'].map(lambda text: TextBlob(text).sentiment.polarity)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Sentiment Analysis - Histogram, Pie Chart, Word Cloud"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.000000    2108\n",
       "0.333333     357\n",
       "1.000000     278\n",
       "0.500000     277\n",
       "0.100000      95\n",
       "0.166667      93\n",
       "0.750000      89\n",
       "0.400000      79\n",
       "0.900000      77\n",
       "0.200000      60\n",
       "Name: subjectivity, dtype: int64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df4['subjectivity'].value_counts().head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0,0.5,'Frequency')"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "ax = df4['subjectivity'].plot.hist(figsize=(12, 8), color='purple')\n",
    "ax.set_title('Sentiment Subjectivity Distribution of Tweets Using North Korea')\n",
    "ax.set_xlabel('Subjectivity')\n",
    "ax.set_ylabel('Frequency')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Polarity analysis on segement with objective tweets filtered out"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "subjective = df4[df4['subjectivity'] != 0]\n",
    "#filtered out 0 for objective tweets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/ariggs/myENV/lib/python3.5/site-packages/ipykernel_launcher.py:8: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  \n"
     ]
    },
    {
     "data": {
      "text/plain": [
       " 0.250000    429\n",
       " 0.000000    291\n",
       " 0.500000    157\n",
       " 0.125000    111\n",
       " 0.200000    101\n",
       "-0.500000     60\n",
       " 0.800000     58\n",
       " 0.100000     57\n",
       " 0.333333     49\n",
       " 0.136364     46\n",
       " 0.400000     46\n",
       "-0.125000     39\n",
       "-0.250000     35\n",
       " 0.600000     33\n",
       "-0.300000     32\n",
       "-0.400000     31\n",
       " 0.350000     31\n",
       "-0.100000     30\n",
       " 0.375000     30\n",
       " 0.300000     30\n",
       " 1.000000     29\n",
       "-0.200000     29\n",
       " 0.285714     27\n",
       "-1.000000     25\n",
       " 0.700000     24\n",
       " 0.187500     24\n",
       "-0.050000     21\n",
       " 0.166667     20\n",
       "-0.600000     18\n",
       "-0.166667     18\n",
       "            ... \n",
       " 0.341667      1\n",
       "-0.051852      1\n",
       " 0.092857      1\n",
       " 0.305556      1\n",
       " 0.293750      1\n",
       " 0.256566      1\n",
       " 0.095238      1\n",
       " 0.450000      1\n",
       " 0.159524      1\n",
       "-0.056250      1\n",
       "-0.056818      1\n",
       "-0.112500      1\n",
       "-0.104167      1\n",
       " 0.272727      1\n",
       "-0.002976      1\n",
       "-0.070833      1\n",
       " 0.308333      1\n",
       " 0.141667      1\n",
       " 0.283333      1\n",
       "-0.337500      1\n",
       "-0.350000      1\n",
       "-0.178571      1\n",
       " 0.126667      1\n",
       "-0.062500      1\n",
       " 0.268182      1\n",
       "-0.249167      1\n",
       "-0.181818      1\n",
       " 0.193182      1\n",
       " 0.068750      1\n",
       " 0.194444      1\n",
       "Name: polarity, Length: 437, dtype: int64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from textblob import TextBlob\n",
    "def sentiment_polarity(text):\n",
    "    try:\n",
    "        return TextBlob(text).sentiment.polarity\n",
    "    except:\n",
    "        return None\n",
    "    \n",
    "subjective['polarity'] = subjective['tweets_clean'].map(lambda text: TextBlob(text).sentiment.polarity)\n",
    "\n",
    "subjective['polarity'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0,0.5,'Frequency')"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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e05+rB2cLQ7R6D3RrrX0t03jkUza3fHdUpuENu/V17J7p+JBHZhqisnT5oySPWGlf7gH7eZmO+Zh1zf56X7osjX9+WvWDD6tqr6r6tb788Ul+vqYDsjdlCu0rHlRaVbfrz+2mTB84v5uV2/g6mb4RuKimg3OXHxB6hf1gFccm+d+Zjot5w8z0FyZ5dn/PT1X9SFUNPVUgzBKu2Zl8I9PX1yfXdPaKkzIdif+kJGmtvTFTT+ar+9eSn8h00N08TswUMs6rqhG9Ic/P9A/s7VX1jV7rz89536WviC+squWn9prHQzP19p2T5I1JjmqtvXOF5V6eqQfw7EzjxU9aYZlV9W8Ojk3y+f517T59+vsz/fP9cGttta/Jlzykqi7JFIyOzxT0f66tfO7ba2Ya6/uVTF/x/0im8cfJ1rfZyZnGGn8l0xCDB7bWLuzznp7pIK6vZRrjuTQuNq21b/Xl39+3/QrnLe7ruG+mffPCJH+c5L5b09PWn7unJ3l9ph7Hm2WFnt6r4L2Zehg/PHP72pk5gDXTcJxzMoXIizP1wv5Yr+/9SR6fadjARZkOPH5YLu+pfGamD5oXVdXvZeohfXOm1/MnMn0Qec0qtT0t0xCA/840VOjPkjy4tfbZPv+WmY6d+EamkPxXbY3ntu7DqX4100HIX8t0IPLbsvlTfP5cLj+A+OAkH5rjcT6T5Lgk1+qTHphpm45trZ23dMn0YeW6WX34x4syDb26+8y0MzJ92Fy6PKyPHf/bTAfpfj3Th8W791rOzfQ+8YJM+/5+SU5dZZv3zPQN4UVJPp/pPeP5Kyz3V5mGgVyYad85Ydn85yb5jZrO5PSXq2zbq/p2v7WP217yl0nemeTE/n76X5naHRairjhcEGD91XRKtFe11rb4Yx+wvanpdI7P7gF1h9d7pc/LdNaZhf7wDmwEeq6B7UpNv5h5cFbvjYTtSlXduQ81uHpVPSbTtwPvWO+6Fqmm05nuUVW7Zhqy8q3M0QMPO4NNW14EYNuoqmMyfa3+hGVnLIHt2U9k+jC4W6YhFr+6Exws90uZzk6yKdPwnAe01rb2fOOwQzEsBAAABjEsBAAABhGuAQBgkA095voGN7hBO+CAA9a7DAAAdnAf+tCHvtJa23tLy23ocH3AAQfklFPmOfc+AABsvara0m8vJDEsBAAAhhGuAQBgEOEaAAAGEa4BAGAQ4RoAAAYRrgEAYBDhGgAABhGuAQBgEOEaAAAGEa4BAGAQ4RoAAAYRrgEAYBDhGgAABhGuAQBgEOEaAAAGEa4BAGAQ4RoAAAYRrgEAYBDhGgAABtm03gUAsG0dXUevdwnb3FHtqPUuAdhJ6LkGAIBBhGsAABhEuAYAgEGEawAAGES4BgCAQYRrAAAYRLgGAIBBhGsAABhEuAYAgEGEawAAGES4BgCAQYRrAAAYRLgGAIBBhGsAABhEuAYAgEGEawAAGES4BgCAQYRrAAAYRLgGAIBBhGsAABhEuAYAgEGEawAAGES4BgCAQYRrAAAYRLgGAIBBhGsAABhEuAYAgEGEawAAGES4BgCAQYRrAAAYRLgGAIBBhGsAABhEuAYAgEGEawAAGES4BgCAQYRrAAAYRLgGAIBBhGsAABhkoeG6qv6wqj5ZVZ+oqmOrateqOrCqTq6qM6rqNVV1jb7sNfvtM/r8AxZZGwAAjLawcF1V+yZ5fJJDWms/mWSXJIcn+Yskz22t/ViSryV5dL/Lo5N8rU9/bl8OAAA2jEUPC9mU5FpVtSnJbknOTXKXJMf1+cckOaxfP7TfTp9/16qqBdcHAADDbFrUiltrZ1fVXyX5UpJLk7w9yYeSXNRa+15f7Kwk+/br+yY5s9/3e1V1cZLrJ/nKomoEYOdwdB293iVsc0e1o9a7BNgpLXJYyF6ZeqMPTLJPkmsnueeA9T6mqk6pqlMuuOCCq7o6AAAYZpHDQu6W5H9aaxe01i5L8oYkt0+yZx8mkiT7JTm7Xz87yf5J0ufvkeTC5Sttrb2otXZIa+2Qvffee4HlAwDA2iwyXH8pye2qarc+dvquST6V5N1JHtiXOSLJm/v14/vt9PknttbaAusDAIChFhauW2snZzow8cNJTu2P9aIkT07yxKo6I9OY6pf0u7wkyfX79CcmOXJRtQEAwCIs7IDGJGmtHZVk+REVn09y2xWW/XaSBy2yHgAAWCS/0AgAAIMI1wAAMIhwDQAAgwjXAAAwiHANAACDCNcAADCIcA0AAIMI1wAAMIhwDQAAgwjXAAAwiHANAACDCNcAADCIcA0AAIMI1wAAMIhwDQAAgwjXAAAwiHANAACDCNcAADCIcA0AAIMI1wAAMIhwDQAAgwjXAAAwiHANAACDCNcAADCIcA0AAIMI1wAAMIhwDQAAgwjXAAAwiHANAACDCNcAADCIcA0AAIMI1wAAMIhwDQAAgwjXAAAwiHANAACDCNcAADCIcA0AAIMI1wAAMIhwDQAAgwjXAAAwiHANAACDCNcAADCIcA0AAIMI1wAAMIhwDQAAgwjXAAAwiHANAACDCNcAADCIcA0AAIMI1wAAMIhwDQAAgwjXAAAwiHANAACDCNcAADCIcA0AAIMI1wAAMIhwDQAAgwjXAAAwiHANAACDCNcAADCIcA0AAIMI1wAAMIhwDQAAgwjXAAAwiHANAACDCNcAADCIcA0AAIMI1wAAMIhwDQAAgwjXAAAwiHANAACDCNcAADCIcA0AAIMI1wAAMIhwDQAAgwjXAAAwiHANAACDCNcAADCIcA0AAIMI1wAAMIhwDQAAgwjXAAAwiHANAACDCNcAADDIQsN1Ve1ZVcdV1aer6rSq+oWqul5VvaOqTu9/9+rLVlW9oKrOqKqPV9XBi6wNAABGW3TP9fOT/Htr7RZJfibJaUmOTPKu1tpBSd7VbyfJvZIc1C+PSfIPC64NAACGWli4rqo9kvxSkpckSWvtu621i5IcmuSYvtgxSQ7r1w9N8vI2OSnJnlV140XVBwAAoy2y5/rAJBck+eeq+khVvbiqrp3khq21c/sy5yW5Yb++b5IzZ+5/Vp8GAAAbwiLD9aYkByf5h9bazyb5Zi4fApIkaa21JG0tK62qx1TVKVV1ygUXXDCsWAAAuKoWGa7PSnJWa+3kfvu4TGH7y0vDPfrf8/v8s5PsP3P//fq0K2itvai1dkhr7ZC99957YcUDAMBaLSxct9bOS3JmVd28T7prkk8lOT7JEX3aEUne3K8fn+Q3+llDbpfk4pnhIwAAsN3btOD1/36SV1bVNZJ8PsmjMgX611bVo5N8McmD+7InJLl3kjOSfKsvCwAAG8ZCw3Vr7aNJDllh1l1XWLYl+d1F1gMAAIvkFxoBAGAQ4RoAAAYRrgEAYBDhGgAABhGuAQBgEOEaAAAGEa4BAGAQ4RoAAAYRrgEAYBDhGgAABhGuAQBgEOEaAAAGEa4BAGAQ4RoAAAYRrgEAYBDhGgAABhGuAQBgEOEaAAAGEa4BAGAQ4RoAAAYRrgEAYBDhGgAABhGuAQBgEOEaAAAGEa4BAGAQ4RoAAAYRrgEAYBDhGgAABhGuAQBgEOEaAAAGEa4BAGCQucJ1Vf3UogsBAICNbt6e67+vqg9U1e9U1R4LrQgAADaoucJ1a+2OSR6eZP8kH6qqV1XV3RdaGQAAbDBzj7lurZ2e5GlJnpzkTkleUFWfrqpfXVRxAACwkcw75vqnq+q5SU5Lcpck92ut3bJff+4C6wMAgA1j05zL/U2SFyd5amvt0qWJrbVzquppC6kMAAA2mHnD9X2SXNpa+36SVNXVkuzaWvtWa+0VC6sOAAA2kHnHXL8zybVmbu/WpwEAAN284XrX1tolSzf69d0WUxIAAGxM84brb1bVwUs3qurnkly6meUBAGCnM++Y6z9I8rqqOidJJblRkocsrCoAANiA5grXrbUPVtUtkty8T/pMa+2yxZUFAAAbz7w910lymyQH9PscXFVprb18IVUBAMAGNFe4rqpXJLlZko8m+X6f3JII1wAA0M3bc31Iklu11toiiwEAgI1s3rOFfCLTQYwAAMAq5u25vkGST1XVB5J8Z2lia+3+C6kKAAA2oHnD9TMWWQQAAOwI5j0V33ur6iZJDmqtvbOqdkuyy2JLAwCAjWWuMddV9VtJjkvyj33SvknetKiiAABgI5r3gMbfTXL7JF9Pktba6Ul+ZFFFAQDARjRvuP5Oa+27SzeqalOm81wDAADdvOH6vVX11CTXqqq7J3ldkrcsriwAANh45g3XRya5IMmpSR6b5IQkT1tUUQAAsBHNe7aQHyT5p34BAABWMFe4rqr/yQpjrFtrNx1eEQAAbFDz/ojMITPXd03yoCTXG18OAABsXHONuW6tXThzObu19rwk91lwbQAAsKHMOyzk4JmbV8vUkz1vrzcAAOwU5g3Ifz1z/XtJvpDkwcOrAQCADWzes4XcedGFAADARjfvsJAnbm5+a+05Y8oBAICNay1nC7lNkuP77fsl+UCS0xdRFAAAbETzhuv9khzcWvtGklTVM5L8W2vtEYsqDAAANpp5f/78hkm+O3P7u30aAADQzdtz/fIkH6iqN/bbhyU5ZjElAQDAxjTv2UKeWVVvTXLHPulRrbWPLK4sAADYeOYdFpIkuyX5emvt+UnOqqoDF1QTAABsSHOF66o6KsmTkzylT7p6kn9ZVFEAALARzdtz/YAk90/yzSRprZ2T5DqLKgoAADaiecP1d1trLUlLkqq69uJKAgCAjWnecP3aqvrHJHtW1W8leWeSf1pcWQAAsPHMe7aQv6qquyf5epKbJ/nT1to7FloZAABsMFsM11W1S5J3ttbunESgBgCAVWxxWEhr7ftJflBVe2yDegAAYMOa9xcaL0lyalW9I/2MIUnSWnv8QqoCAIANaN5w/YZ+AQAAVrHZcF1VP9pa+1Jr7ZhtVRAAAGxUWxpz/aalK1X1+gXXAgAAG9qWwnXNXL/pIgsBAICNbkvhuq1yHQAAWGZLBzT+TFV9PVMP9rX69fTbrbV23YVWBwAAG8hmw3VrbZdtVQgAAGx0W/wRmauqqnapqo9U1b/22wdW1clVdUZVvaaqrtGnX7PfPqPPP2DRtQEAwEgLD9dJnpDktJnbf5Hkua21H0vytSSP7tMfneRrffpz+3IAALBhLDRcV9V+Se6T5MX9diW5S5Lj+iLHJDmsXz+0306ff9e+PAAAbAiL7rl+XpI/TvKDfvv6SS5qrX2v3z4ryb79+r5JzkySPv/ivvwVVNVjquqUqjrlggsuWGTtAACwJgsL11V13yTnt9Y+NHK9rbUXtdYOaa0dsvfee49cNQAAXCVbOhXfVXH7JPevqnsn2TXJdZM8P8meVbWp907vl+TsvvzZSfZPclZVbUqyR5ILF1gfAAAMtbCe69baU1pr+7XWDkhyeJITW2sPT/LuJA/six2R5M39+vH9dvr8E1trfrgGAIANY1ucLWS5Jyd5YlWdkWlM9Uv69JckuX6f/sQkR65DbQAAsNUWOSzkh1pr70nynn7980luu8Iy307yoG1RDwAALMJ69FwDAMAOSbgGAIBBhGsAABhEuAYAgEGEawAAGES4BgCAQYRrAAAYRLgGAIBBhGsAABhEuAYAgEGEawAAGES4BgCAQYRrAAAYRLgGAIBBhGsAABhEuAYAgEGEawAAGES4BgCAQYRrAAAYRLgGAIBBhGsAABhEuAYAgEGEawAAGES4BgCAQYRrAAAYRLgGAIBBhGsAABhEuAYAgEGEawAAGES4BgCAQYRrAAAYRLgGAIBBhGsAABhEuAYAgEGEawAAGES4BgCAQYRrAAAYRLgGAIBBhGsAABhk03oXALCejq6j17sEAHYgeq4BAGAQ4RoAAAYRrgEAYBDhGgAABhGuAQBgEOEaAAAGEa4BAGAQ4RoAAAYRrgEAYBC/0AgAO6Cd7ddHj2pHrXcJkETPNQAADCNcAwDAIMI1AAAMIlwDAMAgwjUAAAwiXAMAwCDCNQAADCJcAwDAIMI1AAAMIlwDAMAgwjUAAAwiXAMAwCDCNQAADCJcAwDAIMI1AAAMIlwDAMAgwjUAAAwiXAMAwCDCNQAADCJcAwDAIMI1AAAMIlwDAMAgwjUAAAwiXAMAwCDCNQAADCLSc5lXAAANf0lEQVRcAwDAIMI1AAAMIlwDAMAgm9a7AGD7cXQdvd4lAMCGpucaAAAGEa4BAGAQ4RoAAAYRrgEAYJCFheuq2r+q3l1Vn6qqT1bVE/r061XVO6rq9P53rz69quoFVXVGVX28qg5eVG0AALAIi+y5/l6SJ7XWbpXkdkl+t6puleTIJO9qrR2U5F39dpLcK8lB/fKYJP+wwNoAAGC4hYXr1tq5rbUP9+vfSHJakn2THJrkmL7YMUkO69cPTfLyNjkpyZ5VdeNF1QcAAKNtkzHXVXVAkp9NcnKSG7bWzu2zzktyw3593yRnztztrD4NAAA2hIWH66raPcnrk/xBa+3rs/Naay1JW+P6HlNVp1TVKRdccMHASgEA4KpZaLiuqqtnCtavbK29oU/+8tJwj/73/D797CT7z9x9vz7tClprL2qtHdJaO2TvvfdeXPEAALBGizxbSCV5SZLTWmvPmZl1fJIj+vUjkrx5Zvpv9LOG3C7JxTPDRwAAYLu3aYHrvn2SX09yalV9tE97apJnJ3ltVT06yReTPLjPOyHJvZOckeRbSR61wNoAAGC4hYXr1tp/JqlVZt91heVbkt9dVD0AALBofqERAAAGEa4BAGAQ4RoAAAYRrgEAYBDhGgAABhGuAQBgEOEaAAAGEa4BAGAQ4RoAAAYRrgEAYBDhGgAABhGuAQBgEOEaAAAGEa4BAGAQ4RoAAAYRrgEAYBDhGgAABhGuAQBgEOEaAAAGEa4BAGAQ4RoAAAYRrgEAYBDhGgAABhGuAQBgkE3rXQBsr46uo9e7BABgg9FzDQAAgwjXAAAwiHANAACDCNcAADCIcA0AAIMI1wAAMIhwDQAAgwjXAAAwiHANAACDCNcAADCIcA0AAIMI1wAAMIhwDQAAgwjXAAAwiHANAACDCNcAADCIcA0AAINsWu8CAABYu6Pr6PUuYZs7qh213iVskZ5rAAAYRLgGAIBBhGsAABhEuAYAgEGEawAAGES4BgCAQYRrAAAYRLgGAIBBhGsAABhEuAYAgEGEawAAGES4BgCAQYRrAAAYRLgGAIBBhGsAABhk03oXAABwVR1dR693CZBEzzUAAAwjXAMAwCDCNQAADCJcAwDAIMI1AAAMIlwDAMAgTsXHXJziCABgy/RcAwDAIMI1AAAMIlwDAMAgwjUAAAzigMat5AA/AACW03MNAACDCNcAADCIcA0AAIMI1wAAMIhwDQAAgwjXAAAwiHANAACDCNcAADCIcA0AAIMI1wAAMIhwDQAAgwjXAAAwiHANAACDbFfhuqruWVWfqaozqurI9a4HAADWYrsJ11W1S5K/S3KvJLdK8tCqutX6VgUAAPPbbsJ1ktsmOaO19vnW2neTvDrJoetcEwAAzG17Ctf7Jjlz5vZZfRoAAGwIm9a7gLWqqsckeUy/eUlVfWadSrlBkq+s02NvRNprbbTX2mivtdFea6O91kZ7rY32WoNn1DPWs71uMs9C21O4PjvJ/jO39+vTrqC19qIkL9pWRa2mqk5prR2y3nVsFNprbbTX2mivtdFea6O91kZ7rY32WpuN0F7b07CQDyY5qKoOrKprJDk8yfHrXBMAAMxtu+m5bq19r6p+L8nbkuyS5KWttU+uc1kAADC37SZcJ0lr7YQkJ6x3HXNa96EpG4z2WhvttTbaa22019por7XRXmujvdZmu2+vaq2tdw0AALBD2J7GXAMAwIYmXK+iqh5UVZ+sqh9U1apHpa72k+39wMyT+/TX9IM0d1hVdb2qekdVnd7/7rXCMneuqo/OXL5dVYf1eS+rqv+ZmXfrbb8V29Y8bdaX+/5Muxw/M90+duVlbl1V/91fux+vqofMzNsp9rHV3pNm5l+z7y9n9P3ngJl5T+nTP1NVv7It614Pc7TVE6vqU31feldV3WRm3oqvyx3dHG32yKq6YKZtfnNm3hH99Xt6VR2xbStfH3O013Nn2uqzVXXRzLydah+rqpdW1flV9YlV5ldVvaC35cer6uCZedvXvtVac1nhkuSWSW6e5D1JDlllmV2SfC7JTZNcI8nHktyqz3ttksP79Rcm+e313qYFt9dfJjmyXz8yyV9sYfnrJflqkt367ZcleeB6b8f22GZJLlllun3sysv8eJKD+vV9kpybZM9+e4ffxzb3njSzzO8keWG/fniS1/Trt+rLXzPJgX09u6z3Nq1zW9155j3qt5faqt9e8XW5I1/mbLNHJvnbFe57vSSf73/36tf3Wu9tWu/2Wrb872c6mcNOuY8l+aUkByf5xCrz753krUkqye2SnLy97lt6rlfRWjuttbalH6hZ8Sfbq6qS3CXJcX25Y5IctrhqtwuHZtrOZL7tfWCSt7bWvrXQqrZva22zH7KPrby9rbXPttZO79fPSXJ+kr23WYXrb8X3pGXLzLbjcUnu2venQ5O8urX2ndba/yQ5o69vR7XFtmqtvXvmPeqkTL+/sDObZ/9aza8keUdr7autta8leUeSey6ozu3FWtvroUmO3SaVbYdaa/+RqdNtNYcmeXmbnJRkz6q6cbbDfUu4vmpW+8n26ye5qLX2vWXTd2Q3bK2d26+fl+SGW1j+8Fz5TeSZ/aue51bVNYdXuP2Zt812rapTquqkpWE0sY9tcR+rqttm6i363MzkHX0fW+09acVl+v5zcab9aZ777kjWur2PztRrtmSl1+WObt42+7X+OjuuqpZ+HG5n27+SNWxzH3J0YJITZybvjPvY5qzWntvdvrVdnYpvW6uqdya50Qqz/qS19uZtXc/2bnPtNXujtdaqatXT0PRPmj+V6ZzmS56SKTBdI9Npdp6c5P9c1ZrX26A2u0lr7eyqummSE6vq1EyBaIczeB97RZIjWms/6JN3yH2MxauqRyQ5JMmdZiZf6XXZWvvcymvYqbwlybGtte9U1WMzfUtyl3WuaSM4PMlxrbXvz0yzj21QO3W4bq3d7SquYrWfbL8w09cVm3rP0Io/5b7RbK69qurLVXXj1tq5Pdicv5lVPTjJG1trl82se6lH8jtV9c9J/mhI0etsRJu11s7ufz9fVe9J8rNJXh/72IrtVVXXTfJvmT4knzSz7h1yH1tmtfeklZY5q6o2Jdkj03vWPPfdkcy1vVV1t0wf7u7UWvvO0vRVXpc7evDZYpu11i6cufniTMdKLN33l5fd9z3DK9y+rOU1dXiS352dsJPuY5uzWntud/uWYSFXzYo/2d6mEfbvzjSuOEmOSLKj94Qfn2k7ky1v75XGlfWwtDSW+LAkKx4tvIPZYptV1V5Lwxeq6gZJbp/kU/axVdvrGknemGlc3nHL5u0M+9iK70nLlpltxwcmObHvT8cnObyms4kcmOSgJB/YRnWvhy22VVX9bJJ/THL/1tr5M9NXfF1us8rXzzxtduOZm/dPclq//rYk9+htt1eSe+SK317uiOZ5PaaqbpHpQLz/npm2s+5jm3N8kt/oZw25XZKLe6fJ9rdvrefRlNvzJckDMo3b+U6SLyd5W5++T5ITZpa7d5LPZvo0+Scz02+a6R/TGUlel+Sa671NC26v6yd5V5LTk7wzyfX69EOSvHhmuQMyfcq82rL7n5jk1EyB51+S7L7e27Q9tFmSX+zt8rH+99H2sc221yOSXJbkozOXW+9M+9hK70mZhr/cv1/fte8vZ/T956Yz9/2Tfr/PJLnXem/LdtBW7+zv/0v70vF9+qqvyx39Mkeb/XmST/a2eXeSW8zc93/1/e6MJI9a723ZHtqr335Gkmcvu99Ot49l6nQ7t7+Hn5XpOIfHJXlcn19J/q635amZOZPb9rZv+YVGAAAYxLAQAAAYRLgGAIBBhGsAABhEuAYAgEGEawAAGES4Btggqur7VfXRqvpEVb2uqnbbwvKXbMVjnFBVe/bL72x9tQA7J+EaYOO4tLV269baTyb5bqZzwA7Rf5jhaq21e7fWLkqyZxLhGmCNhGuAjel9SX4sSarqib03+xNV9QfLF6yq3avqXVX14ao6taoO7dMPqKrPVNXLM/24zv5V9YX+i3DPTnKz3lP+/6rq5VV12Mw6X7m0HgAu50dkADaIqrqktbZ7VW1K8vok/57pVxZfluR2mX7B7OQkj2itfWTZ8ru11r7eg/NJmX7e/CZJPp/kF1trJ/XH+EKmX73cPcm/9l7yVNWdkvxha+2wqtoj0y8WHtRa+9622n6AjUDPNcDGca2q+miSU5J8KclLktwhyRtba99srV2S5A1J7rjsfpXkWVX18Uw/6b1vkhv2eV9cCtab01p7b5KDqmrvJA9N8nrBGuDKNq13AQDM7dLW2q1nJ1TVPPd7eJK9k/xca+2y3ju9a5/3zTU8/suTPCLJ4UketYb7Aew09FwDbGzvS3JYVe1WVddO8oA+bdYeSc7vwfrOmYaDbMk3klxn2bSXJfmDJGmtfeoqVQ2wg9JzDbCBtdY+XFUvyzT2Okle3Fr7yLLFXpnkLVV1aqYhJZ+eY70XVtX7q+oTSd7aWvvfrbUvV9VpSd40cBMAdigOaARgLv282qcmObi1dvF61wOwPTIsBIAtqqq7JTktyd8I1gCr03MNAACD6LkGAIBBhGsAABhEuAYAgEGEawAAGES4BgCAQYRrAAAY5P8DVXzXcKRISXAAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "ax = subjective['polarity'].plot.hist(figsize=(12, 8), color='purple')\n",
    "ax.set_title('Sentiment Polarity Distribution of Tweets Using #NARLegislative')\n",
    "ax.set_xlabel('Polarity')\n",
    "ax.set_ylabel('Frequency')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### To compare, polarity analysis on all tweets before subjectivity analysis was run"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       " 0.000000    2390\n",
       " 0.250000     429\n",
       " 0.500000     157\n",
       " 0.125000     111\n",
       " 0.200000     101\n",
       "-0.500000      60\n",
       " 0.800000      58\n",
       " 0.100000      57\n",
       " 0.333333      49\n",
       " 0.400000      46\n",
       "Name: polarity, dtype: int64"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df4['polarity'].value_counts().head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0,0.5,'Frequency')"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "ax = df4['polarity'].plot.hist(figsize=(12, 8), color='purple')\n",
    "ax.set_title('Sentiment Polarity Distribution of Tweets Using North Korea')\n",
    "ax.set_xlabel('Polarity')\n",
    "ax.set_ylabel('Frequency')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.000000    2108\n",
       "0.333333     357\n",
       "1.000000     278\n",
       "0.500000     277\n",
       "0.100000      95\n",
       "0.166667      93\n",
       "0.750000      89\n",
       "0.400000      79\n",
       "0.900000      77\n",
       "0.200000      60\n",
       "Name: subjectivity, dtype: int64"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df4['subjectivity'].value_counts().head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Objective              2119\n",
       "Somewhat subjective     468\n",
       "Very Subjective         305\n",
       "Name: subjectivity_range, dtype: int64"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df4['subjectivity_range'] = pd.cut(df4['subjectivity'],bins=[0,.667,.9,1], labels=['Objective','Somewhat subjective','Very Subjective'])\n",
    "sub2 = df4['subjectivity_range'].value_counts()\n",
    "sub2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Subjectivity Pie Chart"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([<matplotlib.axes._subplots.AxesSubplot object at 0x7fe64b69c9b0>],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sub2.plot(kind='pie', subplots=True, figsize=(4, 4), colors=['b', 'c', 'g'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Polarity Pie Chart with Objective Tweets Filtered Out"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/ariggs/myENV/lib/python3.5/site-packages/ipykernel_launcher.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  \"\"\"Entry point for launching an IPython kernel.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Positive    1852\n",
       "Negative     602\n",
       "Neutral      413\n",
       "Name: polarity_range, dtype: int64"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "subjective['polarity_range'] = pd.cut(subjective['polarity'],bins=[-1,-.1,0,1], labels=['Negative','Neutral','Positive'])\n",
    "pol1 = subjective['polarity_range'].value_counts()\n",
    "pol1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([<matplotlib.axes._subplots.AxesSubplot object at 0x7fe64b6c1cc0>],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 288x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pol1.plot(kind='pie', subplots=True, figsize=(4, 4), colors=['g', 'b', 'c'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Polairty Pie Chart of All Tweets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Neutral     2514\n",
       "Positive    1852\n",
       "Negative     609\n",
       "Name: polarity_range, dtype: int64"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df4['polarity_range'] = pd.cut(df4['polarity'],bins=[-1,-.1,0,1], labels=['Negative','Neutral','Positive'])\n",
    "pol2 = df4['polarity_range'].value_counts()\n",
    "pol2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([<matplotlib.axes._subplots.AxesSubplot object at 0x7fe64b6691d0>],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 288x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pol2.plot(kind='pie', subplots=True, figsize=(4, 4), colors=['b', 'g', 'c'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Exploring Negative Tweets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "negative = df4.loc[df4['polarity_range'] == 'Negative'] #df4 of all tweets (609 total)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4       @Jaz_manianDevil You’re going to totally ignor...\n",
       "6       @tedlieu @POTUS @realDonaldTrump Donald J. Tru...\n",
       "14      Trump is a profoundly corrupt, morally squalid...\n",
       "26      @victoriastudio2 @DavidNakamura @mariasacchett...\n",
       "30      @RepDonBeyer You mean the North Korea that Dem...\n",
       "33      \"PRESIDENT\" TRUMP ENTERED NORTH KOREA ILLEGALL...\n",
       "35      Anyone else notice that Trump just illegally c...\n",
       "40      @NoWay7790 @realDonaldTrump Then MOVE to Venez...\n",
       "41      @Purrcival1 @martyn_williams You mean the book...\n",
       "53      Dibs on writing the Trump In North Korea opera...\n",
       "57      @michaelbeatty3 @dianne1h @realDonaldTrump @Ma...\n",
       "70      @RadioFreeTom Can I make a statement that Nobo...\n",
       "72      @diana_declue @mitchellreports @MSNBC Name one...\n",
       "76      Honor?? Makes me sick #TrumpKim meets Kim Jong...\n",
       "77      Its annoying watching liberals turn into hawks...\n",
       "85      Those who are criticising The Worm for meeting...\n",
       "90      @backroads_linda @MikeGravel North Korea has s...\n",
       "112     @GOP @realDonaldTrump Oh, if only stay he and ...\n",
       "122     uhm apparently tr*mp crossed into north korea ...\n",
       "127     #NorthKorea North Korea : not sure what I thin...\n",
       "131     @realDonaldTrump Commander in Show off!   You ...\n",
       "132     #USAPols; New Trump spox #StephanieGrisham was...\n",
       "135     @BauschLomb In North Korea, Tucker Carlson say...\n",
       "136     Trump meets Kim Jong Un, becomes first sitting...\n",
       "148     Trump said he was honored to step into North K...\n",
       "158     Jfc. Some guy on MSNBC just asked if Donald Tr...\n",
       "160     Whys everyone hate Trump? He’s the first presi...\n",
       "162     @tecovas In North Korea, Tucker Carlson says b...\n",
       "182     @backroads_linda @MikeGravel South Korea has t...\n",
       "186     @realDonaldTrump Donald J. Trump\\n✔\\n@realDona...\n",
       "                              ...                        \n",
       "4798    @thehill Why would it be bad if Obama DID meet...\n",
       "4805    @playbookplus @politico The only bad thing abo...\n",
       "4809    @TVietor08 North Korea uses rape as a tool for...\n",
       "4816    Yeah. Thank god. Error only allowed, watch me ...\n",
       "4832    F**ker Carlson is now justifying the murders o...\n",
       "4835    @castobarym To sell to politicians bad we will...\n",
       "4842    @draininbuckets @TylerinElPaso @bjoernstritzel...\n",
       "4855    @funder @realDonaldTrump is working extremely ...\n",
       "4857    #TrumpKim What do we want with North Korea? We...\n",
       "4863    @TedMarmalade Never heard of salon, but it doe...\n",
       "4884    Iherb discount code \\n\\nAHB6653\\n\\nUse the cod...\n",
       "4885    Trump thinks he’s the shit because he went to ...\n",
       "4888    @WhiteHouse For his narcissism @realDonaldTrum...\n",
       "4892    CREEPY @POTUS TAKES SISTER WIFE “Dumb As A Bri...\n",
       "4899    North Korea restaurant ordered closed, Myanmar...\n",
       "4903    @JoyceBruns @Jimryan015 The pathetic cowards w...\n",
       "4912    CREEPY @POTUS TAKES SISTER WIFE “Dumb As A Bri...\n",
       "4916    There has been no denuclearization, yet we hav...\n",
       "4923    North Korea would be stupid to give up its nuk...\n",
       "4941    @jayrosen_nyu Wasn't talking to North Korea 'T...\n",
       "4947    @PaleoPhil @MajedAPhD Removing sanctions from ...\n",
       "4958    This I agree with. Pulling off the North Korea...\n",
       "4959    @CJ_isnowblue It's absurd.\\nWhy?\\nFor legitimi...\n",
       "4964    Pferderennen-Glücksspiel ist nicht mehr illega...\n",
       "4967    @mjfree I bet if he was talking tough on North...\n",
       "4968    Fuck Trump being in North Korea. Keep your fuc...\n",
       "4972    \"Our President shouldn’t be squandering Americ...\n",
       "4975    16 Disturbing Pictures From Inside North Korea...\n",
       "4976    @RyanHillMI @realDonaldTrump Might have been k...\n",
       "4999    Trump’s decision to go into North Korea is hig...\n",
       "Name: Message, Length: 609, dtype: object"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "negative['Message']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "positive = df4.loc[df4['polarity_range'] == 'Positive'] #df4 positive tweets (1852)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1       stephanie grisham the new white house press se...\n",
       "2       seekero94290382 gop realdonaldtrump its not ha...\n",
       "7       washtimes a little bruised and hurt are differ...\n",
       "10      gopchairwoman realdonaldtrump im old enough to...\n",
       "11      kamalaharris so kamala harris wants to go to w...\n",
       "13      dennis rodman is still the most mature adminis...\n",
       "15      goldengateblond wikipedia love letter diplomac...\n",
       "19      infinityday257 this crooked administration is ...\n",
       "20      realdonaldtrump i dont agree with most of what...\n",
       "23      sauterrory here you go rory kju tortures impri...\n",
       "25      georgevassilas realdonaldtrump be thankful you...\n",
       "29      kamalaharris trump goes to north korea to try ...\n",
       "31      raheemkassam trump demonstrated to an enemy th...\n",
       "36      realdonaldtrump great handshake in north korea...\n",
       "39      trump meets kim jong un becomes first sitting ...\n",
       "42      new press secretary stephanie grisham bruised ...\n",
       "44      europe trump first us president to set foot in...\n",
       "47      wonderful peace news president realdonaldtrump...\n",
       "49      mitchellreports msnbc its amazing how nbcs kor...\n",
       "50      trump rebuilds the us relationship with russia...\n",
       "60      solipsismworld andrewyang he created the tensi...\n",
       "61      dear north korea when america sends their peop...\n",
       "62      trump becomes first sitting us president to se...\n",
       "63      youve got to be honest about what it means to ...\n",
       "67      mariabartiromo reptimryan foxnews sundayfuture...\n",
       "68      rolandscahill wasnt obama the one who wanted a...\n",
       "69      donald trump meets kim jong un becomes first s...\n",
       "73      boknowsnews joebiden realdonaldtrump cbsnews y...\n",
       "75      kamalaharris and you madam senator would be a ...\n",
       "83      president trump says north korea has tremendou...\n",
       "                              ...                        \n",
       "4915    trump proud to step over dmz border into north...\n",
       "4925    kamalaharris if just an op and so easily done ...\n",
       "4927    wee have a president that visits north korea s...\n",
       "4928    harry kazianis trumps unconventional north kor...\n",
       "4929    ivanka trump says stepping into north korea su...\n",
       "4930    harry kazianis trumps unconventional north kor...\n",
       "4931    loudobbs realdonaldtrump first sitting preside...\n",
       "4932    perhaps the new ancient vulcan saying is only ...\n",
       "4933    realdonaldtrump hysteric meeting more like it ...\n",
       "4934    pink_lady56 but trump got him out didnt he  wa...\n",
       "4937    well amy the real americans are blown away by ...\n",
       "4938    ananavarro rubbish where were you when obana r...\n",
       "4939    trump becomes first us president to step into ...\n",
       "4940    trump meets kim jong un becomes first sitting ...\n",
       "4944    trump meets kim jong un at dmz becomes first s...\n",
       "4948    timrunshismouth please retweet realdonaldtrump...\n",
       "4953    trump is first sitting us president to step fo...\n",
       "4955    4evernevertrump north korea is one of the worl...\n",
       "4956    kylegriffin1 trump has publicly legitimized no...\n",
       "4961    kamalaharris im sure that you could broker pea...\n",
       "4963    realdonaldtrump im pretty sure the potus just ...\n",
       "4965    mollyjongfast lincolnsbible to be fair north k...\n",
       "4970    realdonaldtrump im sure all your christian fol...\n",
       "4973    washington post celebrates the injury of trump...\n",
       "4984    whitehouse great job mr president however its ...\n",
       "4987    realdonaldtrump is standing on the soil of nor...\n",
       "4990    realdonaldtrump what u did today should disgus...\n",
       "4991    it would be so wonderful if north and south ko...\n",
       "4995    mdubowitz there is a major difference american...\n",
       "4996    wadegarrett1527 msmariat elistokols margaretta...\n",
       "Name: tweets_clean, Length: 1852, dtype: object"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "positive['tweets_clean']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Unigrams in negative tweets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "north 397\n",
      "korea 360\n",
      "trump 183\n",
      "president 90\n",
      "realdonaldtrump 83\n",
      "kim 56\n",
      "just 39\n",
      "like 38\n",
      "donald 31\n",
      "obama 28\n",
      "dont 28\n",
      "jong 27\n",
      "bad 26\n",
      "dictator 25\n",
      "potus 25\n",
      "meeting 23\n",
      "koreas 23\n",
      "know 23\n",
      "hes 21\n",
      "way 21\n",
      "did 21\n",
      "news 21\n",
      "stupid 21\n",
      "didnt 20\n",
      "mean 19\n",
      "time 19\n",
      "trumps 19\n",
      "history 19\n",
      "nuclear 18\n",
      "historic 18\n",
      "trying 17\n",
      "otto 17\n",
      "think 17\n",
      "sad 17\n",
      "people 17\n",
      "brutal 17\n",
      "hate 16\n",
      "kamalaharris 16\n",
      "peace 16\n",
      "world 15\n",
      "war 15\n",
      "ewarren 15\n",
      "step 15\n",
      "code 15\n",
      "shit 14\n",
      "going 14\n",
      "idiot 14\n",
      "photo 13\n",
      "got 13\n",
      "remember 13\n"
     ]
    }
   ],
   "source": [
    "from sklearn.feature_extraction.text import CountVectorizer\n",
    "def get_top_n_words(corpus, n=None):\n",
    "    vec = CountVectorizer(stop_words = 'english').fit(corpus)\n",
    "    bag_of_words = vec.transform(corpus)\n",
    "    sum_words = bag_of_words.sum(axis=0) \n",
    "    words_freq = [(word, sum_words[0, idx]) for word, idx in vec.vocabulary_.items()]\n",
    "    words_freq =sorted(words_freq, key = lambda x: x[1], reverse=True)\n",
    "    return words_freq[:n]\n",
    "common_words = get_top_n_words(negative['tweets_clean'], 50)\n",
    "for word, freq in common_words:\n",
    "    print(word, freq)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Unigrams in positive tweets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "north 1384\n",
      "korea 1291\n",
      "trump 838\n",
      "president 667\n",
      "sitting 267\n",
      "kim 263\n",
      "realdonaldtrump 224\n",
      "step 205\n",
      "foot 174\n",
      "jong 131\n",
      "set 125\n",
      "history 104\n",
      "trumps 100\n",
      "donald 93\n",
      "great 92\n",
      "just 88\n",
      "meets 88\n",
      "dmz 73\n",
      "news 72\n",
      "meeting 70\n",
      "potus 70\n",
      "enter 68\n",
      "obama 68\n",
      "new 66\n",
      "good 65\n",
      "like 64\n",
      "steps 64\n",
      "people 62\n",
      "american 61\n",
      "leader 59\n",
      "strategy 58\n",
      "historic 58\n",
      "right 58\n",
      "prize 57\n",
      "love 56\n",
      "nobel 53\n",
      "peace 53\n",
      "youtube 51\n",
      "korean 50\n",
      "press 49\n",
      "diplomacy 49\n",
      "koreas 49\n",
      "war 47\n",
      "dont 47\n",
      "visit 47\n",
      "amp 45\n",
      "better 44\n",
      "im 44\n",
      "nuclear 43\n",
      "harry 42\n"
     ]
    }
   ],
   "source": [
    "from sklearn.feature_extraction.text import CountVectorizer\n",
    "def get_top_n_words(corpus, n=None):\n",
    "    vec = CountVectorizer(stop_words = 'english').fit(corpus)\n",
    "    bag_of_words = vec.transform(corpus)\n",
    "    sum_words = bag_of_words.sum(axis=0) \n",
    "    words_freq = [(word, sum_words[0, idx]) for word, idx in vec.vocabulary_.items()]\n",
    "    words_freq =sorted(words_freq, key = lambda x: x[1], reverse=True)\n",
    "    return words_freq[:n]\n",
    "common_words = get_top_n_words(positive['tweets_clean'], 50)\n",
    "for word, freq in common_words:\n",
    "    print(word, freq)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Most Common Ngrams Found in Tweets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import nltk\n",
    "nltk.download('punkt')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "12862\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "['north',\n",
       " 'korea',\n",
       " 'to',\n",
       " 'the',\n",
       " 'trump',\n",
       " 'a',\n",
       " 'in',\n",
       " 'and',\n",
       " 'is',\n",
       " 'president',\n",
       " 'with',\n",
       " 'of',\n",
       " 'into',\n",
       " 'kim',\n",
       " 'for',\n",
       " 'us',\n",
       " 'you',\n",
       " 'realdonaldtrump',\n",
       " 'first',\n",
       " 'that',\n",
       " 'i',\n",
       " 'he',\n",
       " 'on',\n",
       " 'it',\n",
       " 'this',\n",
       " 'was',\n",
       " 'becomes',\n",
       " 'sitting',\n",
       " 'jong',\n",
       " 'un',\n",
       " 'be',\n",
       " 'what',\n",
       " 'not',\n",
       " 'has',\n",
       " 'have',\n",
       " 'are',\n",
       " 'step',\n",
       " 'meeting',\n",
       " 'as',\n",
       " 'we',\n",
       " 'at',\n",
       " 'his',\n",
       " 'so',\n",
       " 'if',\n",
       " 'just',\n",
       " 'trumps',\n",
       " 'all',\n",
       " 'history',\n",
       " 'would',\n",
       " 'foot']"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import nltk\n",
    "from nltk.tokenize import word_tokenize\n",
    "\n",
    "tweets = df4.tweets_clean.str.cat(sep=' ')\n",
    "\n",
    "#function to split text into word\n",
    "tokens = word_tokenize(tweets)\n",
    "\n",
    "vocabulary = set(tokens)\n",
    "print(len(vocabulary))\n",
    "\n",
    "frequency_dist = nltk.FreqDist(tokens)\n",
    "sorted(frequency_dist,key=frequency_dist.__getitem__, reverse=True)[0:50]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "from stop_words import get_stop_words\n",
    "stop_words = get_stop_words('en')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['north',\n",
       " 'korea',\n",
       " 'trump',\n",
       " 'president',\n",
       " 'kim',\n",
       " 'us',\n",
       " 'realdonaldtrump',\n",
       " 'first',\n",
       " 'becomes',\n",
       " 'sitting',\n",
       " 'jong',\n",
       " 'un',\n",
       " 'step',\n",
       " 'meeting',\n",
       " 'just',\n",
       " 'trumps',\n",
       " 'history',\n",
       " 'foot',\n",
       " 'obama',\n",
       " 'donald',\n",
       " 'like',\n",
       " 'steps',\n",
       " 'nuclear',\n",
       " 'press',\n",
       " 'potus',\n",
       " 'koreas',\n",
       " 'meets',\n",
       " 'will',\n",
       " 'via',\n",
       " 'dmz',\n",
       " 'set',\n",
       " 'peace',\n",
       " 'can',\n",
       " 'news',\n",
       " 'war',\n",
       " 'secretary',\n",
       " 'historic',\n",
       " 'people',\n",
       " 'dont',\n",
       " 'visit',\n",
       " 'go',\n",
       " 'get',\n",
       " 'now',\n",
       " 'one',\n",
       " 'leader',\n",
       " 'democratic',\n",
       " 'american',\n",
       " 'amp',\n",
       " 'otto',\n",
       " 'korean',\n",
       " 'bruised',\n",
       " 'jongun',\n",
       " 'hes',\n",
       " 'dictator',\n",
       " 'going',\n",
       " 'south',\n",
       " 'nothing',\n",
       " 'stephanie',\n",
       " 'think',\n",
       " 'makes',\n",
       " 'great',\n",
       " 'grisham',\n",
       " 'know',\n",
       " 'security',\n",
       " 'enter',\n",
       " 'see',\n",
       " 'says',\n",
       " 'candidates',\n",
       " 'diplomacy',\n",
       " 'made',\n",
       " 'china',\n",
       " 'talks',\n",
       " 'warmbier',\n",
       " '1st',\n",
       " 'time',\n",
       " 'white',\n",
       " 'making',\n",
       " 'world',\n",
       " 'said',\n",
       " 'want',\n",
       " 'kamalaharris',\n",
       " 'whitehouse',\n",
       " 'im',\n",
       " 'prize',\n",
       " 'photo',\n",
       " 'iran',\n",
       " 'house',\n",
       " 'never',\n",
       " 'russia',\n",
       " 'nobel',\n",
       " 'ewarren',\n",
       " 'way',\n",
       " 'didnt',\n",
       " 'meet',\n",
       " 'new',\n",
       " 'senschumer',\n",
       " 't',\n",
       " 'say',\n",
       " 'country',\n",
       " 'got']"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#top 100 words without stop words\n",
    "tokens_2 = [w for w in tokens if not w in stop_words]\n",
    "frequency_dist = nltk.FreqDist(tokens_2)\n",
    "sorted(frequency_dist,key=frequency_dist.__getitem__, reverse=True)[0:100]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from wordcloud import WordCloud\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "wordcloud = WordCloud(background_color=\"white\").generate_from_frequencies(frequency_dist)\n",
    "\n",
    "plt.imshow(wordcloud)\n",
    "plt.axis(\"off\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Top 20 Unigrams"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "north 3693\n",
      "korea 3421\n",
      "trump 1948\n",
      "president 1048\n",
      "kim 706\n",
      "realdonaldtrump 582\n",
      "sitting 325\n",
      "jong 324\n",
      "meeting 283\n",
      "step 283\n",
      "just 238\n",
      "trumps 230\n",
      "history 223\n",
      "foot 220\n",
      "obama 214\n",
      "donald 203\n",
      "like 195\n",
      "steps 191\n",
      "nuclear 172\n",
      "press 172\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Text(0.5,0,'count')"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.feature_extraction.text import CountVectorizer\n",
    "def get_top_n_words(corpus, n=None):\n",
    "    vec = CountVectorizer(stop_words = 'english').fit(corpus)\n",
    "    bag_of_words = vec.transform(corpus)\n",
    "    sum_words = bag_of_words.sum(axis=0) \n",
    "    words_freq = [(word, sum_words[0, idx]) for word, idx in vec.vocabulary_.items()]\n",
    "    words_freq =sorted(words_freq, key = lambda x: x[1], reverse=True)\n",
    "    return words_freq[:n]\n",
    "common_words = get_top_n_words(df4['tweets_clean'], 20)\n",
    "for word, freq in common_words:\n",
    "    print(word, freq)\n",
    "    \n",
    "df7 = pd.DataFrame(common_words, columns = ['tweets_clean' , 'count'])\n",
    "df7.groupby('tweets_clean').sum()['count'].sort_values(ascending=False).plot.barh().invert_yaxis()\n",
    "plt.title('Top 20 unigrams in tweets after removing stop words')\n",
    "plt.xlabel('count')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Bigrams"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "north korea 3289\n",
      "kim jong 321\n",
      "sitting president 268\n",
      "president trump 202\n",
      "president step 198\n",
      "foot north 197\n",
      "step north 178\n",
      "donald trump 177\n",
      "trump north 169\n",
      "steps north 161\n",
      "trump sitting 157\n",
      "north koreas 156\n",
      "trump meets 145\n",
      "set foot 139\n",
      "press secretary 137\n",
      "meets kim 133\n",
      "president set 131\n",
      "trump president 116\n",
      "trump steps 110\n",
      "kim jongun 106\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Text(0.5,0,'count')"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def get_top_n_bigram(corpus, n=None):\n",
    "    vec = CountVectorizer(stop_words = 'english',ngram_range=(2, 2)).fit(corpus)\n",
    "    bag_of_words = vec.transform(corpus)\n",
    "    sum_words = bag_of_words.sum(axis=0) \n",
    "    words_freq = [(word, sum_words[0, idx]) for word, idx in vec.vocabulary_.items()]\n",
    "    words_freq =sorted(words_freq, key = lambda x: x[1], reverse=True)\n",
    "    return words_freq[:n]\n",
    "common_words = get_top_n_bigram(df4['tweets_clean'], 20)\n",
    "for word, freq in common_words:\n",
    "    print(word, freq)\n",
    "df8 = pd.DataFrame(common_words, columns = ['tweets_clean' , 'count'])\n",
    "df8.groupby('tweets_clean').sum()['count'].sort_values(ascending=False).plot.barh().invert_yaxis()\n",
    "plt.title('Top 20 bigrams in tweets')\n",
    "plt.xlabel('count')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Trigrams"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "foot north korea 186\n",
      "step north korea 168\n",
      "steps north korea 156\n",
      "trump north korea 151\n",
      "president step north 139\n",
      "trump sitting president 138\n",
      "set foot north 131\n",
      "president set foot 129\n",
      "trump meets kim 122\n",
      "sitting president step 102\n",
      "trump steps north 99\n",
      "sitting president set 95\n",
      "north korea meeting 87\n",
      "meets kim jong 83\n",
      "north korea kim 81\n",
      "north koreas kim 79\n",
      "enter north korea 69\n",
      "trump president step 66\n",
      "visit north korea 66\n",
      "north korea security 63\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Text(0.5,0,'count')"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def get_top_n_trigram(corpus, n=None):\n",
    "    vec = CountVectorizer(stop_words = 'english',ngram_range=(3, 3)).fit(corpus)\n",
    "    bag_of_words = vec.transform(corpus)\n",
    "    sum_words = bag_of_words.sum(axis=0) \n",
    "    words_freq = [(word, sum_words[0, idx]) for word, idx in vec.vocabulary_.items()]\n",
    "    words_freq =sorted(words_freq, key = lambda x: x[1], reverse=True)\n",
    "    return words_freq[:n]\n",
    "common_words = get_top_n_trigram(df4['tweets_clean'], 20)\n",
    "for word, freq in common_words:\n",
    "    print(word, freq)\n",
    "df9 = pd.DataFrame(common_words, columns = ['tweets_clean' , 'count'])\n",
    "df9.groupby('tweets_clean').sum()['count'].sort_values(ascending=False).plot.barh().invert_yaxis()\n",
    "plt.title('Top 20 bigrams in tweets')\n",
    "plt.xlabel('count')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Timeline of Tweets "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "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>Created At</th>\n",
       "      <th>Followers</th>\n",
       "      <th>Following</th>\n",
       "      <th>Handle</th>\n",
       "      <th>Likes</th>\n",
       "      <th>Location</th>\n",
       "      <th>Message</th>\n",
       "      <th>Retweet Count</th>\n",
       "      <th>Tweet Favorite Count</th>\n",
       "      <th>User Description</th>\n",
       "      <th>...</th>\n",
       "      <th>word_count</th>\n",
       "      <th>unique word_count</th>\n",
       "      <th>char_count</th>\n",
       "      <th>subjectivity</th>\n",
       "      <th>polarity</th>\n",
       "      <th>subjectivity_range</th>\n",
       "      <th>polarity_range</th>\n",
       "      <th>hashtags</th>\n",
       "      <th>handles</th>\n",
       "      <th>User</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2595</th>\n",
       "      <td>2019-06-30 17:40:24</td>\n",
       "      <td>1142482</td>\n",
       "      <td>248834</td>\n",
       "      <td>charliekirk11</td>\n",
       "      <td>26563</td>\n",
       "      <td>Chicago, Illinois</td>\n",
       "      <td>Barack Obama was given the Nobel Peace Prize i...</td>\n",
       "      <td>2835</td>\n",
       "      <td>7397</td>\n",
       "      <td>Founder &amp; President of @TPUSA Proud capitalist...</td>\n",
       "      <td>...</td>\n",
       "      <td>23</td>\n",
       "      <td>20</td>\n",
       "      <td>130</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Neutral</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>charliekirk11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2914</th>\n",
       "      <td>2019-06-30 17:33:02</td>\n",
       "      <td>1047950</td>\n",
       "      <td>9363</td>\n",
       "      <td>tedlieu</td>\n",
       "      <td>40845</td>\n",
       "      <td>California</td>\n",
       "      <td>We should support diplomacy. I think it's fine...</td>\n",
       "      <td>997</td>\n",
       "      <td>3365</td>\n",
       "      <td>Husband of Betty, the love of my life. Father ...</td>\n",
       "      <td>...</td>\n",
       "      <td>24</td>\n",
       "      <td>22</td>\n",
       "      <td>130</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.416667</td>\n",
       "      <td>Objective</td>\n",
       "      <td>Positive</td>\n",
       "      <td></td>\n",
       "      <td>potus</td>\n",
       "      <td>tedlieu</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1544</th>\n",
       "      <td>2019-06-30 18:05:26</td>\n",
       "      <td>1142457</td>\n",
       "      <td>248834</td>\n",
       "      <td>charliekirk11</td>\n",
       "      <td>26563</td>\n",
       "      <td>Chicago, Illinois</td>\n",
       "      <td>If Hillary Clinton was President we would have...</td>\n",
       "      <td>991</td>\n",
       "      <td>2946</td>\n",
       "      <td>Founder &amp; President of @TPUSA Proud capitalist...</td>\n",
       "      <td>...</td>\n",
       "      <td>22</td>\n",
       "      <td>21</td>\n",
       "      <td>128</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Neutral</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>charliekirk11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2348</th>\n",
       "      <td>2019-06-30 17:46:04</td>\n",
       "      <td>260567</td>\n",
       "      <td>35763</td>\n",
       "      <td>mmpadellan</td>\n",
       "      <td>145421</td>\n",
       "      <td>Brooklyn, NY</td>\n",
       "      <td>There's a reason no other American President h...</td>\n",
       "      <td>322</td>\n",
       "      <td>898</td>\n",
       "      <td>Proud papa. Perpetually pissed. #BlueWave2020,...</td>\n",
       "      <td>...</td>\n",
       "      <td>21</td>\n",
       "      <td>20</td>\n",
       "      <td>130</td>\n",
       "      <td>0.187500</td>\n",
       "      <td>0.031250</td>\n",
       "      <td>Objective</td>\n",
       "      <td>Positive</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>mmpadellan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1119</th>\n",
       "      <td>2019-06-30 18:16:07</td>\n",
       "      <td>164550</td>\n",
       "      <td>285</td>\n",
       "      <td>marklutchman</td>\n",
       "      <td>7693</td>\n",
       "      <td>Philadelphia, PA</td>\n",
       "      <td>President Trump is the first sitting president...</td>\n",
       "      <td>314</td>\n",
       "      <td>1062</td>\n",
       "      <td>Writer - Former Army National Guardsman - 25 y...</td>\n",
       "      <td>...</td>\n",
       "      <td>22</td>\n",
       "      <td>19</td>\n",
