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Vega Datasets

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Collection of datasets used in Vega and Vega-Lite examples. This data lives at https://github.com/vega/vega-datasets.

Common repository for example datasets used by Vega related projects. Keep changes to this repository minimal as other projects (Vega, Vega Editor, Vega-Lite, Polestar, Voyager) use this data in their tests and for examples.

The list of sources is in sources.md.

To access the data in Observable, you can import vega-dataset. Try our example notebook. To access these datasets from Python, you can use the Vega datasets python package. To access them from Julia, you can use the VegaDatasets.jl julia package.

The Vega datasets preview notebook offers a quick way to browse the content of the available datasets.

How to use it

NPM

Get the data on disk

npm i vega-datasets

Now you have all the datasets in a folder in node_modules/vega-datasets/data/.

Get the URLs or Data via URL

npm i vega-datasets

Now you can import data = require('vega-datasets') and access the URLs of any dataset with data[NAME].url. data[NAME]() returns a promise that resolves to the actual data fetched from the URL. We use d3-dsv to parse CSV files.

Here is a full example

import data from 'vega-datasets';

const cars = await data['cars.json']();
// equivalent to
// const cars = await (await fetch(data['cars.json'].url)).json();

console.log(cars);

HTTP

You can also get the data directly via HTTP served by GitHub like:

https://vega.github.io/vega-datasets/data/cars.json

Git subtree

You can use git subtree to add these datasets to a project. Add data git subtree add like:

git subtree add --prefix path-to-data [email protected]:vega/vega-datasets.git gh-pages

Update to the latest version of vega-data with

git subtree pull --prefix path-to-data [email protected]:vega/vega-datasets.git gh-pages

Changelog

Version 2.0

  • Update weather.csv and seattle-weather.csv with better encoded weather condition, indicating more rain.

Version 1.30

  • Update seattle-temps with better sourced data.
  • Update sf-temps with better sourced data.

Version 1.29

  • Add ohlc.json. Thanks to @eitanlees!

Version 1.28

  • Add annual-precip.json. Thanks to @mattijn!

Version 1.27

  • Add volcano.json.

Version 1.26

  • Add uniform-2d.json.

Version 1.22

  • Add windvectors.csv. Thanks to @jwoLondon!

Version 1.20

  • Add us-unemployment.csv. Thanks to @palewire!

Version 1.19

  • Remove time in weather.csv.

Version 1.18

  • Fix typo in city name in us-state-capitals.json

Version 1.17

  • Made data consistent with respect to origin by making them originated from a Unix platform.

Version 1.16

  • Add co2-concentration.csv.

Version 1.15

  • Add earthquakes.json.

Version 1.14

  • Add graticule.json, London borough boundaries, borough centroids and tube (metro) rail lines.

Version 1.13

  • Add disasters.csv with disaster type, year and deaths.

Version 1.12

  • Add 0 padding in zipcode dataset.

Version 1.11

  • Add U district cuisine data

Version 1.10

  • Add weather data for Seattle and New York.

Version 1.9

  • Add income, zipcodes, lookup data, and a dataset with three independent geo variables.

Version 1.8

  • Remove all tabs in github.csv to prevent incorrect field name parsing.

Version 1.7

  • Dates in movies.json are all recognized as date types by datalib.
  • Dates in crimea.json are now in ISO format (YYYY-MM-DD).

Version 1.6

  • Fix cars.json date format.

Version 1.5

Version 1.4

  • Add Anscombe's Quartet dataset.

Version 1.3

  • Change date format in weather data so that it can be parsed in all browsers. Apparently YYYY/MM/DD is fine. Can also omit hours now.

Version 1.2

  • Decode origins in cars dataset.
  • Add Unemployment Across Industries in US.

Version 1.1.1

  • Fixed the date parsing on the CrossFilter datasets -- an older version of the data was copied over on initial import. A script is now available via npm run flights N to re-sample N records from the original flights-3m.csv dataset.

Version 1.1

Version 1.0, October 8, 2015

  • Initial import from Vega and Vega-Lite.
  • Change field names in cars.json to be more descriptive (hp to Horsepower).

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