imclab / mapmakers-cheatsheet

popular tourist locations on the wild and exciting quest to make web maps in fewer tries

• What kind of data do you have?

  • Points
    • How much data?
      • Just enough
        • Convert the data to GeoJSON & make a simple Leaflet map
      • Too much in a confusing way, but each point's data is important?
        • Cluster your points with Leaflet.markercluster
      • Too much and the points have some value that can be aggregated
        • Create hexbins of your points with the QGIS hexbin plugin, to make polygons. Start again at Polygons
      • Too much and the points just represent presence - like tweets
        • Create a heatmap with Leaflet.heat or QGIS heatmap plugin. If you use QGIS heatmap, start again at Raster.
  • Polygons
    • How much data?
      • Just enough
        • Convert the data to GeoJSON & make a simple Leaflet map
      • Too much, the polygons have necessary detail
        • Use TileMill to render an interactive map with UTFGrid
      • Too much, the polygons have unnecessary details
        • Simplify them with TopoJSON or QGIS
    • What kind of attributes do they have?
      • Absolute numbers
        • Convert the points to centroids with QGIS and start from Points
        • Normalize absolutes to rates by dividing over polygon area, and start from Rates
      • Rates or Categories
        • Make a choropleth map with Leaflet for small data, TileMill for big data
      • Temporal data - values over time
        • If there are fewer than 100 samples - like 50 years of data grouped by year, make small multiples: a map per sample.
        • If you can code, make an animation with Leaflet or d3
        • If it's tons of data, use CartoDB and torque
      • Multivariate data: like counts of different species or ethnicities
        • Make a dot density map with englewood
  • Raster
    • Render a map with TileMill and use the tiles in Leaflet
  • Names of places, like countries
    • With IDs:
      • ISO2 or ISO3 codes
        • Download Natural Earth data at the right level, join with QGIS, and start again at Polygons
      • ZIP codes
        • Download ZCTAs and join
    • Without IDs
      • Find data with IDs, or manually join with polygons
  • Addresses
    • You can't map addresses directly. Geocode them with OpenRefine or Geo for Google Docs, and then start at Points
  • A format that I can't read
    • Install GDAL and use ogr2ogr to convert the file
    • Ask your source for a better file format
  • I don't have data yet
    • Contact the town or federal GIS dept you need
    • Use FOIAMachine.org to request data via FOIA
    • If you want to create data, use geojson.io and draw it.

• Visualization defaults

  • Projection:
    • If it's a web map with tiles, use Mercator
    • If using d3 and not using tiles anywhere, use whatever fits best
  • Colors:
    • When in doubt, use ColorBrewer
  • Scales:
    • For any data
      • Try linear first
      • Then quantile
    • For data of rates or compounding
      • Try log and power scales
  • Points:
    • Start with normal circles with no strokes
    • Scale points by area, not diameter
  • Flair:
    • Only add a north arrow if north isn't up
    • Always attribute your data, especially OpenStreetMap, to avoid the nerd wrath
    • If it zooms, add visible zoom controls. Pan isn't necessary, but not everyone has a scroll wheel / multitouch