Meeting People Where They R

This is my blog where I practice sharing my curiosity about R, particularly, the world of cartography and data visualization.
I take this opportunity to invite you to participate in the #30DayChartChallenge.

Always normalize you data

I recently came across a map from the National Atlas of Spain showing the number of libraries by municipality. However, one thing directly caught my attention. There’s a saying that many maps show only the population, and this seems to be the case here. The map does not provide any remarkable information about the distribution of libraries; it merely shows where the most people live.
gis
R
R:elementary
visualization
map
proportional symbol
normalize
Jan 5, 2025
Dominic Royé

Map of circles grouped in multiple locations

In my first post of 2024, which unfortunately has not been possible before April, I will explain how we can group in the same location several proportional circles. In 2022 I was looking for how to represent the number of heat wave days according to the degree of severity in Spain. I found the solution using the circle packing which is also used in the Dorling cartogram.
gis
R
R:advanced
visualization
map
proportional symbol
circles
Apr 20, 2024
Dominic Royé

Inserted maps with ggplot2

A short post on how we can position an outermost territory near the main map or insert an orientation map. In this example we use the typical map of Spain where the Canary Islands are located in the southwest of the peninsula.
gis
R
R:elementary
visualization
Oct 8, 2023
Dominic Royé

Hillshade effects

It is very common to see relief maps with shadow effects, also known as ‘hillshade’, which generates visual depth. How can we create these effects in R and how to include them in ggplot2?
gis
R
R:intermediate
visualization
hillshade
DEM
elevation
Jul 20, 2022
Dominic Royé

Use of multidimensional spatial data

Space-time information is vital in many disciplines, especially in climatology or meteorology, and this makes it necessary to have a format that allows a multidimensional structure. It is also important that this format has a high degree of interchange compatibility and can store a large number of data.
gis
R
R:advanzed
visualization
ncdf
drought
spain
raster
Mar 8, 2022
Dominic Royé

Visualize the day-night cycle on a world map

In April of this year, I made an animation of the 24-hour average temperature of January 2020, also showing the day-night cycle. My biggest problem was finding a way to project correctly the area at night without breaking the geometry. The easiest solution I found was rasterising the night polygon and then reprojecting it. Indeed, a vector approach could be used, but I have preferred to use raster data here.
gis
R
R:intermediate
visualization
world map
day-night
animation
Dec 20, 2021
Dominic Royé

Climate circles

The climate of a place is usually presented through climographs that combine monthly precipitation and temperature in a single chart. However, it is also interesting to visualize the climate on a daily scale showing the thermal amplitude and the daily average temperature. To do this, the averages for each day of the year of the daily minimums, maximums and averages are calculated. The annual climate cycle presents a good opportunity to use a radial or polar which allows us to clearly visualize seasonal patterns.
R
R:elementary
visualization
climate
polar
temperature
Sep 4, 2021
Dominic Royé

Firefly cartography

Firefly maps are promoted and described by John Nelson who published a post in 2016 about its characteristics. However, these types of maps are linked to ArcGIS, which has led me to try to recreate them in R.
gis
R
R:intermediate
visualization
firefly
map
cartography
Jun 1, 2021
Dominic Royé

Bivariate dasymetric map

A disadvantage of choropleth maps is that they tend to distort the relationship between the true underlying geography and the represented variable. It is because the administrative divisions do not usually coincide with the geographical reality where people live. Besides, large areas appear to have a weight that they do not really have because of sparsely populated regions. To better reflect reality, more realistic population distributions are used, such as land use. With Geographic Information Systems techniques, it is possible to redistribute the variable of interest as a function of a variable with a smaller spatial unit.
gis
R
R:advanced
visualization
bivariate
map
income
urban
Mar 1, 2021
Dominic Royé

A heatmap as calendar

Recently I was looking for a visual representation to show the daily changes of temperature, precipitation and wind in an application xeo81.shinyapps.io/MeteoExtremosGalicia (in Spanish), which led me to use a heatmap in the form of a calendar. The shiny application is updated every four hours with new data showing calendars for each weather station.
visualization
R
R:intermediate
calendar
heatmap
climate
Dec 20, 2020
Dominic Royé