       "      <td>131</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>0.250000</td>\n",
       "      <td>Objective</td>\n",
       "      <td>Positive</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>marklutchman</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3186</th>\n",
       "      <td>2019-06-30 17:27:24</td>\n",
       "      <td>75002</td>\n",
       "      <td>2722</td>\n",
       "      <td>KlasfeldReports</td>\n",
       "      <td>16894</td>\n",
       "      <td>New York, NY</td>\n",
       "      <td>This is a passage from a United Nations human ...</td>\n",
       "      <td>305</td>\n",
       "      <td>424</td>\n",
       "      <td>Reporter, @CourthouseNews: NYC+Int’l. RTs=What...</td>\n",
       "      <td>...</td>\n",
       "      <td>19</td>\n",
       "      <td>18</td>\n",
       "      <td>130</td>\n",
       "      <td>0.150000</td>\n",
       "      <td>-0.150000</td>\n",
       "      <td>Objective</td>\n",
       "      <td>Negative</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>klasfeldreports</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2762</th>\n",
       "      <td>2019-06-30 17:36:28</td>\n",
       "      <td>85071</td>\n",
       "      <td>422</td>\n",
       "      <td>hale_razor</td>\n",
       "      <td>36214</td>\n",
       "      <td>Wherever Liberty is Threatened</td>\n",
       "      <td>44 lifts Cuba embargo and watches baseball gam...</td>\n",
       "      <td>285</td>\n",
       "      <td>566</td>\n",
       "      <td>Conservative politics humor. Satire. Snark. Sa...</td>\n",
       "      <td>...</td>\n",
       "      <td>20</td>\n",
       "      <td>18</td>\n",
       "      <td>130</td>\n",
       "      <td>0.200000</td>\n",
       "      <td>-0.200000</td>\n",
       "      <td>Objective</td>\n",
       "      <td>Negative</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>hale_razor</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3090</th>\n",
       "      <td>2019-06-30 17:29:41</td>\n",
       "      <td>234743</td>\n",
       "      <td>1445</td>\n",
       "      <td>RadioFreeTom</td>\n",
       "      <td>54069</td>\n",
       "      <td>Newport, RI</td>\n",
       "      <td>Today's humiliation in North Korea is yet anot...</td>\n",
       "      <td>283</td>\n",
       "      <td>900</td>\n",
       "      <td>Professor, author on Russia, war, nukes, and \"...</td>\n",
       "      <td>...</td>\n",
       "      <td>19</td>\n",
       "      <td>19</td>\n",
       "      <td>132</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>Objective</td>\n",
       "      <td>Positive</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>radiofreetom</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4317</th>\n",
       "      <td>2019-06-30 17:03:10</td>\n",
       "      <td>127089</td>\n",
       "      <td>1479</td>\n",
       "      <td>FrankFigliuzzi1</td>\n",
       "      <td>8849</td>\n",
       "      <td>Tucson, AZ</td>\n",
       "      <td>POTUS makes history as first to say visiting l...</td>\n",
       "      <td>282</td>\n",
       "      <td>742</td>\n",
       "      <td>Former FBI Assistant Director; NBC News Nation...</td>\n",
       "      <td>...</td>\n",
       "      <td>21</td>\n",
       "      <td>21</td>\n",
       "      <td>129</td>\n",
       "      <td>0.541667</td>\n",
       "      <td>0.525000</td>\n",
       "      <td>Objective</td>\n",
       "      <td>Positive</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>frankfigliuzzi1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>841</th>\n",
       "      <td>2019-06-30 18:22:12</td>\n",
       "      <td>297054</td>\n",
       "      <td>2614</td>\n",
       "      <td>GOPChairwoman</td>\n",
       "      <td>5737</td>\n",
       "      <td>NaN</td>\n",
       "      <td>In 2017, Kamala Harris said: \"We must work to ...</td>\n",
       "      <td>246</td>\n",
       "      <td>618</td>\n",
       "      <td>@GOP Chairwoman | Wife, mother of two</td>\n",
       "      <td>...</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>117</td>\n",
       "      <td>0.250000</td>\n",
       "      <td>0.250000</td>\n",
       "      <td>Objective</td>\n",
       "      <td>Positive</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>gopchairwoman</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4278</th>\n",
       "      <td>2019-06-30 17:04:02</td>\n",
       "      <td>14374707</td>\n",
       "      <td>537</td>\n",
       "      <td>ABC</td>\n",
       "      <td>39</td>\n",
       "      <td>New York City / Worldwide</td>\n",
       "      <td>Pres. Trump became the first U.S. president to...</td>\n",
       "      <td>242</td>\n",
       "      <td>662</td>\n",
       "      <td>All the news and information you need to see, ...</td>\n",
       "      <td>...</td>\n",
       "      <td>20</td>\n",
       "      <td>19</td>\n",
       "      <td>130</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>0.250000</td>\n",
       "      <td>Objective</td>\n",
       "      <td>Positive</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>abc</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3379</th>\n",
       "      <td>2019-06-30 17:23:10</td>\n",
       "      <td>54439</td>\n",
       "      <td>16984</td>\n",
       "      <td>C_3C_3</td>\n",
       "      <td>104758</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Trump “appeased” North Korea by shaking Kim’s ...</td>\n",
       "      <td>221</td>\n",
       "      <td>466</td>\n",
       "      <td>Parler: @ C3C3 / Turds will get instablocked</td>\n",
       "      <td>...</td>\n",
       "      <td>18</td>\n",
       "      <td>13</td>\n",
       "      <td>125</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Neutral</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>c_3c_3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4288</th>\n",
       "      <td>2019-06-30 17:03:40</td>\n",
       "      <td>317916</td>\n",
       "      <td>17012</td>\n",
       "      <td>KayaJones</td>\n",
       "      <td>110612</td>\n",
       "      <td>America</td>\n",
       "      <td>Trump isn’t using China🇨🇳 to make peace with N...</td>\n",
       "      <td>169</td>\n",
       "      <td>760</td>\n",
       "      <td>Christian✞ | Grammy Winning Vocalist |Platinum...</td>\n",
       "      <td>...</td>\n",
       "      <td>23</td>\n",
       "      <td>21</td>\n",
       "      <td>127</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Neutral</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>kayajones</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4508</th>\n",
       "      <td>2019-06-30 16:59:28</td>\n",
       "      <td>280076</td>\n",
       "      <td>1577</td>\n",
       "      <td>JohnJHarwood</td>\n",
       "      <td>3149</td>\n",
       "      <td>Washington, DC</td>\n",
       "      <td>there’s no evidence that this “performance” or...</td>\n",
       "      <td>152</td>\n",
       "      <td>433</td>\n",
       "      <td>a Dad who covers Washington, the economy and n...</td>\n",
       "      <td>...</td>\n",
       "      <td>16</td>\n",
       "      <td>16</td>\n",
       "      <td>129</td>\n",
       "      <td>0.383333</td>\n",
       "      <td>0.116667</td>\n",
       "      <td>Objective</td>\n",
       "      <td>Positive</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>johnjharwood</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1295</th>\n",
       "      <td>2019-06-30 18:11:56</td>\n",
       "      <td>235966</td>\n",
       "      <td>1413</td>\n",
       "      <td>MaxBoot</td>\n",
       "      <td>10750</td>\n",
       "      <td>New York</td>\n",
       "      <td>“Complete, verifiable, and irreversible denucl...</td>\n",
       "      <td>123</td>\n",
       "      <td>241</td>\n",
       "      <td>CFR fellow, WaPo columnist, CNN analyst. Autho...</td>\n",
       "      <td>...</td>\n",
       "      <td>18</td>\n",
       "      <td>15</td>\n",
       "      <td>129</td>\n",
       "      <td>0.400000</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>Objective</td>\n",
       "      <td>Positive</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>maxboot</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4488</th>\n",
       "      <td>2019-06-30 16:59:48</td>\n",
       "      <td>140336</td>\n",
       "      <td>355</td>\n",
       "      <td>AngrierWHStaff</td>\n",
       "      <td>5142</td>\n",
       "      <td>NaN</td>\n",
       "      <td>- Gives North Korea another propaganda win\\n\\n...</td>\n",
       "      <td>120</td>\n",
       "      <td>663</td>\n",
       "      <td>Not a current WH Staffer | Politics, NatSec, a...</td>\n",
       "      <td>...</td>\n",
       "      <td>15</td>\n",
       "      <td>14</td>\n",
       "      <td>98</td>\n",
       "      <td>0.366667</td>\n",
       "      <td>0.466667</td>\n",
       "      <td>Objective</td>\n",
       "      <td>Positive</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>angrierwhstaff</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1655</th>\n",
       "      <td>2019-06-30 18:02:59</td>\n",
       "      <td>78162</td>\n",
       "      <td>70266</td>\n",
       "      <td>CHIZMAGA</td>\n",
       "      <td>150681</td>\n",
       "      <td>San Diego, CA</td>\n",
       "      <td>Obama never even tried to meet with Kim Jong U...</td>\n",
       "      <td>110</td>\n",
       "      <td>247</td>\n",
       "      <td>🇺🇸 Proud Supporter of President 🅣🅡🅤🅜🅟</td>\n",
       "      <td>...</td>\n",
       "      <td>25</td>\n",
       "      <td>22</td>\n",
       "      <td>129</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Neutral</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>chizmaga</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>722</th>\n",
       "      <td>2019-06-30 18:24:35</td>\n",
       "      <td>141285</td>\n",
       "      <td>3915</td>\n",
       "      <td>williamlegate</td>\n",
       "      <td>420670</td>\n",
       "      <td>Instagram</td>\n",
       "      <td>When Trump crossed the border into North Korea...</td>\n",
       "      <td>98</td>\n",
       "      <td>590</td>\n",
       "      <td>Self-made American entrepreneur • hacker/tinke...</td>\n",
       "      <td>...</td>\n",
       "      <td>25</td>\n",
       "      <td>23</td>\n",
       "      <td>134</td>\n",
       "      <td>0.900000</td>\n",
       "      <td>0.200000</td>\n",
       "      <td>Somewhat subjective</td>\n",
       "      <td>Positive</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>williamlegate</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3895</th>\n",
       "      <td>2019-06-30 17:11:54</td>\n",
       "      <td>40763</td>\n",
       "      <td>4573</td>\n",
       "      <td>OfficialJoelF</td>\n",
       "      <td>15396</td>\n",
       "      <td>Miami, FL</td>\n",
       "      <td>ICYMI: Trump became the first sitting presiden...</td>\n",
       "      <td>86</td>\n",
       "      <td>255</td>\n",
       "      <td>Breaking news, local news, events, traffic ale...</td>\n",
       "      <td>...</td>\n",
       "      <td>13</td>\n",
       "      <td>13</td>\n",
       "      <td>90</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>0.250000</td>\n",
       "      <td>Objective</td>\n",
       "      <td>Positive</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>officialjoelf</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3519</th>\n",
       "      <td>2019-06-30 17:20:00</td>\n",
       "      <td>3300295</td>\n",
       "      <td>256</td>\n",
       "      <td>thehill</td>\n",
       "      <td>25</td>\n",
       "      <td>Washington, DC</td>\n",
       "      <td>James Clapper: \"In all the deliberations that ...</td>\n",
       "      <td>76</td>\n",
       "      <td>174</td>\n",
       "      <td>The Hill is the premier source for policy and ...</td>\n",
       "      <td>...</td>\n",
       "      <td>20</td>\n",
       "      <td>17</td>\n",
       "      <td>131</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Neutral</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>thehill</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3468</th>\n",
       "      <td>2019-06-30 17:20:56</td>\n",
       "      <td>68571</td>\n",
       "      <td>58280</td>\n",
       "      <td>GrassrootsSpeak</td>\n",
       "      <td>46922</td>\n",
       "      <td>NYC</td>\n",
       "      <td>History was made...\\nWhen Trump visited his 'f...</td>\n",
       "      <td>74</td>\n",
       "      <td>239</td>\n",
       "      <td>I see it. I say it. Won't rest till we've take...</td>\n",
       "      <td>...</td>\n",
       "      <td>19</td>\n",
       "      <td>18</td>\n",
       "      <td>124</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Neutral</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>grassrootsspeak</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2497</th>\n",
       "      <td>2019-06-30 17:42:28</td>\n",
       "      <td>191688</td>\n",
       "      <td>91693</td>\n",
       "      <td>RealMattCouch</td>\n",
       "      <td>208132</td>\n",
       "      <td>Arkansas, USA</td>\n",
       "      <td>Does anyone honestly think any of the Democrat...</td>\n",
       "      <td>72</td>\n",
       "      <td>258</td>\n",
       "      <td>Christian, Father of 2, Investigator, Founder ...</td>\n",
       "      <td>...</td>\n",
       "      <td>16</td>\n",
       "      <td>16</td>\n",
       "      <td>103</td>\n",
       "      <td>0.900000</td>\n",
       "      <td>0.600000</td>\n",
       "      <td>Somewhat subjective</td>\n",
       "      <td>Positive</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>realmattcouch</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3144</th>\n",
       "      <td>2019-06-30 17:28:29</td>\n",
       "      <td>151252</td>\n",
       "      <td>32228</td>\n",
       "      <td>JenniferJJacobs</td>\n",
       "      <td>1454</td>\n",
       "      <td>Washington, DC</td>\n",
       "      <td>Trump’s national security adviser stated just ...</td>\n",
       "      <td>68</td>\n",
       "      <td>130</td>\n",
       "      <td>Sr. White House reporter for Bloomberg. Report...</td>\n",
       "      <td>...</td>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "      <td>129</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Neutral</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>jenniferjjacobs</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2164</th>\n",
       "      <td>2019-06-30 17:50:31</td>\n",
       "      <td>49888</td>\n",
       "      <td>3687</td>\n",
       "      <td>VoteOjeda2020</td>\n",
       "      <td>2901</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Nothing like hearing folks say “It’s time” for...</td>\n",
       "      <td>68</td>\n",
       "      <td>265</td>\n",
       "      <td>I spent 24 years fighting for my country only ...</td>\n",
       "      <td>...</td>\n",
       "      <td>21</td>\n",
       "      <td>19</td>\n",
       "      <td>127</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.250000</td>\n",
       "      <td>Objective</td>\n",
       "      <td>Positive</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>voteojeda2020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2779</th>\n",
