Visiting Research at NYU Shanghai; previously @ Nest, Apple, AOL; faculty @ Olin College, NYU Shanghai.
cases = d3.csvParse(
`date,local,imported,source
2021-01-20,0,9,https://www.shine.cn/news/metro/2101213536/
2021-01-21,6,3,https://www.shine.cn/news/metro/2101213552/
2021-01-22,3,8,https://www.shine.cn/news/metro/2101233648/
2021-01-23,3,3,https://www.shine.cn/news/metro/2101243681/
2021-01-24,1,2,https://www.shine.cn/news/metro/2101253732/
2021-01-25,2,8,https://www.shine.cn/news/metro/2101263806/
2021-01-26,1,5,https://www.shine.cn/news/metro/2101273891/
2021-01-27,0,7,https://www.shine.cn/news/metro/2101283970/
2021-01-28,0,9,https://www.shine.cn/news/metro/2101294033/
2021-01-29,2,9,https://www.shine.cn/news/metro/2101304076/
2021-01-30,0,7,https://www.shine.cn/news/metro/2101314100/
2021-01-31,0,4,https://www.shine.cn/news/metro/2102014132/
`,
createRowConverter({ local: Number, imported: Number })
)
cumulativeLocal = addCumulativeProperty(cases, 'local', 'cumulative_local')
addCumulativeProperty = (data, countProperty, cumulativeProperty) =>
data.reduce(
([acc, total], rec) => {
const totalʹ = total + Number(rec[countProperty]);
return [[...acc, { ...rec, [cumulativeProperty]: totalʹ }], totalʹ];
},
[[], 0]
)[0]
createRowConverter = typeMap => data =>
Object.fromEntries(
Object.entries(data).map(([k, v]) => [k, (typeMap[k] || (v => v))(v)])
)
d3 = require("d3@5")
import {vl} from "@vega/vega-lite-api"
import {table} from "@tmcw/tables@513"
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