Pandas - Add Column Name to Results of groupby [duplicate]

Question

I would like to add column names to the results of a groupby on a DataFrame in Python 3.6.

I tried this code:

import pandas as pd
d = {'timeIndex': [1, 1, 1, 1, 2, 2, 2], 'isZero': [0,0,0,1,0,0,0]}
df = pd.DataFrame(data=d)
df2 = df.groupby(['timeIndex'])['isZero'].sum()
print(df2)

Result

timeIndex
1    1
2    0
Name: isZero, dtype: int64

It looks like timeIndex is a column heading, but attempts to address a column by name produce exceptions.

df2['timeIndex']
# KeyError: 'timeIndex'

df2['isZero']
# KeyError: 'isZero'

I am looking for this result.

df2 

     timeIndex    isZero
0    1    1
1    2    0

df2['isZero']

0    1
1    0

Answer 1

Method 1:

use the argument as_index = False in your groupby:

df2 = df.groupby(['timeIndex'], as_index=False)['isZero'].sum()

>>> df2
   timeIndex  isZero
0          1       1
1          2       0

>>> df2['isZero']
0    1
1    0
Name: isZero, dtype: int64

Method 2:

You can use to_frame with your desired column name and then reset_index:

df2 = df.groupby(['timeIndex'])['isZero'].sum().to_frame('isZero').reset_index()

>>> df2
   timeIndex  isZero
0          1       1
1          2       0

>>> df2['isZero']
0    1
1    0
Name: isZero, dtype: int64