Google Analytics Reporting API GitHub.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Google Analytics Reporting API"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This script requests a report from Google Analytics Reporting API and returns the response as a dataframe. It can handle pivot reports, summary reports with no pivot, and simple reports with no dimensions.\n",
    "\n",
    "To establish proper credentials, you need to:\n",
    "\n",
    "1. Create a project on Google Cloud Platform\n",
    "2. Enable Google Analytics Reporting API for this project\n",
    "3. Create a service account associated with the project\n",
    "4. Generate API keys for the service account\n",
    "5. In GA Admin panel, give your service account (looks like an email address) read access to your site's GA data.\n",
    "\n",
    "\n",
    "Links:\n",
    "\n",
    "Creating projects: https://cloud.google.com/resource-manager/docs/creating-managing-projects\n",
    "Creating service account keys: https://cloud.google.com/iam/docs/creating-managing-service-account-keys\n",
    "Metrics and dimensions: https://ga-dev-tools.appspot.com/dimensions-metrics-explorer/ "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "from google.oauth2 import service_account\n",
    "from apiclient.discovery import build"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def format_summary(response):\n",
    "    try:\n",
    "        # create row index\n",
    "        try: \n",
    "            row_index_names = response['reports'][0]['columnHeader']['dimensions']\n",
    "            row_index = [ element['dimensions'] for element in response['reports'][0]['data']['rows'] ]\n",
    "            row_index_named = pd.MultiIndex.from_arrays(np.transpose(np.array(row_index)), \n",
    "                                                        names = np.array(row_index_names))\n",
    "        except:\n",
    "            row_index_named = None\n",
    "        \n",
    "        # extract column names\n",
    "        summary_column_names = [item['name'] for item in response['reports'][0]\n",
    "                                ['columnHeader']['metricHeader']['metricHeaderEntries']]\n",
    "    \n",
    "        # extract table values\n",
    "        summary_values = [element['metrics'][0]['values'] for element in response['reports'][0]['data']['rows']]\n",
    "    \n",
    "        # combine. I used type 'float' because default is object, and as far as I know, all values are numeric\n",
    "        df = pd.DataFrame(data = np.array(summary_values), \n",
    "                          index = row_index_named, \n",
    "                          columns = summary_column_names).astype('float')\n",
    "    \n",
    "    except:\n",
    "        df = pd.DataFrame()\n",
    "        \n",
    "    return df\n",
    "\n",
    "def format_pivot(response):\n",
    "    try:\n",
    "        # extract table values\n",
    "        pivot_values = [item['metrics'][0]['pivotValueRegions'][0]['values'] for item in response['reports'][0]\n",
    "                        ['data']['rows']]\n",
    "        \n",
    "        # create column index\n",
    "        top_header = [item['dimensionValues'] for item in response['reports'][0]\n",
    "                      ['columnHeader']['metricHeader']['pivotHeaders'][0]['pivotHeaderEntries']]\n",
    "        column_metrics = [item['metric']['name'] for item in response['reports'][0]\n",
    "                          ['columnHeader']['metricHeader']['pivotHeaders'][0]['pivotHeaderEntries']]\n",
    "        array = np.concatenate((np.array(top_header),\n",
    "                                np.array(column_metrics).reshape((len(column_metrics),1))), \n",
    "                               axis = 1)\n",
    "        column_index = pd.MultiIndex.from_arrays(np.transpose(array))\n",
    "        \n",
    "        # create row index\n",
    "        try:\n",
    "            row_index_names = response['reports'][0]['columnHeader']['dimensions']\n",
    "            row_index = [ element['dimensions'] for element in response['reports'][0]['data']['rows'] ]\n",
    "            row_index_named = pd.MultiIndex.from_arrays(np.transpose(np.array(row_index)), \n",
    "                                                        names = np.array(row_index_names))\n",
    "        except: \n",
    "            row_index_named = None\n",
