REFACTOR-#5092: Fix future warning for set_axis function (#5093)

Co-authored-by: Vasily Litvinov <fam1ly.n4me@yandex.ru>
Signed-off-by: Myachev <anatoly.myachev@intel.com>

modin/_compat/pandas_api/latest/base.py

@@ -331,6 +331,8 @@ def sample(
         )
 
     def set_axis(self, labels, axis=0, inplace=no_default, *, copy=no_default):
+        if inplace is True and copy is True:
+            raise ValueError("Cannot specify both inplace=True and copy=True")
         return self._set_axis(
             labels=labels,
             axis=axis,

modin/core/dataframe/pandas/dataframe/dataframe.py

@@ -548,9 +548,7 @@ def _propagate_index_objs(self, axis=None):
         if axis is None:
 
             def apply_idx_objs(df, idx, cols):
-                return df.set_axis(idx, axis="index", inplace=False).set_axis(
-                    cols, axis="columns", inplace=False
-                )
+                return df.set_axis(idx, axis="index").set_axis(cols, axis="columns")
 
             self._partitions = np.array(
                 [
@@ -576,7 +574,7 @@ def apply_idx_objs(df, idx, cols):
         elif axis == 0:
 
             def apply_idx_objs(df, idx):
-                return df.set_axis(idx, axis="index", inplace=False)
+                return df.set_axis(idx, axis="index")
 
             self._partitions = np.array(
                 [
@@ -598,7 +596,7 @@ def apply_idx_objs(df, idx):
         elif axis == 1:
 
             def apply_idx_objs(df, cols):
-                return df.set_axis(cols, axis="columns", inplace=False)
+                return df.set_axis(cols, axis="columns")
 
             self._partitions = np.array(
                 [

modin/core/storage_formats/pandas/query_compiler.py

@@ -1544,9 +1544,9 @@ def infer_objects(self):
     def first_valid_index(self):
         def first_valid_index_builder(df):
             """Get the position of the first valid index in a single partition."""
-            return df.set_axis(
-                pandas.RangeIndex(len(df.index)), axis="index", inplace=False
-            ).apply(lambda df: df.first_valid_index())
+            return df.set_axis(pandas.RangeIndex(len(df.index)), axis="index").apply(
+                lambda df: df.first_valid_index()
+            )
 
         # We get the minimum from each column, then take the min of that to get
         # first_valid_index. The `to_pandas()` here is just for a single value and
@@ -1562,9 +1562,9 @@ def first_valid_index_builder(df):
     def last_valid_index(self):
         def last_valid_index_builder(df):
             """Get the position of the last valid index in a single partition."""
-            return df.set_axis(
-                pandas.RangeIndex(len(df.index)), axis="index", inplace=False
-            ).apply(lambda df: df.last_valid_index())
+            return df.set_axis(pandas.RangeIndex(len(df.index)), axis="index").apply(
+                lambda df: df.last_valid_index()
+            )
 
         # We get the maximum from each column, then take the max of that to get
         # last_valid_index. The `to_pandas()` here is just for a single value and

modin/pandas/base.py

@@ -2206,7 +2206,7 @@ def reorder_levels(self, order, axis=0):  # noqa: PR01, RT01, D200
         """
         axis = self._get_axis_number(axis)
         new_labels = self.axes[axis].reorder_levels(order)
-        return self.set_axis(new_labels, axis=axis, inplace=False)
+        return self.set_axis(new_labels, axis=axis)
 
     def _resample(
         self,
@@ -2533,13 +2533,9 @@ def _set_axis(self, labels, axis, inplace, copy):  # noqa: PR01, RT01, D200
                 stacklevel=2,
             )
             labels, axis = axis, labels
-        if inplace:
-            setattr(self, pandas.DataFrame()._get_axis_name(axis), labels)
-        else:
-            if copy:
-                obj = self.copy()
-            obj.set_axis(labels, axis=axis, inplace=True)
-            return obj
+        obj = self.copy() if copy else self
+        setattr(obj, pandas.DataFrame._get_axis_name(axis), labels)
+        return None if inplace else obj
 
     def _shift(self, periods, freq, axis, fill_value):  # noqa: PR01, RT01, D200
         """
@@ -2745,7 +2741,7 @@ def swaplevel(self, i=-2, j=-1, axis=0):  # noqa: PR01, RT01, D200
         """
         axis = self._get_axis_number(axis)
         idx = self.index if axis == 0 else self.columns
-        return self.set_axis(idx.swaplevel(i, j), axis=axis, inplace=False)
+        return self.set_axis(idx.swaplevel(i, j), axis=axis)
 
     def tail(self, n=5):  # noqa: PR01, RT01, D200
         """
@@ -2940,7 +2936,7 @@ def tshift(self, periods=1, freq=None, axis=0):  # noqa: PR01, RT01, D200
         """
         axis = self._get_axis_number(axis)
         new_labels = self.axes[axis].shift(periods, freq=freq)
-        return self.set_axis(new_labels, axis=axis, inplace=False)
+        return self.set_axis(new_labels, axis=axis)
 
     def transform(self, func, axis=0, *args, **kwargs):  # noqa: PR01, RT01, D200
         """
@@ -2972,7 +2968,7 @@ def tz_convert(self, tz, axis=0, level=None, copy=True):  # noqa: PR01, RT01, D2
         else:
             new_labels = self.axes[axis].tz_convert(tz)
         obj = self.copy() if copy else self
-        return obj.set_axis(new_labels, axis, inplace=not copy)
+        return obj._set_axis(new_labels, axis, inplace=False, copy=copy)
 
     def tz_localize(
         self, tz, axis=0, level=None, copy=True, ambiguous="raise", nonexistent="raise"
@@ -2993,7 +2989,7 @@ def tz_localize(
             )
             .index
         )
-        return self.set_axis(labels=new_labels, axis=axis, inplace=not copy)
+        return self._set_axis(new_labels, axis, inplace=False, copy=copy)
 
     # TODO: uncomment the following lines when #3331 issue will be closed
     # @prepend_to_notes(

modin/pandas/test/dataframe/test_join_sort.py

@@ -348,14 +348,19 @@ def test_sort_index(axis, ascending, na_position):
         for df in [modin_df, pandas_df]:
             df.index = [(i - length / 2) % length for i in range(length)]
 
+    dfs = [modin_df, pandas_df]
+    kw = {"copy": False}
+    if PandasCompatVersion.CURRENT == PandasCompatVersion.PY36:
+        kw = {"inplace": False}
     # Add NaNs to sorted index
-    for df in [modin_df, pandas_df]:
-        sort_index = df.axes[axis]
-        df.set_axis(
+    for idx in range(len(dfs)):
+        sort_index = dfs[idx].axes[axis]
+        dfs[idx] = dfs[idx].set_axis(
             [np.nan if i % 2 == 0 else sort_index[i] for i in range(len(sort_index))],
             axis=axis,
-            inplace=True,
+            **kw,
         )
+    modin_df, pandas_df = dfs
 
     eval_general(
         modin_df,

modin/pandas/test/dataframe/test_map_metadata.py

@@ -1217,12 +1217,15 @@ def test_set_axis(data, axis):
     index = modin_df.columns if x else modin_df.index
     labels = ["{0}_{1}".format(index[i], i) