Path: csiph.com!fu-berlin.de!uni-berlin.de!not-for-mail
From: David Shi <davidgshi@yahoo.co.uk>
Newsgroups: comp.lang.python
Subject: Re: How to put back a number-based index
Date: Fri, 13 May 2016 20:19:12 +0000 (UTC)
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Message-ID: <mailman.646.1463171080.32212.python-list@python.org>
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Hello, Michael,
I typed in df.index
I got the followingMultiIndex(levels=[[1.0, 4.0, 5.0, 6.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0, 24.0, 25.0, 26.0, 27.0, 28.0, 29.0, 30.0, 31.0, 32.0, 33.0, 34.0, 35.0, 36.0, 37.0, 38.0, 39.0, 40.0, 41.0, 42.0, 44.0, 45.0, 46.0, 47.0, 48.0, 49.0, 50.0, 51.0, 53.0, 54.0, 55.0, 56.0], [u'AL', u'AR', u'AZ', u'CA', u'CO', u'CT', u'DC', u'DE', u'FL', u'GA', u'IA', u'ID', u'IL', u'IN', u'KS', u'KY', u'LA', u'MA', u'MD', u'ME', u'MI', u'MN', u'MO', u'MS', u'MT', u'NC', u'ND', u'NE', u'NH', u'NJ', u'NM', u'NV', u'NY', u'OH', u'OK', u'OR', u'PA', u'RI', u'SC', u'SD', u'State', u'TN', u'TX', u'UT', u'VA', u'VT', u'WA', u'WI', u'WV', u'WY']],
           labels=[[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48], [0, 2, 1, 3, 4, 5, 7, 6, 8, 9, 11, 12, 13, 10, 14, 15, 16, 19, 18, 17, 20, 21, 23, 22, 24, 27, 31, 28, 29, 30, 32, 25, 26, 33, 34, 35, 36, 37, 38, 39, 41, 42, 43, 45, 44, 46, 48, 47, 49]],
           names=[u'StateFIPS', 0])Regards.
David 

    On Friday, 13 May 2016, 21:11, David Shi <davidgshi@yahoo.co.uk> wrote:
 

 Dear Michael,
I have done a number of operation in between.
Providing that information does not help you
How to reset index after grouping and various operations is of interest.
How to type in a command to find out its current dataframe?
Regards.
David 

    On Friday, 13 May 2016, 20:58, Michael Selik <michael.selik@gmail.com> wrote:
 

 Just in case I misunderstood, why don't you make a little example of before and after the grouping? This mailing list does not accept attachments, so you'll have to make do with pasting a few rows of comma-separated or tab-separated values.
On Fri, May 13, 2016 at 3:56 PM Michael Selik <michael.selik@gmail.com> wrote:

In order to preserve your index after the aggregation, you need to make sure it is considered a data column (via reset_index) and then choose how your aggregation will operate on that column.
On Fri, May 13, 2016 at 3:29 PM David Shi <davidgshi@yahoo.co.uk> wrote:

Hello, Michael,
Why reset_index before grouping?
Regards.
David 

  On Friday, 13 May 2016, 17:57, Michael Selik <michael.selik@gmail.com> wrote:
 

 

On Fri, May 13, 2016 at 12:27 PM David Shi via Python-list <python-list@python.org> wrote:

I lost my indexes after grouping in Pandas.
I managed to rest_index and got back the index column.
But How can I get back a index row?


Was the grouping an aggregation? If so, the original indexes are meaningless. What you could do is reset_index before the grouping and when you aggregate decide how to handle the formerly-known-as-index column (min, max, mean, ?).