Are you choosing the best way to display your data?

Educators deal with lots of different types of data

Sometimes data needs to be explanatory and not exploratory.  This is also known as static data.  As educators, we are constantly bringing in data about our students in real-time.  We are making anecdotal observations about how they are reading, what standards they are mastering, and whether or not they showed up for the class on any given day. 

We spend a lot of time looking at academic and wellness data. That being said, from time to time, we do want to take a look at overall programs or curriculums.  For this type of information, static data can be helpful.

While creating a report for a school district, I was asked to develop some visualizations that would provide data about overall program attendance across an eight-week period.  There were multiple data sources and the information was a bit scattered. 

However, once I was able to wrangle and clean the data, I could start to make sense of it. Although there were multiple layers to the report I’m going to talk about, I will focus on student participation across three programs that were offered.

Is this the best way to show the data?

I wasn’t really sure exactly what the school district wanted, and they probably didn’t really know either.  That is where I had to put on my “data translator” hat as well as my “data artist” hat and build visualizations that would lead to insights.

I decided to first take a look at overall numbers, by week and by day, across the three programs. This first chart shows the total number of online participants for all three programs for each week.  The numbers are really large and make the program look like it was a success.

We can then take that data and break it down further to look for some possible trends across each of the weeks. This next chart is a bit harder to read because of the granularity of the data. In this particular chart, we have the average daily participation. I chose not to add data labels to each bar because I wanted to show the overall trend by day throughout the eight weeks.

I was originally asked to provide a general overview. I chose a line graph with minimal features to simply show the trend and highlight the highest and lowest points with annotations. The context was provided in the title of the chart.

Yes, but show me more

I was quickly told that it was too limiting and that there needed to be more information.  I decided to break down the days of the week into a column chart instead.  I kept the same title and annotations, however.

After seeing this general overview, the school district had some questions related to participation. They could see the total numbers for each week and each day, as this is what they asked for originally.  They then wanted to know the breakdown for each of the three programs. I decided to show them a few different approaches to their curiosities.

For the first chart, I stuck with the line graph and broke it down by the three programs.  This view does not provide large overall numbers, but it does show the daily comparison across the three programs.

Can you show me another way to display the data?

I wanted to take the weekly data and make it more accessible for the stakeholders by providing more numbers instead of just general trends.  I decided to take the same data set and break it down into a side-by-side column chart.  This allowed for easier comparison across the three programs by week.

I also chose to take the same data set, again, and create a small-multiple chart. The title for the chart is the same, it is just a different way of looking at the numbers. This type of chart allows for comparisons across the program by week. It also allows for comparison within each of the programs.

Same data different views

My goal in creating a variety of charts with the same data set was to allow the school district to see the data in different ways.  This also gave them a chance to choose the best way to share the data with their stakeholders. As you can see, data can be shared and visualized in many different ways.  It all depends on the context of your situation and the story you want to tell with it.  

The next time you set out to make some charts and graphs, consider spending a few extra moments designing more than one visualization.  Get feedback on them and then move forward.  You might just come up with a great way of showing the data that you weren’t thinking about.

Do you have a dataset that you aren’t quite sure how to visualize?  Would you like for me to look at it and give you some feedback and input?  Feel free to reach out to me either on Twitter (@smithrchris) or send an email to [email protected].

Skip to content