Learn to visualize your data like an expert with these practical how-tos for presentation, analysis, and understanding.
By shifting the baseline to a reference point, you can focus a line chart on relative change, which can improve the visibility of smaller categories.
Ooo, bubbles... It's not the most visually efficient method, but it's one of the more visually satisfying ones.
Visualize rankings over time instead of absolute values to focus on order instead of the magnitude of change.
For when you want to show the occurrence of events over time.
Also known as a Marimekko diagram, the mosaic plot lets you compare multiple qualitative variables at once. They can be useful, sometimes.
Using color as the visual encoding, show changes over time in two dimensions.
With latitude and longitude coordinates, there are a number of ways to map geographic data using D3.js and Leaflet.
A combination of a bivariate area chart, animation, and a population pyramid, with a sprinkling of detail and annotation.
Also known as ridgeline plots, the method overlaps time series for a 3-D-ish view of the data. While perhaps not the most visually efficient, the allure is undeniable.
Compare distributions side-by-side with a pyramid chart. Observe the change over the years by animating it.
Show individual data points by splitting bars into smaller cells.
Defaults are generalized settings to work with many datasets. This is fine for analysis, but data graphics for presentation benefit from context-specific design.
When you want to focus on the magnitude of differences between low and high values, use visual cues that highlight distance.
Mapping one dot per person, it's all about putting the pieces together.
Moving your data from the digital screen to something more physical isn't as tricky as it seems. Here's how I did it.
Show connections in the circular layout for a more compact presentation.
Make the unit chart less abstract with icons that represent the data, or use this in place of a bar chart.
Also known as waffle charts. Using animated transitions between values, you can allow for comparisons between categories.
The usually abstract, qualitative and sometimes quantitative chart type shows relationships. You can make them in R, if you must.
Combining small multiples with the grid layout can make for an intuitive geographic reference.
For when you want to show or compare several distributions but don't have a lot of space.
Add interaction so that you can show different segments of the data and allow comparisons.
Add the vertices. Connect them with edges. Repeat as necessary.