docs/pages/tools/notebooks/Astra_Kaskada_Customer_Retention_AwesomeAstra.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 5,
  "metadata": {
    "kernelspec": {
      "display_name": "Python 3 (ipykernel)",
      "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": "3.9.5"
    },
    "colab": {
      "provenance": [],
      "collapsed_sections": [
        "a0d10uDMpYOd",
        "6924ca3e-28b3-4f93-b0cf-5f8afddc11d8",
        "936700a9-e042-401c-9156-7bb18652e109",
        "08f5921d-36dc-41d1-a2a6-ae800b7a11de"
      ],
      "toc_visible": true
    },
    "gpuClass": "standard"
  },
  "cells": [
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "N1WZz8Annop-"
      },
      "id": "N1WZz8Annop-",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5a20a51f"
      },
      "source": [
        "# Astra + Kaskada Demo\n",
        "## Let's use a common ML challenge: Customer Retention. \n",
        "\n",
        "Companies collect massive amounts of data using platforms like Splunk, Heap, Segment, or even basic event logs describing user behavior. How can you use this data to predict user retention, revenue targets, and identify which customers are likely to be the most successful?\n",
        "\n",
        "Then how do we make that information available to the customer success reps to attempt to save accounts, to sales reps to help predict if a new customer might be successful, and to revenue leaders to predict quarterly and annual revenue targets.\n",
        "\n",
        "**Note**: Due to the terms and conditions by which the data used in this notebook is made avaialble, anyone interested in recreating this work will need to download the data and agree to the terms and conditions of this Kaggle [research prediction competition](https://www.kaggle.com/c/kkbox-churn-prediction-challenge/data). "
      ],
      "id": "5a20a51f"
    },
    {
      "cell_type": "markdown",
      "source": [
        "#Step 1: Load data into Kaskada from Astra or Cassandra\n",
        "\n",
        "The diagram below shows how data can be added from AstraDB or Astra Streaming to the Member and Transaction table in Kakaskada."
      ],
      "metadata": {
        "id": "ELUSO3HiFIrM"
      },
      "id": "ELUSO3HiFIrM"
    },
    {
      "cell_type": "markdown",
      "source": [
        "![image.png](data:image/png;base64,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)"
      ],
      "metadata": {
        "id": "2sEpSTfJaB1W"
      },
      "id": "2sEpSTfJaB1W"
    },
    {
      "cell_type": "code",
      "source": [
        "from kaskada import table\n",
        "table.list_tables()"
      ],
      "metadata": {
        "id": "FHuhSXO_SXkk",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 216
        },
        "outputId": "d79a8a86-483c-47c8-c7f0-e1ec6747744c"
      },
      "id": "FHuhSXO_SXkk",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "<style>table.kda_table {\n",
              "    border: 1px solid grey !important;\n",
              "    border-collapse: collapse !important;\n",
              "    border-spacing: 0 !important;\n",
              "    font-size: 14px !important;\n",
              "    margin-bottom: 6px !important;\n",
              "}\n",
              "\n",
              "table.kda_table table {\n",
              "    margin-bottom: 0 !important;\n",
              "}\n",
              "\n",
              ".kda_table td, .kda_table th {\n",
              "    border: 1px solid grey !important;\n",
              "    border-collapse: collapse !important;\n",
              "    padding: 6px !important;\n",
              "    text-align: left !important;\n",
              "    vertical-align: top !important;\n",
              "}\n",
              "\n",
              ".kda_table tr {\n",
              "    background-color: inherit !important;\n",
              "}\n",
              "\n",
              "/* Style the tab */\n",
              ".kda_tab {\n",
              "    overflow: hidden;\n",
              "    border-bottom: 1px solid grey;\n",
              "    background-color: inherit;\n",
              "}\n",
              "\n",
              "/* Style the buttons that are used to open the tab content */\n",
              ".kda_tab button {\n",
              "    background-color: inherit;\n",
              "    border-top: 1px solid grey;\n",
              "    border-right: 1px solid grey;\n",
              "    border-left: 1px solid grey;\n",
              "    border-bottom: none;\n",
              "    border-radius: 5px 5px 0px 0px;\n",
              "    color: inherit;\n",
              "    cursor: pointer;\n",
              "    float: left;\n",
              "    margin: 2px 8px 0px 2px;\n",
              "    outline: none;\n",
              "    padding: 5px 16px;\n",
              "    transition: 0.3s;\n",
              "}\n",
              "\n",
              "/* Change background color of buttons on hover */\n",
              ".kda_tab button:hover {\n",
              "    background-color: grey;\n",
              "}\n",
              "\n",
              "/* Create an active/current tablink class */\n",
              ".kda_tab button.kda_active {\n",
              "    outline: 2px solid grey;\n",
              "}\n",
              "\n",
              "/* Style the tab content */\n",
              ".kda_tabcontent {\n",
              "    display: none;\n",
              "    padding: 6px;\n",
              "    border: 1px solid grey;\n",
              "    border-top: none;\n",
              "}\n",
              "\n",
              ".kda_scroll_container {\n",
              "    max-height: 400px;\n",
              "    overflow: auto;\n",
              "}\n",
              "</style>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "<script type=\"text/javascript\">function openTab(evt, tabName) {\n",
              "    // Declare all variables\n",
              "    var i, rootElement, tabcontent, tablinks, tabshow;\n",
              "\n",
              "    // Get all elements with class=\"tabcontent\" and hide them\n",
              "    rootElement = evt.currentTarget.parentElement.parentElement;\n",
              "    tabcontent = rootElement.getElementsByClassName(\"kda_tabcontent\");\n",
              "    for (i = 0; i < tabcontent.length; i++) {\n",
              "        tabcontent[i].style.display = \"none\";\n",
              "    }\n",
              "\n",
              "    // Get all elements with class=\"tablinks\" and remove the class \"active\"\n",
              "    tablinks = rootElement.getElementsByClassName(\"kda_tablinks\");\n",
              "    for (i = 0; i < tablinks.length; i++) {\n",
              "        tablinks[i].className = tablinks[i].className.replace(\" kda_active\", \"\");\n",
              "    }\n",
              "\n",
              "    // Show the current tab, and add an \"active\" class to the button that opened the tab\n",
              "    tabshow = rootElement.getElementsByClassName(tabName);\n",
              "    for (i = 0; i < tabshow.length; i++) {\n",
              "        tabshow[i].style.display = \"block\";\n",
              "    }\n",
              "    evt.currentTarget.className += \" kda_active\";\n",
              "}\n",
              "</script>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "tables {\n",
              "  table_id: \"26557d82-7032-4532-aa82-94a49f8f3b66\"\n",
              "  table_name: \"Member\"\n",
              "  time_column_name: \"registration_init_time\"\n",
              "  entity_key_column_name: \"msno\"\n",
              "  grouping_id: \"User\"\n",
              "  create_time {\n",
              "    seconds: 1671564439\n",
              "    nanos: 551894000\n",
              "  }\n",
              "  update_time {\n",
              "    seconds: 1671564441\n",
              "    nanos: 419904000\n",
              "  }\n",
              "  version: 10017\n",
              "  schema {\n",
              "    fields {\n",
              "      name: \"msno\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_STRING\n",
              "      }\n",
              "    }\n",
              "    fields {\n",
              "      name: \"city\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_I64\n",
              "      }\n",
              "    }\n",
              "    fields {\n",
              "      name: \"bd\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_I64\n",
              "      }\n",
              "    }\n",
              "    fields {\n",
              "      name: \"gender\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_STRING\n",
              "      }\n",
              "    }\n",
              "    fields {\n",
              "      name: \"registered_via\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_I64\n",
              "      }\n",
              "    }\n",
              "    fields {\n",
              "      name: \"registration_init_time\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_TIMESTAMP_NANOSECOND\n",
              "      }\n",
              "    }\n",
              "    fields {\n",
              "      name: \"idx\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_I64\n",
              "      }\n",
              "    }\n",
              "    fields {\n",
              "      name: \"__index_level_0__\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_I64\n",
              "      }\n",
              "    }\n",
              "  }\n",
              "  subsort_column_name {\n",
              "    value: \"idx\"\n",
              "  }\n",
              "  table_source {\n",
              "    kaskada {\n",
              "    }\n",
              "  }\n",
              "}\n",
              "tables {\n",
              "  table_id: \"05b417ad-53a0-4458-a723-af5ca0b65e7a\"\n",
              "  table_name: \"Transaction\"\n",
              "  time_column_name: \"transaction_date\"\n",
              "  entity_key_column_name: \"msno\"\n",
              "  grouping_id: \"User\"\n",
              "  create_time {\n",
              "    seconds: 1671564437\n",
              "    nanos: 59765000\n",
              "  }\n",
              "  update_time {\n",
              "    seconds: 1671564439\n",
              "    nanos: 271819000\n",
              "  }\n",
              "  version: 10015\n",
              "  schema {\n",
              "    fields {\n",
              "      name: \"msno\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_STRING\n",
              "      }\n",
              "    }\n",
              "    fields {\n",
              "      name: \"payment_method_id\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_I64\n",
              "      }\n",
              "    }\n",
              "    fields {\n",
              "      name: \"payment_plan_days\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_I64\n",
              "      }\n",
              "    }\n",
              "    fields {\n",
              "      name: \"plan_list_price\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_I64\n",
              "      }\n",
              "    }\n",
              "    fields {\n",
              "      name: \"actual_amount_paid\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_I64\n",
              "      }\n",
              "    }\n",
              "    fields {\n",
              "      name: \"is_auto_renew\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_I64\n",
              "      }\n",
              "    }\n",
              "    fields {\n",
              "      name: \"transaction_date\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_TIMESTAMP_NANOSECOND\n",
              "      }\n",
              "    }\n",
              "    fields {\n",
              "      name: \"membership_expire_date\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_TIMESTAMP_NANOSECOND\n",
              "      }\n",
              "    }\n",
              "    fields {\n",
              "      name: \"is_cancel\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_I64\n",
              "      }\n",
              "    }\n",
              "    fields {\n",
              "      name: \"idx\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_I64\n",
              "      }\n",
              "    }\n",
              "    fields {\n",
              "      name: \"__index_level_0__\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_I64\n",
              "      }\n",
              "    }\n",
              "  }\n",
              "  subsort_column_name {\n",
              "    value: \"idx\"\n",
              "  }\n",
              "  table_source {\n",
              "    kaskada {\n",
              "    }\n",
              "  }\n",
              "}\n",
              "request_details {\n",
              "  request_id: \"a619dca4f63e8b337f0c80336ede38b8\"\n",
              "}"
            ],
            "text/html": [
              "<div><div class=\"kda_tab\"><button class=\"kda_tablinks kda_active\" onclick=\"openTab(event, 'details')\">Details</button><button class=\"kda_tablinks\" onclick=\"openTab(event, 'raw')\">Raw</button></div><div class=\"details kda_tabcontent\" style=\"display:block;\"><div class=\"kda_scroll_container\"><table class=\"kda_table\"><tr><td><b>tables</b></td><td><table class=\"kda_table\"><tr><th>index</th><th>name</th></tr><tr><td><pre>0</pre></td><td><pre>Member</pre></td></tr><tr><td><pre>1</pre></td><td><pre>Transaction</pre></td></tr></table></td></tr><tr><td><b>request_details</b></td><td><table class=\"kda_table\"><tr><td><b>request_id</b></td><td><pre>a619dca4f63e8b337f0c80336ede38b8</pre></td></tr></table></td></tr></table></div></div><div class=\"raw kda_tabcontent\" style=\"display:none;\"><div class=\"kda_scroll_container\"><pre>tables {\n",
              "  table_id: \"26557d82-7032-4532-aa82-94a49f8f3b66\"\n",
              "  table_name: \"Member\"\n",
              "  time_column_name: \"registration_init_time\"\n",
              "  entity_key_column_name: \"msno\"\n",
              "  grouping_id: \"User\"\n",
              "  create_time {\n",
              "    seconds: 1671564439\n",
              "    nanos: 551894000\n",
              "  }\n",
              "  update_time {\n",
              "    seconds: 1671564441\n",
              "    nanos: 419904000\n",
              "  }\n",
              "  version: 10017\n",
              "  schema {\n",
              "    fields {\n",
              "      name: \"msno\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_STRING\n",
              "      }\n",
              "    }\n",
              "    fields {\n",
              "      name: \"city\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_I64\n",
              "      }\n",
              "    }\n",
              "    fields {\n",
              "      name: \"bd\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_I64\n",
              "      }\n",
              "    }\n",
              "    fields {\n",
              "      name: \"gender\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_STRING\n",
              "      }\n",
              "    }\n",
              "    fields {\n",
              "      name: \"registered_via\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_I64\n",
              "      }\n",
              "    }\n",
              "    fields {\n",
              "      name: \"registration_init_time\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_TIMESTAMP_NANOSECOND\n",
              "      }\n",
              "    }\n",
              "    fields {\n",
              "      name: \"idx\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_I64\n",
              "      }\n",
              "    }\n",
              "    fields {\n",
              "      name: \"__index_level_0__\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_I64\n",
              "      }\n",
              "    }\n",
              "  }\n",
              "  subsort_column_name {\n",
              "    value: \"idx\"\n",
              "  }\n",
              "  table_source {\n",
              "    kaskada {\n",
              "    }\n",
              "  }\n",
              "}\n",
              "tables {\n",
              "  table_id: \"05b417ad-53a0-4458-a723-af5ca0b65e7a\"\n",
              "  table_name: \"Transaction\"\n",
              "  time_column_name: \"transaction_date\"\n",
              "  entity_key_column_name: \"msno\"\n",
              "  grouping_id: \"User\"\n",
              "  create_time {\n",
              "    seconds: 1671564437\n",
              "    nanos: 59765000\n",
              "  }\n",
              "  update_time {\n",
              "    seconds: 1671564439\n",
              "    nanos: 271819000\n",
              "  }\n",
              "  version: 10015\n",
              "  schema {\n",
              "    fields {\n",
              "      name: \"msno\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_STRING\n",
              "      }\n",
              "    }\n",
              "    fields {\n",
              "      name: \"payment_method_id\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_I64\n",
              "      }\n",
              "    }\n",
              "    fields {\n",
              "      name: \"payment_plan_days\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_I64\n",
              "      }\n",
              "    }\n",
              "    fields {\n",
              "      name: \"plan_list_price\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_I64\n",
              "      }\n",
              "    }\n",
              "    fields {\n",
              "      name: \"actual_amount_paid\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_I64\n",
              "      }\n",
              "    }\n",
              "    fields {\n",
              "      name: \"is_auto_renew\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_I64\n",
              "      }\n",
              "    }\n",
              "    fields {\n",
              "      name: \"transaction_date\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_TIMESTAMP_NANOSECOND\n",
              "      }\n",
              "    }\n",
              "    fields {\n",
              "      name: \"membership_expire_date\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_TIMESTAMP_NANOSECOND\n",
              "      }\n",
              "    }\n",
              "    fields {\n",
              "      name: \"is_cancel\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_I64\n",
              "      }\n",
              "    }\n",
              "    fields {\n",
              "      name: \"idx\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_I64\n",
              "      }\n",
              "    }\n",
              "    fields {\n",
              "      name: \"__index_level_0__\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_I64\n",
              "      }\n",
              "    }\n",
              "  }\n",
              "  subsort_column_name {\n",
              "    value: \"idx\"\n",
              "  }\n",
              "  table_source {\n",
              "    kaskada {\n",
              "    }\n",
              "  }\n",
              "}\n",
              "request_details {\n",
              "  request_id: \"a619dca4f63e8b337f0c80336ede38b8\"\n",
              "}\n",
              "</pre></div></div></div>"
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3a3939a7-1e62-4ed1-9dd2-468d14ba71c1"
      },
      "source": [
        "# Step 2: Feature Engineering\n",
        "## Data scientists love Jupyter\n",
        "### With Kaskada's python library and FENL magic they can keep all their favorite parts\n",
        "- Iterative exploration, drill down and manipulation of data \n",
        "- Data cleaning\n",
        "- Statistical modeling\n",
        "- Visualization story telling with words, graphs and code\n",
        "- Training ML models\n"
      ],
      "id": "3a3939a7-1e62-4ed1-9dd2-468d14ba71c1"
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ab8a2d0d"
      },
      "source": [
        "### Iterative exploration, drill down and manipulation of data with Kaskada\n",
        "\n",
        "#### Connect your event-based data directly to Kaskada\n",
        "\n",
        "Let's take a look at the transaction events and membership information associated with a single member to understand the columns available, `msno=LWekcgcnUIqi22v63xuIMX4GYbxapmPMoDnLMVLFSTs=`"
      ],
      "id": "ab8a2d0d"
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9b0a2f4a-013a-46a8-ba85-9d851c157c33",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 460
        },
        "outputId": "a362a439-6560-40fc-d97b-6bd8e056e9f2"
      },
      "source": [
        "%%fenl\n",
        "Transaction | when(Transaction.msno == \"LWekcgcnUIqi22v63xuIMX4GYbxapmPMoDnLMVLFSTs=\")"
      ],
      "id": "9b0a2f4a-013a-46a8-ba85-9d851c157c33",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "<style>table.kda_table {\n",