       "      <td>2019-06-30 17:35:57</td>\n",
       "      <td>60522</td>\n",
       "      <td>39097</td>\n",
       "      <td>amvetsupport</td>\n",
       "      <td>163130</td>\n",
       "      <td>Palm Desert, CA</td>\n",
       "      <td>After this idiotic North Korea photo op we sho...</td>\n",
       "      <td>66</td>\n",
       "      <td>169</td>\n",
       "      <td>1 of 1,000s of vets who despise trump - Volunt...</td>\n",
       "      <td>...</td>\n",
       "      <td>24</td>\n",
       "      <td>23</td>\n",
       "      <td>134</td>\n",
       "      <td>0.833333</td>\n",
       "      <td>-0.666667</td>\n",
       "      <td>Somewhat subjective</td>\n",
       "      <td>Negative</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>amvetsupport</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3095</th>\n",
       "      <td>2019-06-30 17:29:34</td>\n",
       "      <td>125831</td>\n",
       "      <td>76755</td>\n",
       "      <td>activist360</td>\n",
       "      <td>4245</td>\n",
       "      <td>Lower East Side, New York City</td>\n",
       "      <td>Everything Trump does is motivated by money fo...</td>\n",
       "      <td>65</td>\n",
       "      <td>145</td>\n",
       "      <td>Singer-songwriter, musician, activist, poet, y...</td>\n",
       "      <td>...</td>\n",
       "      <td>20</td>\n",
       "      <td>18</td>\n",
       "      <td>132</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>Very Subjective</td>\n",
       "      <td>Neutral</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>activist360</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4677</th>\n",
       "      <td>2019-06-30 16:55:11</td>\n",
       "      <td>69350</td>\n",
       "      <td>3992</td>\n",
       "      <td>politicususa</td>\n",
       "      <td>561</td>\n",
       "      <td>USA</td>\n",
       "      <td>Trump disgraces America by proclaiming his fri...</td>\n",
       "      <td>62</td>\n",
       "      <td>89</td>\n",
       "      <td>Official Twitter Account for PoliticusUSA 💯Ind...</td>\n",
       "      <td>...</td>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "      <td>133</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Neutral</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>politicususa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1138</th>\n",
       "      <td>2019-06-30 18:15:45</td>\n",
       "      <td>60519</td>\n",
       "      <td>39094</td>\n",
       "      <td>amvetsupport</td>\n",
       "      <td>163101</td>\n",
       "      <td>Palm Desert, CA</td>\n",
       "      <td>I cannot tell you how mad it makes me that thi...</td>\n",
       "      <td>62</td>\n",
       "      <td>166</td>\n",
       "      <td>1 of 1,000s of vets who despise trump - Volunt...</td>\n",
       "      <td>...</td>\n",
       "      <td>26</td>\n",
       "      <td>26</td>\n",
       "      <td>133</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.625000</td>\n",
       "      <td>Very Subjective</td>\n",
       "      <td>Negative</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>amvetsupport</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4770</th>\n",
       "      <td>2019-06-30 16:53:21</td>\n",
       "      <td>157211</td>\n",
       "      <td>68783</td>\n",
       "      <td>RedNationRising</td>\n",
       "      <td>74820</td>\n",
       "      <td>Everywhere, USA</td>\n",
       "      <td>The sad truth:\\n\\nNorth Korea has a better rec...</td>\n",
       "      <td>59</td>\n",
       "      <td>131</td>\n",
       "      <td>Welcome to the Official Red Nation Rising Twit...</td>\n",
       "      <td>...</td>\n",
       "      <td>17</td>\n",
       "      <td>16</td>\n",
       "      <td>96</td>\n",
       "      <td>0.750000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>Somewhat subjective</td>\n",
       "      <td>Neutral</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>rednationrising</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3746</th>\n",
       "      <td>2019-06-30 17:15:00</td>\n",
       "      <td>3300295</td>\n",
       "      <td>256</td>\n",
       "      <td>thehill</td>\n",
       "      <td>25</td>\n",
       "      <td>Washington, DC</td>\n",
       "      <td>President Trump makes history by becoming the ...</td>\n",
       "      <td>58</td>\n",
       "      <td>120</td>\n",
       "      <td>The Hill is the premier source for policy and ...</td>\n",
       "      <td>...</td>\n",
       "      <td>18</td>\n",
       "      <td>17</td>\n",
       "      <td>118</td>\n",
       "      <td>0.591667</td>\n",
       "      <td>0.350000</td>\n",
       "      <td>Objective</td>\n",
       "      <td>Positive</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>thehill</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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3112</th>\n",
       "      <td>2019-06-30 17:29:09</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Scifigirl2020</td>\n",
       "      <td>2006</td>\n",
       "      <td>Arizona, USA</td>\n",
       "      <td>Remember when disgusting Pres Jimmy Carter con...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Hometown: Lorain, OH</td>\n",
       "      <td>...</td>\n",
       "      <td>19</td>\n",
       "      <td>19</td>\n",
       "      <td>131</td>\n",
       "      <td>0.833333</td>\n",
       "      <td>-0.850000</td>\n",
       "      <td>Somewhat subjective</td>\n",
       "      <td>Negative</td>\n",
       "      <td></td>\n",
       "      <td>realdonaldtrump</td>\n",
       "      <td>scifigirl2020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3210</th>\n",
       "      <td>2019-06-30 17:26:49</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>sta_united</td>\n",
       "      <td>18332</td>\n",
       "      <td>USA</td>\n",
       "      <td>North Korea\\nTrump steps into North Korea with...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>'FOLLOWERS &amp; LIST MAKERS WILL BE BLOCKED'</td>\n",
       "      <td>...</td>\n",
       "      <td>11</td>\n",
       "      <td>9</td>\n",
       "      <td>75</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Neutral</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>sta_united</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3296</th>\n",
       "      <td>2019-06-30 17:24:49</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>VdaChristina</td>\n",
       "      <td>32</td>\n",
       "      <td>NaN</td>\n",
       "      <td>An amazing day for our President &amp;amp; our cou...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>22</td>\n",
       "      <td>20</td>\n",
       "      <td>133</td>\n",
       "      <td>0.616667</td>\n",
       "      <td>0.425000</td>\n",
       "      <td>Objective</td>\n",
       "      <td>Positive</td>\n",
       "      <td>kag</td>\n",
       "      <td></td>\n",
       "      <td>vdachristina</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3532</th>\n",
       "      <td>2019-06-30 17:19:38</td>\n",
       "      <td>0</td>\n",
       "      <td>29</td>\n",
       "      <td>Philly_Willie</td>\n",
       "      <td>9</td>\n",
       "      <td>Virginia, USA</td>\n",
       "      <td>@ANTIGOPMVMT Sanders wants to be North Korea.</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Just a family man trying to do his best</td>\n",
       "      <td>...</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>43</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>0.200000</td>\n",
       "      <td>Objective</td>\n",
       "      <td>Positive</td>\n",
       "      <td></td>\n",
       "      <td>antigopmvmt</td>\n",
       "      <td>philly_willie</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3688</th>\n",
       "      <td>2019-06-30 17:16:13</td>\n",
       "      <td>0</td>\n",
       "      <td>16</td>\n",
       "      <td>William23313523</td>\n",
       "      <td>33</td>\n",
       "      <td>NaN</td>\n",
       "      <td>@thehill In other news President Donald Trump ...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>21</td>\n",
       "      <td>18</td>\n",
       "      <td>132</td>\n",
       "      <td>0.177083</td>\n",
       "      <td>0.031250</td>\n",
       "      <td>Objective</td>\n",
       "      <td>Positive</td>\n",
       "      <td></td>\n",
       "      <td>thehill</td>\n",
       "      <td>william23313523</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3768</th>\n",
       "      <td>2019-06-30 17:14:30</td>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
       "      <td>WierKerry</td>\n",
       "      <td>31</td>\n",
       "      <td>NaN</td>\n",
       "      <td>@MSNBC You know if he likes Russia and North K...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>19</td>\n",
       "      <td>19</td>\n",
       "      <td>93</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Neutral</td>\n",
       "      <td></td>\n",
       "      <td>msnbc</td>\n",
       "      <td>wierkerry</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3780</th>\n",
       "      <td>2019-06-30 17:14:09</td>\n",
       "      <td>0</td>\n",
       "      <td>68</td>\n",
       "      <td>Grandpa64</td>\n",
       "      <td>61</td>\n",
       "      <td>NaN</td>\n",
       "      <td>What is the news cycle like in North Korea tod...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>25</td>\n",
       "      <td>20</td>\n",
       "      <td>132</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Neutral</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>grandpa64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3816</th>\n",
       "      <td>2019-06-30 17:13:27</td>\n",
       "      <td>0</td>\n",
       "      <td>21</td>\n",
       "      <td>Brenda46549508</td>\n",
       "      <td>63</td>\n",
       "      <td>United States</td>\n",
       "      <td>@AP I think of Otto and his family. I can’t se...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Christian wife, mother, grandmother. I am an i...</td>\n",
       "      <td>...</td>\n",
       "      <td>25</td>\n",
       "      <td>21</td>\n",
       "      <td>129</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Neutral</td>\n",
       "      <td></td>\n",
       "      <td>ap</td>\n",
       "      <td>brenda46549508</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3889</th>\n",
       "      <td>2019-06-30 17:12:02</td>\n",
       "      <td>0</td>\n",
       "      <td>41</td>\n",
       "      <td>mgan411</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Trump Makes History, Becomes First Sitting U.S...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>16</td>\n",
       "      <td>15</td>\n",
       "      <td>125</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>0.250000</td>\n",
       "      <td>Objective</td>\n",
       "      <td>Positive</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>mgan411</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3890</th>\n",
       "      <td>2019-06-30 17:11:56</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>AbigailFriedri1</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>@realDonaldTrump doesn't that mean you committ...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>life is an adventure</td>\n",
       "      <td>...</td>\n",
       "      <td>11</td>\n",
       "      <td>11</td>\n",
       "      <td>78</td>\n",
       "      <td>0.687500</td>\n",
       "      <td>-0.312500</td>\n",
       "      <td>Somewhat subjective</td>\n",
       "      <td>Negative</td>\n",
       "      <td></td>\n",
       "      <td>realdonaldtrump</td>\n",
       "      <td>abigailfriedri1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3950</th>\n",
       "      <td>2019-06-30 17:10:57</td>\n",
       "      <td>0</td>\n",
       "      <td>103</td>\n",
       "      <td>NNetvision</td>\n",
       "      <td>0</td>\n",
       "      <td>Kampala, Uganda</td>\n",
       "      <td>Trump steps into North Korea during meeting wi...</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>Broadcasting &amp; Media Production</td>\n",
       "      <td>...</td>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>91</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Neutral</td>\n",
       "      <td></td>\n",
       "      <td>youtube</td>\n",
       "      <td>nnetvision</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3952</th>\n",
       "      <td>2019-06-30 17:10:54</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>isIbJVOEBhe608p</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Iherb discount code \\n\\nAHB6653\\n\\nUse the cod...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>انتقي أجود المنتجات الطبيعية من بين أكثر من 30...</td>\n",
       "      <td>...</td>\n",
       "      <td>25</td>\n",
       "      <td>20</td>\n",
       "      <td>129</td>\n",
       "      <td>0.375000</td>\n",
       "      <td>-0.125000</td>\n",
       "      <td>Objective</td>\n",
       "      <td>Negative</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>isibjvoebhe608p</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3953</th>\n",
       "      <td>2019-06-30 17:10:54</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Jiggy_Gigolo</td>\n",
       "      <td>3</td>\n",
       "      <td>Dallas, TX</td>\n",
       "      <td>@funder You and the other Democrats don't care...</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>\"Think for yourselves. Don’t be sheep.\"\\n— Ric...</td>\n",
       "      <td>...</td>\n",
       "      <td>21</td>\n",
       "      <td>20</td>\n",
       "      <td>131</td>\n",
       "      <td>0.375000</td>\n",
       "      <td>-0.125000</td>\n",
       "      <td>Objective</td>\n",
       "      <td>Negative</td>\n",
       "      <td></td>\n",
       "      <td>funder</td>\n",
       "      <td>jiggy_gigolo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3961</th>\n",
       "      <td>2019-06-30 17:10:48</td>\n",
       "      <td>0</td>\n",
       "      <td>19</td>\n",
       "      <td>SHigher00</td>\n",
       "      <td>35</td>\n",
       "      <td>United States</td>\n",
       "      <td>@realDonaldTrump Correction, don’t you mean Di...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Ghost Adventure, Dead Files and 90 Day Fiancé,...</td>\n",
       "      <td>...</td>\n",
       "      <td>21</td>\n",
       "      <td>20</td>\n",
       "      <td>129</td>\n",
       "      <td>0.687500</td>\n",
       "      <td>-0.312500</td>\n",
       "      <td>Somewhat subjective</td>\n",
       "      <td>Negative</td>\n",
       "      <td></td>\n",
       "      <td>realdonaldtrump</td>\n",
       "      <td>shigher00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4029</th>\n",
       "      <td>2019-06-30 17:09:12</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>Cruzgar28746344</td>\n",
       "      <td>17</td>\n",
       "      <td>NaN</td>\n",
       "      <td>@SkyNews Dont bring a wkmen to  north korea 🤦🏽‍♂️</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>9</td>\n",
       "      <td>9</td>\n",
       "      <td>42</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Neutral</td>\n",
       "      <td></td>\n",
       "      <td>skynews</td>\n",
       "      <td>cruzgar28746344</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4032</th>\n",
