Crafting impactful line charts involves more than just throwing together some data points and calling it a day. A dash of creativity and insight can transform you from a good data storyteller to a truly great one. Let’s delve into three distinct ways you can breathe new life into your graphs using our innovative ‘ESCape’ method; Eliminate, Separate and Calculate.
We’ll be utilizing our chart from the final makeover in the “When not to use a stacked bar chart” blog as our subject for this exercise:
Sometimes, less is more. The simplest way to refine your chart is by eliminating any information not relevant to your audience. It may feel uncomfortable at first — we’re often conditioned to believe that an abundance of information is always desirable. However, bear in mind that your data isn’t lost forever. You can retain the deleted detail in an appendix, ready to be referenced as needed.
For instance, when presenting solely on the impact of wind for energy production, we could create a chart with all irrelevant series removed:
When we want to exhibit each renewable energy source individually, we could create a slide for each energy source, similar to what we did for wind. But what if we want to compare the trend across all five energy sources simultaneously?
There’s an influential technique that allows you to fragment a visualization into smaller units and arrange them side by side, enabling you to see the bigger picture. This is known as a ‘small multiple’ chart. Here’s our chart, broken down into small multiples for easier comparison:
Our small multiple presents an abundance of information to our audience. Yet, it does so in an organized manner that simplifies interpretation. Frequently known as a panel chart, a small multiple is akin to a table of charts. It takes multiple charts, shrinks them, and displays numerous versions neatly side-by-side. This technique is adaptable to almost any chart type and proves particularly useful for bar charts, line charts, dot plots, and scatterplots.
So, when you’re faced with an overwhelming chart, ask yourself whether you can deconstruct it into smaller pieces that each present a unique aspect of your data exceptionally well.
Occasionally, the data we possess isn’t necessarily what our audience needs to see. In our initial chart, we’re displaying each energy source as its own series. What if our goal is to determine and present the total energy amount in billion kilowatthours produced by renewable energy sources since 1991? Performing a relatively simple calculation can drastically reduce the series count and allow you to present the data that truly matters.
This chart discards unnecessary details, revealing the significant increase in renewable energy production since 1991. It’s a shining example of how the right calculation can unlock the true value of your data.
As you continue your data storytelling journey, remember the power of the ESCape method. It can guide you to more effective visualizations and empower your audience with clear, actionable insights.