              "    border: 1px solid grey !important;\n",
              "    border-collapse: collapse !important;\n",
              "    border-spacing: 0 !important;\n",
              "    font-size: 14px !important;\n",
              "    margin-bottom: 6px !important;\n",
              "}\n",
              "\n",
              "table.kda_table table {\n",
              "    margin-bottom: 0 !important;\n",
              "}\n",
              "\n",
              ".kda_table td, .kda_table th {\n",
              "    border: 1px solid grey !important;\n",
              "    border-collapse: collapse !important;\n",
              "    padding: 6px !important;\n",
              "    text-align: left !important;\n",
              "    vertical-align: top !important;\n",
              "}\n",
              "\n",
              ".kda_table tr {\n",
              "    background-color: inherit !important;\n",
              "}\n",
              "\n",
              "/* Style the tab */\n",
              ".kda_tab {\n",
              "    overflow: hidden;\n",
              "    border-bottom: 1px solid grey;\n",
              "    background-color: inherit;\n",
              "}\n",
              "\n",
              "/* Style the buttons that are used to open the tab content */\n",
              ".kda_tab button {\n",
              "    background-color: inherit;\n",
              "    border-top: 1px solid grey;\n",
              "    border-right: 1px solid grey;\n",
              "    border-left: 1px solid grey;\n",
              "    border-bottom: none;\n",
              "    border-radius: 5px 5px 0px 0px;\n",
              "    color: inherit;\n",
              "    cursor: pointer;\n",
              "    float: left;\n",
              "    margin: 2px 8px 0px 2px;\n",
              "    outline: none;\n",
              "    padding: 5px 16px;\n",
              "    transition: 0.3s;\n",
              "}\n",
              "\n",
              "/* Change background color of buttons on hover */\n",
              ".kda_tab button:hover {\n",
              "    background-color: grey;\n",
              "}\n",
              "\n",
              "/* Create an active/current tablink class */\n",
              ".kda_tab button.kda_active {\n",
              "    outline: 2px solid grey;\n",
              "}\n",
              "\n",
              "/* Style the tab content */\n",
              ".kda_tabcontent {\n",
              "    display: none;\n",
              "    padding: 6px;\n",
              "    border: 1px solid grey;\n",
              "    border-top: none;\n",
              "}\n",
              "\n",
              ".kda_scroll_container {\n",
              "    max-height: 400px;\n",
              "    overflow: auto;\n",
              "}\n",
              "</style>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "<script type=\"text/javascript\">function openTab(evt, tabName) {\n",
              "    // Declare all variables\n",
              "    var i, rootElement, tabcontent, tablinks, tabshow;\n",
              "\n",
              "    // Get all elements with class=\"tabcontent\" and hide them\n",
              "    rootElement = evt.currentTarget.parentElement.parentElement;\n",
              "    tabcontent = rootElement.getElementsByClassName(\"kda_tabcontent\");\n",
              "    for (i = 0; i < tabcontent.length; i++) {\n",
              "        tabcontent[i].style.display = \"none\";\n",
              "    }\n",
              "\n",
              "    // Get all elements with class=\"tablinks\" and remove the class \"active\"\n",
              "    tablinks = rootElement.getElementsByClassName(\"kda_tablinks\");\n",
              "    for (i = 0; i < tablinks.length; i++) {\n",
              "        tablinks[i].className = tablinks[i].className.replace(\" kda_active\", \"\");\n",
              "    }\n",
              "\n",
              "    // Show the current tab, and add an \"active\" class to the button that opened the tab\n",
              "    tabshow = rootElement.getElementsByClassName(tabName);\n",
              "    for (i = 0; i < tabshow.length; i++) {\n",
              "        tabshow[i].style.display = \"block\";\n",
              "    }\n",
              "    evt.currentTarget.className += \" kda_active\";\n",
              "}\n",
              "</script>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<fenlmagic.QueryResult at 0x7fdf97fd1400>"
            ],
            "text/html": [
              "<div><div class=\"kda_tab\"><button class=\"kda_tablinks kda_active\" onclick=\"openTab(event, 'dataframe')\">Dataframe</button><button class=\"kda_tablinks\" onclick=\"openTab(event, 'details')\">Details</button><button class=\"kda_tablinks\" onclick=\"openTab(event, 'schema')\">Schema</button><button class=\"kda_tablinks\" onclick=\"openTab(event, 'raw')\">Raw</button></div><div class=\"dataframe kda_tabcontent\" style=\"display:block;\"><div class=\"kda_scroll_container\"><html><head></head><body><div><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><table border=\"1\" class=\"dataframe\"><thead><tr style=\"text-align: right;\"><th></th><th>_key</th><th>msno</th><th>payment_method_id</th><th>payment_plan_days</th><th>plan_list_price</th><th>actual_amount_paid</th><th>is_auto_renew</th><th>transaction_date</th><th>membership_expire_date</th><th>is_cancel</th><th>idx</th><th>__index_level_0__</th></tr></thead><tbody><tr><th>0</th><td>LWekcgcnUIqi22v63xuIMX4GYbxapmPMoDnLMVLFSTs=</td><td>LWekcgcnUIqi22v63xuIMX4GYbxapmPMoDnLMVLFSTs=</td><td>41</td><td>30</td><td>149</td><td>149</td><td>1</td><td>2015-01-01</td><td>2015-02-02</td><td>0</td><td>14382</td><td>14382</td></tr><tr><th>1</th><td>LWekcgcnUIqi22v63xuIMX4GYbxapmPMoDnLMVLFSTs=</td><td>LWekcgcnUIqi22v63xuIMX4GYbxapmPMoDnLMVLFSTs=</td><td>41</td><td>30</td><td>149</td><td>149</td><td>1</td><td>2015-02-01</td><td>2015-03-02</td><td>0</td><td>3626985</td><td>3626985</td></tr><tr><th>2</th><td>LWekcgcnUIqi22v63xuIMX4GYbxapmPMoDnLMVLFSTs=</td><td>LWekcgcnUIqi22v63xuIMX4GYbxapmPMoDnLMVLFSTs=</td><td>41</td><td>30</td><td>149</td><td>149</td><td>1</td><td>2015-03-01</td><td>2015-04-02</td><td>0</td><td>2892776</td><td>2892776</td></tr><tr><th>3</th><td>LWekcgcnUIqi22v63xuIMX4GYbxapmPMoDnLMVLFSTs=</td><td>LWekcgcnUIqi22v63xuIMX4GYbxapmPMoDnLMVLFSTs=</td><td>41</td><td>30</td><td>149</td><td>149</td><td>1</td><td>2015-03-09</td><td>2015-03-09</td><td>1</td><td>18569628</td><td>18569628</td></tr><tr><th>4</th><td>LWekcgcnUIqi22v63xuIMX4GYbxapmPMoDnLMVLFSTs=</td><td>LWekcgcnUIqi22v63xuIMX4GYbxapmPMoDnLMVLFSTs=</td><td>41</td><td>30</td><td>149</td><td>149</td><td>1</td><td>2015-12-23</td><td>2016-01-22</td><td>0</td><td>19881564</td><td>19881564</td></tr><tr><th>...</th><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td></tr><tr><th>16</th><td>LWekcgcnUIqi22v63xuIMX4GYbxapmPMoDnLMVLFSTs=</td><td>LWekcgcnUIqi22v63xuIMX4GYbxapmPMoDnLMVLFSTs=</td><td>41</td><td>30</td><td>149</td><td>149</td><td>1</td><td>2016-12-22</td><td>2017-01-22</td><td>0</td><td>18675436</td><td>18675436</td></tr><tr><th>17</th><td>LWekcgcnUIqi22v63xuIMX4GYbxapmPMoDnLMVLFSTs=</td><td>LWekcgcnUIqi22v63xuIMX4GYbxapmPMoDnLMVLFSTs=</td><td>41</td><td>30</td><td>149</td><td>149</td><td>1</td><td>2017-01-22</td><td>2017-02-22</td><td>0</td><td>6252321</td><td>6252321</td></tr><tr><th>18</th><td>LWekcgcnUIqi22v63xuIMX4GYbxapmPMoDnLMVLFSTs=</td><td>LWekcgcnUIqi22v63xuIMX4GYbxapmPMoDnLMVLFSTs=</td><td>41</td><td>30</td><td>149</td><td>149</td><td>1</td><td>2017-02-01</td><td>2017-02-01</td><td>1</td><td>8145718</td><td>8145718</td></tr><tr><th>19</th><td>LWekcgcnUIqi22v63xuIMX4GYbxapmPMoDnLMVLFSTs=</td><td>LWekcgcnUIqi22v63xuIMX4GYbxapmPMoDnLMVLFSTs=</td><td>41</td><td>30</td><td>99</td><td>99</td><td>1</td><td>2017-02-01</td><td>2017-02-28</td><td>0</td><td>13060973</td><td>13060973</td></tr><tr><th>20</th><td>LWekcgcnUIqi22v63xuIMX4GYbxapmPMoDnLMVLFSTs=</td><td>LWekcgcnUIqi22v63xuIMX4GYbxapmPMoDnLMVLFSTs=</td><td>41</td><td>30</td><td>99</td><td>99</td><td>1</td><td>2017-02-28</td><td>2017-03-31</td><td>0</td><td>2898265</td><td>2898265</td></tr></tbody></table><p>21 rows × 12 columns</p></div></body></html></div></div><div class=\"details kda_tabcontent\" style=\"display:none;\"><div class=\"kda_scroll_container\"><table class=\"kda_table\"><tr><td><b>state</b></td><td>SUCCESS</td></tr><tr><td><b>query_id</b></td><td>77150f9d-4400-42ea-8612-df2d2f834424</td></tr><tr><td><b>metrics</b></td><td><table class=\"kda_table\"><tr><td><b>time_preparing</b></td><td>0.036s</td></tr><tr><td><b>time_computing</b></td><td>0.693s</td></tr><tr><td><b>output_files</b></td><td>1</td></tr></table></td></tr><tr><td><b>parquet</b></td><td><table class=\"kda_table\"><tr><th>index</th><th>path</th></tr><tr><td><pre>0</pre></td><td><a href=\"https://studio-us-west-2-prod-kaskada.s3.us-west-2.amazonaws.com/wren/dbv1alpha/results/cac2a62e-70d1-452d-bc65-d4dd832cb5b6/OyQ6oa2e_o4OtTmwcJbzBbNhZLW5weieCYlU9Q/7ca9abcb-bbe5-4b50-b0bf-87aeca64275d.parquet?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=ASIAZJRQG37GWVIVW7CG%2F20221229%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20221229T191743Z&X-Amz-Expires=3600&X-Amz-Security-Token=IQoJb3JpZ2luX2VjEBsaCXVzLXdlc3QtMiJGMEQCIHM2%2F%2BvYM2e7RywlSEwJD7rKvqQxq6Amf6wk2%2BGN4CXbAiAwrjgoBZXMxs8IX15Vm%2BbBZzAbGNwlXWiaaCUj11%2FnQir0BAhkEAIaDDYzODk3NzQ5OTA4NSIMWHLflFNCCCCYfX9fKtEEw%2BgtR6gROyGZyL1faB4u%2F6jToryyOzVgpWCsI36uklgG1Nl21lRQ2Om5edylfSVIfwcYt2o26IbDMyt0l8Mqp5M3DvD3aGYHEztHKHVCKOuoPRFcMs73Tkzd2IbbHTogUmekwSS7y1MITArT%2B40PRBnYZcEysgGr0s0oSfJifmBC2P9dZKye6H9hPTrIpVsnzzJl2YW6QmuuthS13%2B%2Fuvp1TRY7alZMjxT2p%2B98PfMY%2BwnDZyvm52k7f8WX%2B6LeG5huBK4lCHaAny6JXnXlONYhDvbtM5g7KR7YR%2Bz%2FPbMHPZM76Zm1xx0f%2FEPjypHke%2BUphqjA7tvEGHV0iK67npb9eJtso0hP3oeaaD%2FszzeerAgf2orLFHNFHYtq5GzcRGehMzuhLWTYF3RBrRaWkEewpl4BJtIiGvX35M5FsfydKQ0KN04O1m5WbYWCs0HjGd5gaYO1exE8HZtfG382RzpuXdZcnlKh6fSA7fL3U%2B2VqxfG5T5C4QHWzqx3MMTqfWFK5Q%2Bm0VTfpLWYMrCQR61R9rM21esBZYSVDUYlYAS6YqBCPi%2B7ASDJDEcus4jqK7CDR1KEPEYQNTjugaQOZV%2BJ7%2Fl%2FdTZMWDfJm%2B1qokmi4F%2FIGiaGELwkAKaHsVOTr2R2Dk%2FvSjaN11r1lHMVtPNAYFgkPH%2FI32v0yGF7CIoDZz0RQraYSRWeA1EynXmktTNbEGtiDXtQzCe%2BTmKj5qBJWzzSbNG6ybRsEJLIBWXCIQUr7eE6Yq%2Bcf38CG85uF7v1TQRgFW1%2BalPL4gYFjAx8w38O3nQY6mwGkkaWu2yhK5Y6qWhusg%2FePqQQiM9vcFWlmU9y%2Be0EQbx9LvUisuTKSvrzRFv9dtCrcDt7XDB1bbaEJGwxSXOt09vjjls6U3ttbTU0m0o00t7%2BW5MfmCH7%2BPhW77xv61uHAnRW54KZ9W9b8LaC2NUPDoPdXvFUqW%2FFi6a4bjbNXzglXChqsR2qksX23ljxbpAmPceEmYxwd39ss%2FQ%3D%3D&X-Amz-SignedHeaders=host&X-Amz-Signature=fa81e532fa6960f15dc71cf7971bf8e4eeb896fd173a95d72aa350d8c1b2125e\">https://studio-us-west-2-prod-kaskada.s3.us-west-2.amazonaws.com/wren/dbv1alpha/results/cac2a62e-70d1-452d-bc65-d4dd832cb5b6/OyQ6oa2e_o4OtTmwcJbzBbNhZLW5weieCYlU9Q/7ca9abcb-bbe5-4b50-b0bf-87aeca64275d.parquet?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=ASIAZJRQG37GWVIVW7CG%2F20221229%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20221229T191743Z&X-Amz-Expires=3600&X-Amz-Security-Token=IQoJb3JpZ2luX2VjEBsaCXVzLXdlc3QtMiJGMEQCIHM2%2F%2BvYM2e7RywlSEwJD7rKvqQxq6Amf6wk2%2BGN4CXbAiAwrjgoBZXMxs8IX15Vm%2BbBZzAbGNwlXWiaaCUj11%2FnQir0BAhkEAIaDDYzODk3NzQ5OTA4NSIMWHLflFNCCCCYfX9fKtEEw%2BgtR6gROyGZyL1faB4u%2F6jToryyOzVgpWCsI36uklgG1Nl21lRQ2Om5edylfSVIfwcYt2o26IbDMyt0l8Mqp5M3DvD3aGYHEztHKHVCKOuoPRFcMs73Tkzd2IbbHTogUmekwSS7y1MITArT%2B40PRBnYZcEysgGr0s0oSfJifmBC2P9dZKye6H9hPTrIpVsnzzJl2YW6QmuuthS13%2B%2Fuvp1TRY7alZMjxT2p%2B98PfMY%2BwnDZyvm52k7f8WX%2B6LeG5huBK4lCHaAny6JXnXlONYhDvbtM5g7KR7YR%2Bz%2FPbMHPZM76Zm1xx0f%2FEPjypHke%2BUphqjA7tvEGHV0iK67npb9eJtso0hP3oeaaD%2FszzeerAgf2orLFHNFHYtq5GzcRGehMzuhLWTYF3RBrRaWkEewpl4BJtIiGvX35M5FsfydKQ0KN04O1m5WbYWCs0HjGd5gaYO1exE8HZtfG382RzpuXdZcnlKh6fSA7fL3U%2B2VqxfG5T5C4QHWzqx3MMTqfWFK5Q%2Bm0VTfpLWYMrCQR61R9rM21esBZYSVDUYlYAS6YqBCPi%2B7ASDJDEcus4jqK7CDR1KEPEYQNTjugaQOZV%2BJ7%2Fl%2FdTZMWDfJm%2B1qokmi4F%2FIGiaGELwkAKaHsVOTr2R2Dk%2FvSjaN11r1lHMVtPNAYFgkPH%2FI32v0yGF7CIoDZz0RQraYSRWeA1EynXmktTNbEGtiDXtQzCe%2BTmKj5qBJWzzSbNG6ybRsEJLIBWXCIQUr7eE6Yq%2Bcf38CG85uF7v1TQRgFW1%2BalPL4gYFjAx8w38O3nQY6mwGkkaWu2yhK5Y6qWhusg%2FePqQQiM9vcFWlmU9y%2Be0EQbx9LvUisuTKSvrzRFv9dtCrcDt7XDB1bbaEJGwxSXOt09vjjls6U3ttbTU0m0o00t7%2BW5MfmCH7%2BPhW77xv61uHAnRW54KZ9W9b8LaC2NUPDoPdXvFUqW%2FFi6a4bjbNXzglXChqsR2qksX23ljxbpAmPceEmYxwd39ss%2FQ%3D%3D&X-Amz-SignedHeaders=host&X-Amz-Signature=fa81e532fa6960f15dc71cf7971bf8e4eeb896fd173a95d72aa350d8c1b2125e</a></td></tr></table></td></tr><tr><td><b>analysis</b></td><td><table class=\"kda_table\"><tr><td><b>can_execute</b></td><td><pre>True</pre></td></tr></table></td></tr><tr><td><b>schema</b></td><td><pre>(see Schema tab)</pre></td></tr><tr><td><b>data_token_id</b></td><td><pre>d70f10d1-50b6-40a7-a6dd-12a0d400e12b</pre></td></tr><tr><td><b>slice_request</b></td><td><table class=\"kda_table\"><tr><td><b>None</b></td><td><pre>(full dataset used for query)</pre></td></tr></table></td></tr><tr><td><b>request_details</b></td><td><table class=\"kda_table\"><tr><td><b>request_id</b></td><td><pre>dbd5cf73e21ed47e568da47d35ab7915</pre></td></tr></table></td></tr><tr><td><b>query</b></td><td><pre>Transaction | when(Transaction.msno == \"LWekcgcnUIqi22v63xuIMX4GYbxapmPMoDnLMVLFSTs=\")</pre></td></tr></table></div></div><div class=\"schema kda_tabcontent\" style=\"display:none;\"><div class=\"kda_scroll_container\"><html><head></head><body><div><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><table border=\"1\" class=\"dataframe\"><thead><tr style=\"text-align: right;\"><th></th><th>column_name</th><th>column_type</th></tr></thead><tbody><tr><th>0</th><td>msno</td><td>string</td></tr><tr><th>1</th><td>payment_method_id</td><td>i64</td></tr><tr><th>2</th><td>payment_plan_days</td><td>i64</td></tr><tr><th>3</th><td>plan_list_price</td><td>i64</td></tr><tr><th>4</th><td>actual_amount_paid</td><td>i64</td></tr><tr><th>5</th><td>is_auto_renew</td><td>i64</td></tr><tr><th>6</th><td>transaction_date</td><td>timestamp_ns</td></tr><tr><th>7</th><td>membership_expire_date</td><td>timestamp_ns</td></tr><tr><th>8</th><td>is_cancel</td><td>i64</td></tr><tr><th>9</th><td>idx</td><td>i64</td></tr><tr><th>10</th><td>__index_level_0__</td><td>i64</td></tr></tbody></table></div></body></html></div></div><div class=\"raw kda_tabcontent\" style=\"display:none;\"><div class=\"kda_scroll_container\"><pre>{'dataframe': 'RangeIndex: 21 entries, 0 to 20'\n",
              "              'Columns: 12 entries, _key to __index_level_0__'\n",
              "              'dtypes: datetime64[ns](2), int64(8), object(2)'\n",
              "              'memory usage: 2.1+ KB',\n",
              " 'query': 'Transaction | when(Transaction.msno == '\n",
              "          '\"LWekcgcnUIqi22v63xuIMX4GYbxapmPMoDnLMVLFSTs=\")',\n",
              " 'query_response': state: STATE_SUCCESS\n",
              "config {\n",
              "  data_token_id: \"d70f10d1-50b6-40a7-a6dd-12a0d400e12b\"\n",
              "}\n",
              "analysis {\n",
              "  can_execute: true\n",
              "  schema {\n",
              "    fields {\n",
              "      name: \"msno\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_STRING\n",
              "      }\n",
              "    }\n",
              "    fields {\n",
              "      name: \"payment_method_id\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_I64\n",
              "      }\n",
              "    }\n",
              "    fields {\n",
              "      name: \"payment_plan_days\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_I64\n",
              "      }\n",
              "    }\n",
              "    fields {\n",
              "      name: \"plan_list_price\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_I64\n",
              "      }\n",
              "    }\n",
              "    fields {\n",
              "      name: \"actual_amount_paid\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_I64\n",
              "      }\n",
              "    }\n",
              "    fields {\n",
              "      name: \"is_auto_renew\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_I64\n",
              "      }\n",
              "    }\n",
              "    fields {\n",
              "      name: \"transaction_date\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_TIMESTAMP_NANOSECOND\n",
              "      }\n",
              "    }\n",
              "    fields {\n",
              "      name: \"membership_expire_date\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_TIMESTAMP_NANOSECOND\n",
              "      }\n",
              "    }\n",
              "    fields {\n",
              "      name: \"is_cancel\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_I64\n",
              "      }\n",
              "    }\n",
              "    fields {\n",
              "      name: \"idx\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_I64\n",
              "      }\n",
              "    }\n",
              "    fields {\n",
              "      name: \"__index_level_0__\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_I64\n",
              "      }\n",
              "    }\n",
              "  }\n",
              "}\n",
              "fenl_diagnostics {\n",
              "}\n",
              "metrics {\n",
              "  time_preparing {\n",
              "    nanos: 36126629\n",
              "  }\n",
              "  time_computing {\n",
              "    nanos: 693453910\n",
              "  }\n",
              "  output_files: 1\n",
              "}\n",
              "parquet {\n",
              "  paths: \"https://studio-us-west-2-prod-kaskada.s3.us-west-2.amazonaws.com/wren/dbv1alpha/results/cac2a62e-70d1-452d-bc65-d4dd832cb5b6/OyQ6oa2e_o4OtTmwcJbzBbNhZLW5weieCYlU9Q/7ca9abcb-bbe5-4b50-b0bf-87aeca64275d.parquet?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=ASIAZJRQG37GWVIVW7CG%2F20221229%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20221229T191743Z&X-Amz-Expires=3600&X-Amz-Security-Token=IQoJb3JpZ2luX2VjEBsaCXVzLXdlc3QtMiJGMEQCIHM2%2F%2BvYM2e7RywlSEwJD7rKvqQxq6Amf6wk2%2BGN4CXbAiAwrjgoBZXMxs8IX15Vm%2BbBZzAbGNwlXWiaaCUj11%2FnQir0BAhkEAIaDDYzODk3NzQ5OTA4NSIMWHLflFNCCCCYfX9fKtEEw%2BgtR6gROyGZyL1faB4u%2F6jToryyOzVgpWCsI36uklgG1Nl21lRQ2Om5edylfSVIfwcYt2o26IbDMyt0l8Mqp5M3DvD3aGYHEztHKHVCKOuoPRFcMs73Tkzd2IbbHTogUmekwSS7y1MITArT%2B40PRBnYZcEysgGr0s0oSfJifmBC2P9dZKye6H9hPTrIpVsnzzJl2YW6QmuuthS13%2B%2Fuvp1TRY7alZMjxT2p%2B98PfMY%2BwnDZyvm52k7f8WX%2B6LeG5huBK4lCHaAny6JXnXlONYhDvbtM5g7KR7YR%2Bz%2FPbMHPZM76Zm1xx0f%2FEPjypHke%2BUphqjA7tvEGHV0iK67npb9eJtso0hP3oeaaD%2FszzeerAgf2orLFHNFHYtq5GzcRGehMzuhLWTYF3RBrRaWkEewpl4BJtIiGvX35M5FsfydKQ0KN04O1m5WbYWCs0HjGd5gaYO1exE8HZtfG382RzpuXdZcnlKh6fSA7fL3U%2B2VqxfG5T5C4QHWzqx3MMTqfWFK5Q%2Bm0VTfpLWYMrCQR61R9rM21esBZYSVDUYlYAS6YqBCPi%2B7ASDJDEcus4jqK7CDR1KEPEYQNTjugaQOZV%2BJ7%2Fl%2FdTZMWDfJm%2B1qokmi4F%2FIGiaGELwkAKaHsVOTr2R2Dk%2FvSjaN11r1lHMVtPNAYFgkPH%2FI32v0yGF7CIoDZz0RQraYSRWeA1EynXmktTNbEGtiDXtQzCe%2BTmKj5qBJWzzSbNG6ybRsEJLIBWXCIQUr7eE6Yq%2Bcf38CG85uF7v1TQRgFW1%2BalPL4gYFjAx8w38O3nQY6mwGkkaWu2yhK5Y6qWhusg%2FePqQQiM9vcFWlmU9y%2Be0EQbx9LvUisuTKSvrzRFv9dtCrcDt7XDB1bbaEJGwxSXOt09vjjls6U3ttbTU0m0o00t7%2BW5MfmCH7%2BPhW77xv61uHAnRW54KZ9W9b8LaC2NUPDoPdXvFUqW%2FFi6a4bjbNXzglXChqsR2qksX23ljxbpAmPceEmYxwd39ss%2FQ%3D%3D&X-Amz-SignedHeaders=host&X-Amz-Signature=fa81e532fa6960f15dc71cf7971bf8e4eeb896fd173a95d72aa350d8c1b2125e\"\n",
              "}\n",
              "request_details {\n",
              "  request_id: \"dbd5cf73e21ed47e568da47d35ab7915\"\n",
              "}\n",
              "query_id: \"77150f9d-4400-42ea-8612-df2d2f834424\"\n",
              "}</pre></div></div></div>"
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%%fenl\n",
        "Member | when(Member.msno == \"LWekcgcnUIqi22v63xuIMX4GYbxapmPMoDnLMVLFSTs=\")"
      ],
      "metadata": {
        "id": "vjPHTzBQ64lt"
      },
      "id": "vjPHTzBQ64lt",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Data Cleaning\n",
        "\n",
        "* Eliminate 0 or fewer plan days\n",
        "* Select the maximum expiration date\n",
        "* Handle backdated records\n",
        "* Complete a query over all transactions to see how many we have left.\n",
        "* Select and name a subset of columns we want to make available for downstream features"
      ],
      "metadata": {
        "id": "kfF9TQ93YytN"
      },
      "id": "kfF9TQ93YytN"
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Step 2a - FENL Concise Block\n",
        "#### With Kaskada Data Scientists can define features directly from the event based data even when:\n",
        "\n",
        "- The transaction log is quite busy, often with multiple entries recorded on given transaction date (transaction_date) as can be observed for this customer on several dates including 2016-09-25. \n",
        "- Some records have a value of zero or less for payment plan days (payment_plan_days) \n",
        "- Many transaction entries are changing the subscription's expiration date (membership_expire_date). \n",
