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https://lepennec.github.io/ggwordcloud/
A word cloud geom for ggplot2
https://lepennec.github.io/ggwordcloud/
Last synced: about 2 months ago
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A word cloud geom for ggplot2
- Host: GitHub
- URL: https://lepennec.github.io/ggwordcloud/
- Owner: lepennec
- License: gpl-3.0
- Created: 2018-09-23T19:33:25.000Z (about 6 years ago)
- Default Branch: master
- Last Pushed: 2024-06-01T09:35:36.000Z (4 months ago)
- Last Synced: 2024-07-28T10:31:44.760Z (2 months ago)
- Language: R
- Homepage: https://lepennec.github.io/ggwordcloud/
- Size: 13.1 MB
- Stars: 172
- Watchers: 6
- Forks: 8
- Open Issues: 4
-
Metadata Files:
- Readme: README.Rmd
- License: LICENSE.md
Awesome Lists containing this project
README
---
output: github_document
---
```{r setup, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
fig.dev = "grDevices::png",
dpi = 96L,
dev.args = list(),
fig.ext = "png",
fig.width = 700 / 96,
fig.height = NULL,
fig.retina = 2L,
fig.asp = 1 / 1.618,
fig.align = "center"
)
```
# ggwordcloud 
[](https://cran.r-project.org/package=ggwordcloud)
`ggwordcloud` provides a word cloud text geom for `ggplot2`. The placement algorithm implemented in C++ is an hybrid between the one of `wordcloud` and the one of `wordcloud2.js`. The cloud can grow according to a shape and stay within a mask. The size aesthetic is used either to control the font size or the printed area of the words. `ggwordcloud` also supports arbitrary text rotation. The faceting scheme of `ggplot2` can also be used. Two functions meant to be the equivalent of `wordcloud` and `wordcloud2` are proposed. Last but not least you can use `gridtext` markdown/html syntax in the labels.
## Installation
You can install the released version of ggwordcloud from [CRAN](https://CRAN.R-project.org) with:
```{r, eval=FALSE}
install.packages("ggwordcloud")
```
or the development version from the github repository
```{r, eval=FALSE}
devtools::install_github("lepennec/ggwordcloud")
```
Please check the latest development version before submitting an issue.
# Some word clouds
Because sometimes, pictures are better than a thousand words...
```{r}
library(ggwordcloud)
data("love_words_small")
set.seed(42)
ggplot(love_words_small, aes(label = word, size = speakers)) +
geom_text_wordcloud() +
scale_size_area(max_size = 40) +
theme_minimal()
```
```{r}
data("love_words")
set.seed(42)
ggplot(
love_words,
aes(
label = word, size = speakers,
color = speakers
)
) +
geom_text_wordcloud_area(aes(angle = 45 * sample(-2:2, nrow(love_words),
replace = TRUE,
prob = c(1, 1, 4, 1, 1)
)),
mask = png::readPNG(system.file("extdata/hearth.png",
package = "ggwordcloud", mustWork = TRUE
)),
rm_outside = TRUE
) +
scale_size_area(max_size = 40) +
theme_minimal() +
scale_color_gradient(low = "darkred", high = "red")
```
```{r}
library(dplyr, quietly = TRUE, warn.conflicts = FALSE)
library(tidyr, quietly = TRUE)
set.seed(42)
ggplot(
love_words_small %>%
gather(key = "type", value = "speakers", -lang, -word) %>%
arrange(desc(speakers)),
aes(label = word, size = speakers)
) +
geom_text_wordcloud_area() +
scale_size_area(max_size = 40) +
theme_minimal() +
facet_wrap(~type)
```
```{r}
set.seed(42)
ggplot(love_words_small, aes(label = word, size = speakers,
label_content = sprintf("%s(%g)", word, speakers))) +
geom_text_wordcloud_area() +
scale_size_area(max_size = 40) +
theme_minimal()
```
More examples are available in the vignette.