I am finding an inconsistent output with pandas groupby-resample behavior.
Take this dataframe, in which category A has samples on the first and second day and category B has a sample only on the second day:
df1 = pd.DataFrame(index=pd.DatetimeIndex(
['2022-1-1 1:00','2022-1-2 1:00','2022-1-2 1:00']),
data={'category':['A','A','B']})
# Output:
# category
#2022-01-01 01:00:00 A
#2022-01-02 01:00:00 A
#2022-01-02 01:00:00 B
When I groupby-resample I get a Series with multiindex on category and time:
res1 = df1.groupby('category').resample('1D').size()
#Output:
#category
#A 2022-01-01 1
# 2022-01-02 1
#B 2022-01-02 1
#dtype: int64
But if I add one more data point so that B has a sample on day 1, the return value is a dataframe with single-index in category and columns corresponding to the time bins:
df2 = pd.DataFrame(index=pd.DatetimeIndex(
['2022-1-1 1:00','2022-1-2 1:00','2022-1-2 1:00','2022-1-1 1:00']),
data={'category':['A','A','B','B']})
res2 = df2.groupby('category').resample('1D').size()
# Output:
# 2022-01-01 2022-01-02
# category
# A 1 1
# B 1 1
Is this expected behavior? I reproduced this behavior in pandas 1.4.2 and was unable to find a bug report.
