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Converting multiple true/false fields into one dimension while keeping linkages

Example data:

IDStateDeletedUpdatedSavedReverted
101ALTRUEFALSEFALSEFALSE
102CAFALSETRUETRUEFALSE
103COTRUEFALSEFALSETRUE
104TXTRUETRUEFALSEFALSE
105MITRUEFALSEFALSEFALSE
106FLFALSEFALSEFALSETRUE

The real data I'm working with is confidential, but the table above is an example of the same situation I'm facing. The raw data is set up like above, where there is an ID, state, and other identifiers, as well as multiple "Status" columns that have TRUE or FALSE.

What I need is a pie chart that would read this raw data and display four slices for Deleted, Updated, Saved, and Reverted, counting when a record has TRUE for each field. I initially just manually created a new table that has two fields, "Status" and "Status Count", with a row for each status and the corresponding count. However, I still need the data linkage between the other fields. For example, if I select "Deleted" from the pie chart, I need the filter to also filter my other visualizations to only display records that have Deleted = TRUE.

Any insight on how to accomplish this? Thank you in advance.

1 Solution

Accepted Solutions
sunny_talwar

I think you need to transform your data in the script using The Crosstable Load

View solution in original post

4 Replies
sunny_talwar

I think you need to transform your data in the script using The Crosstable Load

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Author

I just figured this out from researching and finding another similar discussion post. CrossTable worked exactly as I needed. Thank you!

sunny_talwar

See if the attached is what you would want to see

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Author

Thank you. That is helpful and what I'm going for, but there's still one issue. I added another pie chart for States in the attached file. What I want it to do, is when I select a Flag, for example Deleted, in the Flag pie chart, I want the State pie chart to filter on records where "Deleted=True". Is there a way I can make a crosstable, but only include records where the Value is TRUE? Does that make sense?

Thanks again.