How to Create a Box and Whisker Plot in Excel

In this tutorial, we will walk through the steps of creating a box and whisker plot in Excel. Additionally, we will explain the different parts of a box and whisker plot, such as the box, whiskers, median, and outliers, and their significance in understanding the data.

A box and whisker plot, also known as a box plot, is a graphical representation of a dataset that shows the distribution of values within a set of data. In this example, we have a list of students and their marks. We want to create a visual representation of how the students are performing. To do this we will use the box plot. Here’s a step-by-step guide in creating a box plot.

  1. Select the data that you want to use for the box plot. In this example, we will highlight the marks of the students.
  2. Go to the “Insert” tab and click on “Chart.” Select the “Box and Whisker” option from the list of charts.
  3. A box plot will appear on your worksheet with the data you selected.
  4. You can format the plot by going to the “Chart Tools” tab and selecting “Design.” Here, you can change the colors, add a title, and add data labels.

In the table, there is a cross button that gives the option of showing the data labels. The data labels will show the values of the lines.

Using the data labels, we can then interpret the data. The bottom whisker represents the bottom 25% of the result, also known as the 1st quartile; the top whisker represents the top 25% of the results; and the box graph represents 50% of the results. Inside the box graph, the crosshair represents the mean value, and the line represents the median value.

Note: If you have dots outside your whiskers, those are called outliers. Those dots are values that fall outside of the range represented by the whiskers.


Box and whisker plots, also known as box plots, provide a simple and effective way to understand the spread and skewness of a dataset. The different parts of a box plot, including the box, median, whiskers, and outliers, provide valuable information about the distribution of the data. By creating a box plot in Excel, formatting it to your liking, and analyzing the data it represents, you can gain a deeper understanding of the dataset and make better-informed decisions.