![]() In matplotlib, each of these is treated as a 2D instance. In our example, we'll pass this argument our x-coordinates.īoxplots are slightly more complicated to style as they are made up of several components: the median, the IQR (or box), the whiskers (range of the data), the caps of the whiskers, and fliers (a.k.a. The location of the boxplots are set with the positions keyword argument. ![]() Similar to bar charts, the width of each box plot can also be specified using the width keyword argument. Therefore, the goal of the plots outlined here is to present data in a straightforward and understandable manner.īox plots are made using the Axes.boxplot() method and are nice in that they show a great deal more information about the data you're plotting than a simple mean and standard deviation. This undermines your goal of communicating your story effectively. Peer-reviewers or readers who aren't as intimate with the data can get distracted or confused by complex graphics or unorthodox represenatations of data.You know the data and it's context very well, therefore its many representations are all very familiar to you (and not so familiar to others).From experience, I've found there are two reasons for this: In the academic realm, the best plots are usually the most simple ones. ![]() Sketching it out also forces you to deal with layout and space requirements up front. It helps you map out the story you want to tell with your data. I do this for everything from a multi-panel figure to a simple bar chart. Before starting any plotting task-especially one centered around creating a figure for others to interpret-it is extremely useful to first sketch out what you want the end product to look like.
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