       "      <td>2019-06-30 17:09:08</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>trump_antonym</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Leaving South Korea after a wonderful meeting ...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Engineering experiment. Not a real user.</td>\n",
       "      <td>...</td>\n",
       "      <td>22</td>\n",
       "      <td>21</td>\n",
       "      <td>132</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>Very Subjective</td>\n",
       "      <td>Positive</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>trump_antonym</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4052</th>\n",
       "      <td>2019-06-30 17:08:29</td>\n",
       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "      <td>thoughtsbydaryl</td>\n",
       "      <td>1</td>\n",
       "      <td>Georgia, USA</td>\n",
       "      <td>So our president just made history by actually...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>I’m a fun American man who loves the world!!</td>\n",
       "      <td>...</td>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "      <td>132</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>Objective</td>\n",
       "      <td>Neutral</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>thoughtsbydaryl</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4142</th>\n",
       "      <td>2019-06-30 17:06:46</td>\n",
       "      <td>0</td>\n",
       "      <td>58</td>\n",
       "      <td>Mitch_W99</td>\n",
       "      <td>23</td>\n",
       "      <td>NaN</td>\n",
       "      <td>@TheRealMrZilla1 @docsdaughter78 @jonkarl @Ste...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>16</td>\n",
       "      <td>16</td>\n",
       "      <td>129</td>\n",
       "      <td>0.650000</td>\n",
       "      <td>0.550000</td>\n",
       "      <td>Objective</td>\n",
       "      <td>Positive</td>\n",
       "      <td></td>\n",
       "      <td>therealmrzilla1 docsdaughter78 jonkarl stephgr...</td>\n",
       "      <td>mitch_w99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4173</th>\n",
       "      <td>2019-06-30 17:05:54</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>bette_sayer</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Iherb discount code \\n\\nAHB6653\\n\\nUse the cod...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>25</td>\n",
       "      <td>20</td>\n",
       "      <td>129</td>\n",
       "      <td>0.375000</td>\n",
       "      <td>-0.125000</td>\n",
       "      <td>Objective</td>\n",
       "      <td>Negative</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>bette_sayer</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4175</th>\n",
       "      <td>2019-06-30 17:05:52</td>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "      <td>pradelpiere</td>\n",
       "      <td>0</td>\n",
       "      <td>New Jersey, USA</td>\n",
       "      <td>Trump becomes 1st U.S. leader to step into Nor...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>male</td>\n",
       "      <td>...</td>\n",
       "      <td>13</td>\n",
       "      <td>13</td>\n",
       "      <td>81</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Neutral</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>pradelpiere</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4275</th>\n",
       "      <td>2019-06-30 17:04:04</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>HEADLINES_Etc</td>\n",
       "      <td>1</td>\n",
       "      <td>SOMEWHERE IN AMERICA</td>\n",
       "      <td>FOX:   Should President Trump be awarded the N...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>THE TRUTH IS OUT THERE</td>\n",
       "      <td>...</td>\n",
       "      <td>20</td>\n",
       "      <td>19</td>\n",
       "      <td>124</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Neutral</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>headlines_etc</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4417</th>\n",
       "      <td>2019-06-30 17:01:13</td>\n",
       "      <td>0</td>\n",
       "      <td>17</td>\n",
       "      <td>Ynot34403716</td>\n",
       "      <td>8</td>\n",
       "      <td>Henderson, NV</td>\n",
       "      <td>@townhallcom How can it be treason,all the san...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "      <td>132</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Neutral</td>\n",
       "      <td></td>\n",
       "      <td>townhallcom</td>\n",
       "      <td>ynot34403716</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4425</th>\n",
       "      <td>2019-06-30 17:01:06</td>\n",
       "      <td>0</td>\n",
       "      <td>14</td>\n",
       "      <td>lawton_ron</td>\n",
       "      <td>52</td>\n",
       "      <td>NaN</td>\n",
       "      <td>@eikrahss @Brasilmagic @realDonaldTrump What h...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>130</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.200000</td>\n",
       "      <td>Objective</td>\n",
       "      <td>Positive</td>\n",
       "      <td></td>\n",
       "      <td>eikrahss brasilmagic realdonaldtrump</td>\n",
       "      <td>lawton_ron</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4434</th>\n",
       "      <td>2019-06-30 17:00:54</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>G6o2fAzdsFtheQI</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Iherb discount code \\n\\nAHB6653\\n\\nUse the cod...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>25</td>\n",
       "      <td>20</td>\n",
       "      <td>129</td>\n",
       "      <td>0.375000</td>\n",
       "      <td>-0.125000</td>\n",
       "      <td>Objective</td>\n",
       "      <td>Negative</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>g6o2fazdsftheqi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4617</th>\n",
       "      <td>2019-06-30 16:56:53</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>Retired420</td>\n",
       "      <td>28</td>\n",
       "      <td>Queens NY/Florida</td>\n",
       "      <td>@tommychong Our President is fucking awesome. ...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Don’t Follow me.</td>\n",
       "      <td>...</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>62</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>Very Subjective</td>\n",
       "      <td>Positive</td>\n",
       "      <td></td>\n",
       "      <td>tommychong</td>\n",
       "      <td>retired420</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4651</th>\n",
       "      <td>2019-06-30 16:55:54</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>PhebeTedford</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Iherb discount code \\n\\nAHB6653\\n\\nUse the cod...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>25</td>\n",
       "      <td>20</td>\n",
       "      <td>129</td>\n",
       "      <td>0.375000</td>\n",
       "      <td>-0.125000</td>\n",
       "      <td>Objective</td>\n",
       "      <td>Negative</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>phebetedford</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4661</th>\n",
       "      <td>2019-06-30 16:55:42</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>tt3091</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Trump becomes first president to step into Nor...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>One Of these people testing things</td>\n",
       "      <td>...</td>\n",
       "      <td>9</td>\n",
       "      <td>9</td>\n",
       "      <td>63</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>0.250000</td>\n",
       "      <td>Objective</td>\n",
       "      <td>Positive</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>tt3091</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4664</th>\n",
       "      <td>2019-06-30 16:55:37</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>TKalamaros</td>\n",
       "      <td>2</td>\n",
       "      <td>South Bend, IN</td>\n",
       "      <td>Trump meets Kim, becomes first U.S. president ...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "      <td>100</td>\n",
       "      <td>0.521212</td>\n",
       "      <td>0.272727</td>\n",
       "      <td>Objective</td>\n",
       "      <td>Positive</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>tkalamaros</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4884</th>\n",
       "      <td>2019-06-30 16:50:54</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>KatlynNewarch</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Iherb discount code \\n\\nAHB6653\\n\\nUse the cod...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>25</td>\n",
       "      <td>20</td>\n",
       "      <td>129</td>\n",
       "      <td>0.375000</td>\n",
       "      <td>-0.125000</td>\n",
       "      <td>Objective</td>\n",
       "      <td>Negative</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>katlynnewarch</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4967</th>\n",
       "      <td>2019-06-30 16:49:05</td>\n",
       "      <td>0</td>\n",
       "      <td>38</td>\n",
       "      <td>Brand4553</td>\n",
       "      <td>45</td>\n",
       "      <td>NaN</td>\n",
       "      <td>@mjfree I bet if he was talking tough on North...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>24</td>\n",
       "      <td>24</td>\n",
       "      <td>130</td>\n",
       "      <td>0.833333</td>\n",
       "      <td>-0.388889</td>\n",
       "      <td>Somewhat subjective</td>\n",
       "      <td>Negative</td>\n",
       "      <td></td>\n",
       "      <td>mjfree</td>\n",
       "      <td>brand4553</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5000 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              Created At  Followers  Following           Handle   Likes  \\\n",
       "2595 2019-06-30 17:40:24    1142482     248834    charliekirk11   26563   \n",
       "2914 2019-06-30 17:33:02    1047950       9363          tedlieu   40845   \n",
       "1544 2019-06-30 18:05:26    1142457     248834    charliekirk11   26563   \n",
       "2348 2019-06-30 17:46:04     260567      35763       mmpadellan  145421   \n",
       "1119 2019-06-30 18:16:07     164550        285     marklutchman    7693   \n",
       "3186 2019-06-30 17:27:24      75002       2722  KlasfeldReports   16894   \n",
       "2762 2019-06-30 17:36:28      85071        422       hale_razor   36214   \n",
       "3090 2019-06-30 17:29:41     234743       1445     RadioFreeTom   54069   \n",
       "4317 2019-06-30 17:03:10     127089       1479  FrankFigliuzzi1    8849   \n",
       "841  2019-06-30 18:22:12     297054       2614    GOPChairwoman    5737   \n",
       "4278 2019-06-30 17:04:02   14374707        537              ABC      39   \n",
       "3379 2019-06-30 17:23:10      54439      16984           C_3C_3  104758   \n",
       "4288 2019-06-30 17:03:40     317916      17012        KayaJones  110612   \n",
       "4508 2019-06-30 16:59:28     280076       1577     JohnJHarwood    3149   \n",
       "1295 2019-06-30 18:11:56     235966       1413          MaxBoot   10750   \n",
       "4488 2019-06-30 16:59:48     140336        355   AngrierWHStaff    5142   \n",
       "1655 2019-06-30 18:02:59      78162      70266         CHIZMAGA  150681   \n",
       "722  2019-06-30 18:24:35     141285       3915    williamlegate  420670   \n",
       "3895 2019-06-30 17:11:54      40763       4573    OfficialJoelF   15396   \n",
       "3519 2019-06-30 17:20:00    3300295        256          thehill      25   \n",
       "3468 2019-06-30 17:20:56      68571      58280  GrassrootsSpeak   46922   \n",
       "2497 2019-06-30 17:42:28     191688      91693    RealMattCouch  208132   \n",
       "3144 2019-06-30 17:28:29     151252      32228  JenniferJJacobs    1454   \n",
       "2164 2019-06-30 17:50:31      49888       3687    VoteOjeda2020    2901   \n",
       "2779 2019-06-30 17:35:57      60522      39097     amvetsupport  163130   \n",
       "3095 2019-06-30 17:29:34     125831      76755      activist360    4245   \n",
       "4677 2019-06-30 16:55:11      69350       3992     politicususa     561   \n",
       "1138 2019-06-30 18:15:45      60519      39094     amvetsupport  163101   \n",
       "4770 2019-06-30 16:53:21     157211      68783  RedNationRising   74820   \n",
       "3746 2019-06-30 17:15:00    3300295        256          thehill      25   \n",
       "...                  ...        ...        ...              ...     ...   \n",
       "3112 2019-06-30 17:29:09          0          0    Scifigirl2020    2006   \n",
       "3210 2019-06-30 17:26:49          0          0       sta_united   18332   \n",
       "3296 2019-06-30 17:24:49          0          3     VdaChristina      32   \n",
       "3532 2019-06-30 17:19:38          0         29    Philly_Willie       9   \n",
       "3688 2019-06-30 17:16:13          0         16  William23313523      33   \n",
       "3768 2019-06-30 17:14:30          0         12        WierKerry      31   \n",
       "3780 2019-06-30 17:14:09          0         68        Grandpa64      61   \n",
       "3816 2019-06-30 17:13:27          0         21   Brenda46549508      63   \n",
       "3889 2019-06-30 17:12:02          0         41          mgan411       0   \n",
       "3890 2019-06-30 17:11:56          0          3  AbigailFriedri1       0   \n",
       "3950 2019-06-30 17:10:57          0        103       NNetvision       0   \n",
       "3952 2019-06-30 17:10:54          0          0  isIbJVOEBhe608p       0   \n",
       "3953 2019-06-30 17:10:54          0          1     Jiggy_Gigolo       3   \n",
       "3961 2019-06-30 17:10:48          0         19        SHigher00      35   \n",
       "4029 2019-06-30 17:09:12          0          2  Cruzgar28746344      17   \n",
       "4032 2019-06-30 17:09:08          0          0    trump_antonym       0   \n",
       "4052 2019-06-30 17:08:29          0         11  thoughtsbydaryl       1   \n",
       "4142 2019-06-30 17:06:46          0         58        Mitch_W99      23   \n",
       "4173 2019-06-30 17:05:54          0          0      bette_sayer       0   \n",
       "4175 2019-06-30 17:05:52          0         13      pradelpiere       0   \n",
       "4275 2019-06-30 17:04:04          0          2    HEADLINES_Etc       1   \n",
       "4417 2019-06-30 17:01:13          0         17     Ynot34403716       8   \n",
       "4425 2019-06-30 17:01:06          0         14       lawton_ron      52   \n",
       "4434 2019-06-30 17:00:54          0          0  G6o2fAzdsFtheQI       0   \n",
       "4617 2019-06-30 16:56:53          0         10       Retired420      28   \n",
       "4651 2019-06-30 16:55:54          0          0     PhebeTedford       0   \n",
       "4661 2019-06-30 16:55:42          0          1           tt3091       0   \n",
       "4664 2019-06-30 16:55:37          0          5       TKalamaros       2   \n",
       "4884 2019-06-30 16:50:54          0          0    KatlynNewarch       0   \n",
       "4967 2019-06-30 16:49:05          0         38        Brand4553      45   \n",
       "\n",
       "                            Location  \\\n",
       "2595               Chicago, Illinois   \n",
       "2914                      California   \n",
       "1544               Chicago, Illinois   \n",