    "        # combine into a dataframe\n",
    "        df = pd.DataFrame(data = np.array(pivot_values), \n",
    "                          index = row_index_named, \n",
    "                          columns = column_index).astype('float')\n",
    "    except:\n",
    "        df = pd.DataFrame()\n",
    "    return df\n",
    "\n",
    "def format_report(response):\n",
    "    summary = format_summary(response)\n",
    "    pivot = format_pivot(response)\n",
    "    if pivot.columns.nlevels == 2:\n",
    "        summary.columns = [['']*len(summary.columns), summary.columns]\n",
    "    \n",
    "    return(pd.concat([summary, pivot], axis = 1))\n",
    "\n",
    "def run_report(body, credentials_file):\n",
    "    #Create service credentials\n",
    "    credentials = service_account.Credentials.from_service_account_file(credentials_file, \n",
    "                                scopes = ['https://www.googleapis.com/auth/analytics.readonly'])\n",
    "    #Create a service object\n",
    "    service = build('analyticsreporting', 'v4', credentials=credentials)\n",
    "    \n",
    "    #Get GA data\n",
    "    response = service.reports().batchGet(body=body).execute()\n",
    "    \n",
    "    return(format_report(response))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The report request is in dictionary/JSON format, and can have a Summary and Pivot section. The request must have a date range and metrics. View ID is the number in GA that identifies your site and the data view associated with it (immediately to the right of the Analytics logo on the top right in GA).   \n",
    "\n",
    "Credentials is the link to your service account key JSON file.\n",
    "\n",
    "Reference:\n",
    "Basics of creating reports: https://developers.google.com/analytics/devguides/reporting/core/v4/basics\n",
    "Dimensions and metrics: https://ga-dev-tools.appspot.com/dimensions-metrics-explorer/ "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "your_view_id = '00000000'\n",
    "ga_keys = 'api_keys.json'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "body = {'reportRequests': [{'viewId': your_view_id, \n",
    "                            'dateRanges': [{'startDate': '2021-01-01', 'endDate': '2021-04-30'}],\n",
    "                            'metrics': [{'expression': 'ga:users'}, \n",
    "                                        {\"expression\": \"ga:bounceRate\"}],\n",
    "                            'dimensions': [{'name': 'ga:yearMonth'}],\n",
    "                            \"pivots\": [{\"dimensions\": [{\"name\": \"ga:channelGrouping\"}],\n",
    "                                        \"metrics\": [{\"expression\": \"ga:users\"},\n",
    "                                                    {\"expression\": \"ga:bounceRate\"}]\n",
    "                                       }]\n",
    "                          }]}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "summary_body = {'reportRequests': [{'viewId': your_view_id, \n",
    "                            'dateRanges': [{'startDate': '2021-01-01', 'endDate': '2021-02-28'}],\n",
    "                            'metrics': [{'expression': 'ga:sessions'}, \n",
    "                                        {'expression': 'ga:totalEvents'}, \n",
    "                                        {\"expression\": \"ga:avgSessionDuration\"}],\n",
    "                            'dimensions': [{'name': 'ga:country'}],\n",
    "                          }]}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "pivot_body = {'reportRequests': [{'viewId': your_view_id, \n",
    "                            'dateRanges': [{'startDate': '2021-01-01', 'endDate': '2021-02-28'}],\n",
    "                            'dimensions': [{'name':  \"ga:channelGrouping\"}],\n",
    "                            \"pivots\": [{\"dimensions\": [{\"name\": 'ga:yearMonth'}],\n",
    "                                        \"metrics\": [{\"expression\": \"ga:users\"},\n",
    "                                                    {\"expression\": \"ga:newUsers\"},\n",
    "                                                    {\"expression\": \"ga:timeOnPage\"}]\n",
    "                                       }]\n",
    "                          }]}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "short_body = {  \"reportRequests\":\n",
    "  [{\n",
