Over the next week we will cover the basics of how to create your own histograms in R. Three options will be explored: basic R commands, ggplot2 and ggvis. These posts are aimed at beginning and intermediate R users who need an accessible and easy-to-understand resource. Want to learn more? Discover the R tutorials at DataCamp.

A histogram is a visual representation of the distribution of a dataset. As such, the shape of a histogram is its most obvious and informative characteristic: it allows you to easily see where a relatively large amount of the data is situated and where there is very little data to be found (Verzani 2004). In other words, you can see where the middle is in your data distribution, how close the data lie around this middle and where possible outliers are to be found. Exactly because of all this, histograms are a great way to get to know your data!

But what does that specific shape of a histogram exactly look like? In short, the histogram consists of an x-axis, an y-axis and various bars of different heights. The y-axis shows how frequently the values on the x-axis occur in the data, while the bars group ranges of values or continuous categories on the x-axis. The latter explains why histograms don’t have gaps between the bars.

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