Tableau charts: Box plot

July 11, 2018

The series, Tableau charts has always focused on one thing, helping Tableau users learn how to create different charts and graphs hence equipping them with different techniques of telling each data story. 

Therefore, in the spirit of this series, we will learn how to build a box plot in Tableau. But first, what is a box plot? According to Wikipedia, box plot is a method of depicting groups of numerical data through their quartiles. Box plot may also have lines extending vertically from the boxes (whiskers) indicating the variability outside the upper and lower quartiles hence terms box and whisker plots. Outliers (Observation that is distant from other observations) may be plotted as individual points. A sample of box plot diagram below.

Using Superstores data set pre-packaged with Tableau app, we’ll seek to depict the distribution of Sales for Product Sub-Category.

Step 1: Build a simple bar chart.

  • Drag dimension Sub-Category to the column shelf.

  • Drag measure Sales to the row shelf. (Note, Sales is aggregated by SUM()).

Executing this, results to a simple bar chart.

 

Step 2: Make the box plot.

  • Under Show Me tab, choose box-and-whisker-plots as shown above.

Note, moving the cursor over the box displays a summary statistic as described in the box plot diagram at the beginning of this article.

Looking carefully at the resulting chart, it shows distribution of Sales at Sub-Category summary level. Suppose, my interest is to see how Sales is distributed within the individual Sub-Category’s while still being able to compare distribution across other Sub-Category’s.

To effect this;

  • Drag dimension Sub-Category to the row shelf.

  • Under Analysis menu uncheck ‘Aggregate measures’.

See below.

And there we’ve our box plot.

Using this box and whisker plot. Simple insights like distribution of Sales for different products Sub-Category’s can be spotted easily. For instance, using interquartile range, one can tell that the Sub-Category Machines and Copiers have the highest distribution of Sales. Outliers can also be spotted easily for different Sub-Category’s.

I hope this article adds to your resources of some of the best techniques you can use to transform how you communicate your data insights.

Thanks for reading.

 

 

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