        "- There are backdated records due to some kind of subscription management activity such as a change in auto-renewal status or the like. "
      ],
      "metadata": {
        "id": "6-mGKygI7fk6"
      },
      "id": "6-mGKygI7fk6"
    },
    {
      "cell_type": "code",
      "source": [
        "%%fenl --var df_cleaned_transactions\n",
        "\n",
        "#Eliminate 0 or fewer plan days\n",
        "let meaningful_txns = Transaction | if(Transaction.payment_plan_days > 0)\n",
        "\n",
        "#Identify backdated records        \n",
        "let max_expires_at = max(meaningful_txns.membership_expire_date)  \n",
        "let expiration_is_previous = (max_expires_at < meaningful_txns.transaction_date)\n",
        "\n",
        "#Calculate new expiration, for backdated transactions        \n",
        "let subscription_expires_at =  max_expires_at | if(not(expiration_is_previous)) | else(meaningful_txns.transaction_date)\n",
        "\n",
        "in {\n",
        "    payment_plan_days: meaningful_txns.payment_plan_days,\n",
        "    payment_method_id: meaningful_txns.payment_method_id,\n",
        "    trans_at: meaningful_txns.transaction_date,\n",
        "    membership_expire_date: meaningful_txns.membership_expire_date,\n",
        "    expires_at: subscription_expires_at\n",
        "}"
      ],
      "metadata": {
        "id": "-Hu_AVABZEan",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 460
        },
        "outputId": "a197679c-38ba-4e5e-ff7d-20ec12ca2b5d"
      },
      "id": "-Hu_AVABZEan",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "<style>table.kda_table {\n",
              "    border: 1px solid grey !important;\n",
              "    border-collapse: collapse !important;\n",
              "    border-spacing: 0 !important;\n",
              "    font-size: 14px !important;\n",
              "    margin-bottom: 6px !important;\n",
              "}\n",
              "\n",
              "table.kda_table table {\n",
              "    margin-bottom: 0 !important;\n",
              "}\n",
              "\n",
              ".kda_table td, .kda_table th {\n",
              "    border: 1px solid grey !important;\n",
              "    border-collapse: collapse !important;\n",
              "    padding: 6px !important;\n",
              "    text-align: left !important;\n",
              "    vertical-align: top !important;\n",
              "}\n",
              "\n",
              ".kda_table tr {\n",
              "    background-color: inherit !important;\n",
              "}\n",
              "\n",
              "/* Style the tab */\n",
              ".kda_tab {\n",
              "    overflow: hidden;\n",
              "    border-bottom: 1px solid grey;\n",
              "    background-color: inherit;\n",
              "}\n",
              "\n",
              "/* Style the buttons that are used to open the tab content */\n",
              ".kda_tab button {\n",
              "    background-color: inherit;\n",
              "    border-top: 1px solid grey;\n",
              "    border-right: 1px solid grey;\n",
              "    border-left: 1px solid grey;\n",
              "    border-bottom: none;\n",
              "    border-radius: 5px 5px 0px 0px;\n",
              "    color: inherit;\n",
              "    cursor: pointer;\n",
              "    float: left;\n",
              "    margin: 2px 8px 0px 2px;\n",
              "    outline: none;\n",
              "    padding: 5px 16px;\n",
              "    transition: 0.3s;\n",
              "}\n",
              "\n",
              "/* Change background color of buttons on hover */\n",
              ".kda_tab button:hover {\n",
              "    background-color: grey;\n",
              "}\n",
              "\n",
              "/* Create an active/current tablink class */\n",
              ".kda_tab button.kda_active {\n",
              "    outline: 2px solid grey;\n",
              "}\n",
              "\n",
              "/* Style the tab content */\n",
              ".kda_tabcontent {\n",
              "    display: none;\n",
              "    padding: 6px;\n",
              "    border: 1px solid grey;\n",
              "    border-top: none;\n",
              "}\n",
              "\n",
              ".kda_scroll_container {\n",
              "    max-height: 400px;\n",
              "    overflow: auto;\n",
              "}\n",
              "</style>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "<script type=\"text/javascript\">function openTab(evt, tabName) {\n",
              "    // Declare all variables\n",
              "    var i, rootElement, tabcontent, tablinks, tabshow;\n",
              "\n",
              "    // Get all elements with class=\"tabcontent\" and hide them\n",
              "    rootElement = evt.currentTarget.parentElement.parentElement;\n",
              "    tabcontent = rootElement.getElementsByClassName(\"kda_tabcontent\");\n",
              "    for (i = 0; i < tabcontent.length; i++) {\n",
              "        tabcontent[i].style.display = \"none\";\n",
              "    }\n",
              "\n",
              "    // Get all elements with class=\"tablinks\" and remove the class \"active\"\n",
              "    tablinks = rootElement.getElementsByClassName(\"kda_tablinks\");\n",
              "    for (i = 0; i < tablinks.length; i++) {\n",
              "        tablinks[i].className = tablinks[i].className.replace(\" kda_active\", \"\");\n",
              "    }\n",
              "\n",
              "    // Show the current tab, and add an \"active\" class to the button that opened the tab\n",
              "    tabshow = rootElement.getElementsByClassName(tabName);\n",
              "    for (i = 0; i < tabshow.length; i++) {\n",
              "        tabshow[i].style.display = \"block\";\n",
              "    }\n",
              "    evt.currentTarget.className += \" kda_active\";\n",
              "}\n",
              "</script>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<fenlmagic.QueryResult at 0x7fdf97fddf40>"
            ],
            "text/html": [
              "<div><div class=\"kda_tab\"><button class=\"kda_tablinks kda_active\" onclick=\"openTab(event, 'dataframe')\">Dataframe</button><button class=\"kda_tablinks\" onclick=\"openTab(event, 'details')\">Details</button><button class=\"kda_tablinks\" onclick=\"openTab(event, 'schema')\">Schema</button><button class=\"kda_tablinks\" onclick=\"openTab(event, 'raw')\">Raw</button></div><div class=\"dataframe kda_tabcontent\" style=\"display:block;\"><div class=\"kda_scroll_container\"><html><head></head><body><div><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><table border=\"1\" class=\"dataframe\"><thead><tr style=\"text-align: right;\"><th></th><th>_key</th><th>payment_plan_days</th><th>payment_method_id</th><th>trans_at</th><th>membership_expire_date</th><th>expires_at</th></tr></thead><tbody><tr><th>0</th><td>LWekcgcnUIqi22v63xuIMX4GYbxapmPMoDnLMVLFSTs=</td><td>30.0</td><td>41.0</td><td>2015-01-01</td><td>2015-02-02</td><td>2015-02-02</td></tr><tr><th>1</th><td>vQ017y/6EVjUSmMb9IJvDZUJtLkHKGnWfUAbt7nxeU0=</td><td>30.0</td><td>41.0</td><td>2015-01-01</td><td>2015-02-01</td><td>2015-02-01</td></tr><tr><th>2</th><td>aQu0EDyd2mjbYCZpm5ObIeZdRiH/wAiM6wzy10mc+3s=</td><td>31.0</td><td>40.0</td><td>2015-01-01</td><td>2015-01-31</td><td>2015-01-31</td></tr><tr><th>3</th><td>UsBmIup1CbiB3i9U2cpJUvupy2BbVqXUxYB/gBhkqBs=</td><td>31.0</td><td>40.0</td><td>2015-01-01</td><td>2015-02-01</td><td>2015-02-01</td></tr><tr><th>4</th><td>AdMs4wOzKfiO6hM9ayoe4CgYcHsXaoV6pDhkqEwtpzk=</td><td>31.0</td><td>40.0</td><td>2015-01-01</td><td>2015-02-01</td><td>2015-02-01</td></tr><tr><th>...</th><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td></tr><tr><th>288556</th><td>TNOcP07Mry/UFtgvxn9bUPgq8Zf6dwdWQjn9kv7P+g0=</td><td>30.0</td><td>41.0</td><td>2017-02-28</td><td>2017-03-31</td><td>2017-03-31</td></tr><tr><th>288557</th><td>My/CEivMfiCWmSl9C1BNarV80eaMdd+LjsqnR8g6fsU=</td><td>30.0</td><td>34.0</td><td>2017-02-28</td><td>2017-03-31</td><td>2017-03-31</td></tr><tr><th>288558</th><td>OKdMxAyGn1bJ43uCyWPpr8hYYX0/gdE1Q8Jrs1mGYuI=</td><td>30.0</td><td>34.0</td><td>2017-02-28</td><td>2017-03-31</td><td>2017-03-31</td></tr><tr><th>288559</th><td>3XvMZe4vmCLvPQJoVdOMNt4QE4U1s5dXIW4JiebDtss=</td><td>30.0</td><td>41.0</td><td>2017-02-28</td><td>2017-03-31</td><td>2017-03-31</td></tr><tr><th>288560</th><td>MvNHn2nZqq7nBBuj6yS7ISvZrvnWx1BJvFpxjNcMvmc=</td><td>30.0</td><td>34.0</td><td>2017-02-28</td><td>2017-03-31</td><td>2017-03-31</td></tr></tbody></table><p>288561 rows × 6 columns</p></div></body></html></div></div><div class=\"details kda_tabcontent\" style=\"display:none;\"><div class=\"kda_scroll_container\"><table class=\"kda_table\"><tr><td><b>state</b></td><td>SUCCESS</td></tr><tr><td><b>query_id</b></td><td>00aab42f-0bb5-4e40-b12f-65fb3668f783</td></tr><tr><td><b>metrics</b></td><td><table class=\"kda_table\"><tr><td><b>time_preparing</b></td><td>0.032s</td></tr><tr><td><b>time_computing</b></td><td>0.928s</td></tr><tr><td><b>output_files</b></td><td>1</td></tr></table></td></tr><tr><td><b>parquet</b></td><td><table class=\"kda_table\"><tr><th>index</th><th>path</th></tr><tr><td><pre>0</pre></td><td><a href=\"https://studio-us-west-2-prod-kaskada.s3.us-west-2.amazonaws.com/wren/dbv1alpha/results/cac2a62e-70d1-452d-bc65-d4dd832cb5b6/v3hh9IcE2Dk0Nn6HOneld_Q1S0uv8zE2MW_56A/2d4fb0ae-41c7-4872-a21f-239be28b5c44.parquet?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=ASIAZJRQG37GWVIVW7CG%2F20221229%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20221229T191811Z&X-Amz-Expires=3600&X-Amz-Security-Token=IQoJb3JpZ2luX2VjEBsaCXVzLXdlc3QtMiJGMEQCIHM2%2F%2BvYM2e7RywlSEwJD7rKvqQxq6Amf6wk2%2BGN4CXbAiAwrjgoBZXMxs8IX15Vm%2BbBZzAbGNwlXWiaaCUj11%2FnQir0BAhkEAIaDDYzODk3NzQ5OTA4NSIMWHLflFNCCCCYfX9fKtEEw%2BgtR6gROyGZyL1faB4u%2F6jToryyOzVgpWCsI36uklgG1Nl21lRQ2Om5edylfSVIfwcYt2o26IbDMyt0l8Mqp5M3DvD3aGYHEztHKHVCKOuoPRFcMs73Tkzd2IbbHTogUmekwSS7y1MITArT%2B40PRBnYZcEysgGr0s0oSfJifmBC2P9dZKye6H9hPTrIpVsnzzJl2YW6QmuuthS13%2B%2Fuvp1TRY7alZMjxT2p%2B98PfMY%2BwnDZyvm52k7f8WX%2B6LeG5huBK4lCHaAny6JXnXlONYhDvbtM5g7KR7YR%2Bz%2FPbMHPZM76Zm1xx0f%2FEPjypHke%2BUphqjA7tvEGHV0iK67npb9eJtso0hP3oeaaD%2FszzeerAgf2orLFHNFHYtq5GzcRGehMzuhLWTYF3RBrRaWkEewpl4BJtIiGvX35M5FsfydKQ0KN04O1m5WbYWCs0HjGd5gaYO1exE8HZtfG382RzpuXdZcnlKh6fSA7fL3U%2B2VqxfG5T5C4QHWzqx3MMTqfWFK5Q%2Bm0VTfpLWYMrCQR61R9rM21esBZYSVDUYlYAS6YqBCPi%2B7ASDJDEcus4jqK7CDR1KEPEYQNTjugaQOZV%2BJ7%2Fl%2FdTZMWDfJm%2B1qokmi4F%2FIGiaGELwkAKaHsVOTr2R2Dk%2FvSjaN11r1lHMVtPNAYFgkPH%2FI32v0yGF7CIoDZz0RQraYSRWeA1EynXmktTNbEGtiDXtQzCe%2BTmKj5qBJWzzSbNG6ybRsEJLIBWXCIQUr7eE6Yq%2Bcf38CG85uF7v1TQRgFW1%2BalPL4gYFjAx8w38O3nQY6mwGkkaWu2yhK5Y6qWhusg%2FePqQQiM9vcFWlmU9y%2Be0EQbx9LvUisuTKSvrzRFv9dtCrcDt7XDB1bbaEJGwxSXOt09vjjls6U3ttbTU0m0o00t7%2BW5MfmCH7%2BPhW77xv61uHAnRW54KZ9W9b8LaC2NUPDoPdXvFUqW%2FFi6a4bjbNXzglXChqsR2qksX23ljxbpAmPceEmYxwd39ss%2FQ%3D%3D&X-Amz-SignedHeaders=host&X-Amz-Signature=0f3494f594c4a2dbb244fded7b28d8386a931b6d59851aab320125258193ce01\">https://studio-us-west-2-prod-kaskada.s3.us-west-2.amazonaws.com/wren/dbv1alpha/results/cac2a62e-70d1-452d-bc65-d4dd832cb5b6/v3hh9IcE2Dk0Nn6HOneld_Q1S0uv8zE2MW_56A/2d4fb0ae-41c7-4872-a21f-239be28b5c44.parquet?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=ASIAZJRQG37GWVIVW7CG%2F20221229%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20221229T191811Z&X-Amz-Expires=3600&X-Amz-Security-Token=IQoJb3JpZ2luX2VjEBsaCXVzLXdlc3QtMiJGMEQCIHM2%2F%2BvYM2e7RywlSEwJD7rKvqQxq6Amf6wk2%2BGN4CXbAiAwrjgoBZXMxs8IX15Vm%2BbBZzAbGNwlXWiaaCUj11%2FnQir0BAhkEAIaDDYzODk3NzQ5OTA4NSIMWHLflFNCCCCYfX9fKtEEw%2BgtR6gROyGZyL1faB4u%2F6jToryyOzVgpWCsI36uklgG1Nl21lRQ2Om5edylfSVIfwcYt2o26IbDMyt0l8Mqp5M3DvD3aGYHEztHKHVCKOuoPRFcMs73Tkzd2IbbHTogUmekwSS7y1MITArT%2B40PRBnYZcEysgGr0s0oSfJifmBC2P9dZKye6H9hPTrIpVsnzzJl2YW6QmuuthS13%2B%2Fuvp1TRY7alZMjxT2p%2B98PfMY%2BwnDZyvm52k7f8WX%2B6LeG5huBK4lCHaAny6JXnXlONYhDvbtM5g7KR7YR%2Bz%2FPbMHPZM76Zm1xx0f%2FEPjypHke%2BUphqjA7tvEGHV0iK67npb9eJtso0hP3oeaaD%2FszzeerAgf2orLFHNFHYtq5GzcRGehMzuhLWTYF3RBrRaWkEewpl4BJtIiGvX35M5FsfydKQ0KN04O1m5WbYWCs0HjGd5gaYO1exE8HZtfG382RzpuXdZcnlKh6fSA7fL3U%2B2VqxfG5T5C4QHWzqx3MMTqfWFK5Q%2Bm0VTfpLWYMrCQR61R9rM21esBZYSVDUYlYAS6YqBCPi%2B7ASDJDEcus4jqK7CDR1KEPEYQNTjugaQOZV%2BJ7%2Fl%2FdTZMWDfJm%2B1qokmi4F%2FIGiaGELwkAKaHsVOTr2R2Dk%2FvSjaN11r1lHMVtPNAYFgkPH%2FI32v0yGF7CIoDZz0RQraYSRWeA1EynXmktTNbEGtiDXtQzCe%2BTmKj5qBJWzzSbNG6ybRsEJLIBWXCIQUr7eE6Yq%2Bcf38CG85uF7v1TQRgFW1%2BalPL4gYFjAx8w38O3nQY6mwGkkaWu2yhK5Y6qWhusg%2FePqQQiM9vcFWlmU9y%2Be0EQbx9LvUisuTKSvrzRFv9dtCrcDt7XDB1bbaEJGwxSXOt09vjjls6U3ttbTU0m0o00t7%2BW5MfmCH7%2BPhW77xv61uHAnRW54KZ9W9b8LaC2NUPDoPdXvFUqW%2FFi6a4bjbNXzglXChqsR2qksX23ljxbpAmPceEmYxwd39ss%2FQ%3D%3D&X-Amz-SignedHeaders=host&X-Amz-Signature=0f3494f594c4a2dbb244fded7b28d8386a931b6d59851aab320125258193ce01</a></td></tr></table></td></tr><tr><td><b>analysis</b></td><td><table class=\"kda_table\"><tr><td><b>can_execute</b></td><td><pre>True</pre></td></tr></table></td></tr><tr><td><b>schema</b></td><td><pre>(see Schema tab)</pre></td></tr><tr><td><b>data_token_id</b></td><td><pre>d70f10d1-50b6-40a7-a6dd-12a0d400e12b</pre></td></tr><tr><td><b>slice_request</b></td><td><table class=\"kda_table\"><tr><td><b>None</b></td><td><pre>(full dataset used for query)</pre></td></tr></table></td></tr><tr><td><b>request_details</b></td><td><table class=\"kda_table\"><tr><td><b>request_id</b></td><td><pre>579eb608ebf6e3857fd9aa68365a16cd</pre></td></tr></table></td></tr><tr><td><b>query</b></td><td><pre>#Eliminate 0 or fewer plan days\n",
              "let meaningful_txns = Transaction | if(Transaction.payment_plan_days > 0)\n",
              "\n",
              "#Identify backdated records        \n",
              "let max_expires_at = max(meaningful_txns.membership_expire_date)\n",
              "let expiration_is_previous = (max_expires_at < meaningful_txns.transaction_date)\n",
              "\n",
              "#Calculate new expiration, for backdated transactions        \n",
              "let subscription_expires_at =  max_expires_at | if(not(expiration_is_previous)) | else(meaningful_txns.transaction_date)\n",
              "\n",
              "in {\n",
              "    payment_plan_days: meaningful_txns.payment_plan_days,\n",
              "    payment_method_id: meaningful_txns.payment_method_id,\n",
              "    trans_at: meaningful_txns.transaction_date,\n",
              "    membership_expire_date: meaningful_txns.membership_expire_date,\n",
              "    expires_at: subscription_expires_at\n",
              "}</pre></td></tr></table></div></div><div class=\"schema kda_tabcontent\" style=\"display:none;\"><div class=\"kda_scroll_container\"><html><head></head><body><div><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><table border=\"1\" class=\"dataframe\"><thead><tr style=\"text-align: right;\"><th></th><th>column_name</th><th>column_type</th></tr></thead><tbody><tr><th>0</th><td>payment_plan_days</td><td>i64</td></tr><tr><th>1</th><td>payment_method_id</td><td>i64</td></tr><tr><th>2</th><td>trans_at</td><td>timestamp_ns</td></tr><tr><th>3</th><td>membership_expire_date</td><td>timestamp_ns</td></tr><tr><th>4</th><td>expires_at</td><td>timestamp_ns</td></tr></tbody></table></div></body></html></div></div><div class=\"raw kda_tabcontent\" style=\"display:none;\"><div class=\"kda_scroll_container\"><pre>{'dataframe': 'RangeIndex: 288561 entries, 0 to 288560'\n",
              "              'Columns: 6 entries, _key to expires_at'\n",
              "              'dtypes: datetime64[ns](3), float64(2), object(1)'\n",
              "              'memory usage: 13.2+ MB',\n",
              " 'query': '#Eliminate 0 or fewer plan days'\n",
              "          'let meaningful_txns = Transaction | '\n",
              "          'if(Transaction.payment_plan_days > 0)'\n",
              "          ''\n",
              "          '#Identify backdated records        '\n",
              "          'let max_expires_at = max(meaningful_txns.membership_expire_date)'\n",
              "          'let expiration_is_previous = (max_expires_at < '\n",
              "          'meaningful_txns.transaction_date)'\n",
              "          ''\n",
              "          '#Calculate new expiration, for backdated transactions        '\n",
              "          'let subscription_expires_at =  max_expires_at | '\n",
              "          'if(not(expiration_is_previous)) | '\n",
              "          'else(meaningful_txns.transaction_date)'\n",
              "          ''\n",
              "          'in {'\n",
              "          '    payment_plan_days: meaningful_txns.payment_plan_days,'\n",
              "          '    payment_method_id: meaningful_txns.payment_method_id,'\n",
              "          '    trans_at: meaningful_txns.transaction_date,'\n",
              "          '    membership_expire_date: '\n",
              "          'meaningful_txns.membership_expire_date,'\n",
              "          '    expires_at: subscription_expires_at'\n",
              "          '}',\n",
              " 'query_response': state: STATE_SUCCESS\n",
              "config {\n",
              "  data_token_id: \"d70f10d1-50b6-40a7-a6dd-12a0d400e12b\"\n",
              "}\n",
              "analysis {\n",
              "  can_execute: true\n",
              "  schema {\n",
              "    fields {\n",
              "      name: \"payment_plan_days\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_I64\n",
              "      }\n",
              "    }\n",
              "    fields {\n",
              "      name: \"payment_method_id\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_I64\n",
              "      }\n",
              "    }\n",
              "    fields {\n",
              "      name: \"trans_at\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_TIMESTAMP_NANOSECOND\n",
              "      }\n",
              "    }\n",
              "    fields {\n",
              "      name: \"membership_expire_date\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_TIMESTAMP_NANOSECOND\n",
              "      }\n",
              "    }\n",
              "    fields {\n",
              "      name: \"expires_at\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_TIMESTAMP_NANOSECOND\n",
              "      }\n",
              "    }\n",
              "  }\n",
              "}\n",
              "fenl_diagnostics {\n",
              "}\n",
              "metrics {\n",
              "  time_preparing {\n",
              "    nanos: 32727635\n",
              "  }\n",
              "  time_computing {\n",
              "    nanos: 928043176\n",
              "  }\n",
              "  output_files: 1\n",
              "}\n",
              "parquet {\n",
              "  paths: \"https://studio-us-west-2-prod-kaskada.s3.us-west-2.amazonaws.com/wren/dbv1alpha/results/cac2a62e-70d1-452d-bc65-d4dd832cb5b6/v3hh9IcE2Dk0Nn6HOneld_Q1S0uv8zE2MW_56A/2d4fb0ae-41c7-4872-a21f-239be28b5c44.parquet?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=ASIAZJRQG37GWVIVW7CG%2F20221229%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20221229T191811Z&X-Amz-Expires=3600&X-Amz-Security-Token=IQoJb3JpZ2luX2VjEBsaCXVzLXdlc3QtMiJGMEQCIHM2%2F%2BvYM2e7RywlSEwJD7rKvqQxq6Amf6wk2%2BGN4CXbAiAwrjgoBZXMxs8IX15Vm%2BbBZzAbGNwlXWiaaCUj11%2FnQir0BAhkEAIaDDYzODk3NzQ5OTA4NSIMWHLflFNCCCCYfX9fKtEEw%2BgtR6gROyGZyL1faB4u%2F6jToryyOzVgpWCsI36uklgG1Nl21lRQ2Om5edylfSVIfwcYt2o26IbDMyt0l8Mqp5M3DvD3aGYHEztHKHVCKOuoPRFcMs73Tkzd2IbbHTogUmekwSS7y1MITArT%2B40PRBnYZcEysgGr0s0oSfJifmBC2P9dZKye6H9hPTrIpVsnzzJl2YW6QmuuthS13%2B%2Fuvp1TRY7alZMjxT2p%2B98PfMY%2BwnDZyvm52k7f8WX%2B6LeG5huBK4lCHaAny6JXnXlONYhDvbtM5g7KR7YR%2Bz%2FPbMHPZM76Zm1xx0f%2FEPjypHke%2BUphqjA7tvEGHV0iK67npb9eJtso0hP3oeaaD%2FszzeerAgf2orLFHNFHYtq5GzcRGehMzuhLWTYF3RBrRaWkEewpl4BJtIiGvX35M5FsfydKQ0KN04O1m5WbYWCs0HjGd5gaYO1exE8HZtfG382RzpuXdZcnlKh6fSA7fL3U%2B2VqxfG5T5C4QHWzqx3MMTqfWFK5Q%2Bm0VTfpLWYMrCQR61R9rM21esBZYSVDUYlYAS6YqBCPi%2B7ASDJDEcus4jqK7CDR1KEPEYQNTjugaQOZV%2BJ7%2Fl%2FdTZMWDfJm%2B1qokmi4F%2FIGiaGELwkAKaHsVOTr2R2Dk%2FvSjaN11r1lHMVtPNAYFgkPH%2FI32v0yGF7CIoDZz0RQraYSRWeA1EynXmktTNbEGtiDXtQzCe%2BTmKj5qBJWzzSbNG6ybRsEJLIBWXCIQUr7eE6Yq%2Bcf38CG85uF7v1TQRgFW1%2BalPL4gYFjAx8w38O3nQY6mwGkkaWu2yhK5Y6qWhusg%2FePqQQiM9vcFWlmU9y%2Be0EQbx9LvUisuTKSvrzRFv9dtCrcDt7XDB1bbaEJGwxSXOt09vjjls6U3ttbTU0m0o00t7%2BW5MfmCH7%2BPhW77xv61uHAnRW54KZ9W9b8LaC2NUPDoPdXvFUqW%2FFi6a4bjbNXzglXChqsR2qksX23ljxbpAmPceEmYxwd39ss%2FQ%3D%3D&X-Amz-SignedHeaders=host&X-Amz-Signature=0f3494f594c4a2dbb244fded7b28d8386a931b6d59851aab320125258193ce01\"\n",
              "}\n",
              "request_details {\n",
              "  request_id: \"579eb608ebf6e3857fd9aa68365a16cd\"\n",
              "}\n",
              "query_id: \"00aab42f-0bb5-4e40-b12f-65fb3668f783\"\n",
              "}</pre></div></div></div>"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Create a view of this query to share the definition of cleaned transactions with all downstream features."
