Published
Edited
Mar 15, 2021
rawData = FileAttachment("city-of-boston-calendar-year-2020-earnings@3.csv").csv()
navio(rawData)
viewof earningsBoston = aq
.fromCSV(
await FileAttachment(
"city-of-boston-calendar-year-2020-earnings@3.csv"
).text()
)
.view({ height: 240 })
earningsBoston.select(0, 1, 3, 10, 11).view()
viewof cleanedEarnings = earningsBoston
.spread(
{ regular: d => op.split(d.REGULAR, '$') },
{ as: ["symbol", "earn"] }
)
.spread({ new: d => op.split(d.earn, ',') }, { as: ["before", "after"] })
.spread({ regular: d => +`${d.before}${d.after}` }, { before: "postal" })
.spread(
{ total_earnings: d => op.split(d.TOTAL_EARNINGS, '$') },
{ as: ["symbol2", "totalEarn"] }
)
.spread(
{ new: d => op.split(d.totalEarn, ',') },
{ as: ["symbol2", "totalEarn"] }
)
.spread({ total: d => +`${d.symbol2}${d.totalEarn}` }, { before: "postal" })
.select("NAME", "DEPARTMENT_NAME", "TITLE", "regular_1", "total_1", "POSTAL")
.view()
cleanedEarnings
.groupby("DEPARTMENT_NAME")
.rollup({
mean_regular: d => op.average(d.regular_1),
mean_total: d => op.mean(d.total_1)
})
.orderby("DEPARTMENT_NAME")
.view()
dataFinal = cleanedEarnings
.groupby("DEPARTMENT_NAME")
.rollup({
mean_regular: d => op.average(d.regular_1),
mean_total: d => op.mean(d.total_1)
})
.orderby("DEPARTMENT_NAME")
.objects()
dataFinal
import { navio } from "@john-guerra/navio"
import { aq, op } from '@uwdata/arquero'
import { Select } from "@observablehq/inputs"
import { vl } from "@vega/vega-lite-api"
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.
