exploring some data & viz |
work account at @alice-liang
plot_percent(full_pw_data, "Has POC")
Plot.plot({
marginLeft: 100,
y: {type: "point", grid: true},
marks: [
Plot.image(full_pw_data, Plot.dodgeX({y:"Year-Isoweek", src: "google_thumbnail", padding: 32, width: 50})),
Plot.text(full_pw_data, Plot.dodgeX({y:"Year-Isoweek", padding:32, textAnchor: "end", dx: 5, dy:-25,
text: d => d['Has POC']==='TRUE' ? "🔵" : "" }))],
height: 15000,
width:1300
})
url = "https://docs.google.com/spreadsheets/d/1Rxz5IFE16bA9pPAY5_B5LhitvPDIlYrlMwp7fmszwOA/edit#gid=0"
raw_data = d3.csv(getCsvUrl(url), d3.autoType)
chart_data_pre = listings_sql.filter(e => form.publishers.includes(e['publisher_group']))
.filter(e => form.has_poc.includes(e['Has POC']))
.filter(e => form.clothing_style.includes(e['Clothing Style']))
.filter(e => form.style.includes(e['Style']))
.filter(e => form.season.includes(e['season']))
.filter(e => e['year'] >= form.yearInterval[0] && e['year'] <= form.yearInterval[1])
full_pw_url = "https://docs.google.com/spreadsheets/d/1t4LbmRXm7F1IjzuLp8GRGyGCH6UdJ5aDHc8_nG6p8i4/edit#gid=0"
full_pw_raw = d3.csv(getCsvUrl(full_pw_url), d3.autoType)
full_pw_data = full_pw_raw.filter(e => e['Year']>=2018).filter(e => e['Has POC']!='DUPLICATE/NA').filter(e => e['Year']<=2023)
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.
