Transform a CSV dataset into GeoJSON, by matching names of places against a line-delimited GeoJSON source of truth.

Additional layers suitable for a data processing pipeline are included.

This is how it works

Bring your own

The PoC looks for administrative boundaries in Mexico from Marco Geoestadístico Nacional, but you could easily swap to other sources, like OSM.

From the command line

To get the polygon of a city in Mexico, type:

% node cli.js --municipality 'Mexicali'

{
  "type": "FeatureCollection",
  "features": [
    {
      "type": "Feature",
      "properties": {
        "place": {
          "municipality": "Mexicali"
        }
      },
      "geometry": {
        "type": "MultiPolygon",
        "coordinates": [...]
      }
    }
  ]
}

Stream a CSV file and output line-delimited GeoJSON FeatureCollection:

✗ cat test/fixtures/dataset.csv | node cli.js -sc > matches.json
✗ wc -l matches.json
6 matches.json
✗ head -n1 matches.json
{"type":"FeatureCollection","features":[
✗ tail -n1 matches.json
]}
✗ cat matches.json | jq '.features[].properties.NOM_ENT'
"Aguascalientes"
"Baja California"
"Nuevo León"

[recommended] Simplify GeoJSON

% npm install simplify-geojson -g
% cat test/fixtures/dataset.csv | node cli.js --state --collection | simplify-geojson -t 0.01 > map.json

Commands:

% node cli.js --help

Setup

Download INEGI data and transform it into GeoJSON:

% ./data.sh -d data -t data

Install dependencies

% npm install

Cool examples

Transform a CSV to a choropleth-ready GeoJSON:

% cat poblacion-estatal.csv | node marco.js --state

Make a map out of an article

% cat your-article.doc | node marco.js --centroid --municipality | geojsonio

See: geojsonio-cli

Find the distance between my city and a hurricane!

% wget EP202015_005adv_TRACK.kml | togeojson > hurricane.json
% node marco.js 'Puerto Escondido' --centroid --municipality | turf-distance hurricane.json

A pluggable geospatial toolset right in your terminal.