Queries.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7b6622d0-f64d-44a8-96ce-288e84ab7928",
   "metadata": {},
   "outputs": [],
   "source": [
    "!pip install google-cloud-bigquery==1.25.0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "15304d35-c9ad-4c73-b905-454b6d35b94f",
   "metadata": {},
   "outputs": [],
   "source": [
    "!pip install --upgrade google-cloud-bigquery-storage"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "9273a939-8cdb-4734-bd9f-7ecec3cc3b71",
   "metadata": {},
   "outputs": [],
   "source": [
    "from google.cloud import bigquery\n",
    "client = bigquery.Client()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4e051ff1-3822-4e70-97a0-cc040a3009f5",
   "metadata": {},
   "source": [
    "# Percentage of Purchasers versus Non-Purchasers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "cbd66e27-452d-4bb4-9c18-20fb3b82df97",
   "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>all_visitors</th>\n",
       "      <th>all_purchasers</th>\n",
       "      <th>all_non_purchasers</th>\n",
       "      <th>purchasers_per</th>\n",
       "      <th>non_purchasers_per</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>714167</td>\n",
       "      <td>10022</td>\n",
       "      <td>710928</td>\n",
       "      <td>0.014033</td>\n",
       "      <td>0.995465</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   all_visitors  all_purchasers  all_non_purchasers  purchasers_per  \\\n",
       "0        714167           10022              710928        0.014033   \n",
       "\n",
       "   non_purchasers_per  \n",
       "0            0.995465  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sql = \"\"\"\n",
    "    WITH \n",
    "    unique_visitors AS (\n",
    "    SELECT COUNT(DISTINCT fullVisitorId) AS all_visitors\n",
    "    FROM `bigquery-public-data.google_analytics_sample.ga_sessions_*`\n",
    "    ),\n",
    "    purchasers AS (\n",
    "    SELECT COUNT(DISTINCT fullVisitorId) AS all_purchasers\n",
    "    FROM `bigquery-public-data.google_analytics_sample.ga_sessions_*`\n",
    "    WHERE totals.transactions IS NOT NULL\n",
    "    ),\n",
    "    non_purchasers AS (\n",
    "    SELECT COUNT(DISTINCT fullVisitorId) AS all_non_purchasers\n",
    "    FROM `bigquery-public-data.google_analytics_sample.ga_sessions_*`\n",
    "    WHERE totals.transactions IS NULL\n",
    "    )\n",
    "    SELECT\n",
    "      all_visitors,\n",
    "      all_purchasers,\n",
    "      all_non_purchasers,\n",
    "      all_purchasers / all_visitors AS purchasers_per,\n",
    "      all_non_purchasers / all_visitors AS non_purchasers_per\n",
    "    FROM unique_visitors, purchasers, non_purchasers;\n",
    "\"\"\"\n",
    "df_purchasers = client.query(sql).to_dataframe()\n",
    "df_purchasers"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9fec6b47-68fe-47e6-a190-2bd774853ccd",
   "metadata": {},
   "source": [
    "# Top 10 Products by Revenue"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "16e87cc1-cd3c-4412-9cb2-d54739eb9687",
   "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>product_name</th>\n",
       "      <th>qty_sold</th>\n",
       "      <th>product_revenue</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Google Men's  Zip Hoodie</td>\n",
       "      <td>6116</td>\n",
       "      <td>47636.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>26 oz Double Wall Insulated Bottle</td>\n",
       "      <td>12963</td>\n",
       "      <td>44454.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Google 22 oz Water Bottle</td>\n",
       "      <td>87090</td>\n",
       "      <td>42995.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Leatherette Journal</td>\n",
       "      <td>22495</td>\n",
       "      <td>38563.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Google Sunglasses</td>\n",
       "      <td>73908</td>\n",
       "      <td>35490.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Google Metallic Notebook Set</td>\n",
       "      <td>33307</td>\n",
       "      <td>28847.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Google Men's 100% Cotton Short Sleeve Hero Tee...</td>\n",
       "      <td>11257</td>\n",
       "      <td>28048.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Recycled Paper Journal Set</td>\n",
       "      <td>40565</td>\n",
       "      <td>27918.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Google Men's 100% Cotton Short Sleeve Hero Tee...</td>\n",
       "      <td>14292</td>\n",
       "      <td>27856.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Google Hard Cover Journal</td>\n",
       "      <td>13267</td>\n",
       "      <td>25433.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                        product_name  qty_sold  \\\n",
       "0                           Google Men's  Zip Hoodie      6116   \n",
       "1                 26 oz Double Wall Insulated Bottle     12963   \n",
       "2                          Google 22 oz Water Bottle     87090   \n",
       "3                                Leatherette Journal     22495   \n",
       "4                                  Google Sunglasses     73908   \n",
       "5                       Google Metallic Notebook Set     33307   \n",
       "6  Google Men's 100% Cotton Short Sleeve Hero Tee...     11257   \n",
       "7                         Recycled Paper Journal Set     40565   \n",
       "8  Google Men's 100% Cotton Short Sleeve Hero Tee...     14292   \n",
       "9                          Google Hard Cover Journal     13267   \n",
       "\n",
       "   product_revenue  \n",
       "0          47636.0  \n",
       "1          44454.0  \n",
       "2          42995.0  \n",
       "3          38563.0  \n",
       "4          35490.0  \n",
       "5          28847.0  \n",
       "6          28048.0  \n",
       "7          27918.0  \n",
       "8          27856.0  \n",
       "9          25433.0  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sql = \"\"\"\n",
    "    SELECT P.v2ProductName AS product_name,\n",
    "      SUM(P.productQuantity) AS qty_sold,\n",
    "      ROUND(SUM(P.localProductRevenue/1000000), 0) AS product_revenue\n",
