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TST: Tests for replace method when column contains pd.NA (#47480) #49805

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TST: Tests for replace method when column contains pd.NA (#47480) #49805

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4bc0e80
TST: Tests for replace method when column contains pd.NA (#47480)
Nov 20, 2022
5094008
Merge branch 'pandas-dev:main' into tests-replace
Nov 21, 2022
c30bd01
BUG: Replace method raising error in col with pd.NA (#47480)
Nov 21, 2022
febffcb
BUG: Replace method raising error in col with pd.NA (#47480)
Nov 21, 2022
6f90ac3
BUG: Replace method raising error in col with pd.NA (#47480)
Nov 22, 2022
44331b4
BUG: Replace method raising error in col with pd.NA (#47480)
Nov 23, 2022
542c4d6
Merge branch 'pandas-dev:main' into tests-replace
Dec 2, 2022
6b2dd72
BUG: Check if array is of numpy type with NAs on mask_missing func (#…
Dec 13, 2022
b2ccbee
Merge branch 'tests-replace' of https://github.com/vs-araujo/pandas i…
Dec 13, 2022
2d8910c
BUG: Check if array has numpy type with NAs on mask_missing func (#47…
Dec 13, 2022
62b3168
Merge branch 'tests-replace' of https://github.com/vs-araujo/pandas i…
Dec 13, 2022
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15 changes: 5 additions & 10 deletions pandas/core/missing.py
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Original file line number Diff line number Diff line change
Expand Up @@ -31,7 +31,6 @@
from pandas.core.dtypes.cast import infer_dtype_from
from pandas.core.dtypes.common import (
is_array_like,
is_numeric_v_string_like,
needs_i8_conversion,
)
from pandas.core.dtypes.missing import (
Expand Down Expand Up @@ -89,15 +88,11 @@ def mask_missing(arr: ArrayLike, values_to_mask) -> npt.NDArray[np.bool_]:
# GH 21977
mask = np.zeros(arr.shape, dtype=bool)
for x in nonna:
if is_numeric_v_string_like(arr, x):
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pls keep this check. it'll avoid some warnings and will be a fastpath

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I'd prefer if you pre-compute a mask in case we have object dtype before entering the loop.
Then you can add another if clause to only update the values that are not na

new_mask[~object_na_mask] = arr[~object_na_mask] == x

# GH#29553 prevent numpy deprecation warnings
pass
else:
new_mask = arr == x
if not isinstance(new_mask, np.ndarray):
# usually BooleanArray
new_mask = new_mask.to_numpy(dtype=bool, na_value=False)
mask |= new_mask
# GH#47480
new_mask = np.vectorize(
lambda value: False if (isna(value) or value != x) else True
)(arr)
mask |= new_mask

if na_mask.any():
mask |= isna(arr)
Expand Down
8 changes: 8 additions & 0 deletions pandas/tests/frame/methods/test_replace.py
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Expand Up @@ -1503,6 +1503,14 @@ def test_replace_value_none_dtype_numeric(self, val):
result = df.replace({val: None})
tm.assert_frame_equal(result, expected)

@pytest.mark.parametrize("dtype", [None, "Int64", "Float64"])
def test_replace_df_containing_na(self, dtype):
# GH#47480
df = DataFrame({"A": [4, 1, pd.NA], "B": [1, 3, 2]}, dtype=dtype)
df.replace(to_replace=1, value=100, inplace=True)
expected = DataFrame({"A": [4, 100, pd.NA], "B": [100, 3, 2]}, dtype=dtype)
tm.assert_frame_equal(df, expected)


class TestDataFrameReplaceRegex:
@pytest.mark.parametrize(
Expand Down
8 changes: 8 additions & 0 deletions pandas/tests/series/methods/test_replace.py
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Expand Up @@ -674,3 +674,11 @@ def test_replace_value_none_dtype_numeric(self, val):
result = ser.replace(val, None)
expected = pd.Series([1, None], dtype=object)
tm.assert_series_equal(result, expected)

@pytest.mark.parametrize("dtype", [None, "Int64", "Float64"])
def test_replace_series_containing_na(self, dtype):
# GH#47480
df = pd.Series([4, 1, pd.NA, 1], dtype=dtype)
df.replace(to_replace=1, value=100, inplace=True)
expected = pd.Series([4, 100, pd.NA, 100], dtype=dtype)
tm.assert_series_equal(df, expected)