{
    "cells": [
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "[![image](https://colab.research.google.com/assets/colab-badge.svg)](https://githubtocolab.com/gee-community/geemap/blob/master/examples/notebooks/101_choropleth.ipynb)\n",
                "[![image](https://mybinder.org/badge_logo.svg)](https://gishub.org/geemap-binder)\n",
                "\n",
                "Uncomment the following line to install [geemap](https://geemap.org) if needed."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [],
            "source": [
                "import geemap"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [],
            "source": [
                "data = geemap.examples.datasets.countries_geojson"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "Available classification schemes: \n",
                "* BoxPlot\n",
                "* EqualInterval\n",
                "* FisherJenks\n",
                "* FisherJenksSampled\n",
                "* HeadTailBreaks\n",
                "* JenksCaspall\n",
                "* JenksCaspallForced\n",
                "* JenksCaspallSampled\n",
                "* MaxP\n",
                "* MaximumBreaks\n",
                "* NaturalBreaks\n",
                "* Quantiles\n",
                "* Percentiles\n",
                "* StdMean\n",
                "* UserDefined"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [],
            "source": [
                "m = geemap.Map()\n",
                "m.add_data(\n",
                "    data, column='POP_EST', scheme='Quantiles', cmap='Blues', legend_title='Population'\n",
                ")\n",
                "m"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [],
            "source": [
                "m = geemap.Map()\n",
                "m.add_data(\n",
                "    data,\n",
                "    column='POP_EST',\n",
                "    scheme='EqualInterval',\n",
                "    cmap='Blues',\n",
                "    legend_title='Population',\n",
                ")\n",
                "m"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [],
            "source": [
                "m = geemap.Map()\n",
                "m.add_data(\n",
                "    data,\n",
                "    column='POP_EST',\n",
                "    scheme='FisherJenks',\n",
                "    cmap='Blues',\n",
                "    legend_title='Population',\n",
                ")\n",
                "m"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [],
            "source": [
                "m = geemap.Map()\n",
                "m.add_data(\n",
                "    data,\n",
                "    column='POP_EST',\n",
                "    scheme='JenksCaspall',\n",
                "    cmap='Blues',\n",
                "    legend_title='Population',\n",
                ")\n",
                "m"
            ]
        }
    ],
    "metadata": {
        "kernelspec": {
            "display_name": "Python 3",
            "language": "python",
            "name": "python3"
        }
    },
    "nbformat": 4,
    "nbformat_minor": 5
}