    "      \"viewId\": your_view_id,\n",
    "      \"dateRanges\": [{\"startDate\": \"7daysAgo\", \"endDate\": \"yesterday\"}],\n",
    "      \"metrics\": [{\"expression\": \"ga:users\"}]\n",
    "    }]}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "untidy_body = {'reportRequests': [{'viewId': your_view_id, \n",
    "                            'dateRanges': [{'startDate': '2021-01-01', 'endDate': '2021-02-28'}],\n",
    "                            \"pivots\": [{\"dimensions\": [{\"name\": 'ga:yearMonth'}, {\"name\": \"ga:channelGrouping\"}],\n",
    "                                        \"metrics\": [{\"expression\": \"ga:users\"},\n",
    "                                                    {\"expression\": \"ga:timeOnPage\"}]\n",
    "                                       }]\n",
    "                          }]}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Example of an output"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "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 tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"2\" halign=\"left\"></th>\n",
       "      <th colspan=\"2\" halign=\"left\">Organic Search</th>\n",
       "      <th colspan=\"2\" halign=\"left\">Direct</th>\n",
       "      <th colspan=\"2\" halign=\"left\">Social</th>\n",
       "      <th colspan=\"2\" halign=\"left\">Referral</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>ga:users</th>\n",
       "      <th>ga:bounceRate</th>\n",
       "      <th>ga:users</th>\n",
       "      <th>ga:bounceRate</th>\n",
       "      <th>ga:users</th>\n",
       "      <th>ga:bounceRate</th>\n",
       "      <th>ga:users</th>\n",
       "      <th>ga:bounceRate</th>\n",
       "      <th>ga:users</th>\n",
       "      <th>ga:bounceRate</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ga:yearMonth</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>202101</th>\n",
       "      <td>317.0</td>\n",
       "      <td>73.972603</td>\n",
       "      <td>195.0</td>\n",
       "      <td>78.205128</td>\n",
       "      <td>78.0</td>\n",
       "      <td>77.235772</td>\n",
       "      <td>42.0</td>\n",
       "      <td>58.904110</td>\n",
       "      <td>2.0</td>\n",
       "      <td>37.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202102</th>\n",
       "      <td>311.0</td>\n",
       "      <td>82.159624</td>\n",
       "      <td>254.0</td>\n",
       "      <td>85.585586</td>\n",
       "      <td>46.0</td>\n",
       "      <td>82.089552</td>\n",
       "      <td>6.0</td>\n",
       "      <td>33.333333</td>\n",
       "      <td>5.0</td>\n",
       "      <td>60.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202103</th>\n",
       "      <td>460.0</td>\n",
       "      <td>86.446886</td>\n",
       "      <td>383.0</td>\n",
       "      <td>87.772926</td>\n",
       "      <td>69.0</td>\n",
       "      <td>86.486486</td>\n",
       "      <td>3.0</td>\n",
       "      <td>22.222222</td>\n",
       "      <td>5.0</td>\n",
       "      <td>80.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202104</th>\n",
       "      <td>532.0</td>\n",
       "      <td>84.671533</td>\n",
       "      <td>411.0</td>\n",
       "      <td>87.927565</td>\n",
       "      <td>103.0</td>\n",
       "      <td>85.333333</td>\n",
       "      <td>9.0</td>\n",
       "      <td>28.571429</td>\n",
       "      <td>9.0</td>\n",
       "      <td>52.941176</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                    Organic Search                 Direct  \\\n",
       "             ga:users ga:bounceRate       ga:users ga:bounceRate ga:users   \n",
       "ga:yearMonth                                                                \n",
       "202101          317.0     73.972603          195.0     78.205128     78.0   \n",
       "202102          311.0     82.159624          254.0     85.585586     46.0   \n",
       "202103          460.0     86.446886          383.0     87.772926     69.0   \n",
       "202104          532.0     84.671533          411.0     87.927565    103.0   \n",
       "\n",
       "                             Social               Referral                \n",
       "             ga:bounceRate ga:users ga:bounceRate ga:users ga:bounceRate  \n",
       "ga:yearMonth                                                              \n",
