file.name
app_clean = aq.from(app_raw)
.derive({
cpa: d => +op.replace(d['Cost Per Applicant 50th Percentile'], '$', ''),
cr: d => +op.replace(d['Conversion Rate 50th Percentile'], '%', '') / 100
})
.objects()
app_raw = FileAttachment("Travel Nurse Benchmark Data for Aya Healthcare 2023.07.11.csv").csv({typed: true})
clean_indeed = aq.from(raw_indeed)
.derive({Date: d => op.parse_date(d.Date)})
.objects()
raw_indeed = FileAttachment("aya-indeed-insights.csv").csv({typed: true})
clean = aq.from(raw_data)
.objects()
raw_data = file.csv({typed: true})
// this is a really cool way of displaying tables. Much more aesthetically pleasing than the defaults of arquero and input.table
import { formatTable } from "@saneef/pretty-tables"
import {toc} from "@nebrius/indented-toc"
date_parser = d3.utcParse('%m/%d/%Y')
// sample of how to place html blocks in a grid
// html `<div style="display: grid; grid-template-columns: 1fr 1fr 1fr; column-gap: 0px; row-gap: 5px;">
// ${viewof spend}
// ${viewof cpl}
// ${viewof cpc}
// </div>`
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.
