---

output: github_document
editor_options:
chunk_output_type: console

knitr::opts_chunk$set(
  collapse = TRUE,
  out.width = "100%",
  dpi = 300,
  fig.width = 7.2916667,
  comment = "#>",
  fig.path = "man/figures/README-"
)
hook_output <- knitr::knit_hooks$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

tmap is an R package for drawing thematic maps. The API is based on A Layered Grammar of Graphics and resembles the syntax of ggplot2, a popular R-library for drawing charts.

Installation

Installation of tmap (version 4) is straightforward:

install.packages("tmap")

The old version of tmap (version 3) is available in the CRAN archive,
but we recommend moving to the new version 4.

Development version

The development version can be installed from the GitHub repository using
remotes and pak packages or from the R-universe repository.

# install.packages("remotes")
remotes::install_github("r-tmap/tmap")

# 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"))

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.

macOS
See https://www.kyngchaos.com/. Please address installation issues in this issue.

Getting started

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:

tm_shape(World) +
	tm_polygons(fill = "HPI")

This map can be enhanced in several ways.
For instance:

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)
				)

Additional Resources for Learning tmap

For more in-depth learning on the tmap package, refer to the following resources:

• Book Chapter: Geocomputation with R includes a chapter on Making Maps with R, which covers tmap.
• Official Vignettes: A collection of vignettes at r-tmap.github.io covers both basic and advanced topics with examples.
• Work-in-Progress Book: Elegant and Informative Maps with tmap is an upcoming book available at tmap.geocompx.org.

These resources provide a solid foundation for working with tmap in R.