Climate animation of maximum temperatures

In the field of data visualization, the animation of spatial data in its temporal dimension can show fascinating changes and patterns. As a result of one of the last publications in the social networks that I have made, I was asked to make a post about how I created it. Well, here we go to start with an example of data from mainland Spain.
visualization
R
R:advanced
animation
temperature
climate
gis
Oct 11, 2020
Dominic Royé

River flow directions

I recently created a visualization of the distribution of river flow directions and also of coastal orientations. Following its publication in social networks, I was asked to make a post about how I did it. Well, here we go to start with an example of rivers, coastal orientation is somewhat more complex.
gis
R
R:advanced
river
directions
distribution
Jul 24, 2020
Dominic Royé

Visualize climate anomalies

When we visualize precipitation and temperature anomalies, we simply use time series as bar graph indicating negative and positive values in red and blue. However, in order to have a better overview we need both anomalies in a single graph. In this way we could more easly answer the question of whether a particular season or month was dry-warm or wet-cold, and even compare these anomalies in the context of previous years.
visualization
R
R:intermediate
climate
anomaly
temperature
Mar 29, 2020
Dominic Royé

Geographic distance

The first post of this year 2020, I will dedicate to a question that I was recently asked. The question was how to calculate the shortest distance between different points and how to know which is the closest point. When we work with spatial data in R, currently the easiest thing is to use the sf package in combination with the tidyverse collection of packages. We also use the units package which is very useful for working with units of measurement.
spatial analysis
R
R:elementary
gis
distance
cities
Jan 19, 2020
Dominic Royé

Visualize urban growth

The General Directorate for the Cadastre of Spain has spatial information of the all buildings except for the Basque Country and Navarra. This data set is part of the implementation of INSPIRE, the Space Information Infrastructure in Europe. More information can be found here. We will use the links (urls) in ATOM format, which is an RSS type for web feeds, allowing us to obtain the download links for each municipality.
visualization
R
R:elementary
gis
city
geography
Nov 1, 2019
Dominic Royé

Visualize monthly precipitation anomalies

Normally when we visualize monthly precipitation anomalies, we simply use a bar graph indicating negative and positive values with red and blue. However, it does not explain the general context of these anomalies. For example, what was the highest or lowest anomaly in each month? In principle, we could use a boxplot to visualize the distribution of the anomalies, but in this particular case they would not fit aesthetically, so we should look for an alternative. Here I present a very useful graphic form.
visualization
R
R:intermediate
anomaly
climate
precipitation
boxplot
Jul 7, 2019
Dominic Royé

Tidy correlation tests in R

When we try to estimate the correlation coefficient between multiple variables, the task is more complicated in order to obtain a simple and tidy result. A simple solution is to use the tidy() function from the {broom} package. As an example, in this post we are going to estimate the correlation coefficients between the annual precipitation of several Spanish cities and climate teleconnections indices.
statistics
R
R:advanced
correlation
tests
Apr 17, 2019
Dominic Royé

Import Excel sheets with R

We usually work with different data sources, and sometimes we can find tables distributed over several Excel sheets. In this post we are going to import the average daily temperature of Madrid and Berlin which is found in two Excel files with sheets for each year between 2000 and 2005.
management
R
R:intermediate
excel
sheets
Mar 10, 2019
Dominic Royé

Calculating the distance to the sea in R

The distance to the sea is a fundamental variable in geography, especially relevant when it comes to modeling. For example, in interpolations of air temperature, the distance to the sea is usually used as a predictor variable, since there is a casual relationship between the two that explains the spatial variation. How can we estimate the (shortest) distance to the coast in R?
gis
R
R:elementary
distance
raster
Jan 8, 2019
Dominic Royé

How to create ‘Warming Stripes’ in R

This year, the so-called warming stripes, which were created by the scientist Ed Hawkins of the University of Reading, became very famous all over the world. These graphs represent and communicate climate change in a very illustrative and effective way.
datavis
R
R:elementary
warming stripes
global warming
visualization
Dec 5, 2018
Dominic Royé

Accessing OpenStreetMap data with R

Recently I created a map of the distribution of gas stations and electric charging stations in Europe. How can you obtain this data? Well, in this case I used points of interest (POIs) from the database of Open Street Maps (OSM). Obviously OSM not only contains the streets and highways, but also information that can be useful when we use a map such as locations of hospitals or gas stations.
visualization
R:elementary
R
map
OSM
point of interest
Nov 3, 2018
Dominic Royé
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