How to Make Box Plot Excel

Box plots are a powerful visualization tool for displaying the distribution of data. They show the median, quartiles, and outliers of a data set in an easy-to-read format. While Excel doesn’t have a built-in box plot chart type, it’s possible to create one using a few simple steps. In this blog post, we’ll show you how to make a box plot in Excel, so you can easily visualize and interpret your data.

Step 1: Prepare Your Data

The first step is to make sure your data is organized correctly. A box plot summarizes five key values from your data set: the minimum value, the first quartile (Q1), the median, the third quartile (Q3), and the maximum value. So you’ll need to have that data handy in your worksheet.

For example, let’s say you have a data set of sales figures for different regions. You’ll need to calculate the quartiles and median for each region and gather it all in one table format in a separate tab.

Step 2: Create a Stacked Bar Chart

The next step is to create a stacked bar chart. You can do this by selecting your data and clicking on the recommended charts icon on the ribbon. From there, select the stacked bar chart type. Once you’ve inserted your chart, you can customize it by removing any unnecessary elements like the legend and axis labels.

Step 3: Format the Stacked Bar Chart

With your stacked bar chart in place, you can now use Excel’s formatting options to turn it into a box plot. The goal is to remove the bars and display only the whisker and box lines for each series.

Remove Unnecessary Elements:

Start by selecting the bars in your chart and pressing the delete key. This will remove them and leave you with just the blank chart. Next, remove the gridlines and any other elements that aren’t necessary.

Add Error Bars:

Next, add error bars to your chart. These will be the whiskers of the box plot and you can use Excel’s formatting options to adjust the length and style of these lines.

Format the Error Bars:

To format the error bars, click on the data series to select it, then right-click and select ‘Format Data Series’. In the ‘Format Data Series’ pane, find the ‘Error Bars’ section and select ‘Both’ in the ‘Direction’ field. You can then adjust the whisker length, end style, and color to your preference.

Add Boxes:

Finally, add boxes to your box plot chart. You can do this by creating a new scatter plot chart and plotting the median and quartiles for each series. Then, format this chart by removing any unnecessary elements and adjusting the size and color of the boxes.

Step 4: Customize the Box Plot

With your box plot in place, use Excel’s formatting tools to customize it to your liking. You can change the colors, fonts, and chart title to make it stand out and convey your message effectively.

Box plots can be a valuable tool in analyzing and presenting data. While Excel doesn’t have a built-in box plot chart type, it’s possible to create one with just a few formatting tricks. By following these simple steps, you can create an informative and visually appealing box plot in Excel.

Tips for Making Effective Box Plots

Now that you know how to make a box plot Excel, it’s important to understand how to make them as effective as possible. Here are a few tips:

Make Sure Your Data is Accurate

Box plots are only useful if you have accurate data. Make sure that you have cleaned and validated your data before creating your chart. If your data is inaccurate, you’ll end up with misleading insights.

Choose the Right Scale

Box plots work best when you use the appropriate scale. Depending on your data, you might want to use a logarithmic or squared scale to display it effectively.

Use Color Effectively

It’s important to use color effectively in your box plot. Use color to highlight specific data points or to differentiate between different series. However, be careful not to overuse color as it can become distracting and confusing.

Keep it Simple

A box plot is meant to be a simple and easy-to-read visualization of your data. Keep it simple and don’t include unnecessary elements that could detract from the message you’re trying to convey.

With these tips and techniques, you can create powerful and effective box plots in Excel. Remember to start by preparing your data, creating a stacked bar chart, formatting the chart, and customizing it to your liking. And don’t forget to choose the right scale, use color effectively, and keep it simple to ensure your box plot is as clear and informative as possible.

FAQ

Here are some frequently asked questions related to box plots in Excel:

Can I create a box plot in Excel without the use of add-ins?

Yes, it’s possible to create a box plot in Excel without any additional add-ins. You can do this by using a combination of stacked bar charts, scatter plots, and error bars, as outlined in this blog post.

What is the difference between a box plot and a histogram?

A histogram displays the distribution of a data set and is best used when the data is continuous and shows a trend over time. On the other hand, a box plot shows the distribution of a data set as well as any outliers and the median, quartiles, and range. Box plots are often preferred to histograms when the data includes outliers, or when you want to compare data from different groups.

Do I need to calculate the median and quartiles before creating a box plot?

Yes, you’ll need to have the median and quartiles calculated for your data set in order to create a box plot. Excel does not calculate these values automatically, so you’ll need to do it manually or use a formula to calculate them.

What should I do if I have multiple data sets I want to compare in a box plot?

If you have multiple data sets you want to compare in a box plot, you can create a grouped box plot. This involves creating multiple box plots side by side, each representing a different group. You can then compare the distribution of the data between the groups.

What are some common mistakes to avoid when making a box plot in Excel?

One common mistake is not properly preparing your data set before creating the box plot. Make sure that your data is accurate and validated before creating the chart. Another mistake is not choosing the appropriate scale for your data. Depending on your data, you might want to use a logarithmic or squared scale to display it effectively.