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https://github.com/MattCowgill/ggdirectlabel
https://github.com/MattCowgill/ggdirectlabel
Last synced: about 2 months ago
JSON representation
- Host: GitHub
- URL: https://github.com/MattCowgill/ggdirectlabel
- Owner: MattCowgill
- License: other
- Created: 2022-01-12T02:57:11.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2023-08-11T05:33:16.000Z (about 1 year ago)
- Last Synced: 2024-07-16T18:58:10.151Z (2 months ago)
- Language: R
- Size: 1.38 MB
- Stars: 41
- Watchers: 3
- Forks: 0
- Open Issues: 2
-
Metadata Files:
- Readme: README.Rmd
- License: LICENSE
Awesome Lists containing this project
README
---
output: github_document
---
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
# out.width = "100%",
fig.retina = 2
)
```
# ggdirectlabel
[](https://github.com/MattCowgill/ggdirectlabel/actions)
[](https://lifecycle.r-lib.org/articles/stages.html#experimental)
[](https://github.com/MattCowgill/ggdirectlabel/actions/workflows/R-CMD-check.yaml)
The goal of ggdirectlabel is to make it easier to directly label ggplot2 charts rather than using legends.
## Installation
You can install the development version of ggdirectlabel from [GitHub](https://github.com/) with:
``` r
# install.packages("devtools")
devtools::install_github("MattCowgill/ggdirectlabel")
```
```{r}
library(ggdirectlabel)
library(ggplot2)
library(magrittr)
```
## Using `geom_richlegend()`
Here's a standard ggplot2 scatterplot:
```{r}
base_scatter <- mtcars |>
ggplot(aes(x = wt, y = mpg, col = factor(cyl))) +
geom_point()
base_scatter
```
This is fine! But sometimes you might like the legend levels (4, 6, and 8 in this example) to be coloured according to the levels in the data. That's where `geom_richlegend()` comes in:
```{r}
base_scatter +
geom_richlegend(aes(label = cyl)) +
theme(legend.position = "none")
```
You can move the 'rich legend' around:
```{r}
base_scatter +
geom_richlegend(aes(label = cyl),
legend.position = "bottomleft",
vjust = 0,
hjust = 0) +
theme(legend.position = "none")
```
`geom_richlegend()` respects facets - it'll place a little legend annotation for each level of the data that appears in that panel:
```{r}
base_scatter +
geom_richlegend(aes(label = paste0(cyl, " cylinders"))) +
facet_wrap(~cyl)
```
## Using `geom_linepoint()`
Without ggirectlabel, we might do something like:
```{r no-directlabel}
ggplot2::economics_long %>%
ggplot(aes(x = date, y = value, col = variable)) +
geom_line() +
geom_point(data = ~dplyr::filter(., date == max(date)),
fill = "white",
shape = 21,
size = 2.5,
stroke = 1.25)
```
This is fine! But this is a more straightforward way to achieve the same thing:
```{r example}
ggplot2::economics_long %>%
ggplot(aes(x = date, y = value, col = variable)) +
geom_linepoint()
```
## Using `scale_x_date_rightalign()`
In time series line charts, it's often important to make clear the date of
your most recent observation. The `scale_x_date_rightalign()` function aligns
the breaks of your x-axis so that the most recent observation is included in
the breaks.
```{r scale_x_date_rightalign}
ggplot2::economics_long %>%
ggplot(aes(x = date, y = value, col = variable)) +
geom_linepoint() +
scale_x_date_rightalign()
```
## Using `geom_finallabel()`
In time series line charts, you may wish to label the final point in the series. The `geom_finallabel()` function makes that easy.
```{r geom_finallabel}
ggplot2::economics_long %>%
ggplot(aes(x = date, y = value, col = variable)) +
geom_linepoint() +
geom_finallabel(aes(label = round(value, 0))) +
scale_x_date_rightalign(expand = expansion(c(0, 0.15))) +
theme(legend.position = "none")
```