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How can I transpose a data table with different types?
Hi,
I have an example enclosed in this post. I would like the final result could be shown in the following format:
Subject PreTest PostTest Test_ID
100 1 5 A
100 3 7 B
100 8 7 C
100 ... ... ...
100
200 10 10 B
200 9 2 D
200 6 4 A
...
The problem I found is when I click on the Tables->Transpose and I select Subject as By and all columns as Transpose Columns, JMP shows an error because Test_ID is Character. I don't understand what's the problem to create columns with different types. If I exclude it from Transpose Columns, JMP creates a Label column which it doesn't match what I would like to have as a final result.
Thank you for your help.
Accepted Solutions
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Re: How can I transpose a data table with different types?
1. Using Standardize Attributies, convert all columns Data Type to Character
2. Using Tables==>Stack select all columns from PreTest 1 thru Test_ID 4. Also select Multiple Series Stack, specify 3 for the number of Series and check the Contiguous checkbox.
3. In the new data table created by the Stacking, change the column named Data to PreTest, the column named Data2 to PostTest and the column named Data3 to Test_ID.
4. Delete the columns Label, Label2 and Label3
5. Change the Data Type for columns PreTest and PostTest to Number and the Modeling Type to Continuous
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Re: How can I transpose a data table with different types?
1. Using Standardize Attributies, convert all columns Data Type to Character
2. Using Tables==>Stack select all columns from PreTest 1 thru Test_ID 4. Also select Multiple Series Stack, specify 3 for the number of Series and check the Contiguous checkbox.
3. In the new data table created by the Stacking, change the column named Data to PreTest, the column named Data2 to PostTest and the column named Data3 to Test_ID.
4. Delete the columns Label, Label2 and Label3
5. Change the Data Type for columns PreTest and PostTest to Number and the Modeling Type to Continuous
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Re: How can I transpose a data table with different types?
Great!! Tnx, Jim!