IPython Notebook - Facebook Friend interested in events through FacebookTrackingExposed CSV

FriendInterestedEvent.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import csv\n",
    "import pandas as pd\n",
    "from datetime import datetime\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "21    2017-09-12 14:08:45\n",
      "125   2017-09-12 14:08:45\n",
      "135   2017-09-12 17:25:43\n",
      "139   2017-09-12 19:13:20\n",
      "245   2017-09-11 14:34:13\n",
      "247   2017-09-12 14:08:45\n",
      "256   2017-09-12 19:13:20\n",
      "376   2017-09-11 21:49:24\n",
      "431   2017-09-11 21:51:45\n",
      "432   2017-09-11 19:26:31\n",
      "Name: publicationTime, dtype: datetime64[ns]\n"
     ]
    }
   ],
   "source": [
    "dataframe = pd.read_csv(\"friend_data.csv\").fillna(\"\")\n",
    "dataframe = dataframe[[\"publicationTime\",\"source\"]]\n",
    "index = dataframe[\"source\"].str.contains(\"is interested in an event.\")\n",
    "times = dataframe[index][\"publicationTime\"]\n",
    "print(pd.to_datetime(times))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'2017-09-12 14': 3, '2017-09-12 17': 1, '2017-09-12 19': 2, '2017-09-11 14': 1, '2017-09-11 21': 2, '2017-09-11 19': 1}\n",
      "[3, 1, 2, 1, 2, 1]\n",
      "[0, 1, 2, 3, 4, 5]\n",
      "['2017-09-12 14', '2017-09-12 17', '2017-09-12 19', '2017-09-11 14', '2017-09-11 21', '2017-09-11 19']\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f1fdf752390>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bucket_per_hour = {}\n",
    "bucket_per_day = {}\n",
    "for row in times:\n",
    "    nameh = (datetime.strptime(row, \"%Y-%m-%dT%H:%M:%S.000Z\").strftime(\"%Y-%m-%d %H\"))\n",
    "    named = (datetime.strptime(row, \"%Y-%m-%dT%H:%M:%S.000Z\").strftime(\"%Y-%m-%d\"))\n",
    "\n",
    "    bucket_per_hour[nameh] = 1 if bucket_per_hour.get(nameh) == None else bucket_per_hour[nameh]+1\n",
    "    bucket_per_day[named] = 1 if bucket_per_day.get(named) == None else bucket_per_day[named]+1\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "names = bucket_per_hour.keys()\n",
    "\n",
    "bd = plt.subplot()\n",
    "indexes = [x for x in range(len(bucket_per_hour.values()))]\n",
    "indexes_labels = [x for x in (bucket_per_hour.keys())]\n",
    "vals = [ x for x in bucket_per_hour.values()]\n",
    "print(bucket_per_hour)\n",
    "print(vals)\n",
    "print(indexes)\n",
    "print(indexes_labels)\n",
    "bd.bar(indexes,height=vals)\n",
    "plt.xticks(indexes, indexes_labels, rotation='-40',ha=\"left\")\n",
    "\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "    "
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3.6",
   "language": "python",
   "name": "python36"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}