       "2348                    Brooklyn, NY   \n",
       "1119                Philadelphia, PA   \n",
       "3186                    New York, NY   \n",
       "2762  Wherever Liberty is Threatened   \n",
       "3090                     Newport, RI   \n",
       "4317                      Tucson, AZ   \n",
       "841                              NaN   \n",
       "4278       New York City / Worldwide   \n",
       "3379                             NaN   \n",
       "4288                         America   \n",
       "4508                  Washington, DC   \n",
       "1295                        New York   \n",
       "4488                             NaN   \n",
       "1655                   San Diego, CA   \n",
       "722                        Instagram   \n",
       "3895                       Miami, FL   \n",
       "3519                  Washington, DC   \n",
       "3468                             NYC   \n",
       "2497                   Arkansas, USA   \n",
       "3144                  Washington, DC   \n",
       "2164                             NaN   \n",
       "2779                 Palm Desert, CA   \n",
       "3095  Lower East Side, New York City   \n",
       "4677                             USA   \n",
       "1138                 Palm Desert, CA   \n",
       "4770                 Everywhere, USA   \n",
       "3746                  Washington, DC   \n",
       "...                              ...   \n",
       "3112                    Arizona, USA   \n",
       "3210                             USA   \n",
       "3296                             NaN   \n",
       "3532                   Virginia, USA   \n",
       "3688                             NaN   \n",
       "3768                             NaN   \n",
       "3780                             NaN   \n",
       "3816                   United States   \n",
       "3889                             NaN   \n",
       "3890                             NaN   \n",
       "3950                 Kampala, Uganda   \n",
       "3952                             NaN   \n",
       "3953                      Dallas, TX   \n",
       "3961                   United States   \n",
       "4029                             NaN   \n",
       "4032                             NaN   \n",
       "4052                    Georgia, USA   \n",
       "4142                             NaN   \n",
       "4173                             NaN   \n",
       "4175                 New Jersey, USA   \n",
       "4275            SOMEWHERE IN AMERICA   \n",
       "4417                   Henderson, NV   \n",
       "4425                             NaN   \n",
       "4434                             NaN   \n",
       "4617               Queens NY/Florida   \n",
       "4651                             NaN   \n",
       "4661                             NaN   \n",
       "4664                  South Bend, IN   \n",
       "4884                             NaN   \n",
       "4967                             NaN   \n",
       "\n",
       "                                                Message  Retweet Count  \\\n",
       "2595  Barack Obama was given the Nobel Peace Prize i...           2835   \n",
       "2914  We should support diplomacy. I think it's fine...            997   \n",
       "1544  If Hillary Clinton was President we would have...            991   \n",
       "2348  There's a reason no other American President h...            322   \n",
       "1119  President Trump is the first sitting president...            314   \n",
       "3186  This is a passage from a United Nations human ...            305   \n",
       "2762  44 lifts Cuba embargo and watches baseball gam...            285   \n",
       "3090  Today's humiliation in North Korea is yet anot...            283   \n",
       "4317  POTUS makes history as first to say visiting l...            282   \n",
       "841   In 2017, Kamala Harris said: \"We must work to ...            246   \n",
       "4278  Pres. Trump became the first U.S. president to...            242   \n",
       "3379  Trump “appeased” North Korea by shaking Kim’s ...            221   \n",
       "4288  Trump isn’t using China🇨🇳 to make peace with N...            169   \n",
       "4508  there’s no evidence that this “performance” or...            152   \n",
       "1295  “Complete, verifiable, and irreversible denucl...            123   \n",
       "4488  - Gives North Korea another propaganda win\\n\\n...            120   \n",
       "1655  Obama never even tried to meet with Kim Jong U...            110   \n",
       "722   When Trump crossed the border into North Korea...             98   \n",
       "3895  ICYMI: Trump became the first sitting presiden...             86   \n",
       "3519  James Clapper: \"In all the deliberations that ...             76   \n",
       "3468  History was made...\\nWhen Trump visited his 'f...             74   \n",
       "2497  Does anyone honestly think any of the Democrat...             72   \n",
       "3144  Trump’s national security adviser stated just ...             68   \n",
       "2164  Nothing like hearing folks say “It’s time” for...             68   \n",
       "2779  After this idiotic North Korea photo op we sho...             66   \n",
       "3095  Everything Trump does is motivated by money fo...             65   \n",
       "4677  Trump disgraces America by proclaiming his fri...             62   \n",
       "1138  I cannot tell you how mad it makes me that thi...             62   \n",
       "4770  The sad truth:\\n\\nNorth Korea has a better rec...             59   \n",
       "3746  President Trump makes history by becoming the ...             58   \n",
       "...                                                 ...            ...   \n",
       "3112  Remember when disgusting Pres Jimmy Carter con...              0   \n",
       "3210  North Korea\\nTrump steps into North Korea with...              0   \n",
       "3296  An amazing day for our President &amp; our cou...              0   \n",
       "3532      @ANTIGOPMVMT Sanders wants to be North Korea.              0   \n",
       "3688  @thehill In other news President Donald Trump ...              0   \n",
       "3768  @MSNBC You know if he likes Russia and North K...              0   \n",
       "3780  What is the news cycle like in North Korea tod...              0   \n",
       "3816  @AP I think of Otto and his family. I can’t se...              0   \n",
       "3889  Trump Makes History, Becomes First Sitting U.S...              0   \n",
       "3890  @realDonaldTrump doesn't that mean you committ...              0   \n",
       "3950  Trump steps into North Korea during meeting wi...              0   \n",
       "3952  Iherb discount code \\n\\nAHB6653\\n\\nUse the cod...              0   \n",
       "3953  @funder You and the other Democrats don't care...              0   \n",
       "3961  @realDonaldTrump Correction, don’t you mean Di...              0   \n",
       "4029  @SkyNews Dont bring a wkmen to  north korea 🤦🏽‍♂️              0   \n",
       "4032  Leaving South Korea after a wonderful meeting ...              0   \n",
       "4052  So our president just made history by actually...              0   \n",
       "4142  @TheRealMrZilla1 @docsdaughter78 @jonkarl @Ste...              0   \n",
       "4173  Iherb discount code \\n\\nAHB6653\\n\\nUse the cod...              0   \n",
       "4175  Trump becomes 1st U.S. leader to step into Nor...              0   \n",
       "4275  FOX:   Should President Trump be awarded the N...              0   \n",
       "4417  @townhallcom How can it be treason,all the san...              0   \n",
       "4425  @eikrahss @Brasilmagic @realDonaldTrump What h...              0   \n",
       "4434  Iherb discount code \\n\\nAHB6653\\n\\nUse the cod...              0   \n",
       "4617  @tommychong Our President is fucking awesome. ...              0   \n",
       "4651  Iherb discount code \\n\\nAHB6653\\n\\nUse the cod...              0   \n",
       "4661  Trump becomes first president to step into Nor...              0   \n",
       "4664  Trump meets Kim, becomes first U.S. president ...              0   \n",
       "4884  Iherb discount code \\n\\nAHB6653\\n\\nUse the cod...              0   \n",
       "4967  @mjfree I bet if he was talking tough on North...              0   \n",
       "\n",
       "      Tweet Favorite Count                                   User Description  \\\n",
       "2595                  7397  Founder & President of @TPUSA Proud capitalist...   \n",
       "2914                  3365  Husband of Betty, the love of my life. Father ...   \n",
       "1544                  2946  Founder & President of @TPUSA Proud capitalist...   \n",
       "2348                   898  Proud papa. Perpetually pissed. #BlueWave2020,...   \n",
       "1119                  1062  Writer - Former Army National Guardsman - 25 y...   \n",
       "3186                   424  Reporter, @CourthouseNews: NYC+Int’l. RTs=What...   \n",
       "2762                   566  Conservative politics humor. Satire. Snark. Sa...   \n",
       "3090                   900  Professor, author on Russia, war, nukes, and \"...   \n",
       "4317                   742  Former FBI Assistant Director; NBC News Nation...   \n",
       "841                    618              @GOP Chairwoman | Wife, mother of two   \n",
       "4278                   662  All the news and information you need to see, ...   \n",
       "3379                   466       Parler: @ C3C3 / Turds will get instablocked   \n",
       "4288                   760  Christian✞ | Grammy Winning Vocalist |Platinum...   \n",
       "4508                   433  a Dad who covers Washington, the economy and n...   \n",
       "1295                   241  CFR fellow, WaPo columnist, CNN analyst. Autho...   \n",
       "4488                   663  Not a current WH Staffer | Politics, NatSec, a...   \n",
       "1655                   247              🇺🇸 Proud Supporter of President 🅣🅡🅤🅜🅟   \n",
       "722                    590  Self-made American entrepreneur • hacker/tinke...   \n",
       "3895                   255  Breaking news, local news, events, traffic ale...   \n",
       "3519                   174  The Hill is the premier source for policy and ...   \n",
       "3468                   239  I see it. I say it. Won't rest till we've take...   \n",
       "2497                   258  Christian, Father of 2, Investigator, Founder ...   \n",
       "3144                   130  Sr. White House reporter for Bloomberg. Report...   \n",
       "2164                   265  I spent 24 years fighting for my country only ...   \n",
       "2779                   169  1 of 1,000s of vets who despise trump - Volunt...   \n",
       "3095                   145  Singer-songwriter, musician, activist, poet, y...   \n",
       "4677                    89  Official Twitter Account for PoliticusUSA 💯Ind...   \n",
       "1138                   166  1 of 1,000s of vets who despise trump - Volunt...   \n",
       "4770                   131  Welcome to the Official Red Nation Rising Twit...   \n",
       "3746                   120  The Hill is the premier source for policy and ...   \n",
       "...                    ...                                                ...   \n",
       "3112                     0                               Hometown: Lorain, OH   \n",
       "3210                     0          'FOLLOWERS & LIST MAKERS WILL BE BLOCKED'   \n",
       "3296                     0                                                NaN   \n",
       "3532                     0            Just a family man trying to do his best   \n",
       "3688                     0                                                NaN   \n",
       "3768                     0                                                NaN   \n",
       "3780                     0                                                NaN   \n",
       "3816                     0  Christian wife, mother, grandmother. I am an i...   \n",
       "3889                     1                                                NaN   \n",
       "3890                     1                               life is an adventure   \n",
       "3950                     2                    Broadcasting & Media Production   \n",
       "3952                     0  انتقي أجود المنتجات الطبيعية من بين أكثر من 30...   \n",
       "3953                     2  \"Think for yourselves. Don’t be sheep.\"\\n— Ric...   \n",
       "3961                     1  Ghost Adventure, Dead Files and 90 Day Fiancé,...   \n",
       "4029                     0                                                NaN   \n",
       "4032                     0           Engineering experiment. Not a real user.   \n",
       "4052                     0       I’m a fun American man who loves the world!!   \n",
       "4142                     0                                                NaN   \n",
       "4173                     0                                                NaN   \n",
       "4175                     0                                               male   \n",
       "4275                     0                             THE TRUTH IS OUT THERE   \n",
       "4417                     0                                                NaN   \n",
       "4425                     1                                                NaN   \n",
       "4434                     0                                                NaN   \n",
       "4617                     1                                   Don’t Follow me.   \n",
       "4651                     0                                                NaN   \n",
       "4661                     0                 One Of these people testing things   \n",
       "4664                     0                                                NaN   \n",
       "4884                     0                                                NaN   \n",
       "4967                     1                                                NaN   \n",
       "\n",
       "           ...        word_count unique word_count  char_count  subjectivity  \\\n",
       "2595       ...                23                20         130      0.000000   \n",
       "2914       ...                24                22         130      0.500000   \n",
       "1544       ...                22                21         128      0.000000   \n",
       "2348       ...                21                20         130      0.187500   \n",
       "1119       ...                22                19         131      0.333333   \n",
       "3186       ...                19                18         130      0.150000   \n",
       "2762       ...                20                18         130      0.200000   \n",
       "3090       ...                19                19         132      0.500000   \n",
       "4317       ...                21                21         129      0.541667   \n",
       "841        ...                18                18         117      0.250000   \n",
       "4278       ...                20                19         130      0.333333   \n",
       "3379       ...                18                13         125      0.000000   \n",
       "4288       ...                23                21         127      0.000000   \n",