       "202101           77.235772     42.0     58.904110      2.0     37.500000  \n",
       "202102           82.089552      6.0     33.333333      5.0     60.000000  \n",
       "202103           86.486486      3.0     22.222222      5.0     80.000000  \n",
       "202104           85.333333      9.0     28.571429      9.0     52.941176  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ga_report = run_report(body, ga_keys)\n",
    "ga_report"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Code Explanation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This section shows what the response looks like on the inside, and how the code gets to the data. This is for demonstration only. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'reports': [{'columnHeader': {'dimensions': ['ga:yearMonth'],\n",
       "    'metricHeader': {'metricHeaderEntries': [{'name': 'ga:users',\n",
       "       'type': 'INTEGER'},\n",
       "      {'name': 'ga:bounceRate', 'type': 'PERCENT'}],\n",
       "     'pivotHeaders': [{'pivotHeaderEntries': [{'dimensionNames': ['ga:channelGrouping'],\n",
       "         'dimensionValues': ['Organic Search'],\n",
       "         'metric': {'name': 'ga:users', 'type': 'INTEGER'}},\n",
       "        {'dimensionNames': ['ga:channelGrouping'],\n",
       "         'dimensionValues': ['Organic Search'],\n",
       "         'metric': {'name': 'ga:bounceRate', 'type': 'PERCENT'}},\n",
       "        {'dimensionNames': ['ga:channelGrouping'],\n",
       "         'dimensionValues': ['Direct'],\n",
       "         'metric': {'name': 'ga:users', 'type': 'INTEGER'}},\n",
       "        {'dimensionNames': ['ga:channelGrouping'],\n",
       "         'dimensionValues': ['Direct'],\n",
       "         'metric': {'name': 'ga:bounceRate', 'type': 'PERCENT'}},\n",
       "        {'dimensionNames': ['ga:channelGrouping'],\n",
       "         'dimensionValues': ['Social'],\n",
       "         'metric': {'name': 'ga:users', 'type': 'INTEGER'}},\n",
       "        {'dimensionNames': ['ga:channelGrouping'],\n",
       "         'dimensionValues': ['Social'],\n",
       "         'metric': {'name': 'ga:bounceRate', 'type': 'PERCENT'}},\n",
       "        {'dimensionNames': ['ga:channelGrouping'],\n",
       "         'dimensionValues': ['Referral'],\n",
       "         'metric': {'name': 'ga:users', 'type': 'INTEGER'}},\n",
       "        {'dimensionNames': ['ga:channelGrouping'],\n",
       "         'dimensionValues': ['Referral'],\n",
       "         'metric': {'name': 'ga:bounceRate', 'type': 'PERCENT'}}],\n",
       "       'totalPivotGroupsCount': 4}]}},\n",
       "   'data': {'rows': [{'dimensions': ['202101'],\n",
       "      'metrics': [{'values': ['317', '73.97260273972603'],\n",
       "        'pivotValueRegions': [{'values': ['195',\n",
       "           '78.2051282051282',\n",
       "           '78',\n",
       "           '77.23577235772358',\n",
       "           '42',\n",
       "           '58.9041095890411',\n",
       "           '2',\n",
       "           '37.5']}]}]},\n",
       "     {'dimensions': ['202102'],\n",
       "      'metrics': [{'values': ['311', '82.15962441314554'],\n",
       "        'pivotValueRegions': [{'values': ['254',\n",
       "           '85.58558558558559',\n",
       "           '46',\n",
       "           '82.08955223880598',\n",
       "           '6',\n",
       "           '33.33333333333333',\n",
       "           '5',\n",
       "           '60.0']}]}]},\n",
       "     {'dimensions': ['202103'],\n",
       "      'metrics': [{'values': ['460', '86.44688644688645'],\n",
       "        'pivotValueRegions': [{'values': ['383',\n",
       "           '87.77292576419214',\n",
       "           '69',\n",
       "           '86.48648648648648',\n",
       "           '3',\n",
       "           '22.22222222222222',\n",
       "           '5',\n",
       "           '80.0']}]}]},\n",
       "     {'dimensions': ['202104'],\n",
       "      'metrics': [{'values': ['532', '84.67153284671532'],\n",
       "        'pivotValueRegions': [{'values': ['411',\n",
       "           '87.92756539235413',\n",
       "           '103',\n",
       "           '85.33333333333334',\n",
       "           '9',\n",
       "           '28.57142857142857',\n",
       "           '9',\n",
       "           '52.94117647058824']}]}]}],\n",
       "    'totals': [{'values': ['1620', '82.38663484486874'],\n",
