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.

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.

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?

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.

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.