{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "0",
   "metadata": {},
   "source": [
    "[![image](https://jupyterlite.rtfd.io/en/latest/_static/badge.svg)](https://demo.leafmap.org/lab/index.html?path=notebooks/09_csv_to_points.ipynb)\n",
    "[![image](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/opengeos/leafmap/blob/master/docs/notebooks/09_csv_to_points.ipynb)\n",
    "[![image](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/opengeos/leafmap/HEAD)\n",
    "\n",
    "**Converting CSV to points**\n",
    "\n",
    "Uncomment the following line to install [leafmap](https://leafmap.org) if needed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1",
   "metadata": {},
   "outputs": [],
   "source": [
    "# !pip install leafmap"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2",
   "metadata": {},
   "source": [
    "This notebook example requires the ipyleaflet plotting backend. Folium is not supported."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import leafmap.leafmap as leafmap"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4",
   "metadata": {},
   "source": [
    "Read a CSV as a Pandas DataFrame."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5",
   "metadata": {},
   "outputs": [],
   "source": [
    "in_csv = \"https://raw.githubusercontent.com/opengeos/data/main/world/world_cities.csv\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = leafmap.csv_to_df(in_csv)\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7",
   "metadata": {},
   "source": [
    "Create a point layer from a CSV file containing lat/long information."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8",
   "metadata": {},
   "outputs": [],
   "source": [
    "Map = leafmap.Map()\n",
    "Map.add_xy_data(in_csv, x=\"longitude\", y=\"latitude\", layer_name=\"World Cities\")\n",
    "Map"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9",
   "metadata": {},
   "source": [
    "Set the output directory."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "10",
   "metadata": {},
   "outputs": [],
   "source": [
    "out_dir = os.path.expanduser(\"~/Downloads\")\n",
    "if not os.path.exists(out_dir):\n",
    "    os.makedirs(out_dir)\n",
    "out_shp = os.path.join(out_dir, \"world_cities.shp\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "11",
   "metadata": {},
   "source": [
    "Convert a CSV file containing lat/long information to a shapefile."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "12",
   "metadata": {},
   "outputs": [],
   "source": [
    "leafmap.csv_to_shp(in_csv, out_shp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "13",
   "metadata": {},
   "outputs": [],
   "source": [
    "out_geojson = os.path.join(out_dir, \"world_cities.geojson\")\n",
    "leafmap.csv_to_geojson(in_csv, out_geojson)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "14",
   "metadata": {},
   "source": [
    "Convert a CSV file containing lat/long information to a GeoPandas GeoDataFrame."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "15",
   "metadata": {},
   "outputs": [],
   "source": [
    "# gdf = leafmap.csv_to_gdf(in_csv)\n",
    "# gdf"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}