How to prevent resample -> aggregate from dropping columns?

Question

Code

df = pd.DataFrame(
    data = {'A': [1, 1, 2], 'B': [None, None, None]},
    index = pd.DatetimeIndex([
        '1990-01-01 00:00:00',
        '1990-01-01 12:00:00',
        '1990-01-02 12:00:00'
    ])
)
print(df.resample('1d').aggregate('mean'))

Output

              A
1990-01-01  1.0
1990-01-02  2.0

Desired output

              A     B
1990-01-01  1.0  None 
1990-01-02  2.0  None

I don’t care whether there’s None, np.nan or pd.NA in column B of the output, the problem is that B is dropped.

Asked By: actual_panda

||

Source

Answer 1

resample will drop the non numeric columns when using a numeric aggregation. You can reindex after aggregation:

df.resample('1d').aggregate('mean').reindex(df.columns, axis=1)

output:

              A   B
1990-01-01  1.0 NaN
1990-01-02  2.0 NaN

Answered By: mozway

Answer 2

df.resample('d').agg({'A':'mean','B':'mean'})

          A   B
1990-01-01  1.0 NaN
1990-01-02  2.0 NaN

Answered By: G.G

How to prevent resample -> aggregate from dropping columns?

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