Visualization, Prototypes, ML, Data wrangling and Art.
Parse Wochenbericht
parsed.map(d => d.date)
tableData = parsed.map(({timestamp, date, themes}) => ({timestamp, date, ...themes.map(d => `${d.key}:${d.value}`)}))
flatData = parsed.map(({date, themes}) => themes.map(({key, value}) => ({ date, key, value }))).flat()
coronaData = flatData.filter(d => d.key.indexOf("Corona") > -1)
groupedData = d3.groups(flatData, d => d.key)
.sort(([, a], [, b]) => d3.descending(a, b))
groupedData.filter(d => d[0].indexOf("Corona") > -1)
themes2category = new Map(
await d3.csv("https://docs.google.com/spreadsheets/d/e/2PACX-1vTLIkT1C1jEGyfgoW8IPGbBB5nJKWRXYDib_MMgVgpkObeLF3AbUn3oHm-vW9-WPfYQg5OeTPzN85-8/pub?gid=1582213456&single=true&output=csv")
.then(data => data.map(d => [d.thema, {korrektur: d.korrektur, kategorie: d.kategorie}]))
)
emptyCategories = flatDataCategory.filter(d => !d.key)
Table(d3.groups(flatDataCategory, d => d.key)
.sort(([, a], [, b]) => d3.descending(a, b)).map(d => ({thema: d[0], num: d[1].length})))
//Table(groupedData.map(d => ({thema: d[0], num: d[1].length, kategorie: themes2category.get(d[0]) })))
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.