      ],
      "metadata": {
        "id": "Clwz6wZVFmKf"
      },
      "id": "Clwz6wZVFmKf"
    },
    {
      "cell_type": "code",
      "source": [
        "view.create_view(\n",
        "  view_name = \"CleanedTransactions\", \n",
        "  expression = df_cleaned_transactions.query,\n",
        ")"
      ],
      "metadata": {
        "id": "YgG3JgbmZNAj"
      },
      "id": "YgG3JgbmZNAj",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Step 3: Generate Labeled Dataset\n",
        "\n",
        "Shift cleaned transactions forward in time 30 days to check if a renewal event happened. \n"
      ],
      "metadata": {
        "id": "JVvkHNUeZUDe"
      },
      "id": "JVvkHNUeZUDe"
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Step 3.a Define labels in FENL"
      ],
      "metadata": {
        "id": "naog1gtC7rye"
      },
      "id": "naog1gtC7rye"
    },
    {
      "cell_type": "code",
      "source": [
        "%%fenl --var df_label_churn\n",
        "\n",
        "# 2. Churned Transactions\n",
        "\n",
        "let shifted_txn = CleanedTransactions \n",
        "    | shift_to($input.membership_expire_date | add_time(days(30)))\n",
        "\n",
        "let last_txn = last(CleanedTransactions)\n",
        "\n",
        "let membership_history = {\n",
        "    trans_at: shifted_txn.trans_at,\n",
        "    expires_at: shifted_txn.membership_expire_date,\n",
        "    churned: shifted_txn.trans_at == last_txn.trans_at,\n",
        "} | when(is_valid(shifted_txn))\n",
        "\n",
        "let initial_txn = membership_history.trans_at | first()\n",
        "let churn_txn = membership_history | if(membership_history.churned) | first()\n",
        "\n",
        "let churn_subscription = {\n",
        "    starts_at: initial_txn,\n",
        "    ends_at: churn_txn.trans_at,\n",
        "    churned: true\n",
        "} \n",
        "let active_subscription = {\n",
        "    starts_at: initial_txn,\n",
        "    ends_at: null,\n",
        "    churned: false\n",
        "}\n",
        "let current_subscription = churn_subscription | if(is_valid(churn_txn)) | else(active_subscription)\n",
        "let first_transaction = CleanedTransactions | first()\n",
        "\n",
        "in{\n",
        "    churned: current_subscription.churned, \n",
        "    payment_plan_days: first_transaction.payment_plan_days,\n",
        "    payment_method_id: first_transaction.payment_method_id,\n",
        "    starts_at: current_subscription.starts_at,\n",
        "    ends_at: current_subscription.ends_at,\n",
        "} | when(is_valid(current_subscription))"
      ],
      "metadata": {
        "id": "8IELSyc7Z5ZJ",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 460
        },
        "outputId": "4722dbb1-6764-424a-f41b-1e83027bd343"
      },
      "id": "8IELSyc7Z5ZJ",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "<style>table.kda_table {\n",
              "    border: 1px solid grey !important;\n",
              "    border-collapse: collapse !important;\n",
              "    border-spacing: 0 !important;\n",
              "    font-size: 14px !important;\n",
              "    margin-bottom: 6px !important;\n",
              "}\n",
              "\n",
              "table.kda_table table {\n",
              "    margin-bottom: 0 !important;\n",
              "}\n",
              "\n",
              ".kda_table td, .kda_table th {\n",
              "    border: 1px solid grey !important;\n",
              "    border-collapse: collapse !important;\n",
              "    padding: 6px !important;\n",
              "    text-align: left !important;\n",
              "    vertical-align: top !important;\n",
              "}\n",
              "\n",
              ".kda_table tr {\n",
              "    background-color: inherit !important;\n",
              "}\n",
              "\n",
              "/* Style the tab */\n",
              ".kda_tab {\n",
              "    overflow: hidden;\n",
              "    border-bottom: 1px solid grey;\n",
              "    background-color: inherit;\n",
              "}\n",
              "\n",
              "/* Style the buttons that are used to open the tab content */\n",
              ".kda_tab button {\n",
              "    background-color: inherit;\n",
              "    border-top: 1px solid grey;\n",
              "    border-right: 1px solid grey;\n",
              "    border-left: 1px solid grey;\n",
              "    border-bottom: none;\n",
              "    border-radius: 5px 5px 0px 0px;\n",
              "    color: inherit;\n",
              "    cursor: pointer;\n",
              "    float: left;\n",
              "    margin: 2px 8px 0px 2px;\n",
              "    outline: none;\n",
              "    padding: 5px 16px;\n",
              "    transition: 0.3s;\n",
              "}\n",
              "\n",
              "/* Change background color of buttons on hover */\n",
              ".kda_tab button:hover {\n",
              "    background-color: grey;\n",
              "}\n",
              "\n",
              "/* Create an active/current tablink class */\n",
              ".kda_tab button.kda_active {\n",
              "    outline: 2px solid grey;\n",
              "}\n",
              "\n",
              "/* Style the tab content */\n",
              ".kda_tabcontent {\n",
              "    display: none;\n",
              "    padding: 6px;\n",
              "    border: 1px solid grey;\n",
              "    border-top: none;\n",
              "}\n",
              "\n",
              ".kda_scroll_container {\n",
              "    max-height: 400px;\n",
              "    overflow: auto;\n",
              "}\n",
              "</style>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "<script type=\"text/javascript\">function openTab(evt, tabName) {\n",
              "    // Declare all variables\n",
              "    var i, rootElement, tabcontent, tablinks, tabshow;\n",
              "\n",
              "    // Get all elements with class=\"tabcontent\" and hide them\n",
              "    rootElement = evt.currentTarget.parentElement.parentElement;\n",
              "    tabcontent = rootElement.getElementsByClassName(\"kda_tabcontent\");\n",
              "    for (i = 0; i < tabcontent.length; i++) {\n",
              "        tabcontent[i].style.display = \"none\";\n",
              "    }\n",
              "\n",
              "    // Get all elements with class=\"tablinks\" and remove the class \"active\"\n",
              "    tablinks = rootElement.getElementsByClassName(\"kda_tablinks\");\n",
              "    for (i = 0; i < tablinks.length; i++) {\n",
              "        tablinks[i].className = tablinks[i].className.replace(\" kda_active\", \"\");\n",
              "    }\n",
              "\n",
              "    // Show the current tab, and add an \"active\" class to the button that opened the tab\n",
              "    tabshow = rootElement.getElementsByClassName(tabName);\n",
              "    for (i = 0; i < tabshow.length; i++) {\n",
              "        tabshow[i].style.display = \"block\";\n",
              "    }\n",
              "    evt.currentTarget.className += \" kda_active\";\n",
              "}\n",
              "</script>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<fenlmagic.QueryResult at 0x7fdf990c8520>"
            ],
            "text/html": [
              "<div><div class=\"kda_tab\"><button class=\"kda_tablinks kda_active\" onclick=\"openTab(event, 'dataframe')\">Dataframe</button><button class=\"kda_tablinks\" onclick=\"openTab(event, 'details')\">Details</button><button class=\"kda_tablinks\" onclick=\"openTab(event, 'schema')\">Schema</button><button class=\"kda_tablinks\" onclick=\"openTab(event, 'raw')\">Raw</button></div><div class=\"dataframe kda_tabcontent\" style=\"display:block;\"><div class=\"kda_scroll_container\"><html><head></head><body><div><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><table border=\"1\" class=\"dataframe\"><thead><tr style=\"text-align: right;\"><th></th><th>_key</th><th>churned</th><th>payment_plan_days</th><th>payment_method_id</th><th>starts_at</th><th>ends_at</th></tr></thead><tbody><tr><th>0</th><td>5z4w+3H7Qu8eJxhO20SAOBc+6nPLW/Q5eY4CMKUJVGU=</td><td>True</td><td>30.0</td><td>24.0</td><td>2015-01-23</td><td>2015-01-23</td></tr><tr><th>1</th><td>KSyMAEmMLIMGSghRfzF44TKzYC/K1zh7wi0gEFc/GAw=</td><td>True</td><td>31.0</td><td>27.0</td><td>2015-01-23</td><td>2015-01-23</td></tr><tr><th>2</th><td>Ge5nM+AdnWxFm+nIORW+bfU2VyMqeGUhXs6RwXsu/+w=</td><td>False</td><td>NaN</td><td>NaN</td><td>2015-01-26</td><td>NaT</td></tr><tr><th>3</th><td>YhjdS3H6Oa444WB7I//4DkEX5kQUq8Yk8lr3djuhS8Y=</td><td>False</td><td>NaN</td><td>NaN</td><td>2015-01-26</td><td>NaT</td></tr><tr><th>4</th><td>Ge5nM+AdnWxFm+nIORW+bfU2VyMqeGUhXs6RwXsu/+w=</td><td>False</td><td>30.0</td><td>24.0</td><td>2015-01-26</td><td>NaT</td></tr><tr><th>...</th><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td></tr><tr><th>492697</th><td>TNOcP07Mry/UFtgvxn9bUPgq8Zf6dwdWQjn9kv7P+g0=</td><td>True</td><td>30.0</td><td>41.0</td><td>2016-12-31</td><td>2017-02-28</td></tr><tr><th>492698</th><td>My/CEivMfiCWmSl9C1BNarV80eaMdd+LjsqnR8g6fsU=</td><td>True</td><td>NaN</td><td>NaN</td><td>2015-11-30</td><td>2017-02-28</td></tr><tr><th>492699</th><td>OKdMxAyGn1bJ43uCyWPpr8hYYX0/gdE1Q8Jrs1mGYuI=</td><td>True</td><td>NaN</td><td>NaN</td><td>2015-11-30</td><td>2017-02-28</td></tr><tr><th>492700</th><td>3XvMZe4vmCLvPQJoVdOMNt4QE4U1s5dXIW4JiebDtss=</td><td>True</td><td>30.0</td><td>41.0</td><td>2015-01-30</td><td>2015-08-31</td></tr><tr><th>492701</th><td>MvNHn2nZqq7nBBuj6yS7ISvZrvnWx1BJvFpxjNcMvmc=</td><td>True</td><td>NaN</td><td>NaN</td><td>2015-11-30</td><td>2017-02-28</td></tr></tbody></table><p>492702 rows × 6 columns</p></div></body></html></div></div><div class=\"details kda_tabcontent\" style=\"display:none;\"><div class=\"kda_scroll_container\"><table class=\"kda_table\"><tr><td><b>state</b></td><td>SUCCESS</td></tr><tr><td><b>query_id</b></td><td>1d024701-8e5e-4d78-bd05-155b73703259</td></tr><tr><td><b>metrics</b></td><td><table class=\"kda_table\"><tr><td><b>time_preparing</b></td><td>0.04s</td></tr><tr><td><b>time_computing</b></td><td>1.269s</td></tr><tr><td><b>output_files</b></td><td>1</td></tr></table></td></tr><tr><td><b>parquet</b></td><td><table class=\"kda_table\"><tr><th>index</th><th>path</th></tr><tr><td><pre>0</pre></td><td><a href=\"https://studio-us-west-2-prod-kaskada.s3.us-west-2.amazonaws.com/wren/dbv1alpha/results/cac2a62e-70d1-452d-bc65-d4dd832cb5b6/SowIgrf0gwmYEtA38eWxzU-zlFjHRGSz22t-LA/6c0dada2-d814-4839-b1ce-8da7beeb28a5.parquet?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=ASIAZJRQG37GWVIVW7CG%2F20221229%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20221229T191847Z&X-Amz-Expires=3600&X-Amz-Security-Token=IQoJb3JpZ2luX2VjEBsaCXVzLXdlc3QtMiJGMEQCIHM2%2F%2BvYM2e7RywlSEwJD7rKvqQxq6Amf6wk2%2BGN4CXbAiAwrjgoBZXMxs8IX15Vm%2BbBZzAbGNwlXWiaaCUj11%2FnQir0BAhkEAIaDDYzODk3NzQ5OTA4NSIMWHLflFNCCCCYfX9fKtEEw%2BgtR6gROyGZyL1faB4u%2F6jToryyOzVgpWCsI36uklgG1Nl21lRQ2Om5edylfSVIfwcYt2o26IbDMyt0l8Mqp5M3DvD3aGYHEztHKHVCKOuoPRFcMs73Tkzd2IbbHTogUmekwSS7y1MITArT%2B40PRBnYZcEysgGr0s0oSfJifmBC2P9dZKye6H9hPTrIpVsnzzJl2YW6QmuuthS13%2B%2Fuvp1TRY7alZMjxT2p%2B98PfMY%2BwnDZyvm52k7f8WX%2B6LeG5huBK4lCHaAny6JXnXlONYhDvbtM5g7KR7YR%2Bz%2FPbMHPZM76Zm1xx0f%2FEPjypHke%2BUphqjA7tvEGHV0iK67npb9eJtso0hP3oeaaD%2FszzeerAgf2orLFHNFHYtq5GzcRGehMzuhLWTYF3RBrRaWkEewpl4BJtIiGvX35M5FsfydKQ0KN04O1m5WbYWCs0HjGd5gaYO1exE8HZtfG382RzpuXdZcnlKh6fSA7fL3U%2B2VqxfG5T5C4QHWzqx3MMTqfWFK5Q%2Bm0VTfpLWYMrCQR61R9rM21esBZYSVDUYlYAS6YqBCPi%2B7ASDJDEcus4jqK7CDR1KEPEYQNTjugaQOZV%2BJ7%2Fl%2FdTZMWDfJm%2B1qokmi4F%2FIGiaGELwkAKaHsVOTr2R2Dk%2FvSjaN11r1lHMVtPNAYFgkPH%2FI32v0yGF7CIoDZz0RQraYSRWeA1EynXmktTNbEGtiDXtQzCe%2BTmKj5qBJWzzSbNG6ybRsEJLIBWXCIQUr7eE6Yq%2Bcf38CG85uF7v1TQRgFW1%2BalPL4gYFjAx8w38O3nQY6mwGkkaWu2yhK5Y6qWhusg%2FePqQQiM9vcFWlmU9y%2Be0EQbx9LvUisuTKSvrzRFv9dtCrcDt7XDB1bbaEJGwxSXOt09vjjls6U3ttbTU0m0o00t7%2BW5MfmCH7%2BPhW77xv61uHAnRW54KZ9W9b8LaC2NUPDoPdXvFUqW%2FFi6a4bjbNXzglXChqsR2qksX23ljxbpAmPceEmYxwd39ss%2FQ%3D%3D&X-Amz-SignedHeaders=host&X-Amz-Signature=71039a87f0de9d0941816ca744b2dcc0f5ee4cacdb368292aefa5d1261b18a00\">https://studio-us-west-2-prod-kaskada.s3.us-west-2.amazonaws.com/wren/dbv1alpha/results/cac2a62e-70d1-452d-bc65-d4dd832cb5b6/SowIgrf0gwmYEtA38eWxzU-zlFjHRGSz22t-LA/6c0dada2-d814-4839-b1ce-8da7beeb28a5.parquet?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=ASIAZJRQG37GWVIVW7CG%2F20221229%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20221229T191847Z&X-Amz-Expires=3600&X-Amz-Security-Token=IQoJb3JpZ2luX2VjEBsaCXVzLXdlc3QtMiJGMEQCIHM2%2F%2BvYM2e7RywlSEwJD7rKvqQxq6Amf6wk2%2BGN4CXbAiAwrjgoBZXMxs8IX15Vm%2BbBZzAbGNwlXWiaaCUj11%2FnQir0BAhkEAIaDDYzODk3NzQ5OTA4NSIMWHLflFNCCCCYfX9fKtEEw%2BgtR6gROyGZyL1faB4u%2F6jToryyOzVgpWCsI36uklgG1Nl21lRQ2Om5edylfSVIfwcYt2o26IbDMyt0l8Mqp5M3DvD3aGYHEztHKHVCKOuoPRFcMs73Tkzd2IbbHTogUmekwSS7y1MITArT%2B40PRBnYZcEysgGr0s0oSfJifmBC2P9dZKye6H9hPTrIpVsnzzJl2YW6QmuuthS13%2B%2Fuvp1TRY7alZMjxT2p%2B98PfMY%2BwnDZyvm52k7f8WX%2B6LeG5huBK4lCHaAny6JXnXlONYhDvbtM5g7KR7YR%2Bz%2FPbMHPZM76Zm1xx0f%2FEPjypHke%2BUphqjA7tvEGHV0iK67npb9eJtso0hP3oeaaD%2FszzeerAgf2orLFHNFHYtq5GzcRGehMzuhLWTYF3RBrRaWkEewpl4BJtIiGvX35M5FsfydKQ0KN04O1m5WbYWCs0HjGd5gaYO1exE8HZtfG382RzpuXdZcnlKh6fSA7fL3U%2B2VqxfG5T5C4QHWzqx3MMTqfWFK5Q%2Bm0VTfpLWYMrCQR61R9rM21esBZYSVDUYlYAS6YqBCPi%2B7ASDJDEcus4jqK7CDR1KEPEYQNTjugaQOZV%2BJ7%2Fl%2FdTZMWDfJm%2B1qokmi4F%2FIGiaGELwkAKaHsVOTr2R2Dk%2FvSjaN11r1lHMVtPNAYFgkPH%2FI32v0yGF7CIoDZz0RQraYSRWeA1EynXmktTNbEGtiDXtQzCe%2BTmKj5qBJWzzSbNG6ybRsEJLIBWXCIQUr7eE6Yq%2Bcf38CG85uF7v1TQRgFW1%2BalPL4gYFjAx8w38O3nQY6mwGkkaWu2yhK5Y6qWhusg%2FePqQQiM9vcFWlmU9y%2Be0EQbx9LvUisuTKSvrzRFv9dtCrcDt7XDB1bbaEJGwxSXOt09vjjls6U3ttbTU0m0o00t7%2BW5MfmCH7%2BPhW77xv61uHAnRW54KZ9W9b8LaC2NUPDoPdXvFUqW%2FFi6a4bjbNXzglXChqsR2qksX23ljxbpAmPceEmYxwd39ss%2FQ%3D%3D&X-Amz-SignedHeaders=host&X-Amz-Signature=71039a87f0de9d0941816ca744b2dcc0f5ee4cacdb368292aefa5d1261b18a00</a></td></tr></table></td></tr><tr><td><b>analysis</b></td><td><table class=\"kda_table\"><tr><td><b>can_execute</b></td><td><pre>True</pre></td></tr></table></td></tr><tr><td><b>schema</b></td><td><pre>(see Schema tab)</pre></td></tr><tr><td><b>data_token_id</b></td><td><pre>d70f10d1-50b6-40a7-a6dd-12a0d400e12b</pre></td></tr><tr><td><b>slice_request</b></td><td><table class=\"kda_table\"><tr><td><b>None</b></td><td><pre>(full dataset used for query)</pre></td></tr></table></td></tr><tr><td><b>request_details</b></td><td><table class=\"kda_table\"><tr><td><b>request_id</b></td><td><pre>d40200bcc6cb9e5ecf24a51142438178</pre></td></tr></table></td></tr><tr><td><b>query</b></td><td><pre># 2. Churned Transactions\n",
              "\n",
              "let shifted_txn = CleanedTransactions \n",
              "    | shift_to($input.membership_expire_date | add_time(days(30)))\n",
              "\n",
              "let last_txn = last(CleanedTransactions)\n",
              "\n",
              "let membership_history = {\n",
              "    trans_at: shifted_txn.trans_at,\n",
              "    expires_at: shifted_txn.membership_expire_date,\n",
              "    churned: shifted_txn.trans_at == last_txn.trans_at,\n",
              "} | when(is_valid(shifted_txn))\n",
              "\n",
              "let initial_txn = membership_history.trans_at | first()\n",
              "let churn_txn = membership_history | if(membership_history.churned) | first()\n",
              "\n",
              "let churn_subscription = {\n",
              "    starts_at: initial_txn,\n",
              "    ends_at: churn_txn.trans_at,\n",
              "    churned: true\n",
              "} \n",
              "let active_subscription = {\n",
              "    starts_at: initial_txn,\n",
              "    ends_at: null,\n",
              "    churned: false\n",
              "}\n",
              "let current_subscription = churn_subscription | if(is_valid(churn_txn)) | else(active_subscription)\n",
              "let first_transaction = CleanedTransactions | first()\n",
              "\n",
              "in{\n",
              "    churned: current_subscription.churned, \n",
              "    payment_plan_days: first_transaction.payment_plan_days,\n",
              "    payment_method_id: first_transaction.payment_method_id,\n",
              "    starts_at: current_subscription.starts_at,\n",
              "    ends_at: current_subscription.ends_at,\n",
              "} | when(is_valid(current_subscription))</pre></td></tr></table></div></div><div class=\"schema kda_tabcontent\" style=\"display:none;\"><div class=\"kda_scroll_container\"><html><head></head><body><div><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><table border=\"1\" class=\"dataframe\"><thead><tr style=\"text-align: right;\"><th></th><th>column_name</th><th>column_type</th></tr></thead><tbody><tr><th>0</th><td>churned</td><td>bool</td></tr><tr><th>1</th><td>payment_plan_days</td><td>i64</td></tr><tr><th>2</th><td>payment_method_id</td><td>i64</td></tr><tr><th>3</th><td>starts_at</td><td>timestamp_ns</td></tr><tr><th>4</th><td>ends_at</td><td>timestamp_ns</td></tr></tbody></table></div></body></html></div></div><div class=\"raw kda_tabcontent\" style=\"display:none;\"><div class=\"kda_scroll_container\"><pre>{'dataframe': 'RangeIndex: 492702 entries, 0 to 492701'\n",
              "              'Columns: 6 entries, _key to ends_at'\n",
              "              'dtypes: bool(1), datetime64[ns](2), float64(2), object(1)'\n",
              "              'memory usage: 19.3+ MB',\n",
              " 'query': '# 2. Churned Transactions'\n",
              "          ''\n",
              "          'let shifted_txn = CleanedTransactions '\n",
              "          '    | shift_to($input.membership_expire_date | add_time(days(30)))'\n",
              "          ''\n",
              "          'let last_txn = last(CleanedTransactions)'\n",
              "          ''\n",
              "          'let membership_history = {'\n",
              "          '    trans_at: shifted_txn.trans_at,'\n",
              "          '    expires_at: shifted_txn.membership_expire_date,'\n",
              "          '    churned: shifted_txn.trans_at == last_txn.trans_at,'\n",
              "          '} | when(is_valid(shifted_txn))'\n",
              "          ''\n",
              "          'let initial_txn = membership_history.trans_at | first()'\n",
              "          'let churn_txn = membership_history | if(membership_history.churned) '\n",
              "          '| first()'\n",
              "          ''\n",
              "          'let churn_subscription = {'\n",
              "          '    starts_at: initial_txn,'\n",
              "          '    ends_at: churn_txn.trans_at,'\n",
              "          '    churned: true'\n",
              "          '} '\n",
              "          'let active_subscription = {'\n",
              "          '    starts_at: initial_txn,'\n",
              "          '    ends_at: null,'\n",
              "          '    churned: false'\n",
              "          '}'\n",
              "          'let current_subscription = churn_subscription | '\n",
              "          'if(is_valid(churn_txn)) | else(active_subscription)'\n",
              "          'let first_transaction = CleanedTransactions | first()'\n",
              "          ''\n",
              "          'in{'\n",
              "          '    churned: current_subscription.churned, '\n",
              "          '    payment_plan_days: first_transaction.payment_plan_days,'\n",
              "          '    payment_method_id: first_transaction.payment_method_id,'\n",
              "          '    starts_at: current_subscription.starts_at,'\n",
              "          '    ends_at: current_subscription.ends_at,'\n",
              "          '} | when(is_valid(current_subscription))',\n",
              " 'query_response': state: STATE_SUCCESS\n",
              "config {\n",
              "  data_token_id: \"d70f10d1-50b6-40a7-a6dd-12a0d400e12b\"\n",
              "}\n",
              "analysis {\n",
              "  can_execute: true\n",
              "  schema {\n",
              "    fields {\n",
              "      name: \"churned\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_BOOL\n",
              "      }\n",
              "    }\n",
              "    fields {\n",
              "      name: \"payment_plan_days\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_I64\n",
              "      }\n",
              "    }\n",
              "    fields {\n",
              "      name: \"payment_method_id\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_I64\n",
              "      }\n",
              "    }\n",
              "    fields {\n",
              "      name: \"starts_at\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_TIMESTAMP_NANOSECOND\n",
              "      }\n",
              "    }\n",
              "    fields {\n",
              "      name: \"ends_at\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_TIMESTAMP_NANOSECOND\n",
              "      }\n",
              "    }\n",
              "  }\n",
              "}\n",
              "fenl_diagnostics {\n",
