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README.Rmd
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README.Rmd
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---
output: github_document
editor_options:
chunk_output_type: console
---
```{r setup, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-"
)
hook_output <- knitr::knit_hooks$get("output")
knitr::knit_hooks$set(output = function(x, options) {
lines <- options$output.lines
if (is.null(lines)) {
return(hook_output(x, options)) # pass to default hook
}
x <- unlist(strsplit(x, "\n"))
more <- "..."
if (length(lines)==1) { # first n lines
if (length(x) > lines) {
# truncate the output, but add ....
x <- c(head(x, lines), more)
}
} else {
x <- c(more, x[lines], more)
}
# paste these lines together
x <- paste(c(x, ""), collapse = "\n")
hook_output(x, options)
})
```
# tmap: thematic maps in R <img src="man/figures/logo.png" align="right" height="139" alt="" />
<!-- badges: start -->
[](https://github.com/r-tmap/tmap/actions/workflows/R-CMD-check.yaml)
[](https://app.codecov.io/gh/r-tmap/tmap?branch=master)
[](https://cran.r-project.org/package=tmap)
[](https://cran.r-project.org/web/checks/check_results_tmap.html)
[](https://www.r-pkg.org:443/pkg/tmap)
[](https://www.gnu.org/licenses/gpl-3.0.html)
[](https://r-tmap.r-universe.dev/tmap)
<!-- badges: end -->
**tmap** is an R package for drawing thematic maps. The API is based on [*A Layered Grammar of Graphics*][4] and resembles the syntax of [**ggplot2**][3], a popular R-library for drawing charts.
## Installation
Installation of **tmap** (version 4) is straightforward:
```{r eval=FALSE}
# install.packages("remotes")
install_github("r-tmap/tmap")
# On Linux, with pak
# install.packages("pak")
pak::pak("r-tmap/tmap")
# Or from r-universe
install.packages("tmap", repos = c("https://r-tmap.r-universe.dev", "https://cloud.r-project.org"))
```
The old version of **tmap** (version 3) is available on [](https://cran.r-project.org/package=tmap), but we recommend to use version 4, which will be on CRAN soon.
For Linux and macOS users who are new to working with spatial data in R, this may fail since additional (non-R) libraries are required (which are automatically installed for Windows users).
**Windows**
No additional installation required.
**Linux (Ubuntu)**
See https://geocompx.org/post/2020/installing-r-spatial-packages-linux/. Please address installation issues in this [issue](https://github.com/r-tmap/tmap/issues/150).
**macOS**
See https://www.kyngchaos.com/. Please address installation issues in this [issue](https://github.com/r-tmap/tmap/issues/149).
# Getting started
```{r echo=FALSE, message=FALSE}
library(tmap)
```
Plot a World map of the happy planet index (HPI) per country.
The object `World` is an example spatial data (`sf`) object that is contained in **tmap**:
```{r fig.height=3, fig.width=8}
tm_shape(World) +
tm_polygons(fill = "HPI")
```
This map can be enhanced in several ways.
For instance:
```{r}
tm_shape(World, crs = "+proj=robin") +
tm_polygons(fill = "HPI",
fill.scale = tm_scale_continuous(values = "matplotlib.rd_yl_bu"),
fill.legend = tm_legend(title = "Happy Planet Index",
orientation = "landscape",
frame = FALSE)
)
```
# Book chapter about tmap
The book [Geocomputation with R](https://r.geocompx.org/) provides a chapter on [Making maps with R](https://r.geocompx.org/adv-map), including a section on **tmap**.
[3]: https://cran.r-project.org/package=ggplot2
[4]: https://vita.had.co.nz/papers/layered-grammar.pdf