In geocompr/geocompkg: Geocomputation with R Metapackage

options(htmltools.dir.version = FALSE)
library(RefManageR)
BibOptions(check.entries = FALSE, 
           bib.style = "authoryear", 
           cite.style = 'alphabetic', 
           style = "markdown",
           first.inits = FALSE,
           hyperlink = FALSE, 
           dashed = FALSE)
my_bib = ReadBib("refs-geostat.bib", check = FALSE)

layout: true background-image: url(xaringan_stuff/img/r_geocomp_background.png) background-size: cover

---

Aim

• What is R and what is it good for?
• An introduction to the tidyverse
• An introduction to the sf package
• Spatial data and the tidyverse
• Making maps with R

install.packages("tidyverse")

sf (first release in 2016) implements the open standard data model simple features. Get sf with:

install.packages("sf")

The workshop also uses a dataset from the spData package, which can be installed with:

install.packages("spData")

For more on this see: github.com/Robinlovelace/geocompr.

---

Why R? (source: stackoverflow.blog)

knitr::include_graphics("https://stackoverflow.blog/wp-content/uploads/2017/10/tag_growth_scatter-1-771x675.png")

---

Introduction to the tidyverse

• Software for 'data science' is evolving
• In R, packages ggplot2 and dplyr are popular
• Now integrated into a 'metapackage': the tidyverse
• Which works with 'tidy data' (from vignette("tidy-data")):

• Each variable forms a column.
• Each observation forms a row.
• Each type of observational unit forms a table

• Historically spatial R packages have not been compatible with the tidyverse

---

background-image: url("https://pbs.twimg.com/media/CvzEQcfWIAAIs-N.jpg") background-size: cover

---

Enter sf

• sf is a recently developed package for spatial (vector) data
• Combines the functionality of three previous packages: sp, rgeos and rgdal
• Has many advantages, including:
  • Faster data I/O
  • More geometry types supported
  • Compatibility with the tidyverse

That's the topic of this workshop

---

background-image: url("https://media1.giphy.com/media/Hw5LkPYy9yfVS/giphy.gif")

---

Geocomputation with R

• Jakub Nowosad: developer of GeoPAT + more.

• Jannes Muenchow, creator of RQGIS.

--

• Robin Lovelace, creator of stplanr, co-author of Efficent R Programming.

--

• Open source book available online from geocompr.robinlovelace.net/

--

• Book now on sale! See Amazon or (cheaper) Wordery

---

Attaching the packages

• You can use packages with packagename::functionname()
• But by usually they are loaded at the beginning of an R session:

library(sf)
library(raster)
library(spData)

---

The structure of spatial data in sf

• Let's look at a dataset representing the United States:

us_states[1:3, 1:2]

Spatial data and the tidyverse

• Works just like normal data in the tidyverse

• Beware of name conflicts though:

library(tidyverse)

---

Data manipulation in the tidyverse (dplyr)

• dplyr provides a 'A grammar for data manipulation'
• It allows arguments to be 'piped', e.g.:

states1 = us_states %>%
  slice(1)
states2 = us_states %>% 
  filter(grepl(pattern = "^A", x = NAME)) %>% 
  top_n(n = 2, wt = total_pop_15)

---

Tidyverse pitfall example: binding rows

rbind(states1, states2)     # works
bind_rows(states1, states2) # fails

Error in .subset2(x, i, exact = exact) : 
  attempt to select less than one element in get1index

Work-around (see article in geocompr.github.io/geocompkg for more pitfalls):

us_data = st_set_geometry(us_states, NULL)
d = bind_rows(us_data, us_data)
d_sf = st_sf(d, geometry = c(us_states$geom, us_states$geom))

---

Making maps with R

• See Chapter 8 on Making maps with R, at: geocompr.robinlovelace.net/adv-map.html

---

Now over to you

• Get into groups of 2-5 and say hello
• What is each person's name?
• How much R experience do you have?

• What do you hope to get out of today?

• Take a look around RStudio

• Create a new project
• Try in install a new package

• Load the packages we'll use in this practical

• The practical

• Navigate to geocompr.robinlovelace.net
• Answer the first 3 questions of Chapter 3
• Take a look at chapter 2
• Answer questions 4:6 in Chapter 3
• Take a look at Chapter 8 and make some maps!
• Challenge: answer all questions in Chapter 3
• Bonus (advanced): make a pull request that improves the book

---

Final thing

A group of us are thinking about starting-up the Leeds R Users group.

• For academic and non-academic researchers
• Interested in getting involved?

Email: [e-mail]

geocompr/geocompkg documentation built on July 5, 2025, 2:35 a.m.