A1 Data Curation.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# A1 Data Curation\n",
    "\n",
    "This notebook covers the acquisition, processing, graphic analysis, and dataset publishing of Wikipedia site traffic. The goal is that this work follows best practices of open scientific reasearch to be fully reproducible and well-documented. Others should be able to follow, and expand upon this work easily.\n",
    "\n",
    "## Initialization\n",
    "\n",
    "This code brings in the library dependencies to be used by subsequent code.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 344,
   "metadata": {},
   "outputs": [],
   "source": [
    "import json                       # For API response handling\n",
    "import requests                   # For API call handling\n",
    "import pandas                     # For dataframes\n",
    "import matplotlib.pyplot as plt   # For plotting"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data acquisition\n",
    "\n",
    "Using Wikimedia's RESTful APIs, we can obtain site traffic data. The [Pagecounts](https://wikitech.wikimedia.org/wiki/Analytics/AQS/Legacy_Pagecounts) API was originally provided from years 2008 to 2016, while the [Pageviews](https://wikitech.wikimedia.org/wiki/Analytics/AQS/Pageviews) API superceded it starting in 2015 to today. To produce site data from 2008 to the latest available information in 2018, the data returned from both APIs will be combined.\n",
    "\n",
    "First, define the endpoint paths to both APIs:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 345,
   "metadata": {},
   "outputs": [],
   "source": [
    "pagecounts = 'https://wikimedia.org/api/rest_v1/metrics/legacy/pagecounts/aggregate/{project}/{access-site}/\\\n",
    "{granularity}/{start}/{end}'\n",
    "\n",
    "pageviews = 'https://wikimedia.org/api/rest_v1/metrics/pageviews/aggregate/{project}/{access}/{agent}/\\\n",
    "{granularity}/{start}/{end}'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Define personal information headers:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 346,
   "metadata": {},
   "outputs": [],
   "source": [
    "headers = {'User-Agent' : 'https://github.com/PK#ing70',\n",
    "           'From'       : 'PKing70@uw.edu'\n",
    "          }"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Define the parameters for pagecounts, call the API, and store the JSON response:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 347,
   "metadata": {},
   "outputs": [],
   "source": [
    "params_pagecounts = {'project'     : 'en.wikipedia.org',\n",
    "                     'access-site' : 'desktop-site',\n",
    "                     'granularity' : 'monthly',\n",
    "                     'start'       : '2001010100',\n",
    "                     'end'         : '2016073100' # Pagecounts returns data until the end of July, 2016\n",
    "                    }\n",
    "\n",
    "call_pagecounts_d = requests.get(pagecounts.format(**params_pagecounts), headers = headers)\n",
    "response_pagecounts_d = call_pagecounts_d.json()  # Desktop-site data\n",
    "\n",
    "params_pagecounts[\"access-site\"] = \"mobile-site\"\n",
    "call_pagecounts_m = requests.get(pagecounts.format(**params_pagecounts), headers = headers)\n",
    "response_pagecounts_m = call_pagecounts_m.json()  # Mobile-site data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Define the parameters for Pageviews, call the API, and store the JSON responses."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 348,
   "metadata": {},
   "outputs": [],
   "source": [
    "params_pageviews =  {\"project\"     : \"en.wikipedia.org\",\n",
    "                     \"access\"      : \"desktop\",\n",
    "                     \"agent\"       : \"user\",\n",
    "                     \"granularity\" : \"monthly\",\n",
    "                     \"start\"       : \"2001010100\",\n",
    "                     \"end\"         : \"2018101800\" # Pagecounts returns data until today\n",
    "                    }\n",
    "\n",
    "call_pageviews_d = requests.get(pageviews.format(**params_pageviews), headers = headers)\n",
    "response_pageviews_d = call_pageviews_d.json()    # Desktop data\n",
    "\n",
    "params_pageviews[\"access\"] = \"mobile-app\"\n",
    "call_pageviews_ma = requests.get(pageviews.format(**params_pageviews), headers = headers)\n",
    "response_pageviews_ma = call_pageviews_ma.json()  # Mobile app data\n",
    "\n",
    "params_pageviews[\"access\"] = \"mobile-web\"\n",
