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# Repeating ID Excel Import Newbie Question

Hi all,

I have been searching the forum and watched most of the videos but am still at the very beginning. So please bear with me.

I am still learning and at the moment and am using a simple Excel file with 3 attributes (see screenshot) I imported the data via "add data".

What I have is simply a list of 4 projects and ratings for specific areas for each of the project area. The project ID is repeated 5x per project to match each area. When I import the data I have 20 example sets (5each per project ID). I now want to run simple stats on this data (distribution of high-medium -low per project ID, maybe decision tree etc)

How do I work with this data, at the moment I get stats for 20 different example sets and not for 4 projects with 5 subareas. Not sure it makes sense but should be more obvious with the screenshot. Maybe you could point me in the right direction re knowledge base. Trying to step up to Rapidminer from Excel Pivots..

Many thanks for your help

Lars

3 REPLIES
Moderator

## Re: Repeating ID Excel Import Newbie Question

Dear Lars,

two operators are of major importance for you.

Aggregate: Aggregate works like a SQL-Aggregate. You can group by coloums and generate statistics like average, std_dev, count etc. It reads a like "count(level) per projectId per Area".

Pivot: Pivot rotates your table. You can get a table like:

ProjectID, Area_A, Area_B, Area_C

with levels in the cells.

I think the Excel Pivot is for some mysterious reason a combination of both.

Best,

Martin

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Head of Data Science Services at RapidMiner
Contributor

## Re: Repeating ID Excel Import Newbie Question

Hi Martin, thanks so much. Exactly what I was looking for !!

All the best

Lars

Community Manager

## Re: Repeating ID Excel Import Newbie Question

[ Edited ]

One of the more handier RapidMiner operators would be the Aggregate operator. You could group by the ID letter and Area and then do a count, mode, etc of the Level value. Give that one a try, it's a great!

Regards,
Thomas
LinkedIn: Thomas Ott
Blog: Neural Market Trends