              "}\n",
              "metrics {\n",
              "  time_preparing {\n",
              "    nanos: 40657490\n",
              "  }\n",
              "  time_computing {\n",
              "    seconds: 1\n",
              "    nanos: 269248023\n",
              "  }\n",
              "  output_files: 1\n",
              "}\n",
              "parquet {\n",
              "  paths: \"https://studio-us-west-2-prod-kaskada.s3.us-west-2.amazonaws.com/wren/dbv1alpha/results/cac2a62e-70d1-452d-bc65-d4dd832cb5b6/SowIgrf0gwmYEtA38eWxzU-zlFjHRGSz22t-LA/6c0dada2-d814-4839-b1ce-8da7beeb28a5.parquet?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=ASIAZJRQG37GWVIVW7CG%2F20221229%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20221229T191847Z&X-Amz-Expires=3600&X-Amz-Security-Token=IQoJb3JpZ2luX2VjEBsaCXVzLXdlc3QtMiJGMEQCIHM2%2F%2BvYM2e7RywlSEwJD7rKvqQxq6Amf6wk2%2BGN4CXbAiAwrjgoBZXMxs8IX15Vm%2BbBZzAbGNwlXWiaaCUj11%2FnQir0BAhkEAIaDDYzODk3NzQ5OTA4NSIMWHLflFNCCCCYfX9fKtEEw%2BgtR6gROyGZyL1faB4u%2F6jToryyOzVgpWCsI36uklgG1Nl21lRQ2Om5edylfSVIfwcYt2o26IbDMyt0l8Mqp5M3DvD3aGYHEztHKHVCKOuoPRFcMs73Tkzd2IbbHTogUmekwSS7y1MITArT%2B40PRBnYZcEysgGr0s0oSfJifmBC2P9dZKye6H9hPTrIpVsnzzJl2YW6QmuuthS13%2B%2Fuvp1TRY7alZMjxT2p%2B98PfMY%2BwnDZyvm52k7f8WX%2B6LeG5huBK4lCHaAny6JXnXlONYhDvbtM5g7KR7YR%2Bz%2FPbMHPZM76Zm1xx0f%2FEPjypHke%2BUphqjA7tvEGHV0iK67npb9eJtso0hP3oeaaD%2FszzeerAgf2orLFHNFHYtq5GzcRGehMzuhLWTYF3RBrRaWkEewpl4BJtIiGvX35M5FsfydKQ0KN04O1m5WbYWCs0HjGd5gaYO1exE8HZtfG382RzpuXdZcnlKh6fSA7fL3U%2B2VqxfG5T5C4QHWzqx3MMTqfWFK5Q%2Bm0VTfpLWYMrCQR61R9rM21esBZYSVDUYlYAS6YqBCPi%2B7ASDJDEcus4jqK7CDR1KEPEYQNTjugaQOZV%2BJ7%2Fl%2FdTZMWDfJm%2B1qokmi4F%2FIGiaGELwkAKaHsVOTr2R2Dk%2FvSjaN11r1lHMVtPNAYFgkPH%2FI32v0yGF7CIoDZz0RQraYSRWeA1EynXmktTNbEGtiDXtQzCe%2BTmKj5qBJWzzSbNG6ybRsEJLIBWXCIQUr7eE6Yq%2Bcf38CG85uF7v1TQRgFW1%2BalPL4gYFjAx8w38O3nQY6mwGkkaWu2yhK5Y6qWhusg%2FePqQQiM9vcFWlmU9y%2Be0EQbx9LvUisuTKSvrzRFv9dtCrcDt7XDB1bbaEJGwxSXOt09vjjls6U3ttbTU0m0o00t7%2BW5MfmCH7%2BPhW77xv61uHAnRW54KZ9W9b8LaC2NUPDoPdXvFUqW%2FFi6a4bjbNXzglXChqsR2qksX23ljxbpAmPceEmYxwd39ss%2FQ%3D%3D&X-Amz-SignedHeaders=host&X-Amz-Signature=71039a87f0de9d0941816ca744b2dcc0f5ee4cacdb368292aefa5d1261b18a00\"\n",
              "}\n",
              "request_details {\n",
              "  request_id: \"d40200bcc6cb9e5ecf24a51142438178\"\n",
              "}\n",
              "query_id: \"1d024701-8e5e-4d78-bd05-155b73703259\"\n",
              "}</pre></div></div></div>"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Save labeled view to generate train test sets at different times"
      ],
      "metadata": {
        "id": "6058-Fecff2s"
      },
      "id": "6058-Fecff2s"
    },
    {
      "cell_type": "code",
      "source": [
        "view.create_view(\n",
        "  view_name = \"LabeledTransactions\", \n",
        "  expression = df_label_churn.query,\n",
        ")"
      ],
      "metadata": {
        "id": "zkS2SXsNbY9S",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 460
        },
        "outputId": "e12ef6bc-31d7-4378-ae29-7021bb0de4be"
      },
      "id": "zkS2SXsNbY9S",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "<style>table.kda_table {\n",
              "    border: 1px solid grey !important;\n",
              "    border-collapse: collapse !important;\n",
              "    border-spacing: 0 !important;\n",
              "    font-size: 14px !important;\n",
              "    margin-bottom: 6px !important;\n",
              "}\n",
              "\n",
              "table.kda_table table {\n",
              "    margin-bottom: 0 !important;\n",
              "}\n",
              "\n",
              ".kda_table td, .kda_table th {\n",
              "    border: 1px solid grey !important;\n",
              "    border-collapse: collapse !important;\n",
              "    padding: 6px !important;\n",
              "    text-align: left !important;\n",
              "    vertical-align: top !important;\n",
              "}\n",
              "\n",
              ".kda_table tr {\n",
              "    background-color: inherit !important;\n",
              "}\n",
              "\n",
              "/* Style the tab */\n",
              ".kda_tab {\n",
              "    overflow: hidden;\n",
              "    border-bottom: 1px solid grey;\n",
              "    background-color: inherit;\n",
              "}\n",
              "\n",
              "/* Style the buttons that are used to open the tab content */\n",
              ".kda_tab button {\n",
              "    background-color: inherit;\n",
              "    border-top: 1px solid grey;\n",
              "    border-right: 1px solid grey;\n",
              "    border-left: 1px solid grey;\n",
              "    border-bottom: none;\n",
              "    border-radius: 5px 5px 0px 0px;\n",
              "    color: inherit;\n",
              "    cursor: pointer;\n",
              "    float: left;\n",
              "    margin: 2px 8px 0px 2px;\n",
              "    outline: none;\n",
              "    padding: 5px 16px;\n",
              "    transition: 0.3s;\n",
              "}\n",
              "\n",
              "/* Change background color of buttons on hover */\n",
              ".kda_tab button:hover {\n",
              "    background-color: grey;\n",
              "}\n",
              "\n",
              "/* Create an active/current tablink class */\n",
              ".kda_tab button.kda_active {\n",
              "    outline: 2px solid grey;\n",
              "}\n",
              "\n",
              "/* Style the tab content */\n",
              ".kda_tabcontent {\n",
              "    display: none;\n",
              "    padding: 6px;\n",
              "    border: 1px solid grey;\n",
              "    border-top: none;\n",
              "}\n",
              "\n",
              ".kda_scroll_container {\n",
              "    max-height: 400px;\n",
              "    overflow: auto;\n",
              "}\n",
              "</style>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "<script type=\"text/javascript\">function openTab(evt, tabName) {\n",
              "    // Declare all variables\n",
              "    var i, rootElement, tabcontent, tablinks, tabshow;\n",
              "\n",
              "    // Get all elements with class=\"tabcontent\" and hide them\n",
              "    rootElement = evt.currentTarget.parentElement.parentElement;\n",
              "    tabcontent = rootElement.getElementsByClassName(\"kda_tabcontent\");\n",
              "    for (i = 0; i < tabcontent.length; i++) {\n",
              "        tabcontent[i].style.display = \"none\";\n",
              "    }\n",
              "\n",
              "    // Get all elements with class=\"tablinks\" and remove the class \"active\"\n",
              "    tablinks = rootElement.getElementsByClassName(\"kda_tablinks\");\n",
              "    for (i = 0; i < tablinks.length; i++) {\n",
              "        tablinks[i].className = tablinks[i].className.replace(\" kda_active\", \"\");\n",
              "    }\n",
              "\n",
              "    // Show the current tab, and add an \"active\" class to the button that opened the tab\n",
              "    tabshow = rootElement.getElementsByClassName(tabName);\n",
              "    for (i = 0; i < tabshow.length; i++) {\n",
              "        tabshow[i].style.display = \"block\";\n",
              "    }\n",
              "    evt.currentTarget.className += \" kda_active\";\n",
              "}\n",
              "</script>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "view {\n",
              "  view_id: \"5ddb16e1-1bc2-4092-8ceb-41e91d7a3386\"\n",
              "  view_name: \"LabeledTransactions\"\n",
              "  expression: \"# 2. Churned Transactions\\n\\nlet shifted_txn = CleanedTransactions \\n    | shift_to($input.membership_expire_date | add_time(days(30)))\\n\\nlet last_txn = last(CleanedTransactions)\\n\\nlet membership_history = {\\n    trans_at: shifted_txn.trans_at,\\n    expires_at: shifted_txn.membership_expire_date,\\n    churned: shifted_txn.trans_at == last_txn.trans_at,\\n} | when(is_valid(shifted_txn))\\n\\nlet initial_txn = membership_history.trans_at | first()\\nlet churn_txn = membership_history | if(membership_history.churned) | first()\\n\\nlet churn_subscription = {\\n    starts_at: initial_txn,\\n    ends_at: churn_txn.trans_at,\\n    churned: true\\n} \\nlet active_subscription = {\\n    starts_at: initial_txn,\\n    ends_at: null,\\n    churned: false\\n}\\nlet current_subscription = churn_subscription | if(is_valid(churn_txn)) | else(active_subscription)\\nlet first_transaction = CleanedTransactions | first()\\n\\nin{\\n    churned: current_subscription.churned, \\n    payment_plan_days: first_transaction.payment_plan_days,\\n    payment_method_id: first_transaction.payment_method_id,\\n    starts_at: current_subscription.starts_at,\\n    ends_at: current_subscription.ends_at,\\n} | when(is_valid(current_subscription))\"\n",
              "  result_type {\n",
              "    struct {\n",
              "      fields {\n",
              "        name: \"churned\"\n",
              "        data_type {\n",
              "          primitive: PRIMITIVE_TYPE_BOOL\n",
              "        }\n",
              "      }\n",
              "      fields {\n",
              "        name: \"payment_plan_days\"\n",
              "        data_type {\n",
              "          primitive: PRIMITIVE_TYPE_I64\n",
              "        }\n",
              "      }\n",
              "      fields {\n",
              "        name: \"payment_method_id\"\n",
              "        data_type {\n",
              "          primitive: PRIMITIVE_TYPE_I64\n",
              "        }\n",
              "      }\n",
              "      fields {\n",
              "        name: \"starts_at\"\n",
              "        data_type {\n",
              "          primitive: PRIMITIVE_TYPE_TIMESTAMP_NANOSECOND\n",
              "        }\n",
              "      }\n",
              "      fields {\n",
              "        name: \"ends_at\"\n",
              "        data_type {\n",
              "          primitive: PRIMITIVE_TYPE_TIMESTAMP_NANOSECOND\n",
              "        }\n",
              "      }\n",
              "    }\n",
              "  }\n",
              "  analysis {\n",
              "    fenl_diagnostics {\n",
              "    }\n",
              "    free_names: \"CleanedTransactions\"\n",
              "    free_names: \"Transaction\"\n",
              "  }\n",
              "}\n",
              "request_details {\n",
              "  request_id: \"b203a5d24801d6a81707a48bec3e46d4\"\n",
              "}\n",
              "analysis {\n",
              "  fenl_diagnostics {\n",
              "  }\n",
              "  free_names: \"CleanedTransactions\"\n",
              "  free_names: \"Transaction\"\n",
              "}"
            ],
            "text/html": [
              "<div><div class=\"kda_tab\"><button class=\"kda_tablinks kda_active\" onclick=\"openTab(event, 'details')\">Details</button><button class=\"kda_tablinks\" onclick=\"openTab(event, 'schema')\">Schema</button><button class=\"kda_tablinks\" onclick=\"openTab(event, 'raw')\">Raw</button></div><div class=\"details kda_tabcontent\" style=\"display:block;\"><div class=\"kda_scroll_container\"><table class=\"kda_table\"><tr><td><b>view</b></td><td><table class=\"kda_table\"><tr><td><b>view_name</b></td><td><pre>LabeledTransactions</pre></td></tr><tr><td><b>expression</b></td><td><pre># 2. Churned Transactions\n",
              "\n",
              "let shifted_txn = CleanedTransactions \n",
              "    | shift_to($input.membership_expire_date | add_time(days(30)))\n",
              "\n",
              "let last_txn = last(CleanedTransactions)\n",
              "\n",
              "let membership_history = {\n",
              "    trans_at: shifted_txn.trans_at,\n",
              "    expires_at: shifted_txn.membership_expire_date,\n",
              "    churned: shifted_txn.trans_at == last_txn.trans_at,\n",
              "} | when(is_valid(shifted_txn))\n",
              "\n",
              "let initial_txn = membership_history.trans_at | first()\n",
              "let churn_txn = membership_history | if(membership_history.churned) | first()\n",
              "\n",
              "let churn_subscription = {\n",
              "    starts_at: initial_txn,\n",
              "    ends_at: churn_txn.trans_at,\n",
              "    churned: true\n",
              "} \n",
              "let active_subscription = {\n",
              "    starts_at: initial_txn,\n",
              "    ends_at: null,\n",
              "    churned: false\n",
              "}\n",
              "let current_subscription = churn_subscription | if(is_valid(churn_txn)) | else(active_subscription)\n",
              "let first_transaction = CleanedTransactions | first()\n",
              "\n",
              "in{\n",
              "    churned: current_subscription.churned, \n",
              "    payment_plan_days: first_transaction.payment_plan_days,\n",
              "    payment_method_id: first_transaction.payment_method_id,\n",
              "    starts_at: current_subscription.starts_at,\n",
              "    ends_at: current_subscription.ends_at,\n",
              "} | when(is_valid(current_subscription))</pre></td></tr><tr><td><b>result_type</b></td><td><pre>&lt;struct&gt; (see Schema tab)</pre></td></tr></table></td></tr><tr><td><b>analysis</b></td><td><table class=\"kda_table\"><tr><td><b>can_execute</b></td><td><pre>False</pre></td></tr></table></td></tr><tr><td><b>request_details</b></td><td><table class=\"kda_table\"><tr><td><b>request_id</b></td><td><pre>b203a5d24801d6a81707a48bec3e46d4</pre></td></tr></table></td></tr></table></div></div><div class=\"schema kda_tabcontent\" style=\"display:none;\"><div class=\"kda_scroll_container\"><html><head></head><body><div><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><table border=\"1\" class=\"dataframe\"><thead><tr style=\"text-align: right;\"><th></th><th>column_name</th><th>column_type</th></tr></thead><tbody><tr><th>0</th><td>churned</td><td>bool</td></tr><tr><th>1</th><td>payment_plan_days</td><td>i64</td></tr><tr><th>2</th><td>payment_method_id</td><td>i64</td></tr><tr><th>3</th><td>starts_at</td><td>timestamp_ns</td></tr><tr><th>4</th><td>ends_at</td><td>timestamp_ns</td></tr></tbody></table></div></body></html></div></div><div class=\"raw kda_tabcontent\" style=\"display:none;\"><div class=\"kda_scroll_container\"><pre>view {\n",
              "  view_id: \"5ddb16e1-1bc2-4092-8ceb-41e91d7a3386\"\n",
              "  view_name: \"LabeledTransactions\"\n",
              "  expression: \"# 2. Churned Transactionslet shifted_txn = CleanedTransactions     | shift_to($input.membership_expire_date | add_time(days(30)))let last_txn = last(CleanedTransactions)let membership_history = {    trans_at: shifted_txn.trans_at,    expires_at: shifted_txn.membership_expire_date,    churned: shifted_txn.trans_at == last_txn.trans_at,} | when(is_valid(shifted_txn))let initial_txn = membership_history.trans_at | first()let churn_txn = membership_history | if(membership_history.churned) | first()let churn_subscription = {    starts_at: initial_txn,    ends_at: churn_txn.trans_at,    churned: true} let active_subscription = {    starts_at: initial_txn,    ends_at: null,    churned: false}let current_subscription = churn_subscription | if(is_valid(churn_txn)) | else(active_subscription)let first_transaction = CleanedTransactions | first()in{    churned: current_subscription.churned,     payment_plan_days: first_transaction.payment_plan_days,    payment_method_id: first_transaction.payment_method_id,    starts_at: current_subscription.starts_at,    ends_at: current_subscription.ends_at,} | when(is_valid(current_subscription))\"\n",
              "  result_type {\n",
              "    struct {\n",
              "      fields {\n",
              "        name: \"churned\"\n",
              "        data_type {\n",
              "          primitive: PRIMITIVE_TYPE_BOOL\n",
              "        }\n",
              "      }\n",
              "      fields {\n",
              "        name: \"payment_plan_days\"\n",
              "        data_type {\n",
              "          primitive: PRIMITIVE_TYPE_I64\n",
              "        }\n",
              "      }\n",
              "      fields {\n",
              "        name: \"payment_method_id\"\n",
              "        data_type {\n",
              "          primitive: PRIMITIVE_TYPE_I64\n",
              "        }\n",
              "      }\n",
              "      fields {\n",
              "        name: \"starts_at\"\n",
              "        data_type {\n",
              "          primitive: PRIMITIVE_TYPE_TIMESTAMP_NANOSECOND\n",
              "        }\n",
              "      }\n",
              "      fields {\n",
              "        name: \"ends_at\"\n",
              "        data_type {\n",
              "          primitive: PRIMITIVE_TYPE_TIMESTAMP_NANOSECOND\n",
              "        }\n",
              "      }\n",
              "    }\n",
              "  }\n",
              "  analysis {\n",
              "    fenl_diagnostics {\n",
              "    }\n",
              "    free_names: \"CleanedTransactions\"\n",
              "    free_names: \"Transaction\"\n",
              "  }\n",
              "}\n",
              "request_details {\n",
              "  request_id: \"b203a5d24801d6a81707a48bec3e46d4\"\n",
              "}\n",
              "analysis {\n",
              "  fenl_diagnostics {\n",
              "  }\n",
              "  free_names: \"CleanedTransactions\"\n",
              "  free_names: \"Transaction\"\n",
              "}\n",
              "</pre></div></div></div>"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Generate train/test sets for any date ranges\n",
        "Example of how to use views with a when to generate various train/test dataset(s) at different times as needed"
      ],
      "metadata": {
        "id": "a0PEcxgyNpsk"
      },
      "id": "a0PEcxgyNpsk"
    },
    {
      "cell_type": "code",
      "source": [
        "%%fenl\n",
        "#Training set \n",
        "LabeledTransactions | when( (LabeledTransactions.starts_at > (\"2017-02-01T00:00:00Z\" as timestamp_ns))\n",
        "    and (LabeledTransactions.starts_at <= (\"2017-02-28T00:00:00Z\" as timestamp_ns)))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 460
        },
        "id": "Y-VGXSjhJ4h-",
        "outputId": "00609576-dd5b-4cb2-e99d-87802b2733de"
      },
      "id": "Y-VGXSjhJ4h-",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "<style>table.kda_table {\n",
              "    border: 1px solid grey !important;\n",
              "    border-collapse: collapse !important;\n",
              "    border-spacing: 0 !important;\n",
              "    font-size: 14px !important;\n",
              "    margin-bottom: 6px !important;\n",
              "}\n",
              "\n",
              "table.kda_table table {\n",
              "    margin-bottom: 0 !important;\n",
              "}\n",
              "\n",
              ".kda_table td, .kda_table th {\n",
              "    border: 1px solid grey !important;\n",
              "    border-collapse: collapse !important;\n",
              "    padding: 6px !important;\n",
              "    text-align: left !important;\n",
              "    vertical-align: top !important;\n",
              "}\n",
              "\n",
              ".kda_table tr {\n",
              "    background-color: inherit !important;\n",
              "}\n",
              "\n",
              "/* Style the tab */\n",
              ".kda_tab {\n",
              "    overflow: hidden;\n",
              "    border-bottom: 1px solid grey;\n",
              "    background-color: inherit;\n",
              "}\n",
              "\n",
              "/* Style the buttons that are used to open the tab content */\n",
              ".kda_tab button {\n",
              "    background-color: inherit;\n",
              "    border-top: 1px solid grey;\n",
              "    border-right: 1px solid grey;\n",
              "    border-left: 1px solid grey;\n",
              "    border-bottom: none;\n",
              "    border-radius: 5px 5px 0px 0px;\n",
              "    color: inherit;\n",
              "    cursor: pointer;\n",
              "    float: left;\n",
              "    margin: 2px 8px 0px 2px;\n",
              "    outline: none;\n",
              "    padding: 5px 16px;\n",
              "    transition: 0.3s;\n",
              "}\n",
              "\n",
              "/* Change background color of buttons on hover */\n",
              ".kda_tab button:hover {\n",
              "    background-color: grey;\n",
              "}\n",
              "\n",
              "/* Create an active/current tablink class */\n",
              ".kda_tab button.kda_active {\n",
              "    outline: 2px solid grey;\n",
              "}\n",
              "\n",
              "/* Style the tab content */\n",
              ".kda_tabcontent {\n",
              "    display: none;\n",
              "    padding: 6px;\n",
              "    border: 1px solid grey;\n",
