vega-datasets
Advanced tools
Collection of datasets used in Vega and Vega-Lite examples. This data lives at https://github.com/vega/vega-datasets and https://cdn.jsdelivr.net/npm/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.
We use semantic versioning. However, since this package serve datasets we have additional rules about how we version data.
We do not change data in patch releases except to resolve formatting issues. Minor releases may change the data but only update datasets in ways that do not change field names or file names. Minor releases may also add datasets. Major versions may change file names, file contents, and remove or update files.
You can also get the data directly via HTTP served by GitHub or jsDelivr (a fast CDN) like:
https://vega.github.io/vega-datasets/data/cars.json or with a fixed version (recommended) such as https://cdn.jsdelivr.net/npm/vega-datasets@2/data/cars.json.
You can find a full listing of the available datasets at https://cdn.jsdelivr.net/npm/vega-datasets/data/.
npm i vega-datasets
Now you have all the datasets in a folder in node_modules/vega-datasets/data/.
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);
Install dependencies with yarn.
Publishing is handled by a 2-branch pre-release process, configured in publish.yml. All changes should be based off the default next branch, and are published automatically.
next pre-release tag on NPM. The result can be installed with npm install vega-datasets/@next.
next, please use the squash and merge strategy.next into stable using this compare link.
next into stable, please use the create a merge commit strategy.v2.4.0 (Thu Jul 14 2022)
:tada: This release contains work from new contributors! :tada:
Thanks for all your work!
:heart: Cameron Yick (@hydrosquall)
:heart: null@PBI-David
platformer-terrain.json.sp500-2000.csv.version property to js module.football.json. Thanks to @eitanlees!penguins.json.seattle-weather-hourly-normals.csv.weather.csv and seattle-weather.csv with better encoded weather condition, indicating more rain. Thanks to @visnup!seattle-weather.csv.weball26.json to political-contributions.json.birdstrikes.json to birdstrikes.csv and use ISO 8601 dates.movies.json to use column names with spaces and use ISO 8601 dates.climate.json.seattle-temps.csv with more general seattle-weather-hourly-normals.csv.sf-temps.csv.graticule.json. Use graticule generator instead.points.json.iris.json. Use penguins.json instead.FAQs
Common repository for example datasets used by Vega related projects.
The npm package vega-datasets receives a total of 421 weekly downloads. As such, vega-datasets popularity was classified as not popular.
We found that vega-datasets demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 0 open source maintainers collaborating on the project.
Did you know?
Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.
Security News
Ransomware negotiators share how modern cybercriminals operate like corporations, using specialized teams, negotiation tactics, and reputation management.
Security News
PyPI confirms no security flaws were exploited in the Ultralytics supply chain attack and highlights improvements for safer package publishing.
Security News
Research
The Socket Research Team breaks down a malicious wrapper package that uses obfuscation to harvest credentials and exfiltrate sensitive data.