Data inputs can be very confusing when there's columns representing multiple variables. The transpose tool becomes very useful in this case.
Today we worked on some Alteryx challenges, essentially transforming this data set...
Into this one
Evidently the variables Sales, GM, Quarters and Years had to be transformed into their own columns for cleaner data. In order to do this we first transpose all the original data columns (except product) into rows using the transpose tool. This creates a brand-new column that lists all the columns we had into row values.
![](https://www.thedataschool.co.uk/content/images/2022/02/Screenshot-2022-02-21-170119.png)
To then get these variables separated, the text to column tool was used. In this way the variables are all separated into separate columns. To finish off, we used the crosstab tool to apply GM and Sales on the top columns, as they are independent variables. As a result, we get quarters, year, GM and Sales all on separated columns. Magic!