![]() This highlights a challenge that sometimes arises, which is when the series flip flop, changing position relative to each other, that doesn’t necessarily stand out. In the preceding example, countries are arranged by the difference-with cases where a greater proportion of women smoke than men at the top, to the greatest gap between proportion of women and men at the bottom. How you sort the data is one consideration when designing a dot plot (as it is for many types of graphs). For example, the following visual (created by Anna Dzikowska) shows the percent of women compared to the percent of men who smoke by country. ![]() The connected dot plot can sometimes be useful to show group comparison (a slopegraph is another alternative). Through them, you’ll see a number of different design choices illustrated as well. Let’s look at some more here! The connected dot plot is the most nuanced and has a few interesting and varied use cases, so let’s take a look at some examples of these. However, they may be met by unfamiliar audiences with resistance or confusion, so assess whether it makes sense to use one given the specific situation and take careful steps to label and explain. In some instances, that may be a plus (bored with bars? try a dot plot!). That said, dot plots aren’t as common as bars. For the Cleveland and connected dot plots, an additional freedom that is sometimes useful is that the axis does not have to begin at zero (like it does with a bar chart or traditional dot plot, which encode data by length or height with the other dot plot variations, we focus more on relative position in space than distance from the axis). What are some pros and cons of dot plots?Ĭompared to the more common bar chart, dots in a plot use less ink, which means there is more space to add annotations, or simply have a lighter feeling graph. The connected dot plot encodes the absolute values (via positions of the dots), but puts emphasis on the difference or change between the data series due to the visual connection between the dots. Let’s use the same example as previously, only now I’ll add a second data series. It functions the same way as the Cleveland dot plot, but graphs two (or sometimes more) data series. Like bar charts, it can be a worthwhile endeavor to consider both layouts (vertical and horizontal) to determine which makes more sense or feels more intuitive in the given situation and data (if in doubt, ask others for feedback).Īn additional common variation is the connected dot plot. Which orientation you choose will depend on the data itself, the length of category names, and other elements. I’ve illustrated with a horizontal version in this case, but you can also rotate (imagine the dots replacing a vertical bar chart in similar manner to what I’ve illustrated above). We might add light gridlines or lines from each category on the left to its respective dot to lend greater structure to the graph (this latter variation with lines from axis to dot is often referred to as a lollipop chart). For example, we could label the individual values within each dot, eliminating the need for the x-axis. You can perhaps imagine additional formatting changes we could apply. The third view above doesn’t have to be the final one. Rather, this example is simply meant to illustrate how this type of dot plot works, by transitioning to it from something familiar. You don’t have to actually go through this progression to create a dot plot. ![]() Check out the following example to see what I mean. One way to think of it is as an alternative to a bar chart. This graph encodes quantitative data across categories. Cleveland, sometimes referred to as the Cleveland dot plot. Today, the more common type of dot plot I encounter (in a business setting, at least) is the one developed by William S. They tend to work best for small data sets (when you have more data, something that aggregates the individual points, like a histogram or box plot, may better suit). However in this type of dot plot, because each dot represents an individual data point, the dots don’t necessarily have to be uniformly spaced along the horizontal axis. It looks similar to a histogram (which encodes a distribution of data in bars rather than as dots). This can be useful if you want to see the your data to get a sense of the shape or identify outliers. They were originally hand drawn and are used to show the distribution of data. This graph has been used going pretty far back in time. The first, I’d refer to as a traditional dot plot (labeled simply “dot plot” above). ![]()
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