Lyra.jl

Julia wrapper for the Lyra Visualization Design Environment
Author queryverse
Popularity
2 Stars
Updated Last
2 Years Ago
Started In
March 2020

Lyra

Project Status: WIP – Initial development is in progress, but there has not yet been a stable, usable release suitable for the public. codecov.io

Overview

This package provides Julia integration for the Lyra Visualization Design Environment.

NOTE THAT THIS PACKAGE CURRENTLY USES A VERY EXPERIMENTAL AND UNSTABLE BUILD OF LYRA AND IS NOT READY FOR REAL USE.

Getting Started

Lyra.jl is an interactive environment that enables custom visualization design without writing any code.

You can install the package at the Pkg REPL-mode with:

pkg> add https://github.com/queryverse/Lyra.jl

Visualizing data

You create a new Lyra window by calling LyraWindow:

using Lyra

l = LyraWindow()

By itself this is not very useful, the next step is to load some data into Lyra. Lets assume your data is in a DataFrame:

using DataFrames, Lyra

data = DataFrame(a=rand(100), b=randn(100))

l = LyraWindow(data)

You can also use the pipe to load data into Lyra:

using DataFrames, Lyra

data = DataFrame(a=rand(100), b=randn(100))

l = data |> LyraWindow()

With a more interesting data source

using VegaDatasets, Lyra

l = dataset("cars") |> LyraWindow()

You can load any source that implements the TableTraits.jl interface into Lyra, i.e. not just DataFrames. For example, you can load some data from a CSV file with CSVFiles.jl, filter them with Query.jl and then visualize the result with Lyra:

using FileIO, CSVFiles, Query, Lyra

l = load("data.csv") |> @filter(_.age>30) |> LyraWindow()

In this example the data is streamed directly into Lyra and at no point is any DataFrame allocated.

The datasets we added so far were named with the default name dataset. You can also give the dataset your own name, by passing a Pair instead of the raw data to LyraWindow:

using VegaDatasets, Lyra

l = LyraWindow(:cars=>dataset("cars"))

You can also make multiple datasets available to the Lyra environment. In that case you need to give each a unique name. The following example passes both the cars and movies dataset to Lyra:

using VegaDatasets, Lyra

l = LyraWindow(:cars=>dataset("cars"), :movies=>dataset("movies"))

You can use the add! function to add additional datasets to an existing Lyra window:

using VegaDatasets, Lyra

l = LyraWindow()

add!(l, :movies=>dataset("movies"))

Extracting plots

You can also access a plot that you have created in the Lyra UI from Julia, for example to save the plot to disc.

You can access the currently active plot in a given Lyra window l with the brackets syntax:

using VegaDatasets, Lyra, VegaLite

l = dataset("cars") |> LyraWindow()

plot1 = l[]

At this point plot1 will hold a standard VegaLite.jl plot object. You can use the normal VegaLite.jl functions to display such a plot, or save it to disc:

display(plot1)

plot1 |> save("figure1.pdf")

A useful pattern here is to save the plot as a Vega JSON file to disc, without the data:

using VegaDatasets, Lyra, VegaLite

l = dataset("cars") |> LyraWindow()

# Now create the plot in the UI

l[] |> save("figure1.vega")

At a later point you can then load this plot specification again, but pipe new data into it [TODO Make sure this works]:

using VegaLite, VegaDatasets

dataset("cars") |> load("figure1.vega")

Used By Packages

No packages found.