Hey, this is my first post to the forum and I haven't reviewed the rules too thoroughly, so I hope my post does not violate any. I have a dataset (pictured below) with 100+categories that just have letters. I would like to be able to identify strings that appear less than 5 times and categorize rows that contain that value as "Rare". I can't use a summarize node with a group by and a count, because I would have to add all 100+ of them and the count would just count the exact match of the combination of letters instead of the individual letter. Any thoughts or ideas?
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try the field summary tool and run all your fields through it. It should generate a nice meta data table and interactive report.
Thank you for your answer! The transpose and first summarize worked perfect. I am, however, a bit confused on the second summarize. Could you explain what you mean by "Then you can summarize on the new value and count the occurences"? So now that I have the two columns "name" which includes all the categories and the "concat_value", what do I do in the second summarize? I tried grouping it by the concat_value and counting the concat_value but I'm running in the same problem as before where it's counting the exact match instead of the letter.
Apologies on my lack of knowledge, I'm a student taking a class that involves alteryx, so by no means an expert.
Simon, thanks for your reply! Again, I'm not an expert so I could be wrong, but wouldn't the field summary give me a summary of each column? I would like to know how often the string occurs in the data as a whole instead of in individual columns, and finding that out by looking at the report for each one seems challenging. I just ran it, and I can only seem to find unique values for each column as well.
Amazing!! Thank you so much for all your help!!! It worked like a charm ![]()