Sample datasets

To help you get started, Observable Framework provides a handful of sample datasets by default. If you reference any of these variables (aapl, alphabet, cars, citywages, diamonds, flare, industries, miserables, olympians, penguins, pizza, or weather) in your code, their definition defaults to a Promise loading the corresponding file and returning the data. This makes it easier to get started, with simpler examples of charts and data transformations.

The source data files are downloaded on demand from the @observablehq/sample-datasets npm package, and served from your app’s cache. Note that these names are not “reserved”: you can define alphabet or industries as you see fit, if you need a variable or a function with that name in your app.

The following lists the provenance of each of the sample datasets:

aapl

Yahoo! Finance
https://finance.yahoo.com/lookup

alphabet

Cryptographical Mathematics by Robert Edward Lewand
http://cs.wellesley.edu/~fturbak/codman/letterfreq.html

cars

1983 ASA Data Exposition
http://lib.stat.cmu.edu/datasets/

citywages

The New York Times
https://www.nytimes.com/2019/12/02/upshot/wealth-poverty-divide-american-cities.html

diamonds

ggplot2 “diamonds” dataset
https://github.com/tidyverse/ggplot2/blob/master/data-raw/diamonds.csv

flare

Flare visualization toolkit package hierarchy
https://observablehq.com/@d3/treemap

industries

Bureau of Labor Statistics
https://www.bls.gov/

miserables

Character interactions in the chapters of “Les Miserables”, Donald Knuth, Stanford Graph Base
https://www-cs-faculty.stanford.edu/~knuth/sgb.html

olympians

Matt Riggott/IOC
https://www.flother.is/2017/olympic-games-data/

penguins

Dr. Kristen Gorman
https://github.com/allisonhorst/palmerpenguins

pizza

Pizza Paradise, Observable
https://observablehq.com/@observablehq/pizza-paradise-data

weather

NOAA/Vega
https://www.ncdc.noaa.gov/cdo-web/datatools/records
https://github.com/vega/vega-datasets/blob/master/scripts/weather.py