We’ll be using the Palmer Archipelago (Antarctica) penguin dataset. boxplot() simplifies the analysis and graphical representation of the columns in a dataset. The Pandas plotting module has a library of statistical functions, one of which is the boxplot() function. Here’s a sketch to show you the components of the box plot.įigure: Boxplot annotated with standard terminology Using The Pandas Plotting Module’s boxplot() Function Any data that lie outside these minimum and maximum points are treated as outliers.
Multiple 1.5 by the interquartile range and add it to the third quartile to calculate the maximum figure. Multiply 1.5 by the interquartile range and subtract it from the first quartile to calculate the minimum figure. You use this figure to set the minimum and maximum points for the range of data. If you take the first quartile away from the third quartile, you get the interquartile range. The interquartile range, also known as the middle-50%, is a statistical measure of data dispersion. You may be asking how you get figures that lie outside the maximum and minimum percentiles? Well, that’s where an understanding of the interquartile range comes in.
The boxplot will also identify any data lying outside the minimum and maximum percentiles, known as outliers. These are the minimum, maximum, median, and the first and third percentiles. Using The Pandas Plotting Module’s boxplot() FunctionĪ boxplot is a standard method of showing a dataset, highlighting five of the most important statistical measures.
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