BUG: fix non-existent variable in NDFrame.interpolate (pandas-dev#29142)

Author: ellequelle

doc/source/whatsnew/v1.0.0.rst

@@ -301,7 +301,6 @@ Performance improvements
 Bug fixes
 ~~~~~~~~~
 
-- Bug in :meth:`DataFrame.to_html` when using ``formatters=<list>`` and ``max_cols`` together. (:issue:`25955`)
 
 Categorical
 ^^^^^^^^^^^
@@ -349,6 +348,7 @@ Numeric
 - Bug in :meth:`DataFrame.quantile` with zero-column :class:`DataFrame` incorrectly raising (:issue:`23925`)
 - :class:`DataFrame` flex inequality comparisons methods (:meth:`DataFrame.lt`, :meth:`DataFrame.le`, :meth:`DataFrame.gt`, :meth: `DataFrame.ge`) with object-dtype and ``complex`` entries failing to raise ``TypeError`` like their :class:`Series` counterparts (:issue:`28079`)
 - Bug in :class:`DataFrame` logical operations (`&`, `|`, `^`) not matching :class:`Series` behavior by filling NA values (:issue:`28741`)
+- Bug in :meth:`DataFrame.interpolate` where specifying axis by name references variable before it is assigned (:issue:`29142`)
 -
 
 Conversion
@@ -409,6 +409,7 @@ I/O
 - Bug in :meth:`DataFrame.read_json` where using ``orient="index"`` would not maintain the order (:issue:`28557`)
 - Bug in :meth:`DataFrame.to_html` where the length of the ``formatters`` argument was not verified (:issue:`28469`)
 - Bug in :meth:`pandas.io.formats.style.Styler` formatting for floating values not displaying decimals correctly (:issue:`13257`)
+- Bug in :meth:`DataFrame.to_html` when using ``formatters=<list>`` and ``max_cols`` together. (:issue:`25955`)
 
 Plotting
 ^^^^^^^^

pandas/core/generic.py

@@ -7048,14 +7048,15 @@ def interpolate(
         """
         inplace = validate_bool_kwarg(inplace, "inplace")
 
+        axis = self._get_axis_number(axis)
+
         if axis == 0:
             ax = self._info_axis_name
             _maybe_transposed_self = self
         elif axis == 1:
             _maybe_transposed_self = self.T
             ax = 1
-        else:
-            _maybe_transposed_self = self
+
         ax = _maybe_transposed_self._get_axis_number(ax)
 
         if _maybe_transposed_self.ndim == 2:

pandas/tests/frame/test_missing.py

@@ -391,13 +391,15 @@ def test_fillna_categorical_nan(self):
         cat = Categorical([np.nan, 2, np.nan])
         val = Categorical([np.nan, np.nan, np.nan])
         df = DataFrame({"cats": cat, "vals": val})
-        res = df.fillna(df.median())
+        with tm.assert_produces_warning(RuntimeWarning):
+            res = df.fillna(df.median())
         v_exp = [np.nan, np.nan, np.nan]
         df_exp = DataFrame({"cats": [2, 2, 2], "vals": v_exp}, dtype="category")
         tm.assert_frame_equal(res, df_exp)
 
         result = df.cats.fillna(np.nan)
         tm.assert_series_equal(result, df.cats)
+
         result = df.vals.fillna(np.nan)
         tm.assert_series_equal(result, df.vals)
 
@@ -876,6 +878,23 @@ def test_interp_rowwise(self):
         expected = df.interpolate()
         assert_frame_equal(result, expected)
 
+    @pytest.mark.parametrize(
+        "axis_name, axis_number",
+        [
+            pytest.param("rows", 0, id="rows_0"),
+            pytest.param("index", 0, id="index_0"),
+            pytest.param("columns", 1, id="columns_1"),
+        ],
+    )
+    def test_interp_axis_names(self, axis_name, axis_number):
+        # GH 29132: test axis names
+        data = {0: [0, np.nan, 6], 1: [1, np.nan, 7], 2: [2, 5, 8]}
+
+        df = DataFrame(data, dtype=np.float64)
+        result = df.interpolate(axis=axis_name, method="linear")
+        expected = df.interpolate(axis=axis_number, method="linear")
+        assert_frame_equal(result, expected)
+
     def test_rowwise_alt(self):
         df = DataFrame(
             {