Building and Using Tools to See.
UVA Architecture + Data Science. IT Director. Instructor.
Maps (Geographic)base codeMultiple LayersAdd Zoom and PanProjectionsDotMapCentroids, Bounds, AbstractionsSparklines at centroidsUS States Grid MapWorld Grid MapLeafletMapBox GLMapBox GL - layersMapBox GL - dot locationsObservable Plot - Base World MapObservable Plot - Add GIS LayersObservable Plot - ProjectionsObservable Plot - ChoroplethObservable Plot - Dot mapUS map with Powerplant Pack CirclesRing plot on Map - Trust Gap?Fixed location Network GraphConnecting multiple visuals in one spacegeoContainsPolygons by [lon,lat] sets on Map (geo)
Choropleth
viewof year = Inputs.range([1961, 2011], {label: "Year", step:1, value:1994})
map = d3.select(mapContainer)
import {getMapData, drawMapLayer} from "@emfielduva/dvlib_maps"
world = getMapData("world110m")
mapLayers = {
let mapLayers = [];
mapLayers["countries"] = drawMapLayer(map,"countries",world.features,world.idField);
return mapLayers;
}
<style>
#countries path {fill: #eeeeee; stroke: #ccc}
</style>
gdp = FileAttachment("world-gdp-growth.csv").csv()
import {colorByID, toNum} from "@emfielduva/dvlib"
colorScale = d3.scaleLinear().domain([-25,0,25]).range(["red","gray","green"])
//year = "1994" // this is commented out to use the range slider at the top to define year
Now invoke the colorByID function imported.
This connects the "Country Code" in the gdp dataset to the "id" in the geographic map data.
The syntax of this command is:
colorByID
colorByID(mapLayers["countries"],gdp,"id","Country Code",year,'',colorScale)
// data.forEach(d => {
// objectSet.filter(o=>o[objectIDfield] == d[dataIDfield])
// .style("fill",colorScale(toNum(d[dataValueField])))
// })
Purpose-built for displays of data
Observable is your go-to platform for exploring data and creating expressive data visualizations. Use reactive JavaScript notebooks for prototyping and a collaborative canvas for visual data exploration and dashboard creation.