              "    border-top: none;\n",
              "}\n",
              "\n",
              ".kda_scroll_container {\n",
              "    max-height: 400px;\n",
              "    overflow: auto;\n",
              "}\n",
              "</style>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "<script type=\"text/javascript\">function openTab(evt, tabName) {\n",
              "    // Declare all variables\n",
              "    var i, rootElement, tabcontent, tablinks, tabshow;\n",
              "\n",
              "    // Get all elements with class=\"tabcontent\" and hide them\n",
              "    rootElement = evt.currentTarget.parentElement.parentElement;\n",
              "    tabcontent = rootElement.getElementsByClassName(\"kda_tabcontent\");\n",
              "    for (i = 0; i < tabcontent.length; i++) {\n",
              "        tabcontent[i].style.display = \"none\";\n",
              "    }\n",
              "\n",
              "    // Get all elements with class=\"tablinks\" and remove the class \"active\"\n",
              "    tablinks = rootElement.getElementsByClassName(\"kda_tablinks\");\n",
              "    for (i = 0; i < tablinks.length; i++) {\n",
              "        tablinks[i].className = tablinks[i].className.replace(\" kda_active\", \"\");\n",
              "    }\n",
              "\n",
              "    // Show the current tab, and add an \"active\" class to the button that opened the tab\n",
              "    tabshow = rootElement.getElementsByClassName(tabName);\n",
              "    for (i = 0; i < tabshow.length; i++) {\n",
              "        tabshow[i].style.display = \"block\";\n",
              "    }\n",
              "    evt.currentTarget.className += \" kda_active\";\n",
              "}\n",
              "</script>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<fenlmagic.QueryResult at 0x7fdf955c9280>"
            ],
            "text/html": [
              "<div><div class=\"kda_tab\"><button class=\"kda_tablinks kda_active\" onclick=\"openTab(event, 'dataframe')\">Dataframe</button><button class=\"kda_tablinks\" onclick=\"openTab(event, 'details')\">Details</button><button class=\"kda_tablinks\" onclick=\"openTab(event, 'schema')\">Schema</button><button class=\"kda_tablinks\" onclick=\"openTab(event, 'raw')\">Raw</button></div><div class=\"dataframe kda_tabcontent\" style=\"display:block;\"><div class=\"kda_scroll_container\"><html><head></head><body><div><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><table border=\"1\" class=\"dataframe\"><thead><tr style=\"text-align: right;\"><th></th><th>_key</th><th>churned</th><th>payment_plan_days</th><th>payment_method_id</th><th>starts_at</th><th>ends_at</th></tr></thead><tbody><tr><th>0</th><td>kPtjurZOqN6ulJJz5j/f8ViI6oVcELan6Bsgmj6a53c=</td><td>True</td><td>30</td><td>41</td><td>2017-02-02</td><td>2017-02-02</td></tr><tr><th>1</th><td>USh5g9s7QotP1EWZMHdm/jYZwC52NSrQrbAtNFWXzdg=</td><td>True</td><td>30</td><td>41</td><td>2017-02-03</td><td>2017-02-03</td></tr><tr><th>2</th><td>xaPJHHoEgFQh8bTtiEO5lguwsZeWV0kpAhaBW7F1++c=</td><td>True</td><td>30</td><td>41</td><td>2017-02-04</td><td>2017-02-04</td></tr><tr><th>3</th><td>0V43KsVYP758SYQSRA8SbnqoZdwFiPIYOgVhLDB3BYw=</td><td>True</td><td>30</td><td>41</td><td>2017-02-04</td><td>2017-02-04</td></tr><tr><th>4</th><td>iNXZRu3iohLYBOQjTKHCGI0imcaWb38CooYRibeBBf0=</td><td>True</td><td>30</td><td>41</td><td>2017-02-04</td><td>2017-02-04</td></tr><tr><th>...</th><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td></tr><tr><th>1098</th><td>kOD8VdKdkFoBilDI5F8MAEFpH+K9cEU3S7NImJqc9/g=</td><td>True</td><td>30</td><td>41</td><td>2017-02-28</td><td>2017-02-28</td></tr><tr><th>1099</th><td>DDrGFzUkw5rp0Sj29TD3rpCNnCBSY+CJwC6tmEca9d0=</td><td>True</td><td>30</td><td>23</td><td>2017-02-05</td><td>2017-02-28</td></tr><tr><th>1100</th><td>uEhSZBjCCt2RjDXtBC3K3/5ilDxlVawfzKMaSkn/Jf4=</td><td>True</td><td>30</td><td>41</td><td>2017-02-28</td><td>2017-02-28</td></tr><tr><th>1101</th><td>LcDrm/2RarwCnb3bKAtlhKufegKcoSrjAzXIpVRIono=</td><td>True</td><td>30</td><td>38</td><td>2017-02-13</td><td>2017-02-13</td></tr><tr><th>1102</th><td>IO542475pPNBBZU+Lf5SVtT4KZd571mDkdVQ5M1slms=</td><td>True</td><td>30</td><td>41</td><td>2017-02-28</td><td>2017-02-28</td></tr></tbody></table><p>1103 rows × 6 columns</p></div></body></html></div></div><div class=\"details kda_tabcontent\" style=\"display:none;\"><div class=\"kda_scroll_container\"><table class=\"kda_table\"><tr><td><b>state</b></td><td>SUCCESS</td></tr><tr><td><b>query_id</b></td><td>5342569f-27cc-482d-8485-67f1a46c3ae1</td></tr><tr><td><b>metrics</b></td><td><table class=\"kda_table\"><tr><td><b>time_preparing</b></td><td>0.034s</td></tr><tr><td><b>time_computing</b></td><td>0.859s</td></tr><tr><td><b>output_files</b></td><td>1</td></tr></table></td></tr><tr><td><b>parquet</b></td><td><table class=\"kda_table\"><tr><th>index</th><th>path</th></tr><tr><td><pre>0</pre></td><td><a href=\"https://studio-us-west-2-prod-kaskada.s3.us-west-2.amazonaws.com/wren/dbv1alpha/results/cac2a62e-70d1-452d-bc65-d4dd832cb5b6/_qLHQ8TpOSoUAXTHbrPhBiwB9lYiSIzeYQKRXA/71e7a0e8-1a7c-4514-abd5-887d605865a1.parquet?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=ASIAZJRQG37GR2T7FKHT%2F20221229%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20221229T191908Z&X-Amz-Expires=3600&X-Amz-Security-Token=IQoJb3JpZ2luX2VjEBsaCXVzLXdlc3QtMiJIMEYCIQDGNPQeP5JKF7hOP5I0BRaFwRFPeO47F%2FJkJ2ngj9zRLgIhAJUS4644RdkiJKwApv%2FGXY7Lzdq0ItJySCJ%2FthizSzBYKvQECGQQAhoMNjM4OTc3NDk5MDg1IgwZZs06h2QX9MgbGxkq0QSTzHEyxitLIiFb7PL94E2%2F6ptSD1uo9YiT7nqQsEQnHds2id6Aahuj%2F6ZBlV1myw2gqsKQNN5QTR7nJlTn8CZzac9IfC%2BxXnfIC%2F5p2YXNfpjzIGUioe4JuR9tqbE9AZ5zEXI9s9wnXrc9bKwgEyySnTaMIhY1gTyEZFdC6vTmXF5C2vnNRCThyu3MqxcyE5QonSfEXBEyyq4lpctGBLGM1rwDjht16YYWfmqYj8WoUVrcha%2BWpC9d%2BpPU3n%2Fi%2BAMcOmckVoHLdQHZQPeB2yTOTKgjcZ2HhGlrHHq0rZAJbYcJa6fAMMuK3G3Xlw%2Fvz2Qh6PQ%2BqjPUy4Pm2w1UqherNA2Uq0qVjL8Ubp9mmwaYVD9LIu47nN%2FZA0AuYeDkf0J2boH885w6FxYfjbvHYZLHlPNg1trted0BzmPhj6%2F8ycdHN18oI0i7sXXgI2odMWf1IrywHzAtRD0VFLzjO4XUjaWEJpXpmlrZNCy43rDuNEyAVX4A3kgvnZQFvK74IPsgtyYmE09X%2FwVhdRcqXurt9v7II826ECdCFVlmbwh7hK9Zgq1ZlrC4veXSeLcQE7ANj3A%2F0w4q%2BLKo8sNRfrtpcCXBXsewseN9iOrxXFGlAZkaP3A4qYn2mK8yHFckHAdXAbfn29sCbc7SyahxI1xPpFFBo4xM2aTVC%2BC0EhRGo0hx4eb5LuEmYmMjEKLOcgAV2O%2BJ98d1ox1bQ1fQCQDTMarJ9KkcwnTHmL%2BPj5LC1sRMaSgdBvq7JG9v8u74rRULSOr6UOQzw%2F5Vu69KB85cKDDcw7edBjqZAQXvO0%2FeRSqLnYeLJZ58259i3eL8GI9mX9%2FmIS8yVNsOL6HuabcUzbe3vXO2AmMRs%2FafTsFKF2D6ekuwVHF%2BseKnmkez4%2BoUPCe%2FS0xnmB%2B9hzPbpqNJ2Ki2bT3nlwPA03VLIuglkcLXm40zLDJ09oHKu6ZDtsVW%2BSg7y51gZPDYFA5GohfYx3PGJfpAlBUbKLDb9mYMTQZvZA%3D%3D&X-Amz-SignedHeaders=host&X-Amz-Signature=c8b9faf9a3c6be3678647d35f3404a53a0a9e5e7a9136488dde70e4f4eff6e85\">https://studio-us-west-2-prod-kaskada.s3.us-west-2.amazonaws.com/wren/dbv1alpha/results/cac2a62e-70d1-452d-bc65-d4dd832cb5b6/_qLHQ8TpOSoUAXTHbrPhBiwB9lYiSIzeYQKRXA/71e7a0e8-1a7c-4514-abd5-887d605865a1.parquet?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=ASIAZJRQG37GR2T7FKHT%2F20221229%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20221229T191908Z&X-Amz-Expires=3600&X-Amz-Security-Token=IQoJb3JpZ2luX2VjEBsaCXVzLXdlc3QtMiJIMEYCIQDGNPQeP5JKF7hOP5I0BRaFwRFPeO47F%2FJkJ2ngj9zRLgIhAJUS4644RdkiJKwApv%2FGXY7Lzdq0ItJySCJ%2FthizSzBYKvQECGQQAhoMNjM4OTc3NDk5MDg1IgwZZs06h2QX9MgbGxkq0QSTzHEyxitLIiFb7PL94E2%2F6ptSD1uo9YiT7nqQsEQnHds2id6Aahuj%2F6ZBlV1myw2gqsKQNN5QTR7nJlTn8CZzac9IfC%2BxXnfIC%2F5p2YXNfpjzIGUioe4JuR9tqbE9AZ5zEXI9s9wnXrc9bKwgEyySnTaMIhY1gTyEZFdC6vTmXF5C2vnNRCThyu3MqxcyE5QonSfEXBEyyq4lpctGBLGM1rwDjht16YYWfmqYj8WoUVrcha%2BWpC9d%2BpPU3n%2Fi%2BAMcOmckVoHLdQHZQPeB2yTOTKgjcZ2HhGlrHHq0rZAJbYcJa6fAMMuK3G3Xlw%2Fvz2Qh6PQ%2BqjPUy4Pm2w1UqherNA2Uq0qVjL8Ubp9mmwaYVD9LIu47nN%2FZA0AuYeDkf0J2boH885w6FxYfjbvHYZLHlPNg1trted0BzmPhj6%2F8ycdHN18oI0i7sXXgI2odMWf1IrywHzAtRD0VFLzjO4XUjaWEJpXpmlrZNCy43rDuNEyAVX4A3kgvnZQFvK74IPsgtyYmE09X%2FwVhdRcqXurt9v7II826ECdCFVlmbwh7hK9Zgq1ZlrC4veXSeLcQE7ANj3A%2F0w4q%2BLKo8sNRfrtpcCXBXsewseN9iOrxXFGlAZkaP3A4qYn2mK8yHFckHAdXAbfn29sCbc7SyahxI1xPpFFBo4xM2aTVC%2BC0EhRGo0hx4eb5LuEmYmMjEKLOcgAV2O%2BJ98d1ox1bQ1fQCQDTMarJ9KkcwnTHmL%2BPj5LC1sRMaSgdBvq7JG9v8u74rRULSOr6UOQzw%2F5Vu69KB85cKDDcw7edBjqZAQXvO0%2FeRSqLnYeLJZ58259i3eL8GI9mX9%2FmIS8yVNsOL6HuabcUzbe3vXO2AmMRs%2FafTsFKF2D6ekuwVHF%2BseKnmkez4%2BoUPCe%2FS0xnmB%2B9hzPbpqNJ2Ki2bT3nlwPA03VLIuglkcLXm40zLDJ09oHKu6ZDtsVW%2BSg7y51gZPDYFA5GohfYx3PGJfpAlBUbKLDb9mYMTQZvZA%3D%3D&X-Amz-SignedHeaders=host&X-Amz-Signature=c8b9faf9a3c6be3678647d35f3404a53a0a9e5e7a9136488dde70e4f4eff6e85</a></td></tr></table></td></tr><tr><td><b>analysis</b></td><td><table class=\"kda_table\"><tr><td><b>can_execute</b></td><td><pre>True</pre></td></tr></table></td></tr><tr><td><b>schema</b></td><td><pre>(see Schema tab)</pre></td></tr><tr><td><b>data_token_id</b></td><td><pre>d70f10d1-50b6-40a7-a6dd-12a0d400e12b</pre></td></tr><tr><td><b>slice_request</b></td><td><table class=\"kda_table\"><tr><td><b>None</b></td><td><pre>(full dataset used for query)</pre></td></tr></table></td></tr><tr><td><b>request_details</b></td><td><table class=\"kda_table\"><tr><td><b>request_id</b></td><td><pre>0cdccb8d6fa272c1abf599d6f98e9c8f</pre></td></tr></table></td></tr><tr><td><b>query</b></td><td><pre>#Training set \n",
              "LabeledTransactions | when( (LabeledTransactions.starts_at > (\"2017-02-01T00:00:00Z\" as timestamp_ns))\n",
              "    and (LabeledTransactions.starts_at <= (\"2017-02-28T00:00:00Z\" as timestamp_ns)))</pre></td></tr></table></div></div><div class=\"schema kda_tabcontent\" style=\"display:none;\"><div class=\"kda_scroll_container\"><html><head></head><body><div><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><table border=\"1\" class=\"dataframe\"><thead><tr style=\"text-align: right;\"><th></th><th>column_name</th><th>column_type</th></tr></thead><tbody><tr><th>0</th><td>churned</td><td>bool</td></tr><tr><th>1</th><td>payment_plan_days</td><td>i64</td></tr><tr><th>2</th><td>payment_method_id</td><td>i64</td></tr><tr><th>3</th><td>starts_at</td><td>timestamp_ns</td></tr><tr><th>4</th><td>ends_at</td><td>timestamp_ns</td></tr></tbody></table></div></body></html></div></div><div class=\"raw kda_tabcontent\" style=\"display:none;\"><div class=\"kda_scroll_container\"><pre>{'dataframe': 'RangeIndex: 1103 entries, 0 to 1102'\n",
              "              'Columns: 6 entries, _key to ends_at'\n",
              "              'dtypes: bool(1), datetime64[ns](2), int64(2), object(1)'\n",
              "              'memory usage: 44.3+ KB',\n",
              " 'query': '#Training set '\n",
              "          'LabeledTransactions | when( (LabeledTransactions.starts_at > '\n",
              "          '(\"2017-02-01T00:00:00Z\" as timestamp_ns))'\n",
              "          '    and (LabeledTransactions.starts_at <= (\"2017-02-28T00:00:00Z\" '\n",
              "          'as timestamp_ns)))',\n",
              " 'query_response': state: STATE_SUCCESS\n",
              "config {\n",
              "  data_token_id: \"d70f10d1-50b6-40a7-a6dd-12a0d400e12b\"\n",
              "}\n",
              "analysis {\n",
              "  can_execute: true\n",
              "  schema {\n",
              "    fields {\n",
              "      name: \"churned\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_BOOL\n",
              "      }\n",
              "    }\n",
              "    fields {\n",
              "      name: \"payment_plan_days\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_I64\n",
              "      }\n",
              "    }\n",
              "    fields {\n",
              "      name: \"payment_method_id\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_I64\n",
              "      }\n",
              "    }\n",
              "    fields {\n",
              "      name: \"starts_at\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_TIMESTAMP_NANOSECOND\n",
              "      }\n",
              "    }\n",
              "    fields {\n",
              "      name: \"ends_at\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_TIMESTAMP_NANOSECOND\n",
              "      }\n",
              "    }\n",
              "  }\n",
              "}\n",
              "fenl_diagnostics {\n",
              "}\n",
              "metrics {\n",
              "  time_preparing {\n",
              "    nanos: 34113702\n",
              "  }\n",
              "  time_computing {\n",
              "    nanos: 859724530\n",
              "  }\n",
              "  output_files: 1\n",
              "}\n",
              "parquet {\n",
              "  paths: \"https://studio-us-west-2-prod-kaskada.s3.us-west-2.amazonaws.com/wren/dbv1alpha/results/cac2a62e-70d1-452d-bc65-d4dd832cb5b6/_qLHQ8TpOSoUAXTHbrPhBiwB9lYiSIzeYQKRXA/71e7a0e8-1a7c-4514-abd5-887d605865a1.parquet?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=ASIAZJRQG37GR2T7FKHT%2F20221229%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20221229T191908Z&X-Amz-Expires=3600&X-Amz-Security-Token=IQoJb3JpZ2luX2VjEBsaCXVzLXdlc3QtMiJIMEYCIQDGNPQeP5JKF7hOP5I0BRaFwRFPeO47F%2FJkJ2ngj9zRLgIhAJUS4644RdkiJKwApv%2FGXY7Lzdq0ItJySCJ%2FthizSzBYKvQECGQQAhoMNjM4OTc3NDk5MDg1IgwZZs06h2QX9MgbGxkq0QSTzHEyxitLIiFb7PL94E2%2F6ptSD1uo9YiT7nqQsEQnHds2id6Aahuj%2F6ZBlV1myw2gqsKQNN5QTR7nJlTn8CZzac9IfC%2BxXnfIC%2F5p2YXNfpjzIGUioe4JuR9tqbE9AZ5zEXI9s9wnXrc9bKwgEyySnTaMIhY1gTyEZFdC6vTmXF5C2vnNRCThyu3MqxcyE5QonSfEXBEyyq4lpctGBLGM1rwDjht16YYWfmqYj8WoUVrcha%2BWpC9d%2BpPU3n%2Fi%2BAMcOmckVoHLdQHZQPeB2yTOTKgjcZ2HhGlrHHq0rZAJbYcJa6fAMMuK3G3Xlw%2Fvz2Qh6PQ%2BqjPUy4Pm2w1UqherNA2Uq0qVjL8Ubp9mmwaYVD9LIu47nN%2FZA0AuYeDkf0J2boH885w6FxYfjbvHYZLHlPNg1trted0BzmPhj6%2F8ycdHN18oI0i7sXXgI2odMWf1IrywHzAtRD0VFLzjO4XUjaWEJpXpmlrZNCy43rDuNEyAVX4A3kgvnZQFvK74IPsgtyYmE09X%2FwVhdRcqXurt9v7II826ECdCFVlmbwh7hK9Zgq1ZlrC4veXSeLcQE7ANj3A%2F0w4q%2BLKo8sNRfrtpcCXBXsewseN9iOrxXFGlAZkaP3A4qYn2mK8yHFckHAdXAbfn29sCbc7SyahxI1xPpFFBo4xM2aTVC%2BC0EhRGo0hx4eb5LuEmYmMjEKLOcgAV2O%2BJ98d1ox1bQ1fQCQDTMarJ9KkcwnTHmL%2BPj5LC1sRMaSgdBvq7JG9v8u74rRULSOr6UOQzw%2F5Vu69KB85cKDDcw7edBjqZAQXvO0%2FeRSqLnYeLJZ58259i3eL8GI9mX9%2FmIS8yVNsOL6HuabcUzbe3vXO2AmMRs%2FafTsFKF2D6ekuwVHF%2BseKnmkez4%2BoUPCe%2FS0xnmB%2B9hzPbpqNJ2Ki2bT3nlwPA03VLIuglkcLXm40zLDJ09oHKu6ZDtsVW%2BSg7y51gZPDYFA5GohfYx3PGJfpAlBUbKLDb9mYMTQZvZA%3D%3D&X-Amz-SignedHeaders=host&X-Amz-Signature=c8b9faf9a3c6be3678647d35f3404a53a0a9e5e7a9136488dde70e4f4eff6e85\"\n",
              "}\n",
              "request_details {\n",
              "  request_id: \"0cdccb8d6fa272c1abf599d6f98e9c8f\"\n",
              "}\n",
              "query_id: \"5342569f-27cc-482d-8485-67f1a46c3ae1\"\n",
              "}</pre></div></div></div>"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Enrich with additional labels"
      ],
      "metadata": {
        "id": "phvKsW2FeqK5"
      },
      "id": "phvKsW2FeqK5"
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Step 3.c Extend any view with additional FENL Features as needed\n",
        "\n",
        "*   Duration of subscription\n",
        "*   Channels and plan selection\n",
        "\n"
      ],
      "metadata": {
        "id": "p9MnHJLPa160"
      },
      "id": "p9MnHJLPa160"
    },
    {
      "cell_type": "code",
      "source": [
        "%%fenl --var df_training\n",
        "LabeledTransactions | extend({\n",
        "    duration_days: days_between(LabeledTransactions.ends_at, LabeledTransactions.starts_at) as i32,\n",
        "    registered_via: first(Member).registered_via | else(-1)\n",
        "}) | when(is_valid(LabeledTransactions.churned))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 460
        },
        "id": "at-YfgMoHal-",
        "outputId": "12f1f69e-dc97-4cd7-902a-574fdafe9db9"
      },
      "id": "at-YfgMoHal-",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "<style>table.kda_table {\n",
              "    border: 1px solid grey !important;\n",
              "    border-collapse: collapse !important;\n",
              "    border-spacing: 0 !important;\n",
              "    font-size: 14px !important;\n",
              "    margin-bottom: 6px !important;\n",
              "}\n",
              "\n",
              "table.kda_table table {\n",
              "    margin-bottom: 0 !important;\n",
              "}\n",
              "\n",
              ".kda_table td, .kda_table th {\n",
              "    border: 1px solid grey !important;\n",
              "    border-collapse: collapse !important;\n",
              "    padding: 6px !important;\n",
              "    text-align: left !important;\n",
              "    vertical-align: top !important;\n",
              "}\n",
              "\n",
              ".kda_table tr {\n",
              "    background-color: inherit !important;\n",
              "}\n",
              "\n",
              "/* Style the tab */\n",
              ".kda_tab {\n",
              "    overflow: hidden;\n",
              "    border-bottom: 1px solid grey;\n",
              "    background-color: inherit;\n",
              "}\n",
              "\n",
              "/* Style the buttons that are used to open the tab content */\n",
              ".kda_tab button {\n",
              "    background-color: inherit;\n",
              "    border-top: 1px solid grey;\n",
              "    border-right: 1px solid grey;\n",
              "    border-left: 1px solid grey;\n",
              "    border-bottom: none;\n",
              "    border-radius: 5px 5px 0px 0px;\n",
              "    color: inherit;\n",
              "    cursor: pointer;\n",
              "    float: left;\n",
              "    margin: 2px 8px 0px 2px;\n",
              "    outline: none;\n",
              "    padding: 5px 16px;\n",
              "    transition: 0.3s;\n",
              "}\n",
              "\n",
              "/* Change background color of buttons on hover */\n",
              ".kda_tab button:hover {\n",
              "    background-color: grey;\n",
              "}\n",
              "\n",
              "/* Create an active/current tablink class */\n",
              ".kda_tab button.kda_active {\n",
              "    outline: 2px solid grey;\n",
              "}\n",
              "\n",
              "/* Style the tab content */\n",
              ".kda_tabcontent {\n",
              "    display: none;\n",
              "    padding: 6px;\n",
              "    border: 1px solid grey;\n",
              "    border-top: none;\n",
              "}\n",
              "\n",
              ".kda_scroll_container {\n",
              "    max-height: 400px;\n",
              "    overflow: auto;\n",
              "}\n",
              "</style>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "<script type=\"text/javascript\">function openTab(evt, tabName) {\n",
              "    // Declare all variables\n",
              "    var i, rootElement, tabcontent, tablinks, tabshow;\n",
              "\n",
              "    // Get all elements with class=\"tabcontent\" and hide them\n",
              "    rootElement = evt.currentTarget.parentElement.parentElement;\n",
              "    tabcontent = rootElement.getElementsByClassName(\"kda_tabcontent\");\n",
              "    for (i = 0; i < tabcontent.length; i++) {\n",
              "        tabcontent[i].style.display = \"none\";\n",
              "    }\n",
              "\n",
              "    // Get all elements with class=\"tablinks\" and remove the class \"active\"\n",
              "    tablinks = rootElement.getElementsByClassName(\"kda_tablinks\");\n",
              "    for (i = 0; i < tablinks.length; i++) {\n",
              "        tablinks[i].className = tablinks[i].className.replace(\" kda_active\", \"\");\n",
              "    }\n",
              "\n",
              "    // Show the current tab, and add an \"active\" class to the button that opened the tab\n",
              "    tabshow = rootElement.getElementsByClassName(tabName);\n",
              "    for (i = 0; i < tabshow.length; i++) {\n",
              "        tabshow[i].style.display = \"block\";\n",
              "    }\n",
              "    evt.currentTarget.className += \" kda_active\";\n",
              "}\n",
              "</script>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<fenlmagic.QueryResult at 0x7fdf962a89a0>"
            ],
            "text/html": [
