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 […]

“Information is Beautiful” is our data visualization book of the month and it can be yours!

Last month we gave away “The Wall Street Journal to Information Graphics,” and it’s on the way to Australia to Terry Fitzgerald from Shop A Docket. Congratulations! In December our data visualization book of the month is “Information is Beautiful” by David McCandless. Contrary to our previous pick, this book doesn’t contain any prescriptive techniques […]

DataViz Tip #9: Learn the Basics of Statistics

In the previous tips, we’ve discussed that transforming your data can often expose the information in a new light and provide new insights to the person analyzing your visualization. Aggregating atomic data points into aggregates for periods is a powerful tool in helping users make more sense of the data. But the way you aggregate […]

DataViz Tip #8: Do Not Expose Your Private Data

If you are used to creating charts in Excel, server-side libraries or other desktop software that produces static images, you may be comfortable with taking your private (often confidential) data and creating visualizations straight from it. After all, you control that end-users only see percentages or other aggregate values. On the other hand, when your […]

DataViz Tip #7: Tools to Transform Data

Last week we have shown that transforming our data can help us create different and, likely, better visualizations. Let’s cover some tools that can help us in the process… Pivot Tables Pivot Tables is a great feature that lets you slice and dice the data you have in your spreadsheet. In Microsoft’s own words: PivotTables […]