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Using an imported CSV file, I indexed the DataFrame like this...

 rdata.set_index(['race_date', 'track_code', 'race_number', 'horse_name'])

This is what a section of the DataFrame looks like...

 race_date track_code race_number horse_name work_date work_track 2007-08-24 BM 8 Count Me Twice 2007-05-31 PLN Count Me Twice 2007-06-09 PLN Count Me Twice 2007-06-16 PLN Count Me Twice 2007-06-23 PLN Count Me Twice 2007-08-05 PLN Judge's Choice 2007-06-07 BM Judge's Choice 2007-06-14 BM Judge's Choice 2007-07-08 BM Judge's Choice 2007-08-18 BM

Why isn't the 'horse_name' column being grouped like the date, track and race? Perhaps it's by design, thus how can I slice this larger DataFrame by race to have a new DataFrame with 'horse_name' as its index?

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  • looks like a bug, the correct place for bug reports is on github :) Good find! Commented Aug 6, 2013 at 3:23
  • 1
    This question appears to be off-topic because it is a bug report. Commented Aug 6, 2013 at 5:22

1 Answer 1

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It's not a bug. This is exactly how it's intended to work.

DataFrame has to show show every single item in it's data. So if the index has one level, that level will be fully expanded. If it has two levels, first level will be grouped and the second will be fully expanded, if it has tree levels, first two will be grouped and the third will be expanded, and so on.

So this is why the horse name is not grouped. How would you be able to see all the items in the DataFrame if you group also by the horse name :)

Try doing:

 rdata.set_index(['race_date', 'track_code', 'race_number'])

or:

 rdata.set_index(['race_date', 'track_code'])

You'll see that the last level of the index is always fully expanded, to enable you to see all the items in the DataFrame.

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