README.Rmd

---
output: github_document
---

<!-- README.md is generated from README.Rmd. Please edit that file -->

```{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 <img src="man/figures/logo.png" align="right" height=140/>
 
[![CRAN status](https://www.r-pkg.org/badges/version/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<span style='font-size:7.5pt'>(%g)</span>", word, speakers))) +
  geom_text_wordcloud_area() +
  scale_size_area(max_size = 40) +
  theme_minimal()
```

More examples are available in the vignette.