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How to change multi-index to flat column names

I have this dataframe:

import pandas as pd
df = pd.DataFrame(data={'Status' : ['green','green','red','blue','red','yellow','black'],
 'Group' : ['A','A','B','C','A','B','C'],
 'City' : ['Toronto','Montreal','Vancouver','Toronto','Edmonton','Winnipeg','Windsor'],
 'Sales' : [13,6,16,8,4,3,1]})
df.drop('Status',axis=1,inplace=True)
ndf = pd.pivot_table(df,values=['Sales'],index=['City'],columns=['Group'],fill_value=0,margins=False)

It looks like this:

In [321]: ndf
Out[321]:
          Sales
Group         A   B  C
City
Edmonton      4   0  0
Montreal      6   0  0
Toronto      13   0  8
Vancouver     0  16  0
Windsor       0   0  1
Winnipeg      0   3  0

How can I flatten it to become a simple dataframe:

    City          A   B  C
    Edmonton      4   0  0
    Montreal      6   0  0
    Toronto      13   0  8
    Vancouver     0  16  0
    Windsor       0   0  1
    Winnipeg      0   3  0
+3


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3 answers 


ndf = ndf.Sales.reset_index()
ndf

Out[4]: 
Group       City   A   B  C
0       Edmonton   4   0  0
1       Montreal   6   0  0
2        Toronto  13   0  8
3      Vancouver   0  16  0
4        Windsor   0   0  1
5       Winnipeg   0   3  0


+2


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Drop the level from the column index, then drop it:



In [94]: ndf.columns = ndf.columns.droplevel()

In [95]: ndf.columns.name=None

In [96]: ndf
            A   B  C
City
Edmonton    4   0  0
Montreal    6   0  0
Toronto    13   0  8
Vancouver   0  16  0
Windsor     0   0  1
Winnipeg    0   3  0
+1


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You need to reset the columns like this:

ndf.columns = ndf.columns.droplevel()

>>> ndf
Group       A   B  C
City                
Edmonton    4   0  0
Montreal    6   0  0
Toronto    13   0  8
Vancouver   0  16  0
Windsor     0   0  1
Winnipeg    0   3  0
0


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