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BUG: fix astype conversion string -> float #37974

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Merged
merged 11 commits into from
Nov 29, 2020
Merged

BUG: fix astype conversion string -> float #37974

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8d310d6
Special handling of string -> float.
mlondschien Nov 19, 2020
4ec6295
Add tests.
mlondschien Nov 19, 2020
95e8605
Use pd.Series in test.
mlondschien Nov 20, 2020
cce3fde
Add changelog entry.
mlondschien Nov 20, 2020
3fe70c9
Some love for FloatingDtype
mlondschien Nov 22, 2020
7fe9f17
Parametrize dtypes.
mlondschien Nov 22, 2020
db9e708
Use ser and np dtypes.
mlondschien Nov 22, 2020
7d7fd60
Try again.
mlondschien Nov 22, 2020
02b0fa4
Implement suggestion.
mlondschien Nov 23, 2020
f32694e
Merge branch 'master' into issue-37626
mlondschien Nov 23, 2020
3db01b8
Reference issue in changelog.
mlondschien Nov 24, 2020
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1 change: 1 addition & 0 deletions doc/source/whatsnew/v1.2.0.rst
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Expand Up @@ -574,6 +574,7 @@ Conversion
^^^^^^^^^^

- Bug in :meth:`DataFrame.to_dict` with ``orient='records'`` now returns python native datetime objects for datetimelike columns (:issue:`21256`)
- Bug in :meth:`Series.astype` conversion from ``string`` to ``float`` raised in presence of ``pd.NA`` values.
-

Strings
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16 changes: 15 additions & 1 deletion pandas/core/arrays/string_.py
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Expand Up @@ -18,7 +18,8 @@

from pandas.core import ops
from pandas.core.array_algos import masked_reductions
from pandas.core.arrays import IntegerArray, PandasArray
from pandas.core.arrays import FloatingArray, IntegerArray, PandasArray
from pandas.core.arrays.floating import FloatingDtype
from pandas.core.arrays.integer import _IntegerDtype
from pandas.core.construction import extract_array
from pandas.core.indexers import check_array_indexer
Expand Down Expand Up @@ -298,6 +299,19 @@ def astype(self, dtype, copy=True):
arr[mask] = 0
values = arr.astype(dtype.numpy_dtype)
return IntegerArray(values, mask, copy=False)
elif isinstance(dtype, FloatingDtype):
arr = self.copy()
mask = self.isna()
arr[mask] = "0"
values = arr.astype(dtype.numpy_dtype)
return FloatingArray(values, mask, copy=False)
elif np.issubdtype(dtype, np.floating):
arr = self._ndarray.copy()
mask = self.isna()
arr[mask] = 0
values = arr.astype(dtype)
values[mask] = np.nan
return values

return super().astype(dtype, copy)

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12 changes: 12 additions & 0 deletions pandas/tests/arrays/string_/test_string.py
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Expand Up @@ -226,6 +226,18 @@ def test_astype_int():
tm.assert_extension_array_equal(result, expected)


@pytest.mark.parametrize(
"dtype", ["float", "float32", "Float32", "Float64", np.single, np.double]
)
def test_astype_float(dtype):
# Don't compare arrays (37974)
ser = pd.Series(["1.1", pd.NA, "3.3"], dtype="string")

result = ser.astype(dtype)
expected = pd.Series([1.1, np.nan, 3.3], dtype=dtype)
tm.assert_series_equal(result, expected)


@pytest.mark.parametrize("skipna", [True, False])
@pytest.mark.xfail(reason="Not implemented StringArray.sum")
def test_reduce(skipna):
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