“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 […]
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 […]
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 […]
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 […]
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 […]
The data you store and get back is often the most granular – that’s always great to have but not necessarily the best data to expose to users and comprehend. Suppose you have data for daily site visitors, page views and sales. You can expose all of this data as is in 3 line graphs […]
After seeing beautiful amCharts demos, you may have an urge to drop straight into your code editor and start coding. While sometimes you know precisely what chart represents your data best, other times it may not be as obvious. While developing a visualization with amCharts is easy, it is still more work than doing a quick […]
An excellent way to start thinking about your visualization is to ask yourself “what would I want my viewers to tweet about this chart?” Consider this chart of visits to a fictional website: What would someone tweet after looking at this chart? Maybe something like “Most visits to the website come from the USA, followed […]
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Consider the following chart which represents monthly visits to a fictional website. Based on your first quick impression, how many more visits did the site get in April compared to February? I’d say about 50 times more. Now, look at the values on the axis. As you can see the correct answer is less than […]