data = {
const data = [];
names.forEach(d => {
const race_data = raw_race_data.find(t => t.geoid == d);
const age_data = raw_age_data.find(t => t.geoid == d);
const income_data = raw_income_data.find(t => t.geoid == d);
const education_data = raw_education_data.find(t => t.geoid == d);
const tenure_data = raw_tenure_data.find(t => t.geoid == d);
const cdc_data = raw_cdc_data.get(d) != undefined ? raw_cdc_data.get(d) : [undefined, undefined];
data.push({
"geoid": d,
"Non-white population (%)": ((+race_data.total-race_data.white_alone)/+race_data.total)*100,
"Median household income ($)": +income_data.median,
"Bachelor's degree or higher (%)": (+education_data.total_bachelors_or_higher/+education_data.total)*100,
"Renter-occupied units (%)": (+tenure_data.renter_occupied/+tenure_data.housing_units)*100,
"Median age": +age_data.median,
"Diabetes rate": cdc_data[0]
})
})
return Object.assign(data, {columns:[
"Non-white population (%)",
"Median household income ($)",
"Bachelor's degree or higher (%)",
"Renter-occupied units (%)",
"Median age",
"Diabetes rate"
]});
}
names = raw_income_data.map(d => d.geoid)
raw_cdc_data = Object.assign(new Map(await d3.csv("https://gist.githubusercontent.com/mbostock/74a5eafd839597f6c66a1c1dcb6f499f/raw/1742edce177a3b6d059715d2e04fa1315f23c600/cdc-diabetes-obesity.csv", ({county, diabetes, obesity}) => [county, [+diabetes, +obesity]])), {title: ["Diabetes", "Obesity"]})
raw_tenure_data = await d3.csv("https://raw.githubusercontent.com/datadesk/census-data-downloader/714bf0e5c03572360dd750fe93c0873218351973/data/processed/acs5_2017_tenure_counties.csv")
raw_education_data = await d3.csv("https://raw.githubusercontent.com/datadesk/census-data-downloader/714bf0e5c03572360dd750fe93c0873218351973/data/processed/acs5_2017_education_counties.csv")
raw_income_data = await d3.csv("https://raw.githubusercontent.com/datadesk/census-data-downloader/714bf0e5c03572360dd750fe93c0873218351973/data/processed/acs5_2017_medianhouseholdincome_counties.csv")
raw_age_data = await d3.csv("https://raw.githubusercontent.com/datadesk/census-data-downloader/714bf0e5c03572360dd750fe93c0873218351973/data/processed/acs5_2017_medianage_counties.csv")
raw_race_data = await d3.csv("https://raw.githubusercontent.com/datadesk/census-data-downloader/07bfd86ac885f01115488e4b5b6143e0b5c7d38c/data/processed/acs5_2017_race_counties.csv")
keys = data.columns
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.
