The picture above is today's goal. I will talk about
1. Measure Name and Measure Value.
The reference for this training is here. If you haven't downloaded yet, please see this post.(Edit it later)
Before I start, I'd like to revise my Sales per Customer variable. Since I used R to do this calculation, all records that has a certain customer name have the same amount of sales. This is the example.
So, I calculate Sales_Per_Customer and Profit_Per_Customer again in Tableau. For how to calculate them in Tableau, see Series 1-1. The formula is like this below. Here is a link for other functions in Tableau.
If the data size is "n times m", if the result of the calculation doesn't have n rows, we shouldn't do the calculation in R, because we produce duplicated data.
So let's start making worksheets with the bar chart. The first idea we will do can be like this for a bar chart that has many measures.
However, I recommend you to use "Measure Value" and "Measure Name" if you have more than 2 or 3, because it makes it easy and makes the window less messy. I believe in many times it is better to use Measure Value and Measure Name to organize them in an easier way. This is the example.
As for the other charts, I believe that you can make them by yourself if you finish Tableau Training Video so let me skip them.
Finally, I would like to show "Action" function for highlighting.
By the way, when I see the scatter plot, I feel that we can do a clustering. It seems that there are more than 3 groups based on Profit Margin. I may talk about this later.
I also have finished Shipping Dashboard, but it was so easy to talk about something new. I just mention how to add the grid lines.
I hope you enjoy today's topic. Next time, I will talk about how to use R in Tableau. As I mentioned before this series, my goal is to integrate R, Tableau and Google Analytics into an entire system. We will start with clustering and predictive modeling with this superstore data.