---

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 is straightforward:

install.packages("tmap")

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).

Development version

The development version can be installed from the GitHub repository using
remotes or 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"))

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 frame (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)
				)

Book chapter about tmap

The book Geocomputation with R provides a chapter on Making maps with R, including a section on tmap.