pandas concat ignore_index doesn't work

Question

I am trying to column-bind dataframes and having issue with pandas concat, as ignore_index=True doesn't seem to work:

df1 = pd.DataFrame({'A': ['A0', 'A1', 'A2', 'A3'],                     'B': ['B0', 'B1', 'B2', 'B3'],                     'D': ['D0', 'D1', 'D2', 'D3']},                     index=[0, 2, 3,4])  df2 = pd.DataFrame({'A1': ['A4', 'A5', 'A6', 'A7'],                     'C': ['C4', 'C5', 'C6', 'C7'],                     'D2': ['D4', 'D5', 'D6', 'D7']},                     index=[ 5, 6, 7,3]) df1 #     A   B   D # 0  A0  B0  D0 # 2  A1  B1  D1 # 3  A2  B2  D2 # 4  A3  B3  D3  df2 #    A1   C  D2 # 5  A4  C4  D4 # 6  A5  C5  D5 # 7  A6  C6  D6 # 3  A7  C7  D7  dfs = [df1,df2] df = pd.concat( dfs,axis=1,ignore_index=True)      print df    

and the result is

     0    1    2    3    4    5     0   A0   B0   D0  NaN  NaN  NaN   2   A1   B1   D1  NaN  NaN  NaN     3   A2   B2   D2   A7   C7   D7    4   A3   B3   D3  NaN  NaN  NaN   5  NaN  NaN  NaN   A4   C4   D4   6  NaN  NaN  NaN   A5   C5   D5   7  NaN  NaN  NaN   A6   C6   D6            

Even if I reset index using

 df1.reset_index()      df2.reset_index()  

and then try

pd.concat([df1,df2],axis=1)  

it still produces the same result!

Answer 1

If I understood you correctly, this is what you would like to do.

import pandas as pd  df1 = pd.DataFrame({'A': ['A0', 'A1', 'A2', 'A3'],                     'B': ['B0', 'B1', 'B2', 'B3'],                     'D': ['D0', 'D1', 'D2', 'D3']},                     index=[0, 2, 3,4])  df2 = pd.DataFrame({'A1': ['A4', 'A5', 'A6', 'A7'],                     'C': ['C4', 'C5', 'C6', 'C7'],                     'D2': ['D4', 'D5', 'D6', 'D7']},                     index=[ 4, 5, 6 ,7])   df1.reset_index(drop=True, inplace=True) df2.reset_index(drop=True, inplace=True)  df = pd.concat( [df1, df2], axis=1)  

Which gives:

    A   B   D   A1  C   D2 0   A0  B0  D0  A4  C4  D4 1   A1  B1  D1  A5  C5  D5 2   A2  B2  D2  A6  C6  D6 3   A3  B3  D3  A7  C7  D7 

Actually, I would have expected that df = pd.concat(dfs,axis=1,ignore_index=True) gives the same result.

This is the excellent explanation from jreback:

ignore_index=True ‘ignores’, meaning doesn’t align on the joining axis. it simply pastes them together in the order that they are passed, then reassigns a range for the actual index (e.g. range(len(index))) so the difference between joining on non-overlapping indexes (assume axis=1 in the example), is that with ignore_index=False (the default), you get the concat of the indexes, and with ignore_index=True you get a range.