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CLN: remove unused out kwd from take functions #40934

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Apr 20, 2021
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CLN: remove unused out kwd from take functions #40934

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38 changes: 15 additions & 23 deletions pandas/core/array_algos/take.py
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Original file line number Diff line number Diff line change
Expand Up @@ -100,14 +100,13 @@ def take_nd(
return arr.take(indexer, fill_value=fill_value, allow_fill=allow_fill)

arr = np.asarray(arr)
return _take_nd_ndarray(arr, indexer, axis, None, fill_value, allow_fill)
return _take_nd_ndarray(arr, indexer, axis, fill_value, allow_fill)


def _take_nd_ndarray(
arr: np.ndarray,
indexer,
axis: int,
out: np.ndarray | None,
fill_value,
allow_fill: bool,
) -> np.ndarray:
Expand All @@ -119,7 +118,7 @@ def _take_nd_ndarray(
indexer = ensure_platform_int(indexer)

indexer, dtype, fill_value, mask_info = _take_preprocess_indexer_and_fill_value(
arr, indexer, out, fill_value, allow_fill
arr, indexer, fill_value, allow_fill
)

flip_order = False
Expand All @@ -129,23 +128,20 @@ def _take_nd_ndarray(
if flip_order:
arr = arr.T
axis = arr.ndim - axis - 1
if out is not None:
out = out.T

# at this point, it's guaranteed that dtype can hold both the arr values
# and the fill_value
if out is None:
out_shape_ = list(arr.shape)
out_shape_[axis] = len(indexer)
out_shape = tuple(out_shape_)
if arr.flags.f_contiguous and axis == arr.ndim - 1:
# minor tweak that can make an order-of-magnitude difference
# for dataframes initialized directly from 2-d ndarrays
# (s.t. df.values is c-contiguous and df._mgr.blocks[0] is its
# f-contiguous transpose)
out = np.empty(out_shape, dtype=dtype, order="F")
else:
out = np.empty(out_shape, dtype=dtype)
out_shape_ = list(arr.shape)
out_shape_[axis] = len(indexer)
out_shape = tuple(out_shape_)
if arr.flags.f_contiguous and axis == arr.ndim - 1:
# minor tweak that can make an order-of-magnitude difference
# for dataframes initialized directly from 2-d ndarrays
# (s.t. df.values is c-contiguous and df._mgr.blocks[0] is its
# f-contiguous transpose)
out = np.empty(out_shape, dtype=dtype, order="F")
else:
out = np.empty(out_shape, dtype=dtype)

func = _get_take_nd_function(
arr.ndim, arr.dtype, out.dtype, axis=axis, mask_info=mask_info
Expand Down Expand Up @@ -190,7 +186,7 @@ def take_1d(
return arr.take(indexer)

indexer, dtype, fill_value, mask_info = _take_preprocess_indexer_and_fill_value(
arr, indexer, None, fill_value, True
arr, indexer, fill_value, True
)

# at this point, it's guaranteed that dtype can hold both the arr values
Expand Down Expand Up @@ -516,7 +512,6 @@ def _take_2d_multi_object(
def _take_preprocess_indexer_and_fill_value(
arr: np.ndarray,
indexer: np.ndarray,
out: np.ndarray | None,
fill_value,
allow_fill: bool,
):
Expand All @@ -534,10 +529,7 @@ def _take_preprocess_indexer_and_fill_value(
mask = indexer == -1
needs_masking = mask.any()
mask_info = mask, needs_masking
if needs_masking:
if out is not None and out.dtype != dtype:
raise TypeError("Incompatible type for fill_value")
else:
if not needs_masking:
# if not, then depromote, set fill_value to dummy
# (it won't be used but we don't want the cython code
# to crash when trying to cast it to dtype)
Expand Down