Palette in Hanoi.
// Danfo.js only accepts CSVs from the internet and has no methods for parsing local CSVs into DataFrames. If anyone knows a workaround, please comment!
// Right now, there are some hoops to jump if you want to upload a local file:
// (1) Fork this notebook and upload your file in the fork.
// (2) Publish the fork so that the file lives in Observable's server (ergo the internet) as opposed to just a blob URL that danfo won't accept. Now it has an URL that can be fed into danfo.read_csv().
// (3) Unpubish the fork and read in the file using the new, non-blob URL.
// Default URL: COMPAS dataset acquired by ProPublica. Refer to Northpointe-ProPublica controversy:
// * News article: https://www.propublica.org/article/machine-bias-risk-assessments-in-criminal-sentencing
// * Northpointe's response: https://www.equivant.com/response-to-propublica-demonstrating-accuracy-equity-and-predictive-parity/
// * ProPublica's rejoinder: https://www.propublica.org/article/propublica-responds-to-companys-critique-of-machine-bias-story
url = "https://raw.githubusercontent.com/DataResponsibly/RankingFacts/master/NotebookVersion/dataset/COMPAS_gender.csv"
// A column must have no more than this number of unique values to be categorical; otherwise it's continuous. Change this according to your data.
categoricalNumUniques = 10
//import { fileInput } from "@mbostock/file-input"
/*viewof temp = csvInput({
initialUrl: url
})*/
/*function csvInput({ initialUrl, init, accept = ".csv" }) {
return fileInput({
initialUrl,
accept,
load(url) {
return dfd
.read_csv(url)
.then(df => df)
.catch(error => {
throw new Error(error);
});
}
});
}*/
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.