    "    FROM `bigquery-public-data.google_analytics_sample.ga_sessions_*`,\n",
    "    UNNEST (hits) as H,\n",
    "    UNNEST (H.product) as P\n",
    "    GROUP BY product_name\n",
    "    ORDER BY product_revenue DESC\n",
    "    LIMIT 10\n",
    "\"\"\"\n",
    "df_products = client.query(sql).to_dataframe()\n",
    "df_products"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "f0f423da-678c-4211-a8e4-3e60556745eb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='product_name'>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1500x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "p_products = df_products.pivot(index='product_name', columns='product_revenue', values='product_revenue')\n",
    "p_products.plot(kind='bar', stacked=True, figsize=(15, 7))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "92dc1224-3040-4e4c-aabf-5d93c62292a8",
   "metadata": {},
   "source": [
    "# Top 10 Countries by Visitors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "ab683752-5923-41b9-95c1-a38682613fad",
   "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>unique_visitors</th>\n",
       "      <th>country</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>251830</td>\n",
       "      <td>United States</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>45289</td>\n",
       "      <td>India</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>31653</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>23332</td>\n",
       "      <td>Vietnam</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>19356</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>19153</td>\n",
       "      <td>Turkey</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>18792</td>\n",
       "      <td>Thailand</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>17963</td>\n",
       "      <td>Brazil</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>17069</td>\n",
       "      <td>Germany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>16041</td>\n",
       "      <td>Japan</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   unique_visitors         country\n",
       "0           251830   United States\n",
       "1            45289           India\n",
       "2            31653  United Kingdom\n",
       "3            23332         Vietnam\n",
       "4            19356          Canada\n",
       "5            19153          Turkey\n",
       "6            18792        Thailand\n",
       "7            17963          Brazil\n",
       "8            17069         Germany\n",
       "9            16041           Japan"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sql = \"\"\"\n",
    "    SELECT\n",
    "        COUNT(DISTINCT fullVisitorId) AS unique_visitors,\n",
    "        IFNULL(geoNetwork.country, \"\") AS country\n",
    "    FROM `bigquery-public-data.google_analytics_sample.ga_sessions_*`\n",
    "    GROUP BY country\n",
    "    ORDER BY unique_visitors DESC\n",
    "    Limit 10\n",
    "\"\"\"\n",
    "df_countries = client.query(sql).to_dataframe()\n",
    "df_countries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "243ca651-796b-4107-953e-3a128bb79c57",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='country'>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "p_countries = df_countries.pivot(index='country', columns='unique_visitors', values='unique_visitors')\n",
    "p_countries.plot(kind='bar', stacked=True, figsize=(15, 7))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b1ceaa1b-d538-4257-90ca-daebb216d479",
   "metadata": {},
   "source": [
    "# Visitors by Channel Grouping"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "6d870b20-a249-4eb5-bb6d-1446f109768f",
   "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>unique_visitors</th>\n",
       "      <th>channel</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>212374</td>\n",
       "      <td>Social</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>65661</td>\n",
       "      <td>Referral</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>18702</td>\n",
       "      <td>Paid Search</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>311607</td>\n",
       "      <td>Organic Search</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4103</td>\n",
       "      <td>Display</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>109830</td>\n",
       "      <td>Direct</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>13400</td>\n",
       "      <td>Affiliates</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>90</td>\n",
       "      <td>(Other)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   unique_visitors         channel\n",
       "0           212374          Social\n",
       "1            65661        Referral\n",
       "2            18702     Paid Search\n",
       "3           311607  Organic Search\n",
       "4             4103         Display\n",
       "5           109830          Direct\n",
       "6            13400      Affiliates\n",
       "7               90         (Other)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sql = \"\"\"\n",
    "    SELECT\n",
    "      COUNT(DISTINCT fullVisitorId) AS unique_visitors,\n",
    "      channelGrouping AS channel\n",
    "    FROM `bigquery-public-data.google_analytics_sample.ga_sessions_*`\n",
    "    GROUP BY channel\n",
    "    ORDER BY channel DESC\n",
    "\"\"\"\n",
    "df_channel = client.query(sql).to_dataframe()\n",
    "df_channel"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "a00a3bfb-cf05-4654-bbd9-b507e29c971d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='channel'>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "p_channel = df_channel.pivot(index='channel', columns='unique_visitors', values='unique_visitors')\n",
    "p_channel.plot(kind='bar', stacked=True, figsize=(15, 7))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ed28cc82-95bf-4af7-81cb-ff0d8ead0491",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "environment": {
   "kernel": "python3",
   "name": "common-cpu.m104",
   "type": "gcloud",
   "uri": "gcr.io/deeplearning-platform-release/base-cpu:m104"
  },
  "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": "3.7.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}