       "      'pivotValueRegions': [{'values': ['1243',\n",
       "         '85.87385019710906',\n",
       "         '296',\n",
       "         '82.6086956521739',\n",
       "         '60',\n",
       "         '46.774193548387096',\n",
       "         '21',\n",
       "         '54.285714285714285']}]}],\n",
       "    'rowCount': 4,\n",
       "    'minimums': [{'values': ['311', '73.97260273972603'],\n",
       "      'pivotValueRegions': [{'values': ['195',\n",
       "         '78.2051282051282',\n",
       "         '46',\n",
       "         '77.23577235772358',\n",
       "         '3',\n",
       "         '22.22222222222222',\n",
       "         '2',\n",
       "         '37.5']}]}],\n",
       "    'maximums': [{'values': ['532', '86.44688644688645'],\n",
       "      'pivotValueRegions': [{'values': ['411',\n",
       "         '87.92756539235413',\n",
       "         '103',\n",
       "         '86.48648648648648',\n",
       "         '42',\n",
       "         '58.9041095890411',\n",
       "         '9',\n",
       "         '80.0']}]}],\n",
       "    'isDataGolden': True}}]}"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "credentials = service_account.Credentials.from_service_account_file(ga_keys, \n",
    "                                scopes = ['https://www.googleapis.com/auth/analytics.readonly'])\n",
    "    #Create a service object\n",
    "service = build('analyticsreporting', 'v4', credentials=credentials)\n",
    "    \n",
    "    #Get GA data\n",
    "response = service.reports().batchGet(body=body).execute()\n",
    "response"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"2\" halign=\"left\">Organic Search</th>\n",
       "      <th colspan=\"2\" halign=\"left\">Direct</th>\n",
       "      <th colspan=\"2\" halign=\"left\">Social</th>\n",
       "      <th colspan=\"2\" halign=\"left\">Referral</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>ga:users</th>\n",
       "      <th>ga:bounceRate</th>\n",
       "      <th>ga:users</th>\n",
       "      <th>ga:bounceRate</th>\n",
       "      <th>ga:users</th>\n",
       "      <th>ga:bounceRate</th>\n",
       "      <th>ga:users</th>\n",
       "      <th>ga:bounceRate</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ga:yearMonth</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>202101</th>\n",
       "      <td>195.0</td>\n",
       "      <td>78.205128</td>\n",
       "      <td>78.0</td>\n",
       "      <td>77.235772</td>\n",
       "      <td>42.0</td>\n",
       "      <td>58.904110</td>\n",
       "      <td>2.0</td>\n",
       "      <td>37.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202102</th>\n",
       "      <td>254.0</td>\n",
       "      <td>85.585586</td>\n",
       "      <td>46.0</td>\n",
       "      <td>82.089552</td>\n",
       "      <td>6.0</td>\n",
       "      <td>33.333333</td>\n",
       "      <td>5.0</td>\n",
       "      <td>60.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202103</th>\n",
       "      <td>383.0</td>\n",
       "      <td>87.772926</td>\n",
       "      <td>69.0</td>\n",
       "      <td>86.486486</td>\n",
       "      <td>3.0</td>\n",
       "      <td>22.222222</td>\n",
       "      <td>5.0</td>\n",
       "      <td>80.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202104</th>\n",
       "      <td>411.0</td>\n",
       "      <td>87.927565</td>\n",
       "      <td>103.0</td>\n",
       "      <td>85.333333</td>\n",
       "      <td>9.0</td>\n",
       "      <td>28.571429</td>\n",
       "      <td>9.0</td>\n",
       "      <td>52.941176</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Organic Search                 Direct                 Social  \\\n",
       "                   ga:users ga:bounceRate ga:users ga:bounceRate ga:users   \n",
       "ga:yearMonth                                                                \n",
       "202101                195.0     78.205128     78.0     77.235772     42.0   \n",
       "202102                254.0     85.585586     46.0     82.089552      6.0   \n",
       "202103                383.0     87.772926     69.0     86.486486      3.0   \n",
       "202104                411.0     87.927565    103.0     85.333333      9.0   \n",
       "\n",
       "                           Referral                \n",
       "             ga:bounceRate ga:users ga:bounceRate  \n",