              "<div><div class=\"kda_tab\"><button class=\"kda_tablinks kda_active\" onclick=\"openTab(event, 'dataframe')\">Dataframe</button><button class=\"kda_tablinks\" onclick=\"openTab(event, 'details')\">Details</button><button class=\"kda_tablinks\" onclick=\"openTab(event, 'schema')\">Schema</button><button class=\"kda_tablinks\" onclick=\"openTab(event, 'raw')\">Raw</button></div><div class=\"dataframe kda_tabcontent\" style=\"display:block;\"><div class=\"kda_scroll_container\"><html><head></head><body><div><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><table border=\"1\" class=\"dataframe\"><thead><tr style=\"text-align: right;\"><th></th><th>_key</th><th>duration_days</th><th>registered_via</th><th>churned</th><th>payment_plan_days</th><th>payment_method_id</th><th>starts_at</th><th>ends_at</th></tr></thead><tbody><tr><th>0</th><td>5z4w+3H7Qu8eJxhO20SAOBc+6nPLW/Q5eY4CMKUJVGU=</td><td>0.0</td><td>9</td><td>True</td><td>30.0</td><td>24.0</td><td>2015-01-23</td><td>2015-01-23</td></tr><tr><th>1</th><td>KSyMAEmMLIMGSghRfzF44TKzYC/K1zh7wi0gEFc/GAw=</td><td>0.0</td><td>3</td><td>True</td><td>31.0</td><td>27.0</td><td>2015-01-23</td><td>2015-01-23</td></tr><tr><th>2</th><td>Ge5nM+AdnWxFm+nIORW+bfU2VyMqeGUhXs6RwXsu/+w=</td><td>NaN</td><td>9</td><td>False</td><td>NaN</td><td>NaN</td><td>2015-01-26</td><td>NaT</td></tr><tr><th>3</th><td>YhjdS3H6Oa444WB7I//4DkEX5kQUq8Yk8lr3djuhS8Y=</td><td>NaN</td><td>3</td><td>False</td><td>NaN</td><td>NaN</td><td>2015-01-26</td><td>NaT</td></tr><tr><th>4</th><td>Ge5nM+AdnWxFm+nIORW+bfU2VyMqeGUhXs6RwXsu/+w=</td><td>NaN</td><td>9</td><td>False</td><td>30.0</td><td>24.0</td><td>2015-01-26</td><td>NaT</td></tr><tr><th>...</th><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td></tr><tr><th>492697</th><td>TNOcP07Mry/UFtgvxn9bUPgq8Zf6dwdWQjn9kv7P+g0=</td><td>-59.0</td><td>7</td><td>True</td><td>30.0</td><td>41.0</td><td>2016-12-31</td><td>2017-02-28</td></tr><tr><th>492698</th><td>My/CEivMfiCWmSl9C1BNarV80eaMdd+LjsqnR8g6fsU=</td><td>-456.0</td><td>9</td><td>True</td><td>NaN</td><td>NaN</td><td>2015-11-30</td><td>2017-02-28</td></tr><tr><th>492699</th><td>OKdMxAyGn1bJ43uCyWPpr8hYYX0/gdE1Q8Jrs1mGYuI=</td><td>-456.0</td><td>9</td><td>True</td><td>NaN</td><td>NaN</td><td>2015-11-30</td><td>2017-02-28</td></tr><tr><th>492700</th><td>3XvMZe4vmCLvPQJoVdOMNt4QE4U1s5dXIW4JiebDtss=</td><td>-213.0</td><td>7</td><td>True</td><td>30.0</td><td>41.0</td><td>2015-01-30</td><td>2015-08-31</td></tr><tr><th>492701</th><td>MvNHn2nZqq7nBBuj6yS7ISvZrvnWx1BJvFpxjNcMvmc=</td><td>-456.0</td><td>9</td><td>True</td><td>NaN</td><td>NaN</td><td>2015-11-30</td><td>2017-02-28</td></tr></tbody></table><p>492702 rows × 8 columns</p></div></body></html></div></div><div class=\"details kda_tabcontent\" style=\"display:none;\"><div class=\"kda_scroll_container\"><table class=\"kda_table\"><tr><td><b>state</b></td><td>SUCCESS</td></tr><tr><td><b>query_id</b></td><td>a509c59f-c015-4e96-ad10-71d4c6d5ac7c</td></tr><tr><td><b>metrics</b></td><td><table class=\"kda_table\"><tr><td><b>time_preparing</b></td><td>0.075s</td></tr><tr><td><b>time_computing</b></td><td>1.476s</td></tr><tr><td><b>output_files</b></td><td>1</td></tr></table></td></tr><tr><td><b>parquet</b></td><td><table class=\"kda_table\"><tr><th>index</th><th>path</th></tr><tr><td><pre>0</pre></td><td><a href=\"https://studio-us-west-2-prod-kaskada.s3.us-west-2.amazonaws.com/wren/dbv1alpha/results/cac2a62e-70d1-452d-bc65-d4dd832cb5b6/Qnj36FSvcUvWf40V9gyBbE9NY_mYwa-pFwdgRw/b0ec5870-ab8a-4966-bbd5-3673acc5dd7d.parquet?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=ASIAZJRQG37GWVIVW7CG%2F20221229%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20221229T191949Z&X-Amz-Expires=3600&X-Amz-Security-Token=IQoJb3JpZ2luX2VjEBsaCXVzLXdlc3QtMiJGMEQCIHM2%2F%2BvYM2e7RywlSEwJD7rKvqQxq6Amf6wk2%2BGN4CXbAiAwrjgoBZXMxs8IX15Vm%2BbBZzAbGNwlXWiaaCUj11%2FnQir0BAhkEAIaDDYzODk3NzQ5OTA4NSIMWHLflFNCCCCYfX9fKtEEw%2BgtR6gROyGZyL1faB4u%2F6jToryyOzVgpWCsI36uklgG1Nl21lRQ2Om5edylfSVIfwcYt2o26IbDMyt0l8Mqp5M3DvD3aGYHEztHKHVCKOuoPRFcMs73Tkzd2IbbHTogUmekwSS7y1MITArT%2B40PRBnYZcEysgGr0s0oSfJifmBC2P9dZKye6H9hPTrIpVsnzzJl2YW6QmuuthS13%2B%2Fuvp1TRY7alZMjxT2p%2B98PfMY%2BwnDZyvm52k7f8WX%2B6LeG5huBK4lCHaAny6JXnXlONYhDvbtM5g7KR7YR%2Bz%2FPbMHPZM76Zm1xx0f%2FEPjypHke%2BUphqjA7tvEGHV0iK67npb9eJtso0hP3oeaaD%2FszzeerAgf2orLFHNFHYtq5GzcRGehMzuhLWTYF3RBrRaWkEewpl4BJtIiGvX35M5FsfydKQ0KN04O1m5WbYWCs0HjGd5gaYO1exE8HZtfG382RzpuXdZcnlKh6fSA7fL3U%2B2VqxfG5T5C4QHWzqx3MMTqfWFK5Q%2Bm0VTfpLWYMrCQR61R9rM21esBZYSVDUYlYAS6YqBCPi%2B7ASDJDEcus4jqK7CDR1KEPEYQNTjugaQOZV%2BJ7%2Fl%2FdTZMWDfJm%2B1qokmi4F%2FIGiaGELwkAKaHsVOTr2R2Dk%2FvSjaN11r1lHMVtPNAYFgkPH%2FI32v0yGF7CIoDZz0RQraYSRWeA1EynXmktTNbEGtiDXtQzCe%2BTmKj5qBJWzzSbNG6ybRsEJLIBWXCIQUr7eE6Yq%2Bcf38CG85uF7v1TQRgFW1%2BalPL4gYFjAx8w38O3nQY6mwGkkaWu2yhK5Y6qWhusg%2FePqQQiM9vcFWlmU9y%2Be0EQbx9LvUisuTKSvrzRFv9dtCrcDt7XDB1bbaEJGwxSXOt09vjjls6U3ttbTU0m0o00t7%2BW5MfmCH7%2BPhW77xv61uHAnRW54KZ9W9b8LaC2NUPDoPdXvFUqW%2FFi6a4bjbNXzglXChqsR2qksX23ljxbpAmPceEmYxwd39ss%2FQ%3D%3D&X-Amz-SignedHeaders=host&X-Amz-Signature=0f7052706b84eeeff2dd61b18be930b79667b52527d934c4513ca34d6a713ab1\">https://studio-us-west-2-prod-kaskada.s3.us-west-2.amazonaws.com/wren/dbv1alpha/results/cac2a62e-70d1-452d-bc65-d4dd832cb5b6/Qnj36FSvcUvWf40V9gyBbE9NY_mYwa-pFwdgRw/b0ec5870-ab8a-4966-bbd5-3673acc5dd7d.parquet?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=ASIAZJRQG37GWVIVW7CG%2F20221229%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20221229T191949Z&X-Amz-Expires=3600&X-Amz-Security-Token=IQoJb3JpZ2luX2VjEBsaCXVzLXdlc3QtMiJGMEQCIHM2%2F%2BvYM2e7RywlSEwJD7rKvqQxq6Amf6wk2%2BGN4CXbAiAwrjgoBZXMxs8IX15Vm%2BbBZzAbGNwlXWiaaCUj11%2FnQir0BAhkEAIaDDYzODk3NzQ5OTA4NSIMWHLflFNCCCCYfX9fKtEEw%2BgtR6gROyGZyL1faB4u%2F6jToryyOzVgpWCsI36uklgG1Nl21lRQ2Om5edylfSVIfwcYt2o26IbDMyt0l8Mqp5M3DvD3aGYHEztHKHVCKOuoPRFcMs73Tkzd2IbbHTogUmekwSS7y1MITArT%2B40PRBnYZcEysgGr0s0oSfJifmBC2P9dZKye6H9hPTrIpVsnzzJl2YW6QmuuthS13%2B%2Fuvp1TRY7alZMjxT2p%2B98PfMY%2BwnDZyvm52k7f8WX%2B6LeG5huBK4lCHaAny6JXnXlONYhDvbtM5g7KR7YR%2Bz%2FPbMHPZM76Zm1xx0f%2FEPjypHke%2BUphqjA7tvEGHV0iK67npb9eJtso0hP3oeaaD%2FszzeerAgf2orLFHNFHYtq5GzcRGehMzuhLWTYF3RBrRaWkEewpl4BJtIiGvX35M5FsfydKQ0KN04O1m5WbYWCs0HjGd5gaYO1exE8HZtfG382RzpuXdZcnlKh6fSA7fL3U%2B2VqxfG5T5C4QHWzqx3MMTqfWFK5Q%2Bm0VTfpLWYMrCQR61R9rM21esBZYSVDUYlYAS6YqBCPi%2B7ASDJDEcus4jqK7CDR1KEPEYQNTjugaQOZV%2BJ7%2Fl%2FdTZMWDfJm%2B1qokmi4F%2FIGiaGELwkAKaHsVOTr2R2Dk%2FvSjaN11r1lHMVtPNAYFgkPH%2FI32v0yGF7CIoDZz0RQraYSRWeA1EynXmktTNbEGtiDXtQzCe%2BTmKj5qBJWzzSbNG6ybRsEJLIBWXCIQUr7eE6Yq%2Bcf38CG85uF7v1TQRgFW1%2BalPL4gYFjAx8w38O3nQY6mwGkkaWu2yhK5Y6qWhusg%2FePqQQiM9vcFWlmU9y%2Be0EQbx9LvUisuTKSvrzRFv9dtCrcDt7XDB1bbaEJGwxSXOt09vjjls6U3ttbTU0m0o00t7%2BW5MfmCH7%2BPhW77xv61uHAnRW54KZ9W9b8LaC2NUPDoPdXvFUqW%2FFi6a4bjbNXzglXChqsR2qksX23ljxbpAmPceEmYxwd39ss%2FQ%3D%3D&X-Amz-SignedHeaders=host&X-Amz-Signature=0f7052706b84eeeff2dd61b18be930b79667b52527d934c4513ca34d6a713ab1</a></td></tr></table></td></tr><tr><td><b>analysis</b></td><td><table class=\"kda_table\"><tr><td><b>can_execute</b></td><td><pre>True</pre></td></tr></table></td></tr><tr><td><b>schema</b></td><td><pre>(see Schema tab)</pre></td></tr><tr><td><b>data_token_id</b></td><td><pre>d70f10d1-50b6-40a7-a6dd-12a0d400e12b</pre></td></tr><tr><td><b>slice_request</b></td><td><table class=\"kda_table\"><tr><td><b>None</b></td><td><pre>(full dataset used for query)</pre></td></tr></table></td></tr><tr><td><b>request_details</b></td><td><table class=\"kda_table\"><tr><td><b>request_id</b></td><td><pre>f7add9a1d7c7ab78f669527b239bd80c</pre></td></tr></table></td></tr><tr><td><b>query</b></td><td><pre>LabeledTransactions | extend({\n",
              "    duration_days: days_between(LabeledTransactions.ends_at, LabeledTransactions.starts_at) as i32,\n",
              "    registered_via: first(Member).registered_via | else(-1)\n",
              "}) | when(is_valid(LabeledTransactions.churned))</pre></td></tr></table></div></div><div class=\"schema kda_tabcontent\" style=\"display:none;\"><div class=\"kda_scroll_container\"><html><head></head><body><div><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><table border=\"1\" class=\"dataframe\"><thead><tr style=\"text-align: right;\"><th></th><th>column_name</th><th>column_type</th></tr></thead><tbody><tr><th>0</th><td>duration_days</td><td>i32</td></tr><tr><th>1</th><td>registered_via</td><td>i64</td></tr><tr><th>2</th><td>churned</td><td>bool</td></tr><tr><th>3</th><td>payment_plan_days</td><td>i64</td></tr><tr><th>4</th><td>payment_method_id</td><td>i64</td></tr><tr><th>5</th><td>starts_at</td><td>timestamp_ns</td></tr><tr><th>6</th><td>ends_at</td><td>timestamp_ns</td></tr></tbody></table></div></body></html></div></div><div class=\"raw kda_tabcontent\" style=\"display:none;\"><div class=\"kda_scroll_container\"><pre>{'dataframe': 'RangeIndex: 492702 entries, 0 to 492701'\n",
              "              'Columns: 8 entries, _key to ends_at'\n",
              "              'dtypes: bool(1), datetime64[ns](2), float64(3), int64(1), '\n",
              "              'object(1)'\n",
              "              'memory usage: 26.8+ MB',\n",
              " 'query': 'LabeledTransactions | extend({'\n",
              "          '    duration_days: days_between(LabeledTransactions.ends_at, '\n",
              "          'LabeledTransactions.starts_at) as i32,'\n",
              "          '    registered_via: first(Member).registered_via | else(-1)'\n",
              "          '}) | when(is_valid(LabeledTransactions.churned))',\n",
              " 'query_response': state: STATE_SUCCESS\n",
              "config {\n",
              "  data_token_id: \"d70f10d1-50b6-40a7-a6dd-12a0d400e12b\"\n",
              "}\n",
              "analysis {\n",
              "  can_execute: true\n",
              "  schema {\n",
              "    fields {\n",
              "      name: \"duration_days\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_I32\n",
              "      }\n",
              "    }\n",
              "    fields {\n",
              "      name: \"registered_via\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_I64\n",
              "      }\n",
              "    }\n",
              "    fields {\n",
              "      name: \"churned\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_BOOL\n",
              "      }\n",
              "    }\n",
              "    fields {\n",
              "      name: \"payment_plan_days\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_I64\n",
              "      }\n",
              "    }\n",
              "    fields {\n",
              "      name: \"payment_method_id\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_I64\n",
              "      }\n",
              "    }\n",
              "    fields {\n",
              "      name: \"starts_at\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_TIMESTAMP_NANOSECOND\n",
              "      }\n",
              "    }\n",
              "    fields {\n",
              "      name: \"ends_at\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_TIMESTAMP_NANOSECOND\n",
              "      }\n",
              "    }\n",
              "  }\n",
              "}\n",
              "fenl_diagnostics {\n",
              "}\n",
              "metrics {\n",
              "  time_preparing {\n",
              "    nanos: 75131200\n",
              "  }\n",
              "  time_computing {\n",
              "    seconds: 1\n",
              "    nanos: 476349604\n",
              "  }\n",
              "  output_files: 1\n",
              "}\n",
              "parquet {\n",
              "  paths: \"https://studio-us-west-2-prod-kaskada.s3.us-west-2.amazonaws.com/wren/dbv1alpha/results/cac2a62e-70d1-452d-bc65-d4dd832cb5b6/Qnj36FSvcUvWf40V9gyBbE9NY_mYwa-pFwdgRw/b0ec5870-ab8a-4966-bbd5-3673acc5dd7d.parquet?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=ASIAZJRQG37GWVIVW7CG%2F20221229%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20221229T191949Z&X-Amz-Expires=3600&X-Amz-Security-Token=IQoJb3JpZ2luX2VjEBsaCXVzLXdlc3QtMiJGMEQCIHM2%2F%2BvYM2e7RywlSEwJD7rKvqQxq6Amf6wk2%2BGN4CXbAiAwrjgoBZXMxs8IX15Vm%2BbBZzAbGNwlXWiaaCUj11%2FnQir0BAhkEAIaDDYzODk3NzQ5OTA4NSIMWHLflFNCCCCYfX9fKtEEw%2BgtR6gROyGZyL1faB4u%2F6jToryyOzVgpWCsI36uklgG1Nl21lRQ2Om5edylfSVIfwcYt2o26IbDMyt0l8Mqp5M3DvD3aGYHEztHKHVCKOuoPRFcMs73Tkzd2IbbHTogUmekwSS7y1MITArT%2B40PRBnYZcEysgGr0s0oSfJifmBC2P9dZKye6H9hPTrIpVsnzzJl2YW6QmuuthS13%2B%2Fuvp1TRY7alZMjxT2p%2B98PfMY%2BwnDZyvm52k7f8WX%2B6LeG5huBK4lCHaAny6JXnXlONYhDvbtM5g7KR7YR%2Bz%2FPbMHPZM76Zm1xx0f%2FEPjypHke%2BUphqjA7tvEGHV0iK67npb9eJtso0hP3oeaaD%2FszzeerAgf2orLFHNFHYtq5GzcRGehMzuhLWTYF3RBrRaWkEewpl4BJtIiGvX35M5FsfydKQ0KN04O1m5WbYWCs0HjGd5gaYO1exE8HZtfG382RzpuXdZcnlKh6fSA7fL3U%2B2VqxfG5T5C4QHWzqx3MMTqfWFK5Q%2Bm0VTfpLWYMrCQR61R9rM21esBZYSVDUYlYAS6YqBCPi%2B7ASDJDEcus4jqK7CDR1KEPEYQNTjugaQOZV%2BJ7%2Fl%2FdTZMWDfJm%2B1qokmi4F%2FIGiaGELwkAKaHsVOTr2R2Dk%2FvSjaN11r1lHMVtPNAYFgkPH%2FI32v0yGF7CIoDZz0RQraYSRWeA1EynXmktTNbEGtiDXtQzCe%2BTmKj5qBJWzzSbNG6ybRsEJLIBWXCIQUr7eE6Yq%2Bcf38CG85uF7v1TQRgFW1%2BalPL4gYFjAx8w38O3nQY6mwGkkaWu2yhK5Y6qWhusg%2FePqQQiM9vcFWlmU9y%2Be0EQbx9LvUisuTKSvrzRFv9dtCrcDt7XDB1bbaEJGwxSXOt09vjjls6U3ttbTU0m0o00t7%2BW5MfmCH7%2BPhW77xv61uHAnRW54KZ9W9b8LaC2NUPDoPdXvFUqW%2FFi6a4bjbNXzglXChqsR2qksX23ljxbpAmPceEmYxwd39ss%2FQ%3D%3D&X-Amz-SignedHeaders=host&X-Amz-Signature=0f7052706b84eeeff2dd61b18be930b79667b52527d934c4513ca34d6a713ab1\"\n",
              "}\n",
              "request_details {\n",
              "  request_id: \"f7add9a1d7c7ab78f669527b239bd80c\"\n",
              "}\n",
              "query_id: \"a509c59f-c015-4e96-ad10-71d4c6d5ac7c\"\n",
              "}</pre></div></div></div>"
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9b400634-fa26-4202-9fc7-951f2d431532"
      },
      "source": [
        "# Step 4: Going to Production\n",
        "## But, Data and Machine Learning Engineers Hate Jupyter\n",
        "The non-linearity that was so beneficial as a data scientist turns into a nightmarish choose-your-own adventure book for the machine learning engineer trying to recreate the final path that a Data Scientist took. Whereas all the failures, mistakes, and errors that were made are useful for a data scientist to hold onto, it makes the machine learning engineers job closer to archaeology: trying to discover and interpret the hidden meaning behind for loops, boolean statements and drop cols.\n",
        "\n",
        "### With Kaskada you can bridge the gap to production\n",
        "- Kaskada connects directly the event-based data available in production\n",
        "- Data scientists define the predictor features used to power training sets\n",
        "- Data and ML Engineers call Kaskada to compute the **same** features at the time of now() in production\n",
        "- Kaskada provides production grade targets such as Redis for feature and model serving"
      ],
      "id": "9b400634-fa26-4202-9fc7-951f2d431532"
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3b31a82b-bcc2-468c-a624-3b8d94e12e12"
      },
      "source": [
        "### Make Features as Code available for airflow jobs with views\n",
        "Fenl expressions can be shared and re-used by creating a view. A view is a named expression. In subsequent Fenl expressions, the view's name is synonymous with the view's expression. Views are persisted in the Kaskada platform and are accessible to any query.\n",
        "\n",
        "[Read more here](https://docs.kaskada.com/docs/views)"
      ],
      "id": "3b31a82b-bcc2-468c-a624-3b8d94e12e12"
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ec4157fa-7a57-4403-ad1f-0b22f4223232",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 460
        },
        "outputId": "ec4f67e3-fcd5-4d06-813d-21def5ef7fbe"
      },
      "source": [
        "%%fenl --var feature_vector\n",
        "\n",
        "{\n",
        "    payment_plan_days: Transaction.payment_plan_days,\n",
        "    payment_method_id: Transaction.payment_method_id,\n",
        "    trans_at: Transaction.transaction_date,\n",
        "    membership_expire_date: Transaction.membership_expire_date,\n",
        "}"
      ],
      "id": "ec4157fa-7a57-4403-ad1f-0b22f4223232",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "<style>table.kda_table {\n",
              "    border: 1px solid grey !important;\n",
              "    border-collapse: collapse !important;\n",
              "    border-spacing: 0 !important;\n",
              "    font-size: 14px !important;\n",
              "    margin-bottom: 6px !important;\n",
              "}\n",
              "\n",
              "table.kda_table table {\n",
              "    margin-bottom: 0 !important;\n",
              "}\n",
              "\n",
              ".kda_table td, .kda_table th {\n",
              "    border: 1px solid grey !important;\n",
              "    border-collapse: collapse !important;\n",
              "    padding: 6px !important;\n",
              "    text-align: left !important;\n",
              "    vertical-align: top !important;\n",
              "}\n",
              "\n",
              ".kda_table tr {\n",
              "    background-color: inherit !important;\n",
              "}\n",
              "\n",
              "/* Style the tab */\n",
              ".kda_tab {\n",
              "    overflow: hidden;\n",
              "    border-bottom: 1px solid grey;\n",
              "    background-color: inherit;\n",
              "}\n",
              "\n",
              "/* Style the buttons that are used to open the tab content */\n",
              ".kda_tab button {\n",
              "    background-color: inherit;\n",
              "    border-top: 1px solid grey;\n",
              "    border-right: 1px solid grey;\n",
              "    border-left: 1px solid grey;\n",
              "    border-bottom: none;\n",
              "    border-radius: 5px 5px 0px 0px;\n",
              "    color: inherit;\n",
              "    cursor: pointer;\n",
              "    float: left;\n",
              "    margin: 2px 8px 0px 2px;\n",
              "    outline: none;\n",
              "    padding: 5px 16px;\n",
              "    transition: 0.3s;\n",
              "}\n",
              "\n",
              "/* Change background color of buttons on hover */\n",
              ".kda_tab button:hover {\n",
              "    background-color: grey;\n",
              "}\n",
              "\n",
              "/* Create an active/current tablink class */\n",
              ".kda_tab button.kda_active {\n",
              "    outline: 2px solid grey;\n",
              "}\n",
              "\n",
              "/* Style the tab content */\n",
              ".kda_tabcontent {\n",
              "    display: none;\n",
              "    padding: 6px;\n",
              "    border: 1px solid grey;\n",
              "    border-top: none;\n",
              "}\n",
              "\n",
              ".kda_scroll_container {\n",
              "    max-height: 400px;\n",
              "    overflow: auto;\n",
              "}\n",
              "</style>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "<script type=\"text/javascript\">function openTab(evt, tabName) {\n",
              "    // Declare all variables\n",
              "    var i, rootElement, tabcontent, tablinks, tabshow;\n",
              "\n",
              "    // Get all elements with class=\"tabcontent\" and hide them\n",
              "    rootElement = evt.currentTarget.parentElement.parentElement;\n",
              "    tabcontent = rootElement.getElementsByClassName(\"kda_tabcontent\");\n",
              "    for (i = 0; i < tabcontent.length; i++) {\n",
              "        tabcontent[i].style.display = \"none\";\n",
              "    }\n",
              "\n",
              "    // Get all elements with class=\"tablinks\" and remove the class \"active\"\n",
              "    tablinks = rootElement.getElementsByClassName(\"kda_tablinks\");\n",
              "    for (i = 0; i < tablinks.length; i++) {\n",
              "        tablinks[i].className = tablinks[i].className.replace(\" kda_active\", \"\");\n",
              "    }\n",
              "\n",
              "    // Show the current tab, and add an \"active\" class to the button that opened the tab\n",
              "    tabshow = rootElement.getElementsByClassName(tabName);\n",
              "    for (i = 0; i < tabshow.length; i++) {\n",
              "        tabshow[i].style.display = \"block\";\n",
              "    }\n",
              "    evt.currentTarget.className += \" kda_active\";\n",
              "}\n",
              "</script>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<fenlmagic.QueryResult at 0x7fdf9806f1f0>"
            ],
            "text/html": [
