Google Analytics/Google_Analytics_Follow_number_of_sessions_hourly.ipynb

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   "source": [
    "<img width=\"8%\" alt=\"Google Analytics.png\" src=\"https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/.github/assets/logos/Google%20Analytics.png\" style=\"border-radius: 15%\">"
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   "source": [
    "# Google Analytics - Follow number of sessions hourly\n",
    "<a href=\"https://bit.ly/3JyWIk6\">Give Feedback</a> | <a href=\"https://github.com/jupyter-naas/awesome-notebooks/issues/new?assignees=&labels=bug&template=bug_report.md&title=Google+Analytics+-+Follow+number+of+sessions+hourly:+Error+short+description\">Bug report</a>"
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  {
   "cell_type": "markdown",
   "id": "19875963",
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   "source": [
    "**Tags:** #googleanalytics #analytics #marketing #csv #html #plotly #image #png"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "29814b06-df6a-4be0-9b98-a9a523e2f98b",
   "metadata": {
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    "tags": []
   },
   "source": [
    "**Author:** [Florent Ravenel](https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/)"
   ]
  },
  {
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   "source": [
    "**Last update:** 2023-04-12 (Created: 2022-05-31)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "naas-description",
   "metadata": {
    "papermill": {},
    "tags": [
     "description"
    ]
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   "source": [
    "**Description:** This notebook tracks the number of sessions on Google Analytics over the course of an hour."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "55f800df",
   "metadata": {
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    "tags": []
   },
   "source": [
    "## Input"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3f24ee2c",
   "metadata": {
    "papermill": {},
    "tags": []
   },
   "source": [
    "### Import library"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "b2586bcc",
   "metadata": {
    "papermill": {},
    "tags": []
   },
   "outputs": [],
   "source": [
    "import plotly.graph_objects as go\n",
    "import naas\n",
    "import datetime\n",
    "import pandas as pd\n",
    "from naas_drivers import googleanalytics"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8f103e30",
   "metadata": {
    "papermill": {},
    "tags": []
   },
   "source": [
    "### Setup Google Analytics"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7e6ef3e1",
   "metadata": {
    "papermill": {},
    "tags": []
   },
   "source": [
    "👉 Create your own <a href=\"\">Google API JSON credential</a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "04c24e42",
   "metadata": {
    "papermill": {},
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Get your credential from Google Cloud Platform\n",
    "json_path = \"naas-googleanalytics.json\"\n",
    "\n",
    "# Get view id from google analytics\n",
    "view_id = \"228952707\"\n",
    "\n",
    "# Setup your data parameters\n",
    "dimensions = \"hourly\"  # hourly, daily, weekly, monthly\n",
    "start_date = \"7daysAgo\"  # XdaysAgo or date in ISO format %Y-%m-%d\n",
    "end_date = \"today\"  # Today or date in ISO format %Y-%m-%d"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cd3830c6-1c09-4b7a-95bf-a8d9159759ff",
   "metadata": {
    "papermill": {},
    "tags": []
   },
   "source": [
    "### Setup Outputs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "092e3e2e-194a-497e-b824-94077a33da83",
   "metadata": {
    "papermill": {},
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Chart title\n",
    "title = \"Sessions\"\n",
    "\n",
    "# Outputs path\n",
    "name_output = f\"Google_Analytics_sessions_{dimensions}\"\n",
    "csv_output = f\"{name_output}.csv\"\n",
    "image_output = f\"{name_output}.png\"\n",
    "html_output = f\"{name_output}.html\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3729685f-abab-4f5e-919f-3b07ce841f1c",
   "metadata": {
    "papermill": {},
    "tags": []
   },
   "source": [
    "## Model"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d08332b2",
   "metadata": {
    "papermill": {},
    "tags": []
   },
   "source": [
    "### Get trend"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "461de2bd-27c7-4d88-bbb6-63c517ab0cc8",
   "metadata": {
    "papermill": {},
    "tags": []
   },
   "outputs": [],
   "source": [
    "df = googleanalytics.connect(json_path, view_id).sessions.get_trend(\n",
    "    dimensions, start_date, end_date\n",
    ")\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "df5aee5b",
   "metadata": {