       "4508       ...                16                16         129      0.383333   \n",
       "1295       ...                18                15         129      0.400000   \n",
       "4488       ...                15                14          98      0.366667   \n",
       "1655       ...                25                22         129      0.000000   \n",
       "722        ...                25                23         134      0.900000   \n",
       "3895       ...                13                13          90      0.333333   \n",
       "3519       ...                20                17         131      0.000000   \n",
       "3468       ...                19                18         124      0.000000   \n",
       "2497       ...                16                16         103      0.900000   \n",
       "3144       ...                20                20         129      0.000000   \n",
       "2164       ...                21                19         127      0.500000   \n",
       "2779       ...                24                23         134      0.833333   \n",
       "3095       ...                20                18         132      1.000000   \n",
       "4677       ...                20                20         133      0.000000   \n",
       "1138       ...                26                26         133      1.000000   \n",
       "4770       ...                17                16          96      0.750000   \n",
       "3746       ...                18                17         118      0.591667   \n",
       "...        ...               ...               ...         ...           ...   \n",
       "3112       ...                19                19         131      0.833333   \n",
       "3210       ...                11                 9          75      0.000000   \n",
       "3296       ...                22                20         133      0.616667   \n",
       "3532       ...                 7                 7          43      0.100000   \n",
       "3688       ...                21                18         132      0.177083   \n",
       "3768       ...                19                19          93      0.000000   \n",
       "3780       ...                25                20         132      0.000000   \n",
       "3816       ...                25                21         129      0.000000   \n",
       "3889       ...                16                15         125      0.333333   \n",
       "3890       ...                11                11          78      0.687500   \n",
       "3950       ...                14                14          91      0.000000   \n",
       "3952       ...                25                20         129      0.375000   \n",
       "3953       ...                21                20         131      0.375000   \n",
       "3961       ...                21                20         129      0.687500   \n",
       "4029       ...                 9                 9          42      0.000000   \n",
       "4032       ...                22                21         132      1.000000   \n",
       "4052       ...                20                20         132      0.100000   \n",
       "4142       ...                16                16         129      0.650000   \n",
       "4173       ...                25                20         129      0.375000   \n",
       "4175       ...                13                13          81      0.000000   \n",
       "4275       ...                20                19         124      0.000000   \n",
       "4417       ...                20                20         132      0.000000   \n",
       "4425       ...                18                18         130      0.500000   \n",
       "4434       ...                25                20         129      0.375000   \n",
       "4617       ...                 7                 7          62      1.000000   \n",
       "4651       ...                25                20         129      0.375000   \n",
       "4661       ...                 9                 9          63      0.333333   \n",
       "4664       ...                15                15         100      0.521212   \n",
       "4884       ...                25                20         129      0.375000   \n",
       "4967       ...                24                24         130      0.833333   \n",
       "\n",
       "      polarity   subjectivity_range  polarity_range hashtags  \\\n",
       "2595  0.000000                  NaN         Neutral            \n",
       "2914  0.416667            Objective        Positive            \n",
       "1544  0.000000                  NaN         Neutral            \n",
       "2348  0.031250            Objective        Positive            \n",
       "1119  0.250000            Objective        Positive            \n",
       "3186 -0.150000            Objective        Negative            \n",
       "2762 -0.200000            Objective        Negative            \n",
       "3090  0.500000            Objective        Positive            \n",
       "4317  0.525000            Objective        Positive            \n",
       "841   0.250000            Objective        Positive            \n",
       "4278  0.250000            Objective        Positive            \n",
       "3379  0.000000                  NaN         Neutral            \n",
       "4288  0.000000                  NaN         Neutral            \n",
       "4508  0.116667            Objective        Positive            \n",
       "1295  0.100000            Objective        Positive            \n",
       "4488  0.466667            Objective        Positive            \n",
       "1655  0.000000                  NaN         Neutral            \n",
       "722   0.200000  Somewhat subjective        Positive            \n",
       "3895  0.250000            Objective        Positive            \n",
       "3519  0.000000                  NaN         Neutral            \n",
       "3468  0.000000                  NaN         Neutral            \n",
       "2497  0.600000  Somewhat subjective        Positive            \n",
       "3144  0.000000                  NaN         Neutral            \n",
       "2164  0.250000            Objective        Positive            \n",
       "2779 -0.666667  Somewhat subjective        Negative            \n",
       "3095  0.000000      Very Subjective         Neutral            \n",
       "4677  0.000000                  NaN         Neutral            \n",
       "1138 -0.625000      Very Subjective        Negative            \n",
       "4770  0.000000  Somewhat subjective         Neutral            \n",
       "3746  0.350000            Objective        Positive            \n",
       "...        ...                  ...             ...      ...   \n",
       "3112 -0.850000  Somewhat subjective        Negative            \n",
       "3210  0.000000                  NaN         Neutral            \n",
       "3296  0.425000            Objective        Positive      kag   \n",
       "3532  0.200000            Objective        Positive            \n",
       "3688  0.031250            Objective        Positive            \n",
       "3768  0.000000                  NaN         Neutral            \n",
       "3780  0.000000                  NaN         Neutral            \n",
       "3816  0.000000                  NaN         Neutral            \n",
       "3889  0.250000            Objective        Positive            \n",
       "3890 -0.312500  Somewhat subjective        Negative            \n",
       "3950  0.000000                  NaN         Neutral            \n",
       "3952 -0.125000            Objective        Negative            \n",
       "3953 -0.125000            Objective        Negative            \n",
       "3961 -0.312500  Somewhat subjective        Negative            \n",
       "4029  0.000000                  NaN         Neutral            \n",
       "4032  1.000000      Very Subjective        Positive            \n",
       "4052  0.000000            Objective         Neutral            \n",
       "4142  0.550000            Objective        Positive            \n",
       "4173 -0.125000            Objective        Negative            \n",
       "4175  0.000000                  NaN         Neutral            \n",
       "4275  0.000000                  NaN         Neutral            \n",
       "4417  0.000000                  NaN         Neutral            \n",
       "4425  0.200000            Objective        Positive            \n",
       "4434 -0.125000            Objective        Negative            \n",
       "4617  1.000000      Very Subjective        Positive            \n",
       "4651 -0.125000            Objective        Negative            \n",
       "4661  0.250000            Objective        Positive            \n",
       "4664  0.272727            Objective        Positive            \n",
       "4884 -0.125000            Objective        Negative            \n",
       "4967 -0.388889  Somewhat subjective        Negative            \n",
       "\n",
       "                                                handles             User  \n",
       "2595                                                       charliekirk11  \n",
       "2914                                              potus          tedlieu  \n",
       "1544                                                       charliekirk11  \n",
       "2348                                                          mmpadellan  \n",
       "1119                                                        marklutchman  \n",
       "3186                                                     klasfeldreports  \n",
       "2762                                                          hale_razor  \n",
       "3090                                                        radiofreetom  \n",
       "4317                                                     frankfigliuzzi1  \n",
       "841                                                        gopchairwoman  \n",
       "4278                                                                 abc  \n",
       "3379                                                              c_3c_3  \n",
       "4288                                                           kayajones  \n",
       "4508                                                        johnjharwood  \n",
       "1295                                                             maxboot  \n",
       "4488                                                      angrierwhstaff  \n",
       "1655                                                            chizmaga  \n",
       "722                                                        williamlegate  \n",
       "3895                                                       officialjoelf  \n",
       "3519                                                             thehill  \n",
       "3468                                                     grassrootsspeak  \n",
       "2497                                                       realmattcouch  \n",
       "3144                                                     jenniferjjacobs  \n",
       "2164                                                       voteojeda2020  \n",
       "2779                                                        amvetsupport  \n",
       "3095                                                         activist360  \n",
       "4677                                                        politicususa  \n",
       "1138                                                        amvetsupport  \n",
       "4770                                                     rednationrising  \n",
       "3746                                                             thehill  \n",
       "...                                                 ...              ...  \n",
       "3112                                    realdonaldtrump    scifigirl2020  \n",
       "3210                                                          sta_united  \n",
       "3296                                                        vdachristina  \n",
       "3532                                        antigopmvmt    philly_willie  \n",
       "3688                                            thehill  william23313523  \n",
       "3768                                              msnbc        wierkerry  \n",
       "3780                                                           grandpa64  \n",
       "3816                                                 ap   brenda46549508  \n",
       "3889                                                             mgan411  \n",
       "3890                                    realdonaldtrump  abigailfriedri1  \n",
       "3950                                            youtube       nnetvision  \n",
       "3952                                                     isibjvoebhe608p  \n",
       "3953                                             funder     jiggy_gigolo  \n",
       "3961                                    realdonaldtrump        shigher00  \n",
       "4029                                            skynews  cruzgar28746344  \n",
       "4032                                                       trump_antonym  \n",
       "4052                                                     thoughtsbydaryl  \n",
       "4142  therealmrzilla1 docsdaughter78 jonkarl stephgr...        mitch_w99  \n",
       "4173                                                         bette_sayer  \n",
       "4175                                                         pradelpiere  \n",
       "4275                                                       headlines_etc  \n",
       "4417                                        townhallcom     ynot34403716  \n",
       "4425               eikrahss brasilmagic realdonaldtrump       lawton_ron  \n",
       "4434                                                     g6o2fazdsftheqi  \n",
       "4617                                         tommychong       retired420  \n",
       "4651                                                        phebetedford  \n",
       "4661                                                              tt3091  \n",
       "4664                                                          tkalamaros  \n",
       "4884                                                       katlynnewarch  \n",
       "4967                                             mjfree        brand4553  \n",
       "\n",
       "[5000 rows x 22 columns]"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "retweets = df4.sort_values(by=['Retweet Count', 'Followers'] , ascending=False)\n",
    "retweets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fe648e46a20>"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "retweets.plot(x='Created At',y='Retweet Count')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fe648e82828>"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "retweets.plot(x='Created At',y='Followers')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fe6491b16d8>"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tweet_many = df4[df4['Retweet Count'] >= 10]\n",
    "tweet_many.plot(x='Created At', figsize=(16, 6))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python (myENV)",
   "language": "python",
   "name": "myenv"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}