              "<div><div class=\"kda_tab\"><button class=\"kda_tablinks kda_active\" onclick=\"openTab(event, 'dataframe')\">Dataframe</button><button class=\"kda_tablinks\" onclick=\"openTab(event, 'details')\">Details</button><button class=\"kda_tablinks\" onclick=\"openTab(event, 'schema')\">Schema</button><button class=\"kda_tablinks\" onclick=\"openTab(event, 'raw')\">Raw</button></div><div class=\"dataframe kda_tabcontent\" style=\"display:block;\"><div class=\"kda_scroll_container\"><html><head></head><body><div><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><table border=\"1\" class=\"dataframe\"><thead><tr style=\"text-align: right;\"><th></th><th>_key</th><th>payment_plan_days</th><th>payment_method_id</th><th>trans_at</th><th>membership_expire_date</th></tr></thead><tbody><tr><th>0</th><td>LWekcgcnUIqi22v63xuIMX4GYbxapmPMoDnLMVLFSTs=</td><td>30</td><td>41</td><td>2015-01-01</td><td>2015-02-02</td></tr><tr><th>1</th><td>vQ017y/6EVjUSmMb9IJvDZUJtLkHKGnWfUAbt7nxeU0=</td><td>30</td><td>41</td><td>2015-01-01</td><td>2015-02-01</td></tr><tr><th>2</th><td>aQu0EDyd2mjbYCZpm5ObIeZdRiH/wAiM6wzy10mc+3s=</td><td>31</td><td>40</td><td>2015-01-01</td><td>2015-01-31</td></tr><tr><th>3</th><td>UsBmIup1CbiB3i9U2cpJUvupy2BbVqXUxYB/gBhkqBs=</td><td>31</td><td>40</td><td>2015-01-01</td><td>2015-02-01</td></tr><tr><th>4</th><td>AdMs4wOzKfiO6hM9ayoe4CgYcHsXaoV6pDhkqEwtpzk=</td><td>31</td><td>40</td><td>2015-01-01</td><td>2015-02-01</td></tr><tr><th>...</th><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td></tr><tr><th>288556</th><td>TNOcP07Mry/UFtgvxn9bUPgq8Zf6dwdWQjn9kv7P+g0=</td><td>30</td><td>41</td><td>2017-02-28</td><td>2017-03-31</td></tr><tr><th>288557</th><td>My/CEivMfiCWmSl9C1BNarV80eaMdd+LjsqnR8g6fsU=</td><td>30</td><td>34</td><td>2017-02-28</td><td>2017-03-31</td></tr><tr><th>288558</th><td>OKdMxAyGn1bJ43uCyWPpr8hYYX0/gdE1Q8Jrs1mGYuI=</td><td>30</td><td>34</td><td>2017-02-28</td><td>2017-03-31</td></tr><tr><th>288559</th><td>3XvMZe4vmCLvPQJoVdOMNt4QE4U1s5dXIW4JiebDtss=</td><td>30</td><td>41</td><td>2017-02-28</td><td>2017-03-31</td></tr><tr><th>288560</th><td>MvNHn2nZqq7nBBuj6yS7ISvZrvnWx1BJvFpxjNcMvmc=</td><td>30</td><td>34</td><td>2017-02-28</td><td>2017-03-31</td></tr></tbody></table><p>288561 rows × 5 columns</p></div></body></html></div></div><div class=\"details kda_tabcontent\" style=\"display:none;\"><div class=\"kda_scroll_container\"><table class=\"kda_table\"><tr><td><b>state</b></td><td>SUCCESS</td></tr><tr><td><b>query_id</b></td><td>6c9df06b-85aa-49fe-8ca9-fe5948625233</td></tr><tr><td><b>metrics</b></td><td><table class=\"kda_table\"><tr><td><b>time_preparing</b></td><td>0.033s</td></tr><tr><td><b>time_computing</b></td><td>0.739s</td></tr><tr><td><b>output_files</b></td><td>1</td></tr></table></td></tr><tr><td><b>parquet</b></td><td><table class=\"kda_table\"><tr><th>index</th><th>path</th></tr><tr><td><pre>0</pre></td><td><a href=\"https://studio-us-west-2-prod-kaskada.s3.us-west-2.amazonaws.com/wren/dbv1alpha/results/cac2a62e-70d1-452d-bc65-d4dd832cb5b6/bqnmxiezAXyCw0XFfold6JZaAgdZoG12k80wig/2d2aed7a-d6f3-4e87-9550-df35104ef627.parquet?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=ASIAZJRQG37GR2T7FKHT%2F20221229%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20221229T192009Z&X-Amz-Expires=3600&X-Amz-Security-Token=IQoJb3JpZ2luX2VjEBsaCXVzLXdlc3QtMiJIMEYCIQDGNPQeP5JKF7hOP5I0BRaFwRFPeO47F%2FJkJ2ngj9zRLgIhAJUS4644RdkiJKwApv%2FGXY7Lzdq0ItJySCJ%2FthizSzBYKvQECGQQAhoMNjM4OTc3NDk5MDg1IgwZZs06h2QX9MgbGxkq0QSTzHEyxitLIiFb7PL94E2%2F6ptSD1uo9YiT7nqQsEQnHds2id6Aahuj%2F6ZBlV1myw2gqsKQNN5QTR7nJlTn8CZzac9IfC%2BxXnfIC%2F5p2YXNfpjzIGUioe4JuR9tqbE9AZ5zEXI9s9wnXrc9bKwgEyySnTaMIhY1gTyEZFdC6vTmXF5C2vnNRCThyu3MqxcyE5QonSfEXBEyyq4lpctGBLGM1rwDjht16YYWfmqYj8WoUVrcha%2BWpC9d%2BpPU3n%2Fi%2BAMcOmckVoHLdQHZQPeB2yTOTKgjcZ2HhGlrHHq0rZAJbYcJa6fAMMuK3G3Xlw%2Fvz2Qh6PQ%2BqjPUy4Pm2w1UqherNA2Uq0qVjL8Ubp9mmwaYVD9LIu47nN%2FZA0AuYeDkf0J2boH885w6FxYfjbvHYZLHlPNg1trted0BzmPhj6%2F8ycdHN18oI0i7sXXgI2odMWf1IrywHzAtRD0VFLzjO4XUjaWEJpXpmlrZNCy43rDuNEyAVX4A3kgvnZQFvK74IPsgtyYmE09X%2FwVhdRcqXurt9v7II826ECdCFVlmbwh7hK9Zgq1ZlrC4veXSeLcQE7ANj3A%2F0w4q%2BLKo8sNRfrtpcCXBXsewseN9iOrxXFGlAZkaP3A4qYn2mK8yHFckHAdXAbfn29sCbc7SyahxI1xPpFFBo4xM2aTVC%2BC0EhRGo0hx4eb5LuEmYmMjEKLOcgAV2O%2BJ98d1ox1bQ1fQCQDTMarJ9KkcwnTHmL%2BPj5LC1sRMaSgdBvq7JG9v8u74rRULSOr6UOQzw%2F5Vu69KB85cKDDcw7edBjqZAQXvO0%2FeRSqLnYeLJZ58259i3eL8GI9mX9%2FmIS8yVNsOL6HuabcUzbe3vXO2AmMRs%2FafTsFKF2D6ekuwVHF%2BseKnmkez4%2BoUPCe%2FS0xnmB%2B9hzPbpqNJ2Ki2bT3nlwPA03VLIuglkcLXm40zLDJ09oHKu6ZDtsVW%2BSg7y51gZPDYFA5GohfYx3PGJfpAlBUbKLDb9mYMTQZvZA%3D%3D&X-Amz-SignedHeaders=host&X-Amz-Signature=06d80411355018de06ef2e2aa7fdb33508f0542013009567a3a14851983d68fa\">https://studio-us-west-2-prod-kaskada.s3.us-west-2.amazonaws.com/wren/dbv1alpha/results/cac2a62e-70d1-452d-bc65-d4dd832cb5b6/bqnmxiezAXyCw0XFfold6JZaAgdZoG12k80wig/2d2aed7a-d6f3-4e87-9550-df35104ef627.parquet?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=ASIAZJRQG37GR2T7FKHT%2F20221229%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20221229T192009Z&X-Amz-Expires=3600&X-Amz-Security-Token=IQoJb3JpZ2luX2VjEBsaCXVzLXdlc3QtMiJIMEYCIQDGNPQeP5JKF7hOP5I0BRaFwRFPeO47F%2FJkJ2ngj9zRLgIhAJUS4644RdkiJKwApv%2FGXY7Lzdq0ItJySCJ%2FthizSzBYKvQECGQQAhoMNjM4OTc3NDk5MDg1IgwZZs06h2QX9MgbGxkq0QSTzHEyxitLIiFb7PL94E2%2F6ptSD1uo9YiT7nqQsEQnHds2id6Aahuj%2F6ZBlV1myw2gqsKQNN5QTR7nJlTn8CZzac9IfC%2BxXnfIC%2F5p2YXNfpjzIGUioe4JuR9tqbE9AZ5zEXI9s9wnXrc9bKwgEyySnTaMIhY1gTyEZFdC6vTmXF5C2vnNRCThyu3MqxcyE5QonSfEXBEyyq4lpctGBLGM1rwDjht16YYWfmqYj8WoUVrcha%2BWpC9d%2BpPU3n%2Fi%2BAMcOmckVoHLdQHZQPeB2yTOTKgjcZ2HhGlrHHq0rZAJbYcJa6fAMMuK3G3Xlw%2Fvz2Qh6PQ%2BqjPUy4Pm2w1UqherNA2Uq0qVjL8Ubp9mmwaYVD9LIu47nN%2FZA0AuYeDkf0J2boH885w6FxYfjbvHYZLHlPNg1trted0BzmPhj6%2F8ycdHN18oI0i7sXXgI2odMWf1IrywHzAtRD0VFLzjO4XUjaWEJpXpmlrZNCy43rDuNEyAVX4A3kgvnZQFvK74IPsgtyYmE09X%2FwVhdRcqXurt9v7II826ECdCFVlmbwh7hK9Zgq1ZlrC4veXSeLcQE7ANj3A%2F0w4q%2BLKo8sNRfrtpcCXBXsewseN9iOrxXFGlAZkaP3A4qYn2mK8yHFckHAdXAbfn29sCbc7SyahxI1xPpFFBo4xM2aTVC%2BC0EhRGo0hx4eb5LuEmYmMjEKLOcgAV2O%2BJ98d1ox1bQ1fQCQDTMarJ9KkcwnTHmL%2BPj5LC1sRMaSgdBvq7JG9v8u74rRULSOr6UOQzw%2F5Vu69KB85cKDDcw7edBjqZAQXvO0%2FeRSqLnYeLJZ58259i3eL8GI9mX9%2FmIS8yVNsOL6HuabcUzbe3vXO2AmMRs%2FafTsFKF2D6ekuwVHF%2BseKnmkez4%2BoUPCe%2FS0xnmB%2B9hzPbpqNJ2Ki2bT3nlwPA03VLIuglkcLXm40zLDJ09oHKu6ZDtsVW%2BSg7y51gZPDYFA5GohfYx3PGJfpAlBUbKLDb9mYMTQZvZA%3D%3D&X-Amz-SignedHeaders=host&X-Amz-Signature=06d80411355018de06ef2e2aa7fdb33508f0542013009567a3a14851983d68fa</a></td></tr></table></td></tr><tr><td><b>analysis</b></td><td><table class=\"kda_table\"><tr><td><b>can_execute</b></td><td><pre>True</pre></td></tr></table></td></tr><tr><td><b>schema</b></td><td><pre>(see Schema tab)</pre></td></tr><tr><td><b>data_token_id</b></td><td><pre>d70f10d1-50b6-40a7-a6dd-12a0d400e12b</pre></td></tr><tr><td><b>slice_request</b></td><td><table class=\"kda_table\"><tr><td><b>None</b></td><td><pre>(full dataset used for query)</pre></td></tr></table></td></tr><tr><td><b>request_details</b></td><td><table class=\"kda_table\"><tr><td><b>request_id</b></td><td><pre>aed988c071bdb73afd3f2258cc26584e</pre></td></tr></table></td></tr><tr><td><b>query</b></td><td><pre>{\n",
              "    payment_plan_days: Transaction.payment_plan_days,\n",
              "    payment_method_id: Transaction.payment_method_id,\n",
              "    trans_at: Transaction.transaction_date,\n",
              "    membership_expire_date: Transaction.membership_expire_date,\n",
              "}</pre></td></tr></table></div></div><div class=\"schema kda_tabcontent\" style=\"display:none;\"><div class=\"kda_scroll_container\"><html><head></head><body><div><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><table border=\"1\" class=\"dataframe\"><thead><tr style=\"text-align: right;\"><th></th><th>column_name</th><th>column_type</th></tr></thead><tbody><tr><th>0</th><td>payment_plan_days</td><td>i64</td></tr><tr><th>1</th><td>payment_method_id</td><td>i64</td></tr><tr><th>2</th><td>trans_at</td><td>timestamp_ns</td></tr><tr><th>3</th><td>membership_expire_date</td><td>timestamp_ns</td></tr></tbody></table></div></body></html></div></div><div class=\"raw kda_tabcontent\" style=\"display:none;\"><div class=\"kda_scroll_container\"><pre>{'dataframe': 'RangeIndex: 288561 entries, 0 to 288560'\n",
              "              'Columns: 5 entries, _key to membership_expire_date'\n",
              "              'dtypes: datetime64[ns](2), int64(2), object(1)'\n",
              "              'memory usage: 11.0+ MB',\n",
              " 'query': '{'\n",
              "          '    payment_plan_days: Transaction.payment_plan_days,'\n",
              "          '    payment_method_id: Transaction.payment_method_id,'\n",
              "          '    trans_at: Transaction.transaction_date,'\n",
              "          '    membership_expire_date: Transaction.membership_expire_date,'\n",
              "          '}',\n",
              " 'query_response': state: STATE_SUCCESS\n",
              "config {\n",
              "  data_token_id: \"d70f10d1-50b6-40a7-a6dd-12a0d400e12b\"\n",
              "}\n",
              "analysis {\n",
              "  can_execute: true\n",
              "  schema {\n",
              "    fields {\n",
              "      name: \"payment_plan_days\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_I64\n",
              "      }\n",
              "    }\n",
              "    fields {\n",
              "      name: \"payment_method_id\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_I64\n",
              "      }\n",
              "    }\n",
              "    fields {\n",
              "      name: \"trans_at\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_TIMESTAMP_NANOSECOND\n",
              "      }\n",
              "    }\n",
              "    fields {\n",
              "      name: \"membership_expire_date\"\n",
              "      data_type {\n",
              "        primitive: PRIMITIVE_TYPE_TIMESTAMP_NANOSECOND\n",
              "      }\n",
              "    }\n",
              "  }\n",
              "}\n",
              "fenl_diagnostics {\n",
              "}\n",
              "metrics {\n",
              "  time_preparing {\n",
              "    nanos: 33763934\n",
              "  }\n",
              "  time_computing {\n",
              "    nanos: 739392304\n",
              "  }\n",
              "  output_files: 1\n",
              "}\n",
              "parquet {\n",
              "  paths: \"https://studio-us-west-2-prod-kaskada.s3.us-west-2.amazonaws.com/wren/dbv1alpha/results/cac2a62e-70d1-452d-bc65-d4dd832cb5b6/bqnmxiezAXyCw0XFfold6JZaAgdZoG12k80wig/2d2aed7a-d6f3-4e87-9550-df35104ef627.parquet?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=ASIAZJRQG37GR2T7FKHT%2F20221229%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20221229T192009Z&X-Amz-Expires=3600&X-Amz-Security-Token=IQoJb3JpZ2luX2VjEBsaCXVzLXdlc3QtMiJIMEYCIQDGNPQeP5JKF7hOP5I0BRaFwRFPeO47F%2FJkJ2ngj9zRLgIhAJUS4644RdkiJKwApv%2FGXY7Lzdq0ItJySCJ%2FthizSzBYKvQECGQQAhoMNjM4OTc3NDk5MDg1IgwZZs06h2QX9MgbGxkq0QSTzHEyxitLIiFb7PL94E2%2F6ptSD1uo9YiT7nqQsEQnHds2id6Aahuj%2F6ZBlV1myw2gqsKQNN5QTR7nJlTn8CZzac9IfC%2BxXnfIC%2F5p2YXNfpjzIGUioe4JuR9tqbE9AZ5zEXI9s9wnXrc9bKwgEyySnTaMIhY1gTyEZFdC6vTmXF5C2vnNRCThyu3MqxcyE5QonSfEXBEyyq4lpctGBLGM1rwDjht16YYWfmqYj8WoUVrcha%2BWpC9d%2BpPU3n%2Fi%2BAMcOmckVoHLdQHZQPeB2yTOTKgjcZ2HhGlrHHq0rZAJbYcJa6fAMMuK3G3Xlw%2Fvz2Qh6PQ%2BqjPUy4Pm2w1UqherNA2Uq0qVjL8Ubp9mmwaYVD9LIu47nN%2FZA0AuYeDkf0J2boH885w6FxYfjbvHYZLHlPNg1trted0BzmPhj6%2F8ycdHN18oI0i7sXXgI2odMWf1IrywHzAtRD0VFLzjO4XUjaWEJpXpmlrZNCy43rDuNEyAVX4A3kgvnZQFvK74IPsgtyYmE09X%2FwVhdRcqXurt9v7II826ECdCFVlmbwh7hK9Zgq1ZlrC4veXSeLcQE7ANj3A%2F0w4q%2BLKo8sNRfrtpcCXBXsewseN9iOrxXFGlAZkaP3A4qYn2mK8yHFckHAdXAbfn29sCbc7SyahxI1xPpFFBo4xM2aTVC%2BC0EhRGo0hx4eb5LuEmYmMjEKLOcgAV2O%2BJ98d1ox1bQ1fQCQDTMarJ9KkcwnTHmL%2BPj5LC1sRMaSgdBvq7JG9v8u74rRULSOr6UOQzw%2F5Vu69KB85cKDDcw7edBjqZAQXvO0%2FeRSqLnYeLJZ58259i3eL8GI9mX9%2FmIS8yVNsOL6HuabcUzbe3vXO2AmMRs%2FafTsFKF2D6ekuwVHF%2BseKnmkez4%2BoUPCe%2FS0xnmB%2B9hzPbpqNJ2Ki2bT3nlwPA03VLIuglkcLXm40zLDJ09oHKu6ZDtsVW%2BSg7y51gZPDYFA5GohfYx3PGJfpAlBUbKLDb9mYMTQZvZA%3D%3D&X-Amz-SignedHeaders=host&X-Amz-Signature=06d80411355018de06ef2e2aa7fdb33508f0542013009567a3a14851983d68fa\"\n",
              "}\n",
              "request_details {\n",
              "  request_id: \"aed988c071bdb73afd3f2258cc26584e\"\n",
              "}\n",
              "query_id: \"6c9df06b-85aa-49fe-8ca9-fe5948625233\"\n",
              "}</pre></div></div></div>"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "eea827f1-f2f6-429a-934a-f00d2ad98bfd"
      },
      "source": [
        "from kaskada import view\n",
        "\n",
        "view.create_view(\n",
        "  view_name = \"Features\", \n",
        "  expression = feature_vector.query,\n",
        ")"
      ],
      "id": "eea827f1-f2f6-429a-934a-f00d2ad98bfd",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "b0ab9ac0-1d8b-464d-a85d-4780a36d1eb5",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 186
        },
        "outputId": "71f0fdf2-9566-41c1-bf18-8f4aa8d7d36c"
      },
      "source": [
        "view.list_views(search = \"Features\")"
      ],
      "id": "b0ab9ac0-1d8b-464d-a85d-4780a36d1eb5",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "<style>table.kda_table {\n",
              "    border: 1px solid grey !important;\n",
              "    border-collapse: collapse !important;\n",
              "    border-spacing: 0 !important;\n",
              "    font-size: 14px !important;\n",
              "    margin-bottom: 6px !important;\n",
              "}\n",
              "\n",
              "table.kda_table table {\n",
              "    margin-bottom: 0 !important;\n",
              "}\n",
              "\n",
              ".kda_table td, .kda_table th {\n",
              "    border: 1px solid grey !important;\n",
              "    border-collapse: collapse !important;\n",
              "    padding: 6px !important;\n",
              "    text-align: left !important;\n",
              "    vertical-align: top !important;\n",
              "}\n",
              "\n",
              ".kda_table tr {\n",
              "    background-color: inherit !important;\n",
              "}\n",
              "\n",
              "/* Style the tab */\n",
              ".kda_tab {\n",
              "    overflow: hidden;\n",
              "    border-bottom: 1px solid grey;\n",
              "    background-color: inherit;\n",
              "}\n",
              "\n",
              "/* Style the buttons that are used to open the tab content */\n",
              ".kda_tab button {\n",
              "    background-color: inherit;\n",
              "    border-top: 1px solid grey;\n",
              "    border-right: 1px solid grey;\n",
              "    border-left: 1px solid grey;\n",
              "    border-bottom: none;\n",
              "    border-radius: 5px 5px 0px 0px;\n",
              "    color: inherit;\n",
              "    cursor: pointer;\n",
              "    float: left;\n",
              "    margin: 2px 8px 0px 2px;\n",
              "    outline: none;\n",
              "    padding: 5px 16px;\n",
              "    transition: 0.3s;\n",
              "}\n",
              "\n",
              "/* Change background color of buttons on hover */\n",
              ".kda_tab button:hover {\n",
              "    background-color: grey;\n",
              "}\n",
              "\n",
              "/* Create an active/current tablink class */\n",
              ".kda_tab button.kda_active {\n",
              "    outline: 2px solid grey;\n",
              "}\n",
              "\n",
              "/* Style the tab content */\n",
              ".kda_tabcontent {\n",
              "    display: none;\n",
              "    padding: 6px;\n",
              "    border: 1px solid grey;\n",
              "    border-top: none;\n",
              "}\n",
              "\n",
              ".kda_scroll_container {\n",
              "    max-height: 400px;\n",
              "    overflow: auto;\n",
              "}\n",
              "</style>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "<script type=\"text/javascript\">function openTab(evt, tabName) {\n",
              "    // Declare all variables\n",
              "    var i, rootElement, tabcontent, tablinks, tabshow;\n",
              "\n",
              "    // Get all elements with class=\"tabcontent\" and hide them\n",
              "    rootElement = evt.currentTarget.parentElement.parentElement;\n",
              "    tabcontent = rootElement.getElementsByClassName(\"kda_tabcontent\");\n",
              "    for (i = 0; i < tabcontent.length; i++) {\n",
              "        tabcontent[i].style.display = \"none\";\n",
              "    }\n",
              "\n",
              "    // Get all elements with class=\"tablinks\" and remove the class \"active\"\n",
              "    tablinks = rootElement.getElementsByClassName(\"kda_tablinks\");\n",
              "    for (i = 0; i < tablinks.length; i++) {\n",
              "        tablinks[i].className = tablinks[i].className.replace(\" kda_active\", \"\");\n",
              "    }\n",
              "\n",
              "    // Show the current tab, and add an \"active\" class to the button that opened the tab\n",
              "    tabshow = rootElement.getElementsByClassName(tabName);\n",
              "    for (i = 0; i < tabshow.length; i++) {\n",
              "        tabshow[i].style.display = \"block\";\n",
              "    }\n",
              "    evt.currentTarget.className += \" kda_active\";\n",
              "}\n",
              "</script>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "views {\n",
              "  view_id: \"07b93f9b-730c-4858-8d7c-7b78060b0361\"\n",
              "  view_name: \"Features\"\n",
              "  expression: \"{\\n    payment_plan_days: Transaction.payment_plan_days,\\n    payment_method_id: Transaction.payment_method_id,\\n    trans_at: Transaction.transaction_date,\\n    membership_expire_date: Transaction.membership_expire_date,\\n}\"\n",
              "  result_type {\n",
              "    struct {\n",
              "      fields {\n",
              "        name: \"payment_plan_days\"\n",
              "        data_type {\n",
              "          primitive: PRIMITIVE_TYPE_I64\n",
              "        }\n",
              "      }\n",
              "      fields {\n",
              "        name: \"payment_method_id\"\n",
              "        data_type {\n",
              "          primitive: PRIMITIVE_TYPE_I64\n",
              "        }\n",
              "      }\n",
              "      fields {\n",
              "        name: \"trans_at\"\n",
              "        data_type {\n",
              "          primitive: PRIMITIVE_TYPE_TIMESTAMP_NANOSECOND\n",
              "        }\n",
              "      }\n",
              "      fields {\n",
              "        name: \"membership_expire_date\"\n",
              "        data_type {\n",
              "          primitive: PRIMITIVE_TYPE_TIMESTAMP_NANOSECOND\n",
              "        }\n",
              "      }\n",
              "    }\n",
              "  }\n",
              "  analysis {\n",
              "    fenl_diagnostics {\n",
              "    }\n",
              "    free_names: \"Transaction\"\n",
              "  }\n",
              "}\n",
              "request_details {\n",
              "  request_id: \"e5c73e04723dd40ae673b1cc5fb4ec0d\"\n",
              "}"
            ],
            "text/html": [
              "<div><div class=\"kda_tab\"><button class=\"kda_tablinks kda_active\" onclick=\"openTab(event, 'details')\">Details</button><button class=\"kda_tablinks\" onclick=\"openTab(event, 'raw')\">Raw</button></div><div class=\"details kda_tabcontent\" style=\"display:block;\"><div class=\"kda_scroll_container\"><table class=\"kda_table\"><tr><td><b>views</b></td><td><table class=\"kda_table\"><tr><th>index</th><th>name</th></tr><tr><td><pre>0</pre></td><td><pre>Features</pre></td></tr></table></td></tr><tr><td><b>request_details</b></td><td><table class=\"kda_table\"><tr><td><b>request_id</b></td><td><pre>e5c73e04723dd40ae673b1cc5fb4ec0d</pre></td></tr></table></td></tr></table></div></div><div class=\"raw kda_tabcontent\" style=\"display:none;\"><div class=\"kda_scroll_container\"><pre>views {\n",
              "  view_id: \"07b93f9b-730c-4858-8d7c-7b78060b0361\"\n",
              "  view_name: \"Features\"\n",
              "  expression: \"{    payment_plan_days: Transaction.payment_plan_days,    payment_method_id: Transaction.payment_method_id,    trans_at: Transaction.transaction_date,    membership_expire_date: Transaction.membership_expire_date,}\"\n",
              "  result_type {\n",
              "    struct {\n",
              "      fields {\n",
              "        name: \"payment_plan_days\"\n",
              "        data_type {\n",
              "          primitive: PRIMITIVE_TYPE_I64\n",
              "        }\n",
              "      }\n",
              "      fields {\n",
              "        name: \"payment_method_id\"\n",
              "        data_type {\n",
              "          primitive: PRIMITIVE_TYPE_I64\n",
              "        }\n",
              "      }\n",
              "      fields {\n",
              "        name: \"trans_at\"\n",
              "        data_type {\n",
              "          primitive: PRIMITIVE_TYPE_TIMESTAMP_NANOSECOND\n",
              "        }\n",
              "      }\n",
              "      fields {\n",
              "        name: \"membership_expire_date\"\n",
              "        data_type {\n",
              "          primitive: PRIMITIVE_TYPE_TIMESTAMP_NANOSECOND\n",
              "        }\n",
              "      }\n",
              "    }\n",
              "  }\n",
              "  analysis {\n",
              "    fenl_diagnostics {\n",
              "    }\n",
              "    free_names: \"Transaction\"\n",
              "  }\n",
              "}\n",
              "request_details {\n",
              "  request_id: \"e5c73e04723dd40ae673b1cc5fb4ec0d\"\n",
              "}\n",
              "</pre></div></div></div>"
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "The results of a Fenl query can be written to an external data store and kept up to date as the data underlying the query changes using materializations. A materialization is similar to a query, except that the results are updated any time data is added to a table used by the query. Materializations can be used to populate feature vectors in a variety of feature stores, including Casandra and Astra to be used in production for low-latency inference.\n",
        "\n",
        "[Read more here](https://docs.kaskada.com/docs/working-with-materializations)"
      ],
      "metadata": {
        "id": "cLo0jGu4bzkA"
      },
      "id": "cLo0jGu4bzkA"
    }
  ]
}