Published
Edited
May 12, 2020
// load the library
data = (await require('vega-datasets@1.29.0'))
// directly load the json data
countries = data['countries.json']()
countries[0]
vl.markLine()
.data({url: countries.url})
.encode(
vl.x().fieldT("year"),
vl.y().fieldQ("life_expect"),
vl.tooltip().field("country")
)
.render()
vl.markLine()
.data({url: countries.url})
.encode(
vl.x().fieldO("year"),
vl.y().fieldQ("life_expect"),
vl.tooltip().fieldN("country")
)
.render()
vl.markLine()
.data(countries)
.encode(
vl.x().fieldT("year").timeUnit("year"),
vl.y().fieldQ("life_expect"),
vl.tooltip().fieldN("country")
)
.render()
viewof line = vl.markLine()
.data(countries)
.encode(
vl.x().fieldT("year"),
vl.y().fieldQ("life_expect"),
vl.color().fieldN("country")
)
.render()
vl.markLine()
.data(countries)
.encode(
vl.x().fieldO("year").axis({ title: "Year" }),
vl.y().fieldQ("life_expect").axis({ title: "Life expectancy" }),
vl.color().fieldN("country"),
)
.render()
// This copies the countries data without tampering with the original afterwards
// It uses ES6 object literal spread syntax to smush together 2 objects:
// - the countries array as it was, and
// - a year key using a new Date object for the 1st Jan of that year
countries_with_year_as_dates = countries.map(d => ({...d, ...{year: new Date(d.year, 0, 1)}}))
vl.markLine()
.data(countries_with_year_as_dates)
.encode(
vl.x().fieldO("year").axis({ title: "Year" }),
vl.y().fieldQ("life_expect").axis({ title: "Life expectancy" }),
vl.color().fieldN("country")
)
.render()
vl.markLine()
.data(countries_with_year_as_dates)
.encode(
vl.x().fieldT("year").timeUnit("utcyear").axis({ tickCount: 5, title: "Year", format: "‘%y" }),
vl.y().fieldQ("life_expect").axis({ title: "Life expectancy" }),
vl.color().fieldN("country")
)
.render()
vl.markLine()
.data(countries_with_year_as_dates)
.encode(
vl.x().fieldT("year").timeUnit("utcyear").axis({ tickCount: 5, title: "Year", format: "‘%y" }),
vl.y().fieldQ("life_expect").axis({ title: "Life expectancy" }),
vl.color().fieldN("country").sort(vl.max("life_expect").order("descending"))
)
.render()
vl.markLine()
.data(countries_with_year_as_dates.slice(0,20))
.encode(
vl.column().fieldN("country").title("Country"),
vl.x().fieldT("year").timeUnit("utcyear").axis({ tickCount: 5, title: "Year", format: "‘%y" }),
vl.y().fieldQ("life_expect").axis({ title: "Life expectancy" })
)
.render()
vl.markLine({point:true})
.data(countries_with_year_as_dates.slice(0,20))
.encode(
vl.column().fieldN("country").title("Country"),
vl.x().fieldT("year").timeUnit("utcyear").axis({ tickCount: 5, title: "Year", format: "‘%y" }),
vl.y().fieldQ("life_expect").axis({ title: "Life expectancy" }),
vl.tooltip().fieldQ("life_expect") // alternatively: vl.tooltip(['life_expect', 'country'])
)
.render()
vl.markLine({point:true})
.data(countries_with_year_as_dates.slice(0,20))
.encode(
vl.column().fieldN("country").title("Country"),
vl.x().fieldT("year").timeUnit("utcyear").axis({ tickCount: 5, title: "Year", format: "‘%y" }),
vl.y().fieldQ("life_expect").axis({ title: "Life expectancy" }),
)
.title("Life expectancy in Afghanistan and Argentina")
.render()
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