Building and Using Tools to See.
UVA Architecture + Data Science. IT Director. Instructor.
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.
