hcds-a1-data-curation.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# A1: Data Curation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The purpose of this notebook is to showcase a dataset, whilst adhering to principles of reproducible research. The reference articles used for this purpose are \n",
    "  1. [Assessing Reproducability](https://www.practicereproducibleresearch.org/core-chapters/2-assessment.html)\n",
    "  2. [The Basic Reproducible Workflow Template](https://www.practicereproducibleresearch.org/core-chapters/3-basic.html)\n",
    "  \n",
    "### Table of Contents\n",
    "\n",
    "1. [Step 1: Data Acquisition](#s1)  \n",
    "  a. [Getting Legacy PageCounts Data](#s1_1)  \n",
    "  b. [Getting PageViews Data](#s1_2)\n",
    "2. [Step 2: Data Processing](#s2)\n",
    "3. [Step 3: Analysis](#s3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-10-18T08:23:29.338038Z",
     "start_time": "2018-10-18T08:23:28.813499Z"
    }
   },
   "outputs": [],
   "source": [
    "import os\n",
    "import shutil\n",
    "from collections import defaultdict\n",
    "from functools import reduce\n",
    "\n",
    "import json\n",
    "import requests\n",
    "\n",
    "import pandas as pd\n",
    "\n",
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id=\"s1\"></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Step 1 - Data Acquisition"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We use two Wikimedia API endpoints:\n",
    "  1. [Legacy Pagecounts API](https://wikitech.wikimedia.org/wiki/Analytics/AQS/Legacy_Pagecounts)\n",
    "  2. [Pageviews API](https://wikitech.wikimedia.org/wiki/Analytics/AQS/Pageviews)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-10-18T08:23:29.346479Z",
     "start_time": "2018-10-18T08:23:29.340676Z"
    }
   },
   "outputs": [],
   "source": [
    "ENDPOINT_ROOT = \"https://wikimedia.org/api/rest_v1/metrics/\"\n",
    "ENDPOINT_LEGACY = ENDPOINT_ROOT + 'legacy/pagecounts/aggregate/{project}/{access-site}/{granularity}/{start}/{end}'\n",
    "ENDPOINT_PAGEVIEW = ENDPOINT_ROOT + 'pageviews/aggregate/{project}/{access}/{agent}/{granularity}/{start}/{end}'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-10-18T08:23:29.354137Z",
     "start_time": "2018-10-18T08:23:29.348682Z"
    }
   },
   "outputs": [],
   "source": [
    "COMMON_PARAMS = {\n",
    "    \"project\" : \"en.wikipedia.org\",\n",
    "    \"granularity\" : \"monthly\",\n",
    "}\n",
    "\n",
    "OUTPUT_JSON_DIR = \"json\"\n",
    "OUTPUT_CSV_DIR = \"csv\"\n",
    "\n",
    "HEADERS = {\n",
    "    'User-Agent': 'https://github.com/havanagrawal',\n",
    "    'From': 'agrawh@uw.edu'\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-10-18T08:23:29.369940Z",
     "start_time": "2018-10-18T08:23:29.357728Z"
    }
   },
   "outputs": [],
   "source": [
    "# Delete the directory if it already exists, and then recreate it\n",
    "if os.path.exists(OUTPUT_JSON_DIR):\n",
    "    shutil.rmtree(OUTPUT_JSON_DIR)\n",
    "    \n",
    "if os.path.exists(OUTPUT_CSV_DIR):\n",
    "    shutil.rmtree(OUTPUT_CSV_DIR)\n",
    "    \n",
    "os.mkdir(OUTPUT_JSON_DIR)\n",
    "os.mkdir(OUTPUT_CSV_DIR)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-10-18T08:23:29.380558Z",
     "start_time": "2018-10-18T08:23:29.373606Z"
    }
   },
   "outputs": [],
   "source": [
    "def api_call(endpoint, parameters):\n",
    "    call = requests.get(endpoint.format(**parameters), headers=HEADERS)\n",
    "    response = call.json()\n",
    "    \n",
    "    return response"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-10-18T08:23:29.389105Z",
     "start_time": "2018-10-18T08:23:29.383034Z"
    }
   },
   "outputs": [],
   "source": [
    "def get_output_file_path(api_type, accesstype, start, end):\n",
    "    filename = \"{api_type}_{accesstype}_{start}-{end}.json\".format(api_type=api_type, accesstype=accesstype, start=start, end=end)\n",
    "    return os.path.join(OUTPUT_JSON_DIR, filename)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-10-18T08:23:29.403193Z",
