All in Tableau How-Tos

I’ve pulled a set of data for the top pitchers in Major League Baseball in 2017. Let’s say we want to do an analysis to see which of the best pitchers got extra help from their teams and which didn’t.

I’ll start by creating a scatter plot displaying wins and losses by each pitcher. Pitchers with dark blue circles that are farther toward the top did not get much help from their teams. Pitchers with lighter circles that are closer to the bottom did.

A couple weeks ago I was teaching a course and received a question from a student. Her question was “How can I use Tableau to only show the most recent 3 transactions per customer?” I thought I’d have an answer for her quickly, but I was wrong.

My first thought was, let’s just use the “RANK” function to accomplish this. We’ll use it as a Table Calculation to determine the most recent transactions by customer. I was feeling confident until I saw this:

Tree maps are a data visualization used to communicate hierarchical values in a systematic way with nested rectangles. A lot of the tree maps I see look something like this:

I don’t know about you, but I don’t find this to be particularly informative or compelling. I prefer to use tree maps as a way to highlight a few relevant data points. Notice in the dashboard below how I use a tree map to highlight the top 10 items sold.

One of my favorite additions to a dashboard are summary tiles. They’re a great way to quickly communicate a few quick, important data points. In this write-up, I’ll share some of my favorite techniques for building them and making them look crisp. See below for an example of summary tiles I created recently.

I recently got an email from a former student explaining that they were trying to recreate something similar to the image below in Tableau.

The trouble she was running into was recreating the total header called “Planned Cost by Perf”. If you try to use a measure as a discrete header, you end up with the value summed for each partition. Here is an example using Superstore data:

 

When calculating growth rates from one date period to another, it’s important to compare apples to apples. For instance, when building a graph in Tableau to compare quarterly sunscreen sales in Seattle, I probably wouldn’t want to compare Q3 Sales (July - September) to Q2 Sales (April - June) because there will be more sales in Q3. The product has a cyclical sales cycle. Instead, I would rather compare Q3 Sales of this year to Q3 Sales of last year to more accurately understand growth rates.