Software engineer, available for freelance work! • he/him/his
Unlisted
Edited
Nov 8, 2024
2 stars
Plot.plot({
width,
height: 600,
legend: true,
color: { scheme: "blues", legend: true },
projection: {
type: "mercator",
domain: data2
},
marks: [
Plot.geo(data2, {
strokeOpacity: 0.1,
fill: "ratio",
tip: true
})
]
})
data2 = ({
type: "FeatureCollection",
features: raw_data2.map((d) => ({
type: "Feature",
properties: {
precinct: d.Precinct_name,
total_ballots: d.total_ballots,
ratio: JSON.parse(d.votes_by_candidate)[candidate] / d.total_ballots
},
geometry: JSON.parse(d.geometry)
}))
})
contests = query("select distinct Contest_title from election_results").then(
(d) => d.map((d) => d.Contest_title)
)
candidates = Object.keys(JSON.parse(raw_data2[0].votes_by_candidate))
raw_data2 = query(
`select
Precinct_name,
precincts.geometry,
total_ballots,
JSON_GROUP_OBJECT(
candidate_name,
total_votes
) as votes_by_candidate
from
election_results
join precincts on election_results.Precinct_name = precincts.precinct_id
where Contest_title = :contest
group by
Precinct_name,
precincts.geometry,
total_ballots;`,
{ contest }
)
secret = "dsatok_Mg.RthvHCIdfuaUtCpf7HvdOsnZfVY" // lol
query("select * from precincts")
function query(sql, params = {}) {
return fetch(
`https://datasette-public-office-hours.datasette.cloud/data/-/query.json?${new URLSearchParams(
{ sql, _shape: "array", ...params }
).toString()}`,
{
headers: {
Authorization: `Bearer ${secret}`
}
}
).then((r) => r.json());
}
Plot.plot({
width,
height: 600,
legend: true,
color: { scheme: "blues", legend: true },
projection: {
type: "mercator",
domain: null
},
marks: [
Plot.geo(data2, {
strokeOpacity: 0.1,
fill: "ratio",
tip: true
})
]
})
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.
