Public
Edited
May 13
countries = data['countries.json']()
countries
Type Table, then Shift-Enter. Ctrl-space for more options.
bar_chart = {
const bars = vl.markBar()
.data(countries)
.encode(
vl.x().average('fertility'),
vl.y().fieldN('country')
.sort(vl.average('fertility').order('descending'))
)
return bars.render()
}
scatterplot = {
const scatters = vl.hconcat(
// 1980
vl.markPoint()
.data(countries)
.transform(vl.filter("datum.year == 1980"))
.encode(
vl.x().fieldQ("fertility").title("Fertilidade"),
vl.y().fieldQ("p_fertility").title("Fertilidade Projetada"),
vl.tooltip(["country", "fertility", "p_fertility"])
)
.width(300)
.height(300)
.title("1980"),
// 1990
vl.markPoint()
.data(countries)
.transform(vl.filter("datum.year == 1990"))
.encode(
vl.x().fieldQ("fertility").title("Fertilidade"),
vl.y().fieldQ("p_fertility").title("Fertilidade Projetada"),
vl.tooltip(["country", "fertility", "p_fertility"])
)
.width(300)
.height(300)
.title("1990"),
// 2000
vl.markPoint()
.data(countries)
.transform(vl.filter("datum.year == 2000"))
.encode(
vl.x().fieldQ("fertility").title("Fertilidade"),
vl.y().fieldQ("p_fertility").title("Fertilidade Projetada"),
vl.tooltip(["country", "fertility", "p_fertility"])
)
.width(300)
.height(300)
.title("2000")
)
return scatters.render()
}
Modifique esta célula com o link: githubpageshttps://murilovpinheiro.github.io/
import {vl} from '@vega/vega-lite-api-v5'
data = require('vega-datasets')
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.
