BUG: DataFrame.pivot not respecting None as column name (#48293)

* BUG: DataFrame.pivot not respecting None as column name

* Add gh ref

* Fix test

* Add comment

* Update doc/source/whatsnew/v1.6.0.rst

Co-authored-by: Matthew Roeschke <[email protected]>

Co-authored-by: Matthew Roeschke <[email protected]>

Author: phofl

doc/source/whatsnew/v1.6.0.rst

@@ -196,6 +196,7 @@ Groupby/resample/rolling
 
 Reshaping
 ^^^^^^^^^
+- Bug in :meth:`DataFrame.pivot` not respecting ``None`` as column name (:issue:`48293`)
 - Bug in :func:`join` when ``left_on`` or ``right_on`` is or includes a :class:`CategoricalIndex` incorrectly raising ``AttributeError`` (:issue:`48464`)
 -
 

pandas/core/frame.py

@@ -8583,7 +8583,9 @@ 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:
+    def pivot(
+        self, index=lib.NoDefault, columns=lib.NoDefault, values=lib.NoDefault
+    ) -> DataFrame:
         from pandas.core.reshape.pivot import pivot
 
         return pivot(self, index=index, columns=columns, values=values)

pandas/core/reshape/pivot.py

@@ -10,6 +10,7 @@
 
 import numpy as np
 
+from pandas._libs import lib
 from pandas._typing import (
     AggFuncType,
     AggFuncTypeBase,
@@ -482,30 +483,37 @@ def _convert_by(by):
 @deprecate_nonkeyword_arguments(version=None, allowed_args=["data"])
 def pivot(
     data: DataFrame,
-    index: IndexLabel | None = None,
-    columns: IndexLabel | None = None,
-    values: IndexLabel | None = None,
+    index: IndexLabel | lib.NoDefault = lib.NoDefault,
+    columns: IndexLabel | lib.NoDefault = lib.NoDefault,
+    values: IndexLabel | lib.NoDefault = lib.NoDefault,
 ) -> DataFrame:
-    if columns is None:
+    if columns is lib.NoDefault:
         raise TypeError("pivot() missing 1 required argument: 'columns'")
 
     columns_listlike = com.convert_to_list_like(columns)
 
+    # If columns is None we will create a MultiIndex level with None as name
+    # which might cause duplicated names because None is the default for
+    # level names
+    data.index.names = [
+        name if name is not None else lib.NoDefault for name in data.index.names
+    ]
+
     indexed: DataFrame | Series
-    if values is None:
-        if index is not None:
+    if values is lib.NoDefault:
+        if index is not lib.NoDefault:
             cols = com.convert_to_list_like(index)
         else:
             cols = []
 
-        append = index is None
+        append = index is lib.NoDefault
         # error: Unsupported operand types for + ("List[Any]" and "ExtensionArray")
         # error: Unsupported left operand type for + ("ExtensionArray")
         indexed = data.set_index(
             cols + columns_listlike, append=append  # type: ignore[operator]
         )
     else:
-        if index is None:
+        if index is lib.NoDefault:
             if isinstance(data.index, MultiIndex):
                 # GH 23955
                 index_list = [
@@ -531,7 +539,12 @@ def pivot(
     # error: Argument 1 to "unstack" of "DataFrame" has incompatible type "Union
     # [List[Any], ExtensionArray, ndarray[Any, Any], Index, Series]"; expected
     # "Hashable"
-    return indexed.unstack(columns_listlike)  # type: ignore[arg-type]
+    result = indexed.unstack(columns_listlike)  # type: ignore[arg-type]
+    result.index.names = [
+        name if name is not lib.NoDefault else None for name in result.index.names
+    ]
+
+    return result
 
 
 def crosstab(

pandas/tests/reshape/test_pivot.py

@@ -2341,7 +2341,7 @@ def test_pivot_index_list_values_none_immutable_args(self):
         )
         index = ["lev1", "lev2"]
         columns = ["lev3"]
-        result = df.pivot(index=index, columns=columns, values=None)
+        result = df.pivot(index=index, columns=columns)
 
         expected = DataFrame(
             np.array(
@@ -2365,3 +2365,51 @@ def test_pivot_index_list_values_none_immutable_args(self):
 
         assert index == ["lev1", "lev2"]
         assert columns == ["lev3"]
+
+    def test_pivot_columns_not_given(self):
+        # GH#48293
+        df = DataFrame({"a": [1], "b": 1})
+        with pytest.raises(TypeError, match="missing 1 required argument"):
+            df.pivot()
+
+    def test_pivot_columns_is_none(self):
+        # GH#48293
+        df = DataFrame({None: [1], "b": 2, "c": 3})
+        result = df.pivot(columns=None)
+        expected = DataFrame({("b", 1): [2], ("c", 1): 3})
+        tm.assert_frame_equal(result, expected)
+
+        result = df.pivot(columns=None, index="b")
+        expected = DataFrame({("c", 1): 3}, index=Index([2], name="b"))
+        tm.assert_frame_equal(result, expected)
+
+        result = df.pivot(columns=None, index="b", values="c")
+        expected = DataFrame({1: 3}, index=Index([2], name="b"))
+        tm.assert_frame_equal(result, expected)
+
+    def test_pivot_index_is_none(self):
+        # GH#48293
+        df = DataFrame({None: [1], "b": 2, "c": 3})
+
+        result = df.pivot(columns="b", index=None)
+        expected = DataFrame({("c", 2): 3}, index=[1])
+        expected.columns.names = [None, "b"]
+        tm.assert_frame_equal(result, expected)
+
+        result = df.pivot(columns="b", index=None, values="c")
+        expected = DataFrame(3, index=[1], columns=Index([2], name="b"))
+        tm.assert_frame_equal(result, expected)
+
+    def test_pivot_values_is_none(self):
+        # GH#48293
+        df = DataFrame({None: [1], "b": 2, "c": 3})
+
+        result = df.pivot(columns="b", index="c", values=None)
+        expected = DataFrame(
+            1, index=Index([3], name="c"), columns=Index([2], name="b")
+        )
+        tm.assert_frame_equal(result, expected)
+
+        result = df.pivot(columns="b", values=None)
+        expected = DataFrame(1, index=[0], columns=Index([2], name="b"))
+        tm.assert_frame_equal(result, expected)

pandas/tests/reshape/test_pivot_multilevel.py

@@ -1,6 +1,8 @@
 import numpy as np
 import pytest
 
+from pandas._libs import lib
+
 import pandas as pd
 from pandas import (
     Index,
@@ -33,7 +35,7 @@
         (
             ["lev4"],
             "lev3",
-            None,
+            lib.NoDefault,
             [
                 [1.0, np.nan, 1.0, np.nan, 0.0, np.nan],
                 [np.nan, 1.0, np.nan, 1.0, np.nan, 1.0],
@@ -70,7 +72,7 @@
         (
             ["lev1", "lev2"],
             "lev3",
-            None,
+            lib.NoDefault,
             [[1, 2, 0, 1], [3, 4, 2, 3], [5, 6, 4, 5], [7, 8, 6, 7]],
             MultiIndex.from_tuples(
                 [("lev4", 1), ("lev4", 2), ("values", 1), ("values", 2)],
@@ -243,7 +245,7 @@ def test_pivot_df_multiindex_index_none():
     )
     df = df.set_index(["index_1", "index_2"])
 
-    result = df.pivot(index=None, columns="label", values="value")
+    result = df.pivot(columns="label", values="value")
     expected = pd.DataFrame(
         [[1.0, np.nan], [np.nan, 2.0], [3.0, np.nan], [np.nan, 4.0]],
         index=df.index,