When it comes to my favorite chart types, scatter plots are a close third behind bar charts and line graphs. In several industries, and especially scientific journals, scatter plots are the favorite choice because of their ability to reveal and communicate correlations. Another benefit of this chart type is it is one of the few visualizations that allow you to view many marks in a small space. No, you cannot analyze every individual mark because they will likely overlap, but scatter plots make it easy to identify outliers and the aforementioned correlations. But wait – there’s more! Due to the way scatter plots are set up with a measure on each axis, adding reference lines for the average of each axis creates a natural four-quadrant segmentation. This is a great technique for isolating different groups so you can act on them individually. This post will show you how to make scatter plots and take them to the next level in three ways. We’ll cover (1) a formatting trick to make your scatter plots stand out, (2) ideas for maximizing the data-ink ratio in the context of scatter plots, and (3) a calculated field that will automatically break your dimension members into four usable segments.
Maps are one of the most effective chart types in Tableau and are also among the easiest chart types to create. They are effective because they help us decode latitude and longitude combinations almost instantly, allowing us to see patterns between geographic locations that may otherwise be challenging to discover. They are easy to create because Tableau comes prepackaged with thousands of geographic coordinates all over the world. This makes it so that simply double-clicking on a dimension that Tableau recognizes as geographic will create a map on the view. What’s more, Tableau maps are technically scatter plots with points at the combination of each latitude-longitude pair and an image of a map in the background. This unlocks even more applications including the ability to map anything – even if it’s not related to geography. This post will use a map of my top 10 favorite barbecue restaurants to share three ways to take your Tableau maps to the next level. Tips include a formatting trick, instructions for how to unlock additional map styles, and how to create a dual-axis map using a combination of generated and custom coordinates.
As a consultant, I have come across several occasions when my partners needed the ability to display their Tableau dashboard in multiple languages. For example, I’ve worked with a non-profit organization serving children in South America. The company’s offices are in the US and most employees speak English, but their field workers are in South America where Spanish and Portuguese are the primary languages. I also recently gave a presentation in Ottawa, Ontario, Canada where they have a similar challenge of needing to display English to some users, but French to others. I was even asked if it’s possible to create a bilingual dashboard in Tableau. According to Tableau, their software has been localized to Chinese, English, French, German, Japanese, Korean, (Brazilian) Portuguese, and Spanish. This means that navigation options will be translated, dates will show up in the appropriate format, and currency will have local formatting. What this post will show you is how to design entire dashboards in two (or more) different languages and allow your end users to choose which language is displayed throughout a workbook.
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.
In my post, Why do you visualize data?, I share my personal exercise for illustrating the benefits of data visualization. I first show a raw crosstab of data – similar to what most corporate reports still look like today – and ask the audience to answer the basic business question of identifying the highest or lowest number in the table. I then convert the crosstab to a highlight table by introducing the preattentive attribute of color, which reduces the time to insight, increases the accuracy of insights, and improves engagement. In the exercise, I take the highlight table a step further by only coloring the highest and lowest number in the view, further reducing the time to insight and increasing the accuracy of insights. This post shows you how to highlight the highest data point and lowest data point on a view using table calculations. This is as much about sharing some technical know how as it is about introducing the important concept of using Tableau to answer business questions automatically for you.