PERF: groupby is significantly slower for `DatetimeIndex` with timezone about pandas HOT 2 CLOSED

Speed is the same both ways if you do the more idiomatic:

wl_count_peryear = df.resample('A')["values"].count()

The extra time is entirely due to the construction of the PeriodIndex:

In [192]: %time pd.PeriodIndex(df.index, freq='Y')
CPU times: total: 10.4 s
Wall time: 10.4 s

Note that the speed is recovered if you do

df.index.to_period('Y')

but this raises a warning that the timezone information is dropped (since PeriodIndex is not tz-aware).

from pandas.

@Liam3851 thanks a lot for clarifying this. In that case please feel free to close this issue, I will update my code accordingly.

from pandas.