Create R data visualizations easily with a few lines of simple code using the ggcharts R package. Plus, the resulting charts and graphs are customizable ggplot objects. ggplot2 is an enormously ...

The statistical software R is well known for its very flexible graphical capabilities that are user-friendly if one understands the R programming language. One of the greatest aspects of R is the ...

There’s a reason ggplot2 is one of the most popular add-on packages for R: It’s a powerful, flexible and well-thought-out platform to create data visualizations you can customize to your heart’s ...

Sharing, presenting, and publishing life sciences results requires to perform statistics and to make figures. A combination of large data sets, performing the right statistics and being able to code ...

coefDecay = radius^decayFactor/log(percent) # 10% at 50 pixel dat$lureDist = sqrt((dat$GazeX_Shifted-(dat$X_CenterLure+ (1280-1)/2 - dat$X_Center))^2 + (dat$GazeY ...

**Attribution statement:** _The following teaching materials have been iteratively developed by current and former instructors, including: Tom Robinson and Ryan Hübert. This file is based on resources ...

In this tutorial we create basic visualizations (histograms and box plots) using R. The purpose of these basic visualizations is to see the distribution of a particular variable. The distribution ...

Labeling all or some of your data with text can help tell a story — even when your graph is using other cues like color and size. ggplot has a couple of built-in ways of doing this, and the ggrepel ...