Pandas Sorting Values in Data Frames with Keys

Question

I have two Pandas dataframes that are concatenated by column. The left dataframe is keyed as "Old" and the right dataframe is keyed as "New". Each dataframe has the same column names and I'd like to be about to sort_values by one of the "New" columns. I can't seem to access sort though due to the "Old" and "New" keys. Anyone have a work around? Thanks.

Edit#1 - Code example (want to sort by ['New']['Col1'] in df_combined:

df1=pd.DataFrame({'Col1' : [1, 2, 3, 4], 'Col2' : [4, 4, 5, 6], 'Col3' : [11, 
12, 13, 14]})
df2=pd.DataFrame({'Col1' : [7, 1, 51, 6], 'Col2' : [90, 99, 99, 97], 'Col3' : 
[11, 12, 13, 14]})
df_combined=pd.concat([df1, df2], axis='columns', keys=['Old','New'])

Please show your input dataframe.

Scott Boston
– Scott Boston

2017-12-27 23:11:11 +00:00
Commented Dec 27, 2017 at 23:11 — Scott Boston
– Scott Boston, Commented Dec 27, 2017 at 23:11
Updated Scott. Thanks!

Tyler Russell
– Tyler Russell

2017-12-28 15:30:27 +00:00
Commented Dec 28, 2017 at 15:30 — Tyler Russell
– Tyler Russell, Commented Dec 28, 2017 at 15:30
How do you want to sort this dataframe exactly?

Scott Boston
– Scott Boston

2017-12-28 15:31:43 +00:00
Commented Dec 28, 2017 at 15:31 — Scott Boston
– Scott Boston, Commented Dec 28, 2017 at 15:31

Scott Boston · Accepted Answer · 2017-12-28 15:33:07Z

1

To sort this dataframe you must use tuples for column selection:

df_combined.sort_values(by=('New', 'Col1'))

Output:

   Old            New          
  Col1 Col2 Col3 Col1 Col2 Col3
1    2    4   12    1   99   12
3    4    6   14    6   97   14
0    1    4   11    7   90   11
2    3    5   13   51   99   13

answered Dec 28, 2017 at 15:33

Scott Boston

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