    "call_pageviews_mw = requests.get(pageviews.format(**params_pageviews), headers = headers)\n",
    "response_pageviews_mw = call_pageviews_mw.json()  # Mobile web browser data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Store the raw results of each API call into a separate file:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 349,
   "metadata": {},
   "outputs": [],
   "source": [
    "filename = 'pagecounts_desktop-site_200807-201607.json' # Desktop Pagecount JSON file\n",
    "with open(filename, 'w') as file:\n",
    "    json.dump(response_pagecounts_d, file)\n",
    "    \n",
    "filename = 'pagecounts_mobile-site_200807-201607.json' # Mobile Pagecount JSON file\n",
    "with open(filename, 'w') as file:\n",
    "    json.dump(response_pagecounts_m, file)\n",
    "    \n",
    "filename = 'pageviews_desktop_200807-201809.json'  # Desktop Pageview JSON file\n",
    "with open(filename, 'w') as file:\n",
    "    json.dump(response_pageviews_d, file)\n",
    "\n",
    "filename = 'pageviews_mobile-app_200807-201809.json' # Mobile App Pageview JSON file\n",
    "with open(filename, 'w') as file:\n",
    "    json.dump(response_pageviews_ma, file)\n",
    "\n",
    "filename = 'pageviews_mobile-web_200807-201809.json' # Mobile Web Pagecount JSON file\n",
    "with open(filename, 'w') as file:\n",
    "    json.dump(response_pageviews_mw, file)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data Processing\n",
    "\n",
    "Combine the monthly values for mobile-app and mobile-web to create a total mobile traffic count for each month:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 350,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_pagecounts_d = pandas.DataFrame.from_dict(response_pagecounts_d['items']) # DF for Desktop Pagecount\n",
    "data_pagecounts_d['timestamp'] = data_pagecounts_d.timestamp.str[0:6] # Extract year and month from timestamp\n",
    "data_pagecounts_d.rename(columns={'count': 'pagecount_desktop_views'}, inplace=True) # Use final column name\n",
    "\n",
    "data_pagecounts_m = pandas.DataFrame.from_dict(response_pagecounts_m['items']) # DF for Mobile Pagecount\n",
    "data_pagecounts_m['timestamp'] = data_pagecounts_m.timestamp.str[0:6] # Extract year and month from timestamp\n",
    "data_pagecounts_m.rename(columns={'count': 'pagecount_mobile_views'}, inplace=True) # Use final column name\n",
    "\n",
    "data_pageviews_d = pandas.DataFrame.from_dict(response_pageviews_d['items']) # DF for Desktop Pageview\n",
    "data_pageviews_d['timestamp'] = data_pageviews_d.timestamp.str[0:6]   # Extract year and month from timestamp\n",
    "data_pageviews_d.rename(columns={'views': 'pageview_desktop_views'}, inplace=True) # Use final column name\n",
    "\n",
    "data_pageviews_ma = pandas.DataFrame.from_dict(response_pageviews_ma['items']) # DF for Mobile App Pageview\n",
    "data_pageviews_ma['timestamp'] = data_pageviews_ma.timestamp.str[0:6] # Extract year and month from timestamp\n",
    "data_pageviews_ma.rename(columns={'views': 'pageview_mobile-app_views'}, inplace=True) # Use final column name\n",
    "\n",
    "data_pageviews_mw = pandas.DataFrame.from_dict(response_pageviews_mw['items']) # DF for Mobile Web Pagecount\n",
    "data_pageviews_mw['timestamp'] = data_pageviews_mw.timestamp.str[0:6] # Extract year and month from timestamp\n",
    "data_pageviews_mw.rename(columns={'views': 'pageview_mobile-web_views'}, inplace=True) # Use final column name"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Merge the separate, API response-specific dataframes into one, aligned upon timestamp:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 351,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "data_f = data_pagecounts_d[['timestamp','pagecount_desktop_views']]\n",
    "data_f = data_f.merge(data_pagecounts_m[['timestamp','pagecount_mobile_views']], how='outer', on='timestamp')\n",
    "data_f = data_f.merge(data_pageviews_d[['timestamp','pageview_desktop_views']], how='outer', on='timestamp')\n",
    "data_f = data_f.merge(data_pageviews_ma[['timestamp','pageview_mobile-app_views']], how='outer', on='timestamp')\n",
    "data_f = data_f.merge(data_pageviews_mw[['timestamp','pageview_mobile-web_views']], how='outer', on='timestamp')\n",
    "#data_f"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Combine all data into a single CSV file with the following headers:\n",
    "\n",
    "|Column|Value|\n",
    "|---|---|\n",
    "|year|YYYY|\n",
    "|month|MM|\n",
    "|pagecount_all_views|num_views|\n",
    "|pagecount_desktop_views|num_views|\n",
