wb_tidy.csv
Type Table, then Shift-Enter. Ctrl-space for more options.
Plot.plot({
marks: [
Plot.frame(),
Plot.dot(worldbank, {
filter: (d) => d.year == 2010,
x: "gdp",
y: "co2",
fill: "#ccc",
r: "life_exp",
opacity: 0.5
}),
Plot.dot(worldbank, {
filter: (d) => d.year == 2010,
x: "gdp",
y: "co2",
fill: "life_exp",
r: "life_exp",
opacity: 0.9,
fy: "income_group"
})
],
color: { legend: true, scheme: "BuPu" },
r: { domain: d3.extent(worldbank, (d) => d.life_exp), range: [1, 10] },
x: { type: "log" },
y: { type: "log" },
fy: {
domain: [
"NA",
"Low income",
"Lower middle income",
"Upper middle income",
"High income"
],
reverse: true
},
marginRight: 120
})
Plot.plot({
marks: [
Plot.lineY(stocks, {
x: "Date",
y: "Close",
stroke: "symbol",
opacity: 0.3
}),
Plot.lineY(
stocks,
Plot.windowY(
{ k: 30, anchor: "start", reduce: "max" }, //start, middle, end
{ x: "Date", y: "Close", stroke: "symbol" }
)
),
Plot.text(
stocks,
Plot.selectLast({
x: "Date",
y: "Close",
text: "symbol",
fill: "symbol",
textAnchor: "start"
})
)
],
color: { legend: true }
})
Meteorite_Landings.csv
Type Table, then Shift-Enter. Ctrl-space for more options.
Plot.plot({
projection: "equal-earth",
marks: [
Plot.geo(land, { fill: "#ccc" }),
Plot.dot(meteorites, {
x: "reclong",
y: "reclat",
fill: "purple",
r: "mass (g)"
})
]
})
viewof pickColor = Inputs.color({label: "Favorite color", value: "#4682b4"})
// Update the fill option to depend on the value of pickColor to make it interactive!
Plot.plot({
marks: [
Plot.dot(cars, {x: "power (hp)", y: "economy (mpg)"})
]
})
aapl = FileAttachment("aaplStock.csv").csv({typed: true})
goog = FileAttachment("googStock.csv").csv({typed: true})
tsla = FileAttachment("tslaStock.csv").csv({typed: true})
dateParse = d3.timeParse("%m/%d/%y")
stocks = aapl.map(d => ({...d, symbol: "aapl"})).concat(goog.map(d => ({...d, symbol: "goog"})), tsla.map(d => ({...d, symbol: "tsla"}))).map(d => ({...d, Date: dateParse(d.Date)}))
import {land} from "@observablehq/plot-live-earthquake-map"
import { showMe } from "@observablehq/show-me"
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.
