Published
Edited
Apr 12, 2019
Importers
Geodata wrangling for Vega-lite and d3Exploring different visualizationsIAT 355: Spatial Visualization ChallengeInteraction
IAT355: Do you have all the data you need? Working with data in d3 and Vega
mp = vanPopCleaned2.filter(function(nhood) {
return nhood.Area == "Mount Pleasant"});
vegalite({
data: {values: vanPopCleaned2},
mark: "tick",
encoding: {
x: {field: "Population", "type": "quantitative"}
}
})
popCrimeView = embedWithSpecificVersions({
"name": "crimePop",
"data":
{
"name": "crime",
"values": vanCrimeCleaned
},
"transform": [
{
"lookup": "NEIGHBOURHOOD",
"from":
{
"data": {"values": populations},
"key": "Area",
"fields": ["Population"]
}
}],
"mark": {
"type": "bar",
"clip": true
},
"encoding": {
"x": {
"aggregate": "count",
"field": "Offense",
"type": "quantitative",
"scale": {
"zero": false,
"domain": [0,80000]
}
},
"y": {
"field": "NEIGHBOURHOOD",
"type": "nominal",
"scale": {"rangeStep": 15}
},
"color":
{
"type": "quantitative",
"field": "Population",
"scale": {
//"domain": [0,9000000,18000000],
"round": true,
"type": "linear",
//"range": ["#8AB9ED", "#acbdbb","#FDB813"]
}
}
}
})
vega_explicit({
"name": "trellis_crime",
"data": {"values": vanCrime2},
"mark": {
"type": "point",
"clip": true
},
"columns": 2,
"encoding": {
"facet": {
"field": "NEIGHBOURHOOD",
"type": "ordinal",
"sort": {"op": "count", "field": "NEIGHBOURHOOD"}
},
"x": {
"aggregate": "count",
"field": "NEIGHBOURHOOD",
"type": "quantitative",
"scale": {
"zero": false,
"domain": [0,9000]
}
},
"y": {
"field": "Offense",
"type": "nominal",
"scale": {"rangeStep": 12}
},
"color": {"field": "Offense Type", "type": "nominal"}
},
"resolve": {"axis": {"x": "independent", "y": "independent"}}
})
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