Data Cornering

Category: RDataViz

  • Bar chart race in R using ggplot2 and gganimate

    Bar chart race in R using ggplot2 and gganimate

    Here is a relatively simple way to create a bar chart race in R – bar chart with bars overtaking each other. An attractive data visualization to engage your auditory while showing how the situation unfolds. Using the ggplot2 and gganimate, you can create a bar chart race in R and adjust the dynamics of […]

  • How to create a simple heatmap in R ggplot2

    How to create a simple heatmap in R ggplot2

    Here is how to quickly build a heatmap in R ggplot2 and add extra formatting by using a color gradient, data labels, reordering, or custom grid lines. There might be a problem if the data contains missing values. At the end of this post is an example of how to deal with NA values in […]

  • Keep trailing zeros in R ggplot2 geom_text

    Keep trailing zeros in R ggplot2 geom_text

    If you want to keep trailing zeros in R, and in particular for text labels in ggplot2 geom_text, try functions like sprintf, formatC, or digits from the formattable package. Add trailing zeros in the R data frame, ggplot2, and keep numerical properties using the function digits from the formattable.

  • Plot moving average in R using ggplot2

    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.

  • Multi-level axis labels in R plot using ggplot2

    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

    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

    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

    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.

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

    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.

  • How to create a jitter plot in R with ggplot2, plotly, and base

    How to create a jitter plot in R with ggplot2, plotly, and base

    Here are 3 ways to create a jitter plot in R, also called a strip chart or a dot plot which is a one-dimensional scatter plot. A jitter plot in R makes it easier to view overlapping data points by categorical or discrete values. In that scenario, the scatter plot groups all data points in […]