# Category: R

## Plot moving average in R using ggplot2

Here is how to plot the moving average (rolling average or running average) in R using ggplot2 and add actual data in different ways. In that way, you can track the moving average and look at the data around that. Sometimes it helps to spot anomalies in time series.

## How to get the sum by group in R

Here are multiple examples of getting the sum by group in R using the base, dplyr, and data.table capabilities. Depending on the situation, you can choose in your scenario what is the best solution.

## Multi-level axis labels in R plot using ggplot2

Here is an example of how to create multi-level axis labels in an R plot using ggplot2. You can separate them into 2 levels on a plot x-axis or more. It depends on the situation.

## Color gradient in R jitter plot using midpoint or group

Here is how to use the color gradient in R jitter plot using midpoints or different gradients by a group. A good jitter plot in R makes it easier to view overlapping data points by categories. Color gradients might help to see differences better.

## How to modify plot title in R using ggplot2

Here is how to add and modify the plot title in R using ggplot2 in many ways. After adding the ggplot2 title and subtitle, you might want to change the alignment, color, and size, add a bold effect to all or a few words, and do other customizations. Here are multiple examples of that.

## How to add GIF animation to plot in R

Here is how to add GIF animation to the plot in R and draw extra attention. You can take a static ggplot2 plot and join it with GIF frames. As a result, you can create GIF in R with an infinite or finite loop.

## NAs introduced by coercion in R

If you see the warning NAs introduced by coercion in R, don’t panic. It is not necessarily bad, but you should understand if that is acceptable. This warning message usually appears by converting non-numerical values to numerical values with functions like as.numeric or as.integer. It may also appear by creating plots where the correct data…

## Plot mean by group in R using ggplot2 or use other measures

Here is how to plot mean by group in R using ggplot2 or try other measures to summarize values. To demonstrate that, I will use a jitter plot. A jitter plot is great if you want to look at all data points by categories, but additional statistics might be useful for evaluation.