component_check_red_flags_kingfisher.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "s75VrpzLRNkx"
      },
      "source": [
        "## Usability analysis"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "HTkFw9jajocD"
      },
      "source": [
        "Generate a list of the fields published:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "%%sql fields_table <<\n",
        "SELECT\n",
        "    path,\n",
        "    distinct_releases\n",
        "FROM\n",
        "    field_counts\n",
        "WHERE\n",
        "    release_type = 'compiled_release'\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "MgZ3TsCOjozN"
      },
      "outputs": [],
      "source": [
        "fields_list = fields_table.iloc[:, 0].tolist()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "xrxFlHz9Hk48"
      },
      "outputs": [],
      "source": [
        "indicators_dict = get_red_flags_dictionary(fields_list)\n",
        "result = redflags_checks(fields_list, indicators_dict, check_coverage=True)\n",
        "result[\"coverage\"] = get_coverage(indicators_dict)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Fvej9yl_H5oE"
      },
      "source": [
        "### Export results"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "EBmaz2VRITHf"
      },
      "source": [
        "#### Load use case indicators spreadsheet"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "result_final = check_red_flags_indicators(result)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "sbcQgxItIodv"
      },
      "source": [
        "#### Table of results"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "hMJH_IpAIm9V"
      },
      "outputs": [],
      "source": [
        "result_final"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "LXRG5Di4JTC6"
      },
      "source": [
        "#### Most common fields for indicators"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "dU4jyCZyJaqx"
      },
      "source": [
        "This table shows the most frequent fields used to calculate indicators and if they are published.  You can use this table to highlight to the publisher the key data gaps.  "
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "XZVErXpYJXxV"
      },
      "outputs": [],
      "source": [
        "common_fields = most_common_fields_to_calculate_indicators(indicators_dict, fields_table)\n",
        "common_fields"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3001zqj9IxHF"
      },
      "source": [
        "#### Save tables to spreadsheet"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "Qxb5b7wsI0GM"
      },
      "outputs": [],
      "source": [
        "set_spreadsheet_name(\"Red Flags\")\n",
        "save_dataframe_to_sheet(result_final, \"red_flags_table\")\n",
        "save_dataframe_to_sheet(common_fields, \"common_fields_table\")\n",
        "save_dataframe_to_sheet(fields_table, \"fields_list\")"
      ]
    }
  ],
  "metadata": {
    "colab": {
      "provenance": [],
      "toc_visible": true
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}