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When you have a report style input with differing formats on various rows, it always a good idea to load the entire file and then deal with the various sections within the file. There's always a header row that needs to be copied down and applied to various data rows. In your case, the header row is "Users of xxxxxx" row. xxxxxx is that value that needs to be applied to each of the following data rows to be able to group them further in the workflow. Reading the file in as csv as splitting on input, usually ends up breaking up important rows. Starting the input at a specific row, can lead to important data loss, i.e. the initial "Users of" row as well as inadvertently losing data. By starting your import on row 23, you ended up with "BJEON2" as a column header, when it should have been a token value
Attached is an example that deals with your data. Read in the data as flat file to preserve the leading spaces. Get the group names for the "Users in" rows and copy them down until the group ends. After removing the header rows, split the remaining rows to columns. At this point the data is similar to your original where you split Login_date to month and day, the main deference is that you all the token values and they're grouped. The summarize at the top groups by GroupName and token to give you results like this
The bottom branch gives you the groups that don't have any users.