Public
Edited
Apr 22, 2024
1 fork
bertin.draw({
params: { projection: d3.geoMercator(),
margin: 20,
height: 550,
extent: [[22.0856083513, 40.0807890155],[44.3614785833, 52.3350745713]]},
layers: [
{
type: "header",
text: `War impact on grain production in Ukraine`,
fontSize: 30
},
{
type: "mushroom",
geojson: grain_geo,
top_values: "vol_2022",
bottom_values: "vol_2021",
k: 30,
bottom_tooltip: {
fields: ["$region",
d => "Volume: " + Math.round(d.properties.vol_2021 * 10) / 10 + " mmt"],
col: "#4fabd6"
},
top_tooltip: { fields: ["$region",
d => "Volume: " + Math.round(d.properties.vol_2022 * 10) / 10 + " mmt"],
col: "#d64f4f" },
leg_x: 100,
leg_y: 350,
leg_title: "Grain production, mm tons",
leg_top_fill: "none",
leg_bottom_fill: "none",
leg_top_txt: "2022",
leg_bottom_txt: "2021",
leg_fontSize: 16,
leg_round: 1
},
{
type: "layer",
geojson: ukraine,
fill: "#e4d96f",
fillOpacity: 0.5,
stroke: "white"
}
]
})
grain_geo = bertin.merge(geo.centroid(ukraine), "name", grain_agg, "region_alt")
grain_agg = aq.from(grain)
.groupby("year", "region")
.rollup({volume: d => op.sum(d.production / 1000)})
.groupby("region")
.pivot("year", "volume")
.rename({2021: "vol_2021", 2022: "vol_2022"})
.objects()
.map(d => ({...d, region_alt: name_mapping[d.region]})) // change region name spelling
// Mapping between different name spellings in .csv and .geojson files
name_mapping = {
const reg_old = ukraine.features.map(d => d.properties.name).sort()
const reg_new = ["Cherkasy", "Chernihiv", "Chernivtsi", "Crimea", "Dnipropetrovsk", "Donetsk", "Ivano-Frankivsk", "Kharkiv", "Kherson", "Khmelnytskiy", "Kyiv", "Kirovohrad", "Lviv", "Luhansk", "Mykolayiv", "Odesa", "Poltava", "Rivne", "Sumy", "Ternopil", "Zakarpattya", "Vinnytsya", "Volyn", "Zaporizhzhya", "Zhytomyr"]
return _.zipObject(reg_new, reg_old) // merge two arrays into key-value pairs
}
ukraine
grain = FileAttachment("UKR grain 2021-2022@3.csv").csv({typed: true})
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