    "papermill": {},
    "tags": []
   },
   "source": [
    "### Plotting linechart"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "bdd79b47-c8bb-467a-812d-f6d0a6c85a9d",
   "metadata": {
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   "outputs": [],
   "source": [
    "def create_linechart(df: pd.DataFrame, label, value, varv, varp, title):\n",
    "    \"\"\"\n",
    "    Plot linechart as an area chart in Plotly.\n",
    "    \"\"\"\n",
    "    # Prep data\n",
    "    df[\"VALUE_D\"] = df[value].map(\"{:,.0f}\".format).str.replace(\",\", \" \")\n",
    "    df[\"VARV_D\"] = df[varv].map(\"{:,.0f}\".format).str.replace(\",\", \" \")\n",
    "    df.loc[df[varv] > 0, \"VARV_D\"] = \"+\" + df[\"VARV_D\"]\n",
    "    df[\"VARP_D\"] = df[varp].map(\"{:,.0%}\".format).str.replace(\",\", \" \")\n",
    "    df.loc[df[varp] > 0, \"VARP_D\"] = \"+\" + df[\"VARP_D\"]\n",
    "\n",
    "    # Create hovertext\n",
    "    df[\"TEXT\"] = (\n",
    "        f\"<b>{title} as of \"\n",
    "        + df[label].astype(str)\n",
    "        + \" : \"\n",
    "        + df[\"VALUE_D\"]\n",
    "        + \"</b><br><span style='font-size: 13px;'>\"\n",
    "        + df[\"VARP_D\"]\n",
    "        + \" vs last value (\"\n",
    "        + df[\"VARV_D\"]\n",
    "        + \")</span>\"\n",
    "    )\n",
    "\n",
    "    # Get subtitle\n",
    "    title_display = df.loc[df.index[-1], \"TEXT\"]\n",
    "\n",
    "    # Create data\n",
    "    data = go.Scatter(\n",
    "        x=df[label],\n",
    "        y=df[value],\n",
    "        stackgroup=\"one\",\n",
    "        text=df[\"TEXT\"],\n",
    "        hoverinfo=\"text\",\n",
    "    )\n",
    "\n",
    "    # Create layout\n",
    "    layout = go.Layout(\n",
    "        title=title_display,\n",
    "        title_font=dict(family=\"Arial\", size=18, color=\"black\"),\n",
    "        plot_bgcolor=\"#ffffff\",\n",
    "        width=1200,\n",
    "        height=800,\n",
    "        margin_pad=10,\n",
    "    )\n",
    "    fig = go.Figure(data=data, layout=layout)\n",
    "    fig.update_traces(mode=\"lines+markers\")\n",
    "    return fig\n",
    "\n",
    "\n",
    "fig = create_linechart(df, \"DATE\", \"VALUE\", \"VARV\", \"VARP\", title)\n",
    "fig"
   ]
  },
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    "execution": {
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    "papermill": {},
    "tags": []
   },
   "source": [
    "## Output"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7f31f2d2-f301-42dd-8205-00dd34b85fa6",
   "metadata": {
    "papermill": {},
    "tags": []
   },
   "source": [
    "### Save and share csv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bd52dd6c-e915-4025-9a67-2aed83ab9c9f",
   "metadata": {
    "papermill": {},
    "tags": []
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   "outputs": [],
   "source": [
    "df.to_csv(csv_output, index=False)\n",
    "\n",
    "# Share with naas\n",
    "# -> Uncomment the line below (by removing the hashtag) to share your asset with naas\n",
    "# naas.asset.add(csv_output)\n",
    "\n",
    "# -> Uncomment the line below (by removing the hashtag)  to delete your asset\n",
    "# naas.asset.delete(csv_output)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "73cd9e78-7589-48c3-bf10-90598f54693a",
   "metadata": {
    "papermill": {},
    "tags": []
   },
   "source": [
    "### Export and share graph in HTML"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4913d04d-ef6e-48d5-8414-f017bbf52a38",
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   "outputs": [],
   "source": [
    "fig.write_html(html_output)\n",
    "\n",
    "# Share with naas\n",
    "# -> Uncomment the line below (by removing the hashtag) to share your asset with naas\n",
    "# naas.asset.add(html_output, params={\"inline\": True})\n",
    "\n",
    "# -> Uncomment the line below (by removing the hashtag)  to delete your asset\n",
    "# naas.asset.delete(html_output)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ce2768ac-29f1-4c67-8047-cdd15919f785",
   "metadata": {
    "papermill": {},
    "tags": []
   },
   "source": [
    "### Export and share graph in PNG"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d3c87ec1-50be-423c-ad88-230042dca22f",
   "metadata": {
    "papermill": {},
    "tags": []
   },
   "outputs": [],
   "source": [
    "fig.write_image(image_output)\n",
    "\n",
    "# Share with naas\n",
    "# -> Uncomment the line below (by removing the hashtag) to share your asset with naas\n",
    "# naas.asset.add(image_output)\n",
    "\n",
    "# -> Uncomment the line below (by removing the hashtag)  to delete your asset\n",
    "# naas.asset.delete(image_output)"
   ]
  }
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