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DEPR: Deprecate positional arguments in pivot (pandas-dev#48301)
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phofl authored and noatamir committed Nov 9, 2022
1 parent ca5cd56 commit 079ef5f
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Showing 4 changed files with 15 additions and 9 deletions.
1 change: 1 addition & 0 deletions doc/source/whatsnew/v1.5.0.rst
Original file line number Diff line number Diff line change
Expand Up @@ -911,6 +911,7 @@ Other Deprecations
- Deprecated :attr:`Timedelta.freq` and :attr:`Timedelta.is_populated` (:issue:`46430`)
- Deprecated :attr:`Timedelta.delta` (:issue:`46476`)
- Deprecated passing arguments as positional in :meth:`DataFrame.any` and :meth:`Series.any` (:issue:`44802`)
- Deprecated passing positional arguments to :meth:`DataFrame.pivot` and :func:`pivot` except ``data`` (:issue:`30228`)
- Deprecated the methods :meth:`DataFrame.mad`, :meth:`Series.mad`, and the corresponding groupby methods (:issue:`11787`)
- Deprecated positional arguments to :meth:`Index.join` except for ``other``, use keyword-only arguments instead of positional arguments (:issue:`46518`)
- Deprecated positional arguments to :meth:`StringMethods.rsplit` and :meth:`StringMethods.split` except for ``pat``, use keyword-only arguments instead of positional arguments (:issue:`47423`)
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1 change: 1 addition & 0 deletions pandas/core/frame.py
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Expand Up @@ -8580,6 +8580,7 @@ def groupby(

@Substitution("")
@Appender(_shared_docs["pivot"])
@deprecate_nonkeyword_arguments(version=None, allowed_args=["self"])
def pivot(self, index=None, columns=None, values=None) -> DataFrame:
from pandas.core.reshape.pivot import pivot

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2 changes: 2 additions & 0 deletions pandas/core/reshape/pivot.py
Original file line number Diff line number Diff line change
Expand Up @@ -19,6 +19,7 @@
from pandas.util._decorators import (
Appender,
Substitution,
deprecate_nonkeyword_arguments,
)

from pandas.core.dtypes.cast import maybe_downcast_to_dtype
Expand Down Expand Up @@ -478,6 +479,7 @@ def _convert_by(by):

@Substitution("\ndata : DataFrame")
@Appender(_shared_docs["pivot"], indents=1)
@deprecate_nonkeyword_arguments(version=None, allowed_args=["data"])
def pivot(
data: DataFrame,
index: IndexLabel | None = None,
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20 changes: 11 additions & 9 deletions pandas/tests/reshape/test_pivot.py
Original file line number Diff line number Diff line change
Expand Up @@ -480,9 +480,11 @@ def test_pivot_index_with_nan(self, method):
}
)
if method:
result = df.pivot("a", "b", "c")
with tm.assert_produces_warning(FutureWarning):
result = df.pivot("a", columns="b", values="c")
else:
result = pd.pivot(df, "a", "b", "c")
with tm.assert_produces_warning(FutureWarning):
result = pd.pivot(df, "a", columns="b", values="c")
expected = DataFrame(
[
[nan, nan, 17, nan],
Expand All @@ -494,7 +496,7 @@ def test_pivot_index_with_nan(self, method):
columns=Index(["C1", "C2", "C3", "C4"], name="b"),
)
tm.assert_frame_equal(result, expected)
tm.assert_frame_equal(df.pivot("b", "a", "c"), expected.T)
tm.assert_frame_equal(df.pivot(index="b", columns="a", values="c"), expected.T)

@pytest.mark.parametrize("method", [True, False])
def test_pivot_index_with_nan_dates(self, method):
Expand All @@ -510,18 +512,18 @@ def test_pivot_index_with_nan_dates(self, method):
df.loc[1, "b"] = df.loc[4, "b"] = np.nan

if method:
pv = df.pivot("a", "b", "c")
pv = df.pivot(index="a", columns="b", values="c")
else:
pv = pd.pivot(df, "a", "b", "c")
pv = pd.pivot(df, index="a", columns="b", values="c")
assert pv.notna().values.sum() == len(df)

for _, row in df.iterrows():
assert pv.loc[row["a"], row["b"]] == row["c"]

if method:
result = df.pivot("b", "a", "c")
result = df.pivot(index="b", columns="a", values="c")
else:
result = pd.pivot(df, "b", "a", "c")
result = pd.pivot(df, index="b", columns="a", values="c")
tm.assert_frame_equal(result, pv.T)

@pytest.mark.filterwarnings("ignore:Timestamp.freq is deprecated:FutureWarning")
Expand Down Expand Up @@ -2275,11 +2277,11 @@ def test_pivot_duplicates(self):
}
)
with pytest.raises(ValueError, match="duplicate entries"):
data.pivot("a", "b", "c")
data.pivot(index="a", columns="b", values="c")

def test_pivot_empty(self):
df = DataFrame(columns=["a", "b", "c"])
result = df.pivot("a", "b", "c")
result = df.pivot(index="a", columns="b", values="c")
expected = DataFrame()
tm.assert_frame_equal(result, expected, check_names=False)

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