Skip to content

ENH: implement FloatingArray.round() #38866

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

Closed
wants to merge 10 commits into from
Closed

ENH: implement FloatingArray.round() #38866

Show file tree
Hide file tree
Changes from 3 commits
Commits
Show all changes
10 commits
Select commit Hold shift + click to select a range
1df9bf7
add test for nullable float
arw2019 Dec 31, 2020
192ebad
implement round method for FloatingArray
arw2019 Dec 31, 2020
6403026
use pytest fixture
arw2019 Dec 31, 2020
253d279
review: rewriting using _apply
arw2019 Jan 4, 2021
3e0d605
Merge branch 'master' of https://github.com/pandas-dev/pandas into GH…
arw2019 Jan 4, 2021
fe19597
remove explicit FloatingArray reference from _apply
arw2019 Jan 4, 2021
b557a50
move _apply, round to NumericArray
arw2019 Jan 4, 2021
85e6d4f
move _apply, round to NumericArray
arw2019 Jan 4, 2021
f79c0cd
typing, consistency with Series.round
arw2019 Jan 4, 2021
d1cd6d8
whatsnew
arw2019 Jan 4, 2021
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
8 changes: 8 additions & 0 deletions pandas/core/arrays/floating.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -410,6 +410,14 @@ def max(self, *, skipna=True, **kwargs):
nv.validate_max((), kwargs)
return super()._reduce("max", skipna=skipna)

def round(self, decimals=0):
Copy link
Contributor

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

should do this generically (and move to NumericArray), e.g. something like

def round(self, decimals=0):
     return self._apply(np.round, decimals=decimals)

where _apply handles the masking & recasting. I think we discussed similar in .to_numeric

Copy link
Contributor

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

or event better

round = _apply_function(np.round, decimals=0, "nice doc-string here")

Copy link
Member Author

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

If we're going with the second way (may as well) would _apply_function be method on NumericArray (versus a module level function)?

values = self._data[~self._mask]
values = np.round(values, decimals)

data = np.zeros(self._data.shape)
data[~self._mask] = values
return FloatingArray(data, self._mask)

def _maybe_mask_result(self, result, mask, other, op_name: str):
"""
Parameters
Expand Down
20 changes: 14 additions & 6 deletions pandas/tests/series/methods/test_round.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -35,15 +35,23 @@ def test_round_numpy_with_nan(self):
expected = Series([2.0, np.nan, 0.0])
tm.assert_series_equal(result, expected)

def test_round_builtin(self):
ser = Series([1.123, 2.123, 3.123], index=range(3))
result = round(ser)
expected_rounded0 = Series([1.0, 2.0, 3.0], index=range(3))
def test_round_builtin(self, any_float_allowed_nullable_dtype):
ser = Series(
[1.123, 2.123, 3.123],
index=range(3),
dtype=any_float_allowed_nullable_dtype,
)
result = round(ser).astype(any_float_allowed_nullable_dtype)
expected_rounded0 = Series(
[1.0, 2.0, 3.0], index=range(3), dtype=any_float_allowed_nullable_dtype
)
tm.assert_series_equal(result, expected_rounded0)

decimals = 2
expected_rounded = Series([1.12, 2.12, 3.12], index=range(3))
result = round(ser, decimals)
expected_rounded = Series(
[1.12, 2.12, 3.12], index=range(3), dtype=any_float_allowed_nullable_dtype
)
result = round(ser, decimals).astype(any_float_allowed_nullable_dtype)
tm.assert_series_equal(result, expected_rounded)

@pytest.mark.parametrize("method", ["round", "floor", "ceil"])
Expand Down