2022
In this post, we will see how we can convert a static plot created with {ggplot2} to an interactive plot with {ggiraph}, using the example of the top 10 coffee-growing countries.
2021
Inserting the legend directly into a graph often makes it easier to read. In this post, we will see a quick example on how to annotate directly single or faceted area plots.
Soil texture diagrams are widely used in agronomy but can be difficult to plot. Let’s see how we can use {ggplot2} and {ggtern} to estimate and represent an important parameter related to soil texture: the water storage capacity.
In this third part of the tutorial, we will now evaluate the error associated with the model predictions (the Root Mean Square Error, RMSE), and then try to decrease this error by optimizing one of the model parameter.
In this second part of the tutorial, we will investigate the influence of the different parameters on the model’s results. You will learn how to perform a sensivity analysis and an uncertainty analysis.
The tidyverse is a collection of extensions designed to work together and based on a common philosophy, making data manipulation and plotting easier. In this tutorial, following the tidyverse philosophy, we will see how we can program the first part of a crop model: the estimation of the number of plant leaves from temperature data.