     "start_time": "2018-10-18T08:23:29.392184Z"
    }
   },
   "outputs": [],
   "source": [
    "def write_to_json(data, filename):\n",
    "    data_string = json.dumps(data, indent=2)\n",
    "    with open(filename, \"w\") as f:\n",
    "        f.write(data_string)\n",
    "        \n",
    "def read_from_json(filename):\n",
    "    data = {}\n",
    "    with open(filename, \"r\") as f:\n",
    "        data = json.loads(f.read())\n",
    "    \n",
    "    return data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id=\"s1_1\"></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Getting Legacy PageCounts Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-10-18T08:23:29.454664Z",
     "start_time": "2018-10-18T08:23:29.405241Z"
    }
   },
   "outputs": [],
   "source": [
    "def get_legacy_page_count_data(access_site, start, end):\n",
    "    params = {\n",
    "        \"access-site\" : access_site,\n",
    "        \"start\" : start,\n",
    "        \"end\" : end\n",
    "    }\n",
    "    params.update(COMMON_PARAMS)\n",
    "    data = api_call(ENDPOINT_LEGACY, params)\n",
    "    output_filepath = get_output_file_path(\"pagecounts\", access_site, start, end)\n",
    "    \n",
    "    write_to_json(data, output_filepath)\n",
    "    \n",
    "    return output_filepath"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-10-18T08:23:29.813688Z",
     "start_time": "2018-10-18T08:23:29.457452Z"
    }
   },
   "outputs": [],
   "source": [
    "start, end = \"2007120100\", \"2016080100\"\n",
    "pagecount_desktop_file = get_legacy_page_count_data('desktop-site', start, end)\n",
    "pagecount_mobile_file = get_legacy_page_count_data('mobile-site', start, end)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id=\"s1_2\"></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Getting PageViews Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-10-18T08:23:29.825604Z",
     "start_time": "2018-10-18T08:23:29.816320Z"
    }
   },
   "outputs": [],
   "source": [
    "def get_page_view_data(access_site, start, end):\n",
    "    params = {\n",
    "        \"access\" : access_site,\n",
    "        \"start\" : start,\n",
    "        \"end\" : end,\n",
    "        \"agent\": \"user\"\n",
    "    }\n",
    "    params.update(COMMON_PARAMS)\n",
    "    data = api_call(ENDPOINT_PAGEVIEW, params)\n",
    "    output_filepath = get_output_file_path(\"pageviews\", access_site, start, end)\n",
    "    \n",
    "    write_to_json(data, output_filepath)\n",
    "    \n",
    "    return output_filepath"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-10-18T08:23:30.348564Z",
     "start_time": "2018-10-18T08:23:29.828064Z"
    }
   },
   "outputs": [],
   "source": [
    "start, end = \"2015070100\", \"2018100100\"\n",
    "pageview_desktop_file = get_page_view_data(\"desktop\", start, end)\n",
    "pageview_mobile_app_file = get_page_view_data(\"mobile-app\", start, end)\n",
    "pageview_mobile_site_file = get_page_view_data(\"mobile-web\", start, end)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-10-18T08:23:30.359138Z",
     "start_time": "2018-10-18T08:23:30.351533Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['pageviews_mobile-app_2015070100-2018100100.json',\n",
       " 'pagecounts_mobile-site_2007120100-2016080100.json',\n",
       " 'pageviews_desktop_2015070100-2018100100.json',\n",
       " 'pagecounts_desktop-site_2007120100-2016080100.json',\n",
       " 'pageviews_mobile-web_2015070100-2018100100.json']"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Should have 5 files\n",
    "output_files = os.listdir(OUTPUT_JSON_DIR)\n",
    "assert len(output_files) == 5\n",
    "output_files"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id=\"s2\"></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Step 2 - Data Processing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-10-18T08:23:30.369936Z",
     "start_time": "2018-10-18T08:23:30.361842Z"
    }
   },
   "outputs": [],
   "source": [
    "def year(ts):\n",
    "    return int(ts[:4])\n",
