Nieman mapping workshop

This workshop is going to be fun fun fun 😀

Presentation here

##Datasets:

• Ambient air pollution by city and country 2014 from WHO: here
• John Snow cholera deaths and water pumps dataset: here

##Ambient air quality map Download .xls file here

Open in Excel or Numbers or LibreOffice or Open with Google Sheets

(1) Go to countries sheet

or (2) Go to cities sheet

Copy entirety and paste into a new spreadsheet, name it and save it.

Condense titles into one single row along the top

Delete Region column

Make sure we have data for 'Reference for air quality' column

If not, copy and paste from original .xls

Make sure it's clean (enough)

Upload to CartoDB (automatically geocoding)

In map view, enable choropleth

Enable hover infowindow and select country, PM2.5, PM10, and data source

Back to data view to see null in geometry (talk about shapefiles)

Bolivia 🐸

{"type": "MultiPolygon", "coordinates": [[[[-65.19, -22.09], [-65.75, -22.11], [-66.22, -21.78], [-67.18, -22.82], [-67.88, -22.83], [-68.76, -20.41], [-68.44, -19.43], [-69.48, -17.64], [-69.5, -17.51], [-68.82, -16.34], [-69.42, -15.62], [-68.67, -12.5], [-69.57, -10.95], [-68.58, -11.11], [-66.63, -9.91], [-65.38, -9.7], [-64.99, -12.01], [-60.47, -13.81], [-60.16, -16.26], [-58.33, -16.28], [-58.4, -17.25], [-57.52, -18.2], [-58.16, -20.17], [-59.1, -19.35], [-61.74, -19.65], [-62.64, -22.24], [-63.94, -22], [-64.32, -22.87], [-64.59, -22.21], [-65.19, -22.09]]]]}

Find the multipolygon coordinates data here for Venezuela and input it. This is written in JSON. More granular coordinates can be found here.

##Design in mind Projections

Data sources

Point vs. Regional data

Consider elements of design (leading and misleading, typography, palette, the color blind)

##John Snow map: How To with CartoDB import zip files

cholera deaths: http://storybench.org/presentations/cholera_deaths.zip

pumps: http://storybench.org/presentations/pumps.zip

bubble visualization

radius 6 to 12, give or take

retitle infowindow count to 'Deaths'

SQL delete what's in there and add this.

SELECT cartodb_id, the_geom_webmercator, count, 'cholera' as layer FROM cholera_deaths
UNION ALL
SELECT cartodb_id, the_geom_webmercator, NULL as count, 'pump' as layer FROM pumps

This is... "selecting the_geom_webmercator from each table. From the cholera_deaths table we are selecting count so that we can base our bubble size on the value. When we UNION tables we must have the same columns in each table, so for the pumps table we have to include a fake count column with a value of NULL in every row. Finally, We included a column in the results for both tables that indicates a name for the layer the row belongs to."

##CartoCSS (documentation here)

/** bubble visualization */

#cholera_deaths{
  marker-fill-opacity: 0.9;
  marker-line-color: #FFF;
  marker-line-width: 0.5;
  marker-line-opacity: 1;
  marker-placement: point;
  marker-multi-policy: largest;
  marker-type: ellipse;
  marker-fill: #000000;
  marker-allow-overlap: true;
  marker-clip: false;
  marker-comp-op: overlay;
}
#cholera_deaths [layer='pump'] {
  marker-width: 12.0;
  marker-fill: #3399FF;
  marker-line-color: black;
  marker-line-width: 0;
  marker-opacity: 1;
  marker-placement: point;
  marker-type: ellipse;
  marker-allow-overlap: true;
}
#cholera_deaths [ count <= 15] {
   marker-width: 12.0;
}
#cholera_deaths [ count <= 8] {
   marker-width: 11.3;
}
#cholera_deaths [ count <= 8] {
   marker-width: 10.7;
}
#cholera_deaths [ count <= 7] {
   marker-width: 10.0;
}
#cholera_deaths [ count <= 5] {
   marker-width: 9.3;
}
#cholera_deaths [ count <= 5] {
   marker-width: 8.7;
}
#cholera_deaths [ count <= 4] {
   marker-width: 8.0;
}
#cholera_deaths [ count <= 3] {
   marker-width: 7.3;
}
#cholera_deaths [ count <= 2] {
   marker-width: 6.7;
}
#cholera_deaths [ count <= 2] {
   marker-width: 6.0;
}