Pandas: Set_index function does not delete columns

Question

I have the following DataFrame:

df = pd.DataFrame({
'Trader': 'Carl Mark Carl Joe Joe Carl Joe Carl'.split(),
'Product': list('AAAABBAA'),
'Quantity': [5,2,5,10,1,5,2,3],
'Start' : [
    DT.datetime(2013,1,1,9,0),
    DT.datetime(2013,1,1,8,5),
    DT.datetime(2013,2,5,14,0),
    DT.datetime(2013,2,5,16,0),
    DT.datetime(2013,2,8,20,0),                                      
    DT.datetime(2013,2,8,16,50),
    DT.datetime(2013,2,8,7,0),
    DT.datetime(2013,7,4,8,0)]})

When I try to put the index via:

df = df.set_index([df.Start, df.Trader, df.Product])

It does not delete the columns which are used for the index. Even when I specify it explicitly using:

df = df.set_index([df.Start, df.Trader, df.Product], drop=True)

Is this a bug or do I have a mistake in my code?

Thanks

Andy

waitingkuo · Accepted Answer · 2013-05-27 09:32:25Z

7

The parameter is an array of column names but not those series:

In [9]: df.set_index(['Start', 'Trader', 'Product'])
Out[9]: 
                                    Quantity
Start               Trader Product          
2013-01-01 09:00:00 Carl   A               5
2013-01-01 08:05:00 Mark   A               2
2013-02-05 14:00:00 Carl   A               5
2013-02-05 16:00:00 Joe    A              10
2013-02-08 20:00:00 Joe    B               1
2013-02-08 16:50:00 Carl   B               5
2013-02-08 07:00:00 Joe    A               2
2013-07-04 08:00:00 Carl   A               3

answered May 27, 2013 at 9:32

waitingkuo

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1 Comment

Andy Over a year ago

Thanks for the clarification. I am a Pandas beginner and it was not clear to me to see the differences between the two.

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