Curious human. Interested in the mechanics of how things work.
Public
Edited
Jan 27, 2023
1 fork
thresholds=22
changeColor(combined, "black", 12)
function changeColor (chart, color, fontsize) {
d3
.select(chart)
.select("[aria-label=x-axis]")
.selectAll("text")
.each(function (d) {
// d is the tick's value (in this case, a number)
d3.select(this)
.attr("fill", color)
.attr("font-size", fontsize)
.attr("font-family", "IBM Plex Sans");
})
d3
.select(chart)
.select("[aria-label=y-axis]")
.selectAll("text")
.each(function (d) {
// d is the tick's value (in this case, a number)
d3.select(this)
.attr("fill", color)
.attr("font-size", fontsize)
.attr("font-family", "IBM Plex Sans");
})
d3
.select(chart)
.select("[aria-label=x-axis]")
.selectAll("line")
.each(function (d) {
// d is the tick's value (in this case, a number)
d3.select(this)
.attr("stroke", color)
})
d3
.select(chart)
.select("[aria-label=y-axis]")
.selectAll("line")
.each(function (d) {
// d is the tick's value (in this case, a number)
d3.select(this)
.attr("stroke", color)
})
d3.select(chart)
.selectAll("text")
.each(function(d) {
d3.select(this)
.attr("font-family", "IBM Plex Sans");
})
}
Plot.plot({
width:width/1.5,
height: 1000,
marks: [
Plot.dot(data, Plot.dodgeY({x: "urban_10", fill: "sub_continent", fy: "sub_continent", anchor}))
]
})
viewof anchor = Inputs.radio(["top", "middle", "bottom"], {label: "Anchor", value: "bottom"})
Plot.plot({
insetRight: 10,
marginLeft: 100,
height: 400,
width,
marks: [
Plot.dot(
data,
Plot.dodgeX({
y: "sub_continent",
r: "urban_10",
title: d => `${d.NAME}\n${(d.rMVOP / 1e3).toFixed(1)}B`,
fill: "currentColor"
})
),
// Plot.text(
// data,
// Plot.dodgeX({
// filter: (d) => d.rMVOP > 5e3,
// y: "sub_continent",
// r: "urban_10",
// text: d => (d.rMVOP / 1e3).toFixed(),
// fill: "white",
// fontWeight: "bold"
// })
// )
]
})
Plot.plot({
height: 180,
marks: [
Plot.dot(iataGroupedByRegions, Plot.dodgeY({x: "sub_continent",}))
]
})
data =
{
let df = iataGroupedByRegions.filter(row => sub_continents.includes(row['sub_continent']))
for (let i in df){
df[i]['combined_10'] = iataGroupedByRegions[i]['empty_10'] + iataGroupedByRegions[i]['arid_10'];
df[i]['combined_sqkm'] = iataGroupedByRegions[i]['combined_10'] * 13 / 1e6;
df[i]['urban_sqkm'] = iataGroupedByRegions[i]['urban_10'] * 13 / 1e6;
}
return df;
}
range = ["#ff595e", "#ff924c", "#ffca3a", "#8ac926", "#1982c4", "#6a4c93",
"#E04E53", "#DD7275", "#FA8D91", "#FFA6A8",
"#FF924C", "#E0884F", "#FBA771", "#FFCBA9",
"#73AA1C", "#70A51E" ,"#9FC95C" ,"#B9E375", "#B9E375",
"#FFE9AF", "#FFCA3A", "#1982C4",
"#9D88BA",
"#BCE784", "#5DD39E", "#348AA7", "#513B56",
]
domain = ["EU", "AS", "SA", "AF", "NA", "OC",
"Central and East Europe", "North Europe", "South Europe", "West Europe",
"East Asia", "Southeast Asia", "South Asia", "West Asia",
"Central Africa", "East Africa", "North Africa", "South Africa", "West Africa",
"South America", 'Central America', "North America",
"Australia and New Zealand",
"Trains", "Electric aircraft", "Hydrogen aircraft", "Petroleum", ]
colorScale = d3.scaleOrdinal().domain(domain).range(range)
import {sub_continents} from "4b75e48934b7ce6a"
import {iataGroupedByRegions} from "b7b073d13cec22e7"
One platform to build and deploy the best data apps
Experiment and prototype by building visualizations in live JavaScript notebooks. Collaborate with your team and decide which concepts to build out.
Use Observable Framework to build data apps locally. Use data loaders to build in any language or library, including Python, SQL, and R.
Seamlessly deploy to Observable. Test before you ship, use automatic deploy-on-commit, and ensure your projects are always up-to-date.