A diverging bar chart is a bar chart that has the marks for some dimension members pointing up or right, and the marks for other dimension members pointing in the opposite direction (down or left, respectively). What’s unique about a diverging bar chart is the marks flowing down or left do not necessarily represent negative values. The divergent line can represent zero, but it can also be used to simply separate the marks for two dimension members, to represent a goal, or – as often seen with survey data – to show the break between desired and undesired responses. The drawback to using diverging bar charts is that it’s not as easy to compare the values across dimension members as it is with a grouped bar chart. If, on the other hand, your primary objective is to compare the trend of each individual dimension member, a divergent bar chart is a good option. I also feel that this chart type helps declutter a grouped bar chart, making the data more engaging and easier to understand. In this post, we will reverse engineer my viz, 50 Years of AFC vs. NFC Matchups, to show you two different approaches to creating diverging bar charts in Tableau.
To draw a highlight table in Tableau, you need one or more dimensions and exactly one measure. This is the same criteria to draw a raw text table in Tableau, except with highlight tables, you’re limited to one measure instead of one or more measures. This one measure is what encodes the cells in the table by the preattentive attribute of color. It’s essentially a spreadsheet with colored cells. As I shared in my post, Why do you visualize data?, the highlight table is my favorite chart type for introducing the value of data visualization. I think it works well because most companies are still using spreadsheets for most of their reporting, and by converting a text table to a highlight table, the audience is forced to take advantage of the preattentive attribute of color. This kind of becomes a gateway to more complex visualizations. Highlight tables are already more engaging and effective than a text table / crosstab view, but this post aims to provide three more ways to make your highlight tables even better in Tableau.
This is the fourth in a series of five “you are here” Tableau tutorials. These tips will help improve the user experience of your Tableau dashboards by helping guide your end users. Subscribe here to receive new updates. There is a chart type I’ve been gravitating toward a lot this year, but have struggled to find a documented name for it. The chart consists of dots (or the Circle mark type in Tableau) plotted on a shared axis. I’ve been calling this a dot plot for seemingly obvious reasons, but traditional dot plots in statistics are closer to unit charts, where the mark type would simply be changed from Bar to Circle. My examples are slightly different in that they share one axis, or row of dots, and I usually hide the axis header. Being that this is a plot of dots and only includes the minimum amount of data possible, for now I’m calling this a minimalist dot plot. This chart type has some big benefits. First, it’s the closest I’ve seen to getting to a 100% data-to-ink ratio. It provides comparisons which help avoid the dreaded, “So what?”. Also, by hiding the axis header, the user is forced to focus on the insight of comparing dimension members in relation to each other, rather than the exact numbers. Of course, I provide the exact data points on demand via the tooltip when the user hovers over a circle. The chart type is featured prominently in both my Super Sample Superstore and MLS Standings Reinvented dashboards. In the first, the user is able to choose which region they hypothetically manage, and in the latter, the user can choose their favorite team. In both cases, the dot plots then highlight the selection throughout the dashboard so the user can see where they stand in relation to the others. This post will show you how to make a minimalist dot plot in Tableau and how to highlight a specific dimension member throughout multiple views.
The Odds of Going Pro in Sports viz has generated more questions around how it was created than any other viz I have put together during my career with Tableau. With its one dominant funnel chart and icon-based navigation, the viz tells the story about the share of high school athletes progressing to the college and pro levels across several sports for each gender. The most common question I receive: That was made in Tableau? I would be lying if I said that question doesn’t make me want to stand up a little taller, but the secret is, the viz was one of the easiest dashboards I have ever put together. In fact, I put it together in a couple of hours on a Sunday afternoon. Funnel charts are one of the simplest chart types you can create, but they have proved to be incredibly effective in a corporate setting - think conversion rates and customer flows. Funnel charts are not one of the out-of-the-box “Show Me” options in Tableau, so this post will walk you through multiple approaches to creating funnel charts. First, let’s take a look at the full version of What are the odds of going pro in sports?
Dual-axis combination charts, or combo charts, are named that because they have two axes and they display a combination of different mark types. For example, you can create a visualization that displays a measure with bars on one axis and another measure as lines on the second axis. This is one of my favorite chart types to use in Tableau because the ability to add a second axis, and control the axes independently of each other, unlocks some additional flexibility. This newfound flexibility creates several practical applications that can be used to improve your analysis, user experience, and design. This post will show you how to make a dual-axis combo chart in Tableau as well as three different ways to use them: (1) their traditional use (2) a method for making your end user part of the story and (3) an option for improving the aesthetics of your dashboard.