Highlighting Insights in Data Charts: Make Data Chart Easy to Understand.
Discover three practical case studies that simplify your data charts.
Hi guys!
I’m Stephen, a data analyst & data engineer. I'm delighted to welcome you to this publication on data visualization and data analysis. I hope you find it enjoyable and informative!
To recap our previous articles, we've explored:
Previously, we discussed the significance of data visualization and the most effective techniques for implementing it. In this article, I will delve deeper into methods to simplify data charts and make complex information more accessible and understandable.
We don’t just simplify charts for the audience, but also for ourselves.
Explanatory data visualization is about clearly presenting information to an audience. The goal is to communicate ideas effectively and persuade viewers. To achieve this, making the content easy to understand is crucial, often referred to as “reducing the cognitive load“.
For example, consider how to simplify complex data charts. Let's start with a spaghetti plot, typically used to compare different categories.
In Plot 1, on the left side, we have a classic 'spaghetti plot' which shows many categories in a single chart. This type of chart becomes difficult to read as the number of lines increases. When you need to focus on a specific line, there are two ways you can use to display the data.
You can find the first way on the right side of Plot 1. Here, each line is shown separately. This way, viewers can easily concentrate on one category at a time without any distractions, and still compare it with other lines. Of course, you can also try to put shaded lines in the background to offer more information.
If some categories are not as important, Plot 2 offers another solution. To reduce clutter, you can average out these categories. This helps the audience compare the main lines more clearly.
Highlighting the important parts.
There are several ways to simplify a chart. For instance, using the right colors is one of them.
Consider Chart 1, which uses data from the Video Games Sales Dataset. This dataset includes sales figures for various games over different years and regions. I have applied different shades of colors to represent each category, making it easier for viewers to tell them apart. This bar chart is suitable for general use.
If you need to emphasize a specific detail, such as a marketing manager explaining that sales in every region decreased in 2018, the presentation can be simplified. Use gray color to downplay less important information and highlight the key points. Refer to Chart 2 for an example.
Put yourself in the audience’s shoes.
What else can we do to make the chart easy to read for our audience? One effective approach is to look at it from their perspective.
Take a look at these two stacked bar charts for comparison(Chart 3).
Both use the previously mentioned techniques to improve the chart. However, it is easier to compare sales across different regions on the left side. Since I placed them on the same horizon line, they became clearer.
Key Takeaways!
In summary, to keep the chart simple:
Downplay the unimportant information for more clarity.
Put yourself in the audience's shoes. Address any issues that might confuse them, as well as yourself.
I'll explore the second point in more detail in the next article, so stay tuned!
If you have any suggestions or comments, feel free to leave a message or contact me.
Thanks for reading.
-Stephen Wen
