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https://dgkf.github.io/ggpackets/
Cleaner composition of ggplot layers
https://dgkf.github.io/ggpackets/
ggplot plotting r
Last synced: 3 months ago
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Cleaner composition of ggplot layers
- Host: GitHub
- URL: https://dgkf.github.io/ggpackets/
- Owner: dgkf
- License: other
- Created: 2018-01-16T22:01:47.000Z (almost 7 years ago)
- Default Branch: main
- Last Pushed: 2022-10-11T13:58:23.000Z (about 2 years ago)
- Last Synced: 2024-07-16T19:04:47.521Z (4 months ago)
- Topics: ggplot, plotting, r
- Language: R
- Homepage: https://dgkf.github.io/ggpackets
- Size: 13.7 MB
- Stars: 65
- Watchers: 5
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.Rmd
- License: LICENSE
Awesome Lists containing this project
README
---
output: github_document
---
# ggpackets 
[](https://cran.r-project.org/package=ggpackets)
[](https://cran.r-project.org/package=ggpackets)
[](https://github.com/dgkf/ggpackets/actions?query=workflow%3AR-CMD-check)
[](https://app.codecov.io/gh/dgkf/ggpackets)
## Overview
Take a look at the **[ggpackets project page](https://dgkf.github.io/ggpackets/)**!
Easily build components of ggplots without sacrificing the ease of ggplot's
layer parameters and construction syntax.
### Installation
```{r, eval = FALSE}
install.packages("ggpackets")
```
_or install the development version_
```{r, eval = FALSE}
devtools::install_github("dgkf/ggpackets", build_vignettes = TRUE)
```
## Get Involved
There are plenty of ways to help contribute:
1. **File issues!**
Found a bug? Think the syntax looks ugly? Don't like the name? Tell me!
[Issues](https://github.com/dgkf/ggpackets/issues) are the best way to start
the conversation.
2. **Write documentation!**
More resources always helps. Found a function unintuitive? Example code and
improved function descriptors would be helpful. If you use the package and
would feel comfortable writing about a topic not yet covered in a vignette,
feel free to contribute a new vignette for it.
3. **Write Unit Tests!**
There's some pretty sophisticated manipulations going on under the hood to
make everything as clean as possible, because of that it's important to make
sure everything stays working the way we expect it to. Unit test
contributions always welcome!
4. **Contribute Code!**
Last but not least, code contributors are welcome. Reach out and get in
touch if you're passionate about the goal of the project.
## Quick Start
Define common ggplot layer sets together into a singled object. Connect all
your plots with a single plot component definition and debug one central
location. Build beautiful templates and save them once, reuse them easily and
without having to abandon the ggplot construction framework.
```{r, include=FALSE}
knitr::opts_chunk$set(
echo = TRUE,
fig.align='center',
fig.width = 6,
fig.height = 4,
out.width = '600px',
out.height = '400px')
library(ggplot2)
library(ggpackets)
```
```{r}
ggpk_box_and_scatter <- ggpacket() +
geom_point(position = position_jitter(width = 0.4), alpha = 0.02) +
geom_boxplot(outlier.shape = NA, fill = NA, color = 'black') +
geom_text(stat = 'summary', vjust = -1, fun.data = function(d) c(
y = quantile(d, 0.75, names = F) + 1.5 * IQR(d),
label = length(d)
)) +
theme_linedraw() +
scale_color_distiller(palette = "Set1")
```
Now we can use that template repeatedly with a much simpler ggplot call
```{r diamonds.boxplot, eval = FALSE}
ggplot(diamonds, aes(x = cut, y = price, color = carat)) +
ggpk_box_and_scatter() +
ggtitle('Diamond price distribution by cut')
```
## Handle custom arguments & parameter propegation
In addition to simply wrapping multiple `ggplot2` layers, `ggpackets` can
streamline a number of complicated plotting scenarios such as passing arguments
to sets of layers, setting default argument values with scoped overrides,
routing aesthetic mappings to be reused within specific layers for other
aesthetics and scoping data usage over a set of layers.
```{r}
ggpk_labelled_heatmap <- function(...) {
ggpacket(...) %+%
geom_tile(.id = 'tile', color = NA, ...) %+%
geom_text(.id = c("text", "text1"), color = "black", vjust = -0.3,
fontface = "bold", ...) %+%
geom_text(.id = c("text", "text2"),
aes(label = sprintf("(%.1f)", ..fill..)),
color = "black", vjust = 1.1, ...) %+%
theme_void()
}
```
In this function we make use of a number of these specialized behaviors.
1. `.id` parameters are set to tag specific layers with an identifier, which
can be used to prefix arguments to route them to a subset of the `ggpacket`
layers. Multiple IDs can be used, and arguments will filter down into that
layer if they match any of the provided IDs.
1. Ellipsis are first passed to `ggpacket(...)`, which will pass them on as
default values to all `ggpacket` layers.
1. Ellipsis are also passed at the tail end of each layer call, allowing
arguments to mask default values. The placement of the ellipsis determines
whether arguments will override or be overridden by the existing parameters.
After expanding the ellipsis, the last instance of each argument is used to
build the call.
1. Aesthetics are rerouted using the specialized `....` syntax.
1. We use `%+%` instead of the commonly-used `+` to add layers together, which
allows `ggpackets` to accept non-standard arguments before ggplot sends us
warnings about them.
```{r orchid.heatmap, eval = FALSE}
ggplot(as.data.frame(OrchardSprays)) +
aes(x = rowpos, y = colpos, label = treatment, fill = decrease) +
ggpk_labelled_heatmap(text.color = "white", text2.alpha = 0.5) +
ggtitle('Honeybee population decline in repellent trial grid')
```