    "\n",
    "def month(ts):\n",
    "    return int(ts[4:6])\n",
    "\n",
    "def yyyymm(ts):\n",
    "    return str(year(ts)) + str(month(ts)).rjust(2, \"0\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We read the generated JSON files from the previous step"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-10-18T08:23:30.380129Z",
     "start_time": "2018-10-18T08:23:30.371951Z"
    }
   },
   "outputs": [],
   "source": [
    "pageviews_mobile_app = read_from_json('json/pageviews_mobile-app_2015070100-2018100100.json')\n",
    "pageviews_mobile_site = read_from_json('json/pageviews_mobile-web_2015070100-2018100100.json')\n",
    "pageviews_desktop_site = read_from_json(\"json/pageviews_desktop_2015070100-2018100100.json\")\n",
    "\n",
    "pagecount_mobile = read_from_json(\"json/pagecounts_mobile-site_2007120100-2016080100.json\")\n",
    "pagecount_desktop_site = read_from_json(\"json/pagecounts_desktop-site_2007120100-2016080100.json\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-10-18T08:23:30.386979Z",
     "start_time": "2018-10-18T08:23:30.382554Z"
    }
   },
   "outputs": [],
   "source": [
    "pageviews_mobile_views = defaultdict(int)\n",
    "pageviews_desktop_views = defaultdict(int)\n",
    "\n",
    "pagecounts_mobile_views = defaultdict(int)\n",
    "pagecounts_desktop_views = defaultdict(int)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A small utility function that accumulates the views grouped by year-month pairs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-10-18T08:23:30.397275Z",
     "start_time": "2018-10-18T08:23:30.388988Z"
    }
   },
   "outputs": [],
   "source": [
    "def fill_dict(src_data, dest_dict):\n",
    "    for item in src_data['items']:\n",
    "        key = yyyymm(item['timestamp'])\n",
    "        if 'views' in item:\n",
    "            dest_dict[key] += item['views']\n",
    "        else:\n",
    "            dest_dict[key] += item['count']\n",
    "            \n",
    "def make_df(d, value_key):\n",
    "    return pd.DataFrame({'yyyymm': list(d.keys()), value_key: list(d.values())})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Combine the results from the mobile site and mobile web app for the page view data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-10-18T08:23:30.403145Z",
     "start_time": "2018-10-18T08:23:30.399502Z"
    }
   },
   "outputs": [],
   "source": [
    "fill_dict(pageviews_mobile_app, pageviews_mobile_views)\n",
    "fill_dict(pageviews_mobile_site, pageviews_mobile_views)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The others go into their respective independent counting dictionaries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-10-18T08:23:30.412052Z",
     "start_time": "2018-10-18T08:23:30.406465Z"
    }
   },
   "outputs": [],
   "source": [
    "fill_dict(pageviews_desktop_site, pageviews_desktop_views)\n",
    "\n",
    "fill_dict(pagecount_desktop_site, pagecounts_desktop_views)\n",
    "fill_dict(pagecount_mobile, pagecounts_mobile_views)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Since the desired output is a CSV file, the most convenient way to do so would be to convert the JSON into DataFrames, process and merge them, and then write the DataFrame into CSV"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-10-18T08:23:30.430229Z",
     "start_time": "2018-10-18T08:23:30.416975Z"
    }
   },
   "outputs": [],
   "source": [
    "pv_mobile_df = make_df(pageviews_mobile_views, 'pageview_mobile_views')\n",
    "pc_mobile_df = make_df(pagecounts_mobile_views, 'pagecount_mobile_views')\n",
    "\n",
    "pv_desktop_df = make_df(pageviews_desktop_views, 'pageview_desktop_views')\n",
    "pc_desktop_df = make_df(pagecounts_desktop_views, 'pagecount_desktop_views')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We apply a `reduce` function that merges all of the data frames into a single one, using the year-month pair as key."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-10-18T08:23:30.456763Z",
     "start_time": "2018-10-18T08:23:30.434415Z"
