Inzynierka_Gwiazdy/machine_learning/Lib/site-packages/pandas/_libs/reduction.pyx
2023-09-20 19:46:58 +02:00

34 lines
1.1 KiB
Cython

import numpy as np
cimport numpy as cnp
cnp.import_array()
from pandas._libs.util cimport is_array
cdef cnp.dtype _dtype_obj = np.dtype("object")
cpdef check_result_array(object obj, object dtype):
# Our operation is supposed to be an aggregation/reduction. If
# it returns an ndarray, this likely means an invalid operation has
# been passed. See test_apply_without_aggregation, test_agg_must_agg
if is_array(obj):
if dtype != _dtype_obj:
# If it is object dtype, the function can be a reduction/aggregation
# and still return an ndarray e.g. test_agg_over_numpy_arrays
raise ValueError("Must produce aggregated value")
cpdef inline extract_result(object res):
""" extract the result object, it might be a 0-dim ndarray
or a len-1 0-dim, or a scalar """
if hasattr(res, "_values"):
# Preserve EA
res = res._values
if res.ndim == 1 and len(res) == 1:
# see test_agg_lambda_with_timezone, test_resampler_grouper.py::test_apply
res = res[0]
return res