1_exploratory_analysis.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#!/usr/bin/env python\n",
    "# -*- coding: UTF-8 -*-\n",
    "import sys\n",
    "import csv\n",
    "import json\n",
    "import pprint\n",
    "from pymongo import MongoClient\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import collections\n",
    "from datetime import datetime\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "client = MongoClient()\n",
    "db = client.twitter\n",
    "posts = db[\"posts\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "data = []\n",
    "for entry in posts.find():\n",
    "    if db[\"users\"].find_one({\"tweet_id\": entry[\"id\"]}):\n",
    "        data.append(entry['retweet_count'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAy8AAAIcCAYAAAD/tJGHAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10a1aa710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ds = pd.Series(data, index=range(len(data)))\n",
    "sns.set_context(\"poster\")\n",
    "with sns.axes_style(\"darkgrid\"):\n",
    "    ds.plot.hist(bins=500)\n",
    "    plt.xlim(0, 3000)\n",
    "    plt.xlabel('Number of Retweets')\n",
    "    plt.ylabel('Number of NYT news posts')\n",
    "    plt.show()\n",
    "    plt.savefig(\"fig/Retweets_per_post.png\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "users = db[\"user_merge\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "data = []\n",
    "for entry in users.find():\n",
    "    data.append(entry['count'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAy8AAAIcCAYAAAD/tJGHAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nIYQQQgjpEv4PWa9uVibWs0gAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10699b450>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ds = pd.Series(data, index=range(len(data)))\n",
    "with sns.axes_style(\"darkgrid\"):\n",
    "    ds.plot.hist(bins=500)\n",
    "    plt.xlim(0, 150)\n",
    "    plt.xlabel('Number of Retweets')\n",
    "    plt.ylabel('Number of Users')\n",
    "    plt.show()\n",
    "    plt.savefig(\"fig/Retweets_per_user.png\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pprint\n",
    "\n",
    "def SaveDict(filename, mode, root):\n",
    "    if filename[-4:]!=\".txt\":\n",
    "        filename+=\".txt\"\n",
    "    with open(filename, mode) as f:\n",
    "        f.write(pprint.pformat(root))\n",
    "\n",
    "def LoadDict(filename):\n",
    "    if filename[-4:]!=\".txt\":\n",
    "        filename+=\".txt\"\n",
    "    with open(filename, \"r\") as f:\n",
    "        return eval(f.read())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import pickle\n",
    "import json\n",
    "articles = []\n",
    "for article in db.articles.find():\n",
    "    if db.retweeter_list.find_one({\"tweet_id\": article[\"id\"]}):\n",
    "        retweets = db.retweeter_list.find_one({\"tweet_id\": article[\"id\"]})[\"retweeters\"]\n",
    "    articles.append({\"title\": article[\"title\"], \"users\": retweets})\n",
    "json.dump(articles,open('./data/article_users.json','wb'))"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}