https://github.com/queryverse/vegadatasets.jl

Julia package for loading the standard Vega data sets
https://github.com/queryverse/vegadatasets.jl

julia queryverse

Last synced: about 1 year ago
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Julia package for loading the standard Vega data sets

• Host: GitHub
• URL: https://github.com/queryverse/vegadatasets.jl
• Owner: queryverse
• License: other
• Created: 2018-03-03T00:43:59.000Z (over 8 years ago)
• Default Branch: master
• Last Pushed: 2022-12-11T00:36:24.000Z (over 3 years ago)
• Last Synced: 2025-03-26T12:51:13.043Z (about 1 year ago)
• Topics: julia, queryverse
• Language: Julia
• Homepage:
• Size: 6.93 MB
• Stars: 20
• Watchers: 3
• Forks: 7
• Open Issues: 5
• Metadata Files:
  • Readme: README.md
  • License: LICENSE.md

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README

          
# VegaDatasets

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[![Build Status](https://travis-ci.org/queryverse/VegaDatasets.jl.svg?branch=master)](https://travis-ci.org/queryverse/VegaDatasets.jl)

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[![codecov](https://codecov.io/gh/queryverse/VegaDatasets.jl/branch/master/graph/badge.svg)](https://codecov.io/gh/queryverse/VegaDatasets.jl)

## Overview

This package provides an easy way to load the datasets in [vega-datasets](https://github.com/vega/vega-datasets) from julia.

## Installation

You can install this package from the julia REPL with the following command:

````julia

Pkg.add("VegaDatasets")

````

## Getting started

The package only exports one function that takes the name of a dataset and returns a ``VegaDataset`` with that data:

````julia

using VegaDatasets

vg = dataset("iris")

````

``VegaDataset`` implements the [iterable tables](https://github.com/queryverse/IterableTables.jl) interface, so it can be passed to any sink that accepts iterable tables.

For example, to convert a dataset into a ``DataFrame``, you can write:

````julia

using VegaDatasets, DataFrames

df = DataFrame(dataset("iris"))

````

You can pipe a ``VegaDataset`` directly into a [VegaLite.jl](https://github.com/fredo-dedup/VegaLite.jl) plot:

````julia

using VegaLite, VegaDatasets

dataset("iris") |> @vlplot(:point, x=:sepalLength, y=:petalWidth)

````

### Non-tabular datasets

The following datasets are not tabular in nature:

* earthquakes

* graticule

* londonBoroughs

* londonTubeLines

* miserables

* us_10m

* world_110m

In those cases an object is returned that can be lowered to JSON, or one can access the `.path` property for such an object to get a path to the location of the dataset.