       "ga:yearMonth                                       \n",
       "202101           58.904110      2.0     37.500000  \n",
       "202102           33.333333      5.0     60.000000  \n",
       "202103           22.222222      5.0     80.000000  \n",
       "202104           28.571429      9.0     52.941176  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "format_pivot(response)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "MultiIndex([('Organic Search',      'ga:users'),\n",
       "            ('Organic Search', 'ga:bounceRate'),\n",
       "            (        'Direct',      'ga:users'),\n",
       "            (        'Direct', 'ga:bounceRate'),\n",
       "            (        'Social',      'ga:users'),\n",
       "            (        'Social', 'ga:bounceRate'),\n",
       "            (      'Referral',      'ga:users'),\n",
       "            (      'Referral', 'ga:bounceRate')],\n",
       "           )"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top_header = [item['dimensionValues'] for item in response['reports'][0]\n",
    "                      ['columnHeader']['metricHeader']['pivotHeaders'][0]['pivotHeaderEntries']]\n",
    "column_metrics = [item['metric']['name'] for item in response['reports'][0]\n",
    "                          ['columnHeader']['metricHeader']['pivotHeaders'][0]['pivotHeaderEntries']]\n",
    "array = np.concatenate((np.array(top_header),\n",
    "                        np.array(column_metrics).reshape((len(column_metrics),1))),\n",
    "                       axis = 1)\n",
    "column_index = pd.MultiIndex.from_arrays(np.transpose(array))\n",
    "column_index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[['Organic Search'],\n",
       " ['Organic Search'],\n",
       " ['Direct'],\n",
       " ['Direct'],\n",
       " ['Social'],\n",
       " ['Social'],\n",
       " ['Referral'],\n",
       " ['Referral']]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[item.get('dimensionValues') for item in response['reports'][0]['columnHeader']['metricHeader']['pivotHeaders'][0]['pivotHeaderEntries']]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualization Example No 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "body = body = {'reportRequests': [{'viewId': your_view_id, \n",
    "                            'dateRanges': [{'startDate': '2021-01-01', 'endDate': '2021-04-30'}],\n",
    "                            'metrics': [{'expression': 'ga:users'}], \n",
    "                            'dimensions': [{'name': 'ga:yearMonth'}],\n",
    "                            \"pivots\": [{\"dimensions\": [{\"name\": \"ga:channelGrouping\"}],\n",
    "                                        \"metrics\": [{\"expression\": \"ga:users\"},\n",
    "                                                    {\"expression\": \"ga:bounceRate\"}]\n",
    "                                       }]\n",
    "                          }]}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "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 tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th colspan=\"2\" halign=\"left\">Organic Search</th>\n",
       "      <th colspan=\"2\" halign=\"left\">Direct</th>\n",
       "      <th colspan=\"2\" halign=\"left\">Social</th>\n",
       "      <th colspan=\"2\" halign=\"left\">Referral</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>ga:users</th>\n",
       "      <th>ga:users</th>\n",
       "      <th>ga:bounceRate</th>\n",
       "      <th>ga:users</th>\n",
       "      <th>ga:bounceRate</th>\n",
       "      <th>ga:users</th>\n",
       "      <th>ga:bounceRate</th>\n",
       "      <th>ga:users</th>\n",
       "      <th>ga:bounceRate</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ga:yearMonth</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>202101</th>\n",
       "      <td>317.0</td>\n",
       "      <td>195.0</td>\n",
       "      <td>78.205128</td>\n",
       "      <td>78.0</td>\n",
       "      <td>77.235772</td>\n",
       "      <td>42.0</td>\n",
       "      <td>58.904110</td>\n",
       "      <td>2.0</td>\n",
       "      <td>37.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202102</th>\n",
       "      <td>311.0</td>\n",
       "      <td>254.0</td>\n",
       "      <td>85.585586</td>\n",
       "      <td>46.0</td>\n",
       "      <td>82.089552</td>\n",
