PERF: groupby nth w/o dropna can use the cython routines #7569
Labels
Error Reporting
Incorrect or improved errors from pandas
Groupby
Performance
Memory or execution speed performance
see #7568
nth
is a fair bit slower thanfirst/last
which are calling cython routines. In a case where you don'tdropna
you can simply call the cython aggregation routinesgroup_last_object/group_nth_object
fromalgos.pyx
togenerate_code.py
(simply movegroup_last/group_nth
from thegroupby
template to the same asgroup_count
template, which generates the object dtypes)ValueError buffer type mismatch
in the cython trials. This is generated when a built in routine tries to use the cython routines, but the function is not defined (but it SHOULD be defined for all dtypes), so this is a trapped bug (in which case it goes to the python path).The text was updated successfully, but these errors were encountered: