https://jonjup.netlify.app/tags/r-package/ Recent content in R package on Amaltheia Hugo -- gohugo.io en-us <a href="https://creativecommons.org/licenses/by-nc/4.0/" target="_blank" rel="noopener">CC BY-NC 4.0</a> Wed, 29 Sep 2021 00:00:00 +0000 https://jonjup.netlify.app/post/the-rastervis-package/ Wed, 29 Sep 2021 00:00:00 +0000 https://jonjup.netlify.app/post/the-rastervis-package/ Here, we will explore the basic functionality of the rasterVis package. As the name already suggests, the purpose of this package is to display raster data. While the common R packages to work with rasters, like raster or terra, already provide basic plotting functionality, rasterVis extends this substantially. You can find a more extensive documentation for the package here. library(rasterVis) library(terra) First we need to load some rasters. We will use the geodata package to download a digital elevation model of Austria. https://jonjup.netlify.app/post/r-package-of-the-week/ Mon, 20 Sep 2021 00:00:00 +0000 https://jonjup.netlify.app/post/r-package-of-the-week/ This week we will have a look at the corrr package. It includes some nice possibilities to visualize correlations between mutliple variables. I will provide some examples using the varechem data set from the vegan package. First, load the data and have a look at them. data(varechem) head(varechem) ## N P K Ca Mg S Al Fe Mn Zn Mo Baresoil Humdepth ## 18 19.8 42.1 139.9 519. https://jonjup.netlify.app/post/the-geodata-package/ Fri, 17 Sep 2021 00:00:00 +0000 https://jonjup.netlify.app/post/the-geodata-package/ The geodata package is written and maintained by Rob Hijmans who also wrote the raster and terra packages. The purpose of the package is to provide an easy-to-use interface to download different handy spatial data sets directly from R. In this script, I will go through most of the functions that this package provides, show you how to use them and what their outputs look like. https://jonjup.netlify.app/post/the-rayshader-r-package/ Wed, 10 Feb 2021 00:00:00 +0000 https://jonjup.netlify.app/post/the-rayshader-r-package/ In this entry we will go through the basics of rayshader. Rayshader is one of those packages that you see again and again when you follow people from the R-spatial community on twitter. Especially the package’s creator Tyler Morgan-Wall (see here for his website and here for his Twitter) posts videos and images of things he did with it on an almost daily basis. And he has all the reasons to do so. https://jonjup.netlify.app/post/r-package-of-the-week-dataexplorer/ Tue, 09 Feb 2021 00:00:00 +0000 https://jonjup.netlify.app/post/r-package-of-the-week-dataexplorer/ install.packages(&quot;DataExplorer&quot;) library(DataExplorer) data = readRDS(&quot;collected_site_scores.RDS&quot;) This weeks package is similar to last weeks. Just like xray Seibelt (2017), DataExplorer Cui (2020) is used for exploratory data analysis. To highlight the features and capabilities of the package we will use a data set of different diatom metrics derived from a large data set of diatoms, which I unfortunately am not able to share with you. These metrics were computed with the diaThor package, which I will cover in a later post. https://jonjup.netlify.app/post/r-package-of-the-week-xray/ Mon, 25 Jan 2021 00:00:00 +0000 https://jonjup.netlify.app/post/r-package-of-the-week-xray/ For this first post in the series, we will look at small but nice packge called x-ray. Just like a doctor can use x-rays whether something is wrong with your funky looking arm, we can use the x-ray package to see if there is anything wrong with our data set. As an example data set we will use the antTraits data set from the mvabund package which used before in other analyses and later in the post we will also simulate some data to highlight some features of xray.