DataViz Tip #19: Utilize The Center of Donut Charts

Donut charts are not that different from Pie charts, except for that hole in the center (hence the name). That hole changes the aesthetics of the chart which you may or may not like, but it can also be used for practical purposes. You can display a total value in the center or use it […]

DataViz Tip #18: Combine Smaller Pie Chart Slices into “Other”

Pie charts have a bad reputation as slices of a circle are harder for the human brain to compare to each other than, say, bars in a bar chart. Yet, they are a great and widely recognized chart type to show values as part of a whole. Where they really break down, though, is when […]

DataViz Tip #17: Opt For Low Detail Map Charts

Occasionally, I use Microsoft’s Power BI to analyze various business data. While I love the tool in general, the map chart part of it frustrates me, to say the least. The problem is that it is using Bing maps as the basis for the map charts which results in charts like this: Not only does […]

DataViz Tip #16: Keep It Simple, Stupid

As someone responsible for visualizing data, you may lose track of what’s important in the task. Sometimes your goal is to build something visually stunning to impress the public, but most times your goal is to make information easy to understand and analyze. That’s where remembering the KISS principle is very important. In the data […]

DataViz Tip #15: How To Choose A Map Projection

The earth is not flat, unlike what some people may think. The maps, on the other hand, are flat. In most cases what you are looking at is a view of the globe that someone created based on some algorithm. These algorithms are called projections and, as it’s impossible to convert a globe to a […]

DataViz Tip #14: Differentiate Between Actual Values and Estimates

Your viewers should be able to distinguish between factual data and projections or estimates in your visualizations. The most common way to do this is to use a lighter fill for projection/estimate values. This signals to the viewer that these values are less certain than the others. The easiest way to do this with amCharts […]

DataViz Tip #13: Switch To Horizontal Bar Chart When Labels Don’t Fit

A column chart is classic – it’s understood by everyone, easy to comprehend and compare values. However, when you have more than a few columns and not that much space its readability breaks down a bit: There are several ways to resolve this: you can show every other label and force users to interact with […]

DataViz Tip #12: Show Up to Four Lines in a Line Chart

A good rule of thumb is to limit the number of lines shown in a line chart to 3 or 4. Above that the picture gets messy quite fast: When you need to show more than 3-4 lines consider using a different chart type or a panel of “micro charts” instead. Having said that, when […]

DataViz Tip #11: Augment Your Data for Better Visualizations

The data you have is straight to the point most of the times. When you have revenue numbers it’s usually just that. If you want to present the data as revenue-per-employee you have to transform your data to serve your vision. It’s all good while you have all the data that you need. But what […]

DataViz Tip #10: Verify Your Data

“Unlike a misspelled word in a story, one wrong number discredits the whole chart.” ~ Dona M. Wong “The WSJ Guide to Information Graphics” Sometimes you discover a wild outlier in your data when you visualize it. In some cases, this may be a valuable insight, but more often than not it’s just a side-effect […]