I have a large SPSS-file (containing a little over 1 million records, with a little under 150 columns) that I want to convert to a Pandas DataFrame.
It takes a few minut
You can use rawMode=True to speed up things a bit, as in:
rawMode=True
raw_data = spss.SavReader('largefile.sav', returnHeader=True, rawMode=True)
This way, datetime variables (if any) won't be converted to ISO-strings, and SPSS $sysmis values won't be converted to None, and a few other things.
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