The R language allows a quick introduction to data visualization. It doesn’t matter how big the amount of data is or how finely R has to process it. R can best be compared to the Python scripting language.
In this example, we show how to install R and the R-Studio development environment. An interactive tiling diagram should then be created as a graph, which visually shows the proportion of global corona infections by country. In addition, the evolution of corona infections for each country should appear as a curve in another graph. Both projects can be edited as HTML files and quickly integrated into a website. It doesn’t have to be corona numbers – all possible data can be visualized with R.
Countless packages are available for R that make the language easier to use and extend it with out-of-the-box functions. The central collection pool for these packages is called CRAN, which stands for Comprehensive R Archive Network. Around 20,000 packages are gathered there.
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