district_winners = district_data
.map(
({
"Paul Vallas": vallas,
'Jesus "Chuy" Garcia': garcia,
"Lori Lightfoot": lightfoot,
"Brandon Johnson": johnson,
district
}) => ({
district,
...Object.entries({ garcia, vallas, lightfoot, johnson }).reduce((a, b) =>
b[1] > a[1] ? b : a
)
})
)
.map((d) => ({
district: d.district,
candidate: d[0],
votes: d[1]
}))
districts = {
blocks.features.map(
(d) =>
(d.properties.district = assignment_hash.get(d.properties.precinct_id)?.[
selected_map
])
);
return blocks;
}
district_borders = turfjs.dissolve(districts, { propertyName: "district" })
fields = Object.fromEntries(
[
"p1_001n",
"school_age_public",
"total_cvap",
"black_cvap",
"white_cvap",
"latino_cvap",
"paul vallas",
"lori e. lightfoot",
"brandon johnson",
'jesus "chuy" garcia'
].map((f) => [f, rollup(f)])
)
district_data = {
const ids = [...Array(20).keys()];
return ids.map((i) => ({
district: i,
popululation: fields.p1_001n.get(i),
"public school students": fields.school_age_public.get(i),
"total CVAP": fields.total_cvap.get(i),
"Black CVAP %": fields.black_cvap.get(i) / fields.total_cvap.get(i),
"Latino CVAP %": fields.latino_cvap.get(i) / fields.total_cvap.get(i),
"white CVAP %": fields.white_cvap.get(i) / fields.total_cvap.get(i),
'Jesus "Chuy" Garcia': fields['jesus "chuy" garcia'].get(i),
"Paul Vallas": fields["paul vallas"].get(i),
"Lori Lightfoot": fields["lori e. lightfoot"].get(i),
"Brandon Johnson": fields["brandon johnson"].get(i)
}));
}
district_data
Type Table, then Shift-Enter. Ctrl-space for more options.
rollup = (property) =>
d3.rollup(
districts.features,
(v) => d3.sum(v, (d) => d.properties[property]),
(d) => d.properties.district
)
blocks_topo = FileAttachment("blocks@9.topojson").json()
choice = (arr) => {
return arr[Math.floor(Math.random() * arr.length)];
}
mapIds = Array.from({ length: 1000 }, (_, i) => i * 10)
selected_map = {
updateButton;
return choice(mapIds);
}
blocks = topojson.feature(blocks_topo, blocks_topo.objects.blocks)
assignments = FileAttachment("assignment@1.csv").csv({ typed: true })
assignment_hash = new Map(assignments.map((d) => [d.block, d]))
may_5_draft_plan_data = FileAttachment("may_5_draft_plan@2.csv").csv({
typed: true
})
may_5_winners = may_5_draft_plan_data
.map(({ district_name, vallas, garcia, lightfoot, johnson }) => ({
district_name,
...Object.entries({ garcia, vallas, lightfoot, johnson }).reduce((a, b) =>
b[1] > a[1] ? b : a
)
}))
.map((d) => ({
district_name: d.district_name,
candidate: d[0],
votes: d[1]
}))
may_5_draft_plan = FileAttachment("may_5_draft_plan@2.geojson").json()
import { rewind } from "@fil/rewind"
turfjs = require("@turf/turf")
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.
