Publications by R on Dominic Royé
the pie chart
Welcome to my blog! I am Dominic Royé, researcher and lecturer of physical geography at the University of Santiago de Compostela. One of my passions is R programming to visualize and analyze any type of data. Hence, my idea of this blog has its origin in my datavis publications I have been cooking in the last year on Twitter on different topics ...
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Access to climate reanalysis data from R
1 Introduction 2 NCEP 2.1 Packages 2.2 Data download 2.3 Monthly average 2.4 Visualization 3 ERA-Interim 3.1 Installation 3.2 Connection and download with the ECMWF API 3.3 Processing ncdf 4 Update for accessing ERA-5 A friend advised me to introduce R levels as categories. An idea that I now add to each blog post. There are three levels: elem...
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Accessing OpenStreetMap data with R
The database of Open Street Maps Recently I created a map of the distribution of gas stations and electric charging stations in Europe. Population density through the number of gas stations in Europe. #dataviz @AGE_Oficial @mipazos @simongerman600 @openstreetmap pic.twitter.com/eIUx2yn7ej— Dominic Royé (@dr_xeo) February 25, 2018 How can you o...
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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. Visualising global temperature change since records began in 1850. Versions for USA, central E...
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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 (shorte...
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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: download. Packages In this post we will use the following pa...
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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. In this post we are going to estimate the correlation coefficients between the annual precipitation of several Spanish c...
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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 ...
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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 ...
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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 ...
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