    "|pagecount_mobile_views|num_views|\n",
    "|pageview_all_views|num_views|\n",
    "|pageview_desktop_views|num_views|\n",
    "|pageview_mobile_views|num_views|"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 352,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_f_output = pandas.DataFrame({'year':data_f['timestamp'].str[0:4],  # First four char are the year\n",
    "                                  'month':data_f['timestamp'].str[4:6], # Next two are the month\n",
    "                                  'pagecount_all_views':data_f['pagecount_desktop_views']+data_f['pagecount_mobile_views'],\n",
    "                                  'pagecount_desktop_views':data_f['pagecount_desktop_views'], \n",
    "                                  'pagecount_mobile_views':data_f['pagecount_mobile_views'],\n",
    "                                  'pageview_all_views':data_f['pageview_desktop_views']+data_f['pageview_mobile-app_views']+\\\n",
    "                                      data_f['pageview_mobile-web_views'],\n",
    "                                  'pageview_desktop_views':data_f['pageview_desktop_views'],\n",
    "                                  'pageview_mobile_views':data_f['pageview_mobile-app_views']+\\\n",
    "                                      data_f['pageview_mobile-web_views']})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Re-order the columns as specified:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 353,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_f_output = data_f_output[['year',\n",
    "                               'month',\n",
    "                               'pagecount_all_views',\n",
    "                               'pagecount_desktop_views',\n",
    "                               'pagecount_mobile_views',\n",
    "                               'pageview_all_views',\n",
    "                               'pageview_desktop_views',\n",
    "                               'pageview_mobile_views']]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Save to a CSV using the specified filename:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 354,
   "metadata": {},
   "outputs": [],
   "source": [
    "filename = 'en-wikipedia_traffic_200712-201809.csv'\n",
    "data_f_output.to_csv(filename, index=False, )  # Make sure the file is closed if it exists or this won't work"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data analysis\n",
    "\n",
    "We will make a time-series plot of the site traffic data, showing mobile, desktop, and all (combined) data.\n",
    "\n",
    "First, extract dates from our specially formatted year and month columns:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 355,
   "metadata": {},
   "outputs": [],
   "source": [
    "dates = pandas.to_datetime(data_f_output['year'].astype(str)+data_f_output['month'].astype(str), format='%Y%m')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next, construct the plot using matplotlib.pyplot."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 356,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1f68e744780>"
      ]
     },
     "execution_count": 356,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1f68e628978>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.rcParams[\"figure.figsize\"] = (14, 4)\n",
    "\n",
    "# Mimic the style and labels from the target image \n",
    "# https://wiki.communitydata.cc/File:En-wikipedia_traffic_200801-201709_thompson.png\n",
    "plt.grid(True)\n",
    "plt.title('Page Views on English Wikipedia (x 1,000,000)')\n",
    "plt.suptitle('May 2015: a new pageview definition took effect, which eliminated all crawler traffic.'\\\n",
    "             +'Solid lines mark new definition.', y=0.04, color='red');\n",
    "\n",
    "plt.plot(dates, data_f_output['pagecount_desktop_views']/1e6, 'k--') # Divide these by 1e6 to faux-convert to Integer data\n",
    "plt.plot(dates, data_f_output['pagecount_mobile_views']/1e6, 'b--')\n",
    "plt.plot(dates, data_f_output['pagecount_all_views']/1e6, 'g--')\n",
    "\n",
    "plt.plot(dates, data_f_output['pageview_desktop_views']/1e6, 'k-')\n",
    "plt.plot(dates, data_f_output['pageview_mobile_views']/1e6, 'b-')\n",
    "plt.plot(dates, data_f_output['pageview_all_views']/1e6, 'g-')\n",
    "\n",
    "plt.ylim((0,12000))\n",
    "plt.xlim(('2008-01-01','2018-10-18'))\n",
    "\n",
    "plt.legend(['main site','mobile site','total'], loc=2, framealpha=1)\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}