TidierPlots.jl
What is TidierPlots.jl?
TidierPlots.jl is a 100% Julia implementation of the R package ggplot in Julia. Powered by AlgebraOfGraphics.jl, Makie.jl, and Julia’s extensive meta-programming capabilities, TidierPlots.jl is an R user’s love letter to data visualization in Julia.
TidierPlots.jl
has three goals, which differentiate it from other plotting packages in Julia:
-
Stick as closely to tidyverse syntax and behaviour as possible: Whereas other meta-packages introduce Julia-centric idioms for working with plots, this package’s goal is to reimplement ggplot in Julia. This currently just means that
TidierPlots.jl
gives the option for specifyingaes
with the macro@es
to allow unquoted column references, but the use of macros may need to expand as more features are added. -
Stay as compatible as possible with Makie.jl This package is meant to be a thin wrapper around Makie's SpecApi syntax to help introduce R users to plotting in Julia.
-
To Extend ggplot using julia-specific features where appropriate as long as this does not confict with the first two goals. The package aims to behave exactly like ggplot unless told otherwise. Additional options and parameters that are not present in ggplot may be added, but options that are present in R's ggplot should behave the way they do in R.
Installation
For the "stable" version, access the Pkg interface by pressing ]
at the julia>
prompt, then type add TidierPlots
.
For the development version:
using Pkg
Pkg.add(url="https://github.com/TidierOrg/TidierPlots.jl")
What functions does TidierPlots.jl support?
TidierPlots.jl currently supports the top-level function ggplot()
, plus:
Geoms:
geom_point
geom_errorbar
geom_path
,geom_line
, andgeom_step
geom_bar
,geom_col
, andgeom_histogram
geom_boxplot
andgeom_violin
geom_contour
andgeom_tile
geom_density
geom_text
andgeom_label
Makie Themes:
theme_ggplot2()
(the default)theme_dark()
theme_black()
theme_light()
theme_minimal()
Colour Scales:
scale_colo[u]r_manual()
- give a list of hexvalues
enclosed inc()
to define a scalescale_colo[u]r_[discrete|continuous]()
- setpalette =
a Makie palette.
Additional Elements:
scale_[x|y]_[continuous|log[ |2|10]|logit|pseudolog10|sqrt|reverse]
labs
lims
Display Options for Quarto, Jupyter, and Pluto.jl
Use the function TidierPlots_set(option::String, value::Bool)
to control display options. The following options are supported:
- "plot_show" (default true). Enables
ggplot
-like behaviour where plots are displayed when created. - "plot_log" (default true). Prints a text summary of the properties of the ggplot
You will likely want to disable both of these if you are working in a notebook environment. In Pluto.jl, you can get interactive plots (scroll, zoom, labels, etc.) using WGLMakie
by including WGLMakie.activate!()
as the first cell after your imports.
Differences from ggplot2
The goal of this package is to allow you to write code that is as similar to ggplot2 code as possible. The only difference in basic usage is in the aes()
function. TidierPlots.jl accepts multiple forms for aes specification, none of which is exactly the same as ggplot2.
- Option 1:
@aes
macro, aes as in ggplot, e.g.@aes(x = x, y = y)
- Option 2:
@es
macro, aes as in ggplot, e.g.@es(x = x, y = y)
- Option 3:
aes
function, julia-style columns, e.g.aes(x = :x, y = :y)
- Option 4:
aes
function, strings for columns, e.g.aes(x = "x", y = "y")
Specifying aes options positionally, e.g. aes("x", "y")
is also supported for required aesthetics.
Why would I use this instead of ggplot2?
Right now, you probably wouldn't. This package is still early in development, and is not ready for production use. However, there are a couple of advantages already and the list will hopefully get longer over time.
Easier Factor Handling
Sort your categorical variables in order of appearance with a single keyword rather than wrestle with factor ordering!
@chain cars begin
@count(manufacturer)
@arrange(n)
ggplot(cat_inorder = true, xticklabelrotation = .5)
geom_col(@aes(y = n, x = manufacturer))
end
Simple Bar Labels
Access to all axis and plot options from Makie
let you take advantage of nice features like easy bar_labels
:
df = DataFrame(
cat = ["left", "left", "left",
"middle", "middle", "middle",
"right", "right", "right"],
height = 0.1:0.1:0.9,
grp = [1, 2, 3, 1, 2, 3, 1, 2, 3]
)
ggplot(df, yticks = (1:3, ["bottom", "middle", "top"])) +
geom_col(@aes(cat, height, color = grp, bar_labels = height),
position = "dodge", direction = "x") + labs(title = "Dodged Bars") + theme_dark()
See the documentation for more information and examples.
What's New
See NEWS.md for the latest updates.
What's Missing
Lots! Please feel free to file an issue and/or submit a pull request to add additional ggplot-based features. If it is in ggplot, we want to add it.