What I want to do is kind of like imputation, but it's enough different that it needs a post of its own. I don't actually have any missing data, and rather than modifying an existing field (like imputation would) I'd like to create an entirely new row based on calculations on some (or all) of the fields in at least two rows in the original dataset. I have a dataset of about 300 rows, so doing this manually is somewhat impractical
Here's the idea -
An example comma-delimited dataset might look like this -
row one: 1,2,4,purple,5,grape
row two: 3,6,7,green,9,strawberry
I want to create and append to the bottom of the table (or dataframe if you prefer) a new row, number three, that looks something like this-
row three: 2,8,4,Null,9,Null
The "Generate Rows" tool is too simple by itself. It only generates a sequence of numbers to create rows, and it has no provision for creating values in more than one column.
The Multi-Row Formula tool won't work by itself because it creates a new field in an existing row (based on the values in that and/or other rows), and an existing row is not where I need my new values.
If I were coding this in Python or R then it would be relatively straightforward to grab the rows, do the calculation(s), create the new row, store it away, and then append all "n" of them at once when I'm done processing. However, I'm trying to do this in Alteryx, and there don't appear to be any built-in tools that do what I want to do.
I'm wondering if I might have to hack a solution with a batch or iterative macro, but I'd rather avoid the added complexity if possible.