       "      <td>6.0</td>\n",
       "      <td>33.333333</td>\n",
       "      <td>5.0</td>\n",
       "      <td>60.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202103</th>\n",
       "      <td>460.0</td>\n",
       "      <td>383.0</td>\n",
       "      <td>87.772926</td>\n",
       "      <td>69.0</td>\n",
       "      <td>86.486486</td>\n",
       "      <td>3.0</td>\n",
       "      <td>22.222222</td>\n",
       "      <td>5.0</td>\n",
       "      <td>80.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202104</th>\n",
       "      <td>532.0</td>\n",
       "      <td>411.0</td>\n",
       "      <td>87.927565</td>\n",
       "      <td>103.0</td>\n",
       "      <td>85.333333</td>\n",
       "      <td>9.0</td>\n",
       "      <td>28.571429</td>\n",
       "      <td>9.0</td>\n",
       "      <td>52.941176</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      Organic Search                 Direct                \\\n",
       "             ga:users       ga:users ga:bounceRate ga:users ga:bounceRate   \n",
       "ga:yearMonth                                                                \n",
       "202101          317.0          195.0     78.205128     78.0     77.235772   \n",
       "202102          311.0          254.0     85.585586     46.0     82.089552   \n",
       "202103          460.0          383.0     87.772926     69.0     86.486486   \n",
       "202104          532.0          411.0     87.927565    103.0     85.333333   \n",
       "\n",
       "               Social               Referral                \n",
       "             ga:users ga:bounceRate ga:users ga:bounceRate  \n",
       "ga:yearMonth                                                \n",
       "202101           42.0     58.904110      2.0     37.500000  \n",
       "202102            6.0     33.333333      5.0     60.000000  \n",
       "202103            3.0     22.222222      5.0     80.000000  \n",
       "202104            9.0     28.571429      9.0     52.941176  "
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "report = run_report(body, ga_keys)\n",
    "report"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "# set seaborn style\n",
    "sns.set_theme()\n",
    "sns.set(rc={'figure.figsize':(8,6)})\n",
    "\n",
    "plot_data = report.loc[:, (slice(None), \"ga:users\")].iloc[:, 1:] # Pick users columns, drop the first one (sum)\n",
    "plot_data.columns = plot_data.columns.get_level_values(0)\n",
    "plot_data.index = plot_data.index.get_level_values(0)\n",
    "plot_data.plot.bar(stacked = True);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "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>Organic Search</th>\n",
       "      <th>Direct</th>\n",
       "      <th>Social</th>\n",
       "      <th>Referral</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ga:yearMonth</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>202101</th>\n",
       "      <td>195.0</td>\n",
       "      <td>78.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202102</th>\n",
       "      <td>254.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202103</th>\n",
       "      <td>383.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202104</th>\n",
       "      <td>411.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Organic Search  Direct  Social  Referral\n",
       "ga:yearMonth                                          \n",
       "202101                 195.0    78.0    42.0       2.0\n",
       "202102                 254.0    46.0     6.0       5.0\n",
       "202103                 383.0    69.0     3.0       5.0\n",
       "202104                 411.0   103.0     9.0       9.0"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plot_data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualization Example No 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "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>ga:date</th>\n",
       "      <th>ga:channelGrouping</th>\n",
       "      <th>ga:sessions</th>\n",
       "      <th>ga:avgSessionDuration</th>\n",
       "      <th>ga:users</th>\n",
       "      <th>ga:newUsers</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>20210101</td>\n",
       "      <td>Direct</td>\n",
       "      <td>2.0</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>20210101</td>\n",
