Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

CLN: remove ensure_int_or_float #41011

Merged
merged 1 commit into from
Apr 19, 2021
Merged

CLN: remove ensure_int_or_float #41011

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
45 changes: 0 additions & 45 deletions pandas/core/dtypes/common.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -128,51 +128,6 @@ def ensure_str(value: Union[bytes, Any]) -> str:
return value


def ensure_int_or_float(arr: ArrayLike, copy: bool = False) -> np.ndarray:
"""
Ensure that an dtype array of some integer dtype
has an int64 dtype if possible.
If it's not possible, potentially because of overflow,
convert the array to float64 instead.

Parameters
----------
arr : array-like
The array whose data type we want to enforce.
copy: bool
Whether to copy the original array or reuse
it in place, if possible.

Returns
-------
out_arr : The input array cast as int64 if
possible without overflow.
Otherwise the input array cast to float64.

Notes
-----
If the array is explicitly of type uint64 the type
will remain unchanged.
"""
# TODO: GH27506 potential bug with ExtensionArrays
try:
# error: Unexpected keyword argument "casting" for "astype"
return arr.astype("int64", copy=copy, casting="safe") # type: ignore[call-arg]
except TypeError:
pass
try:
# error: Unexpected keyword argument "casting" for "astype"
return arr.astype("uint64", copy=copy, casting="safe") # type: ignore[call-arg]
except TypeError:
if is_extension_array_dtype(arr.dtype):
# pandas/core/dtypes/common.py:168: error: Item "ndarray" of
# "Union[ExtensionArray, ndarray]" has no attribute "to_numpy" [union-attr]
return arr.to_numpy( # type: ignore[union-attr]
dtype="float64", na_value=np.nan
)
return arr.astype("float64", copy=copy)


def ensure_python_int(value: Union[int, np.integer]) -> int:
"""
Ensure that a value is a python int.
Expand Down
9 changes: 5 additions & 4 deletions pandas/core/groupby/ops.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -43,7 +43,6 @@
from pandas.core.dtypes.common import (
ensure_float64,
ensure_int64,
ensure_int_or_float,
ensure_platform_int,
is_bool_dtype,
is_categorical_dtype,
Expand Down Expand Up @@ -582,7 +581,7 @@ def _ea_wrap_cython_operation(

elif is_integer_dtype(values.dtype) or is_bool_dtype(values.dtype):
# IntegerArray or BooleanArray
values = ensure_int_or_float(values)
values = values.to_numpy("float64", na_value=np.nan)
res_values = self._cython_operation(
kind, values, how, axis, min_count, **kwargs
)
Expand Down Expand Up @@ -660,9 +659,11 @@ def _cython_operation(
values = values.view("int64")
is_numeric = True
elif is_bool_dtype(dtype):
values = ensure_int_or_float(values)
values = values.astype("int64")
elif is_integer_dtype(dtype):
values = ensure_int_or_float(values)
# e.g. uint8 -> uint64, int16 -> int64
dtype = dtype.kind + "8"
values = values.astype(dtype, copy=False)
elif is_numeric:
if not is_complex_dtype(dtype):
values = ensure_float64(values)
Expand Down