Introduction
This week we are building a nullity matrix, a tabular visual that helps us to easily see which rows and columns have null data. There is a library for this in Python, but you need to “roll your own” in Power BI.
I found the Python library and liked the idea of visualizing null or missing data, but I disliked the arrangement of data in the visual. Where the missingno library puts column names along the top and row numbers on the rows axis, I transposed this in my version. There is a slight mental adjustment required since source rows have become columns in the visualization. But I think it makes the visual easier to read as column names don’t have a weird orientation to make them fit, and you can fit more source columns. You’ll also notice I added an “explainer” to help consumers understand what they are seeing.
So now it’s your turn to make a nullity matrix. You can use any visual you’d like to make it. I chose to use Deneb because it was pretty quick and did not require a lot of DAX measures. You could likely do this in a core visual, perhaps with the use of conditional formatting or SVGs. Let me know which orientation you prefer: columns names on the x-axis or y-axis.
Requirements
- Retrieve the data from Data.World.
- Replace the underscores with spaces in the column names (hint: you can do this with one line of M code in Power Query).
- Create a nullity matrix that shows a color where data is present and no color where the value is null. Pick 10 columns from the source data to visualize on the rows of the matrix. Use the index column on the x-axis to represent each row.
- Underneath the matrix, create a line chart that shows the count of non-null values for each row. The x-axis of the line chart should align with the x-axis of the matrix.
- Create an explainer or guide to help users understand how to use the visual.
Dataset
Data for this challenge can be found on Data.World at https://data.world/workoutwednesdayforpowerbi/wow2025w14/.
There is a single table in the dataset.
Note: Data.World requires you to create a free account to access the data. You may use the Data.World connector in Power BI or download the file to your local machine and connect to it there.
Share
After you finish your workout, share on social media using the hashtags #WOW2025 and #PowerBI.
On Bluesky, tag @mmarie.bsky.social, @shan-gsd.bsky.social, and @merrykerry.bsky.social.