       "      <td>Organic Search</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1074.400000</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>20210102</td>\n",
       "      <td>Direct</td>\n",
       "      <td>1.0</td>\n",
       "      <td>244.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>20210102</td>\n",
       "      <td>Organic Search</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1082.666667</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>20210103</td>\n",
       "      <td>Direct</td>\n",
       "      <td>2.0</td>\n",
       "      <td>37.500000</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>300</th>\n",
       "      <td>20210429</td>\n",
       "      <td>Organic Search</td>\n",
       "      <td>14.0</td>\n",
       "      <td>15.071429</td>\n",
       "      <td>13.0</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>301</th>\n",
       "      <td>20210429</td>\n",
       "      <td>Referral</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>302</th>\n",
       "      <td>20210429</td>\n",
       "      <td>Social</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>303</th>\n",
       "      <td>20210430</td>\n",
       "      <td>Direct</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>304</th>\n",
       "      <td>20210430</td>\n",
       "      <td>Organic Search</td>\n",
       "      <td>18.0</td>\n",
       "      <td>24.666667</td>\n",
       "      <td>15.0</td>\n",
       "      <td>13.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>305 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      ga:date ga:channelGrouping  ga:sessions  ga:avgSessionDuration  \\\n",
       "0    20210101             Direct          2.0              20.000000   \n",
       "1    20210101     Organic Search          5.0            1074.400000   \n",
       "2    20210102             Direct          1.0             244.000000   \n",
       "3    20210102     Organic Search          3.0            1082.666667   \n",
       "4    20210103             Direct          2.0              37.500000   \n",
       "..        ...                ...          ...                    ...   \n",
       "300  20210429     Organic Search         14.0              15.071429   \n",
       "301  20210429           Referral          1.0               0.000000   \n",
       "302  20210429             Social          1.0               0.000000   \n",
       "303  20210430             Direct          3.0               0.000000   \n",
       "304  20210430     Organic Search         18.0              24.666667   \n",
       "\n",
       "     ga:users  ga:newUsers  \n",
       "0         2.0          2.0  \n",
       "1         3.0          1.0  \n",
       "2         1.0          1.0  \n",
       "3         3.0          1.0  \n",
       "4         2.0          1.0  \n",
       "..        ...          ...  \n",
       "300      13.0          8.0  \n",
       "301       1.0          0.0  \n",
       "302       1.0          0.0  \n",
       "303       3.0          2.0  \n",
       "304      15.0         13.0  \n",
       "\n",
       "[305 rows x 6 columns]"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "body = body = {'reportRequests': [{'viewId': your_view_id, \n",
    "                            'dateRanges': [{'startDate': '2021-01-01', 'endDate': '2021-04-30'}],\n",
    "                            'metrics': [{'expression': 'ga:sessions'},\n",
    "                                        {\"expression\": \"ga:avgSessionDuration\"},\n",
    "                                        {\"expression\": \"ga:users\"},\n",
    "                                        {\"expression\": \"ga:newUsers\"}],\n",
    "                            'dimensions': [{'name': 'ga:date'},\n",
    "                                           {\"name\": \"ga:channelGrouping\"}],\n",
    "                          }]}\n",
    "\n",
    "report = run_report(body, ga_keys).reset_index() # index is turned into columns to help with visualization\n",
    "report"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set(rc={'figure.figsize':(12,8)})\n",
    "plot_data = report.loc[:, [\"ga:users\"]]\n",
    "sns.lineplot(data = report, y = \"ga:sessions\", x = 'ga:date', hue = 'ga:channelGrouping');"
   ]
  }
 ],
 "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": "3.7.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}