Errors can lead to problems when using loops for repetitive tasks like fitting many models or simulating data. In this post I show how to use purrr::possibly() and purrr:safely() to handle errors as well as purrr:quietly() for capturing warnings and messages.

The base::split() function allows you to "split" your data into defined groups, returning a list with one element per group. This post goes through an example to show the utility of split() for looping through groups.

Following up on a previous post, I show how I add conditional elements to automated ggplot2 plots through the use of if() statements within my plotting function.

The task of fitting many similar models can be automated by looping through variables. I show an example of fitting the same model for multiple different response variables and then making residual plots for all models prior to extracting model results.

In this post I show an example of how to automate the process of making many exploratory plots in ggplot2 with multiple continuous response and explanatory variables. To loop through both x and y variables involves nested looping. In the latter section of the post I go over options for saving the resulting plots, either together in a single document, separately, or by creating combined plots prior to saving.