It is possible to use python in SPSS to bypass limitations of the SPSS syntax (f.ex. in loops)?

Question

You can use python to automate things in SPSS or to shorten the way, but I need to know if it is possible to replace the SPSS Syntax with python for example to aggregate data in loops etc..

Or another example. I have 2 datesets with the follwing variables id, begin, end and type. It is possible to put them into different arrays/lists and then compare the arrays/lists so that at the end i have a new table/dataset with non matching entries and a dataset with the matching entries in SPSS. My idea is to extend the context of matching files in SPSS.

Normally programming languages like python or php can handle this.

Excuse me. I hope someone will understand what I mean.

Answer 1

There are many ways to do this sort of thing with Python. The SPSS module Dataset class allows you to read and write the case data. The spssdata module provides a somewhat simpler way to do this. These are included when you install the Python Essentials. There are also utility modules available from the SPSS Community website. In particular, the extended Transforms module provides a standard lookup function and an interval-based lookup.

I'm not sure, though, that the standard MATCH FILES won't do what you need here. Mismatches will generate missing data in the variables, and you can select subsets based on that criterion.

Answer 2

This question explains several ways how to import an SPSS dataset in Python code: Importing SPSS dataset into Python

Afterwards, you can use the standard Python tools to analyze them.

Note: I've had some success with simply formatting the data in a text file. I can then use any diff tool to compare the files.

The advantage of this approach is that's usually very easy to write text exporters which sort the data to make it easier for the diff tool to see what is similar.

The drawback is that text only works for simple cases. When your data has a recursive structure, then text is not ideal. In that case, try an XML diff tool.