    }
   },
   "outputs": [],
   "source": [
    "def merger(d1, d2):\n",
    "    return d1.merge(d2, on='yyyymm', how='outer')\n",
    "\n",
    "df = reduce(merger, [pv_mobile_df, pc_mobile_df, pv_desktop_df, pc_desktop_df])\n",
    "    \n",
    "df.fillna(0, inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Add/remove columns as per the required schema"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-10-18T08:23:30.584672Z",
     "start_time": "2018-10-18T08:23:30.460037Z"
    }
   },
   "outputs": [],
   "source": [
    "df['pagecount_all_views'] = df['pagecount_mobile_views'] + df['pagecount_desktop_views']\n",
    "df['pageview_all_views'] = df['pageview_mobile_views'] + df['pageview_desktop_views']\n",
    "df['year'] = df.yyyymm.apply(str).apply(year)\n",
    "df['month'] = df.yyyymm.apply(str).apply(month)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-10-18T08:23:30.594184Z",
     "start_time": "2018-10-18T08:23:30.587260Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('200712', '201809')"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "min_date, max_date = df.yyyymm.min(), df.yyyymm.max()\n",
    "min_date, max_date"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-10-18T08:23:30.601898Z",
     "start_time": "2018-10-18T08:23:30.596398Z"
    }
   },
   "outputs": [],
   "source": [
    "df.drop('yyyymm', axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And finally write it out into a single CSV file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-10-18T08:23:30.615401Z",
     "start_time": "2018-10-18T08:23:30.604866Z"
    }
   },
   "outputs": [],
   "source": [
    "output_csv_filename = \"en-wikipedia_traffic_{from_date}-{to_date}.csv\".format(from_date=min_date, to_date=max_date)\n",
    "output_csv_filepath = os.path.join(OUTPUT_CSV_DIR, output_csv_filename)\n",
    "df.to_csv(output_csv_filepath, index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id=\"s3\"></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Step 3: Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-10-18T08:23:30.626837Z",
     "start_time": "2018-10-18T08:23:30.617398Z"
    }
   },
   "outputs": [],
   "source": [
    "df = pd.read_csv(output_csv_filepath)\n",
    "df = df.replace(to_replace=0, value=pd.np.nan)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-10-18T08:23:30.644742Z",
     "start_time": "2018-10-18T08:23:30.631464Z"
    }
   },
   "outputs": [],
   "source": [
    "df['date'] = df.apply(lambda r: pd.datetime(int(r.year), int(r.month), 1), axis=1)\n",
    "df = df.sort_values('date')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-10-18T08:23:30.990483Z",
     "start_time": "2018-10-18T08:23:30.646892Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x118ce5908>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(18, 8))\n",
    "\n",
    "plt.plot(df.date, df.pageview_all_views)\n",
    "plt.plot(df.date, df.pageview_mobile_views)\n",
    "plt.plot(df.date, df.pageview_desktop_views)\n",
    "\n",
    "plt.plot(df.date, df.pagecount_all_views)\n",
    "plt.plot(df.date, df.pagecount_mobile_views)\n",
    "plt.plot(df.date, df.pagecount_desktop_views)\n",
    "\n",
    "ymin, ymax = plt.ylim()\n",
    "\n",
    "plt.legend([\"PageView All\", \"PageView Mobile\", \"PageView Desktop\", \"PageCount All\", \"PageCount Mobile\", \"PageCount Desktop\"])\n",
    "\n",
    "vlines = [\n",
    "    df[df.pagecount_all_views.isna()].date.min(), # The last date on which we have page count data\n",
    "    df[df.pageview_all_views.isna()].date.max()   # The first date for which we have page view data\n",
    "]\n",
    "\n",
    "plt.vlines(vlines, ymin=ymin, ymax=ymax, linestyles='dotted')\n",
    "\n",
    "plt.xlabel(\"Year\")\n",
    "plt.ylabel(\"View Count\")\n",
    "\n",
    "plt.title(\"Wikimedia View Counts from 2007 to 2018\")\n",
    "plt.grid()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The dotted lines enclose the region of overlap"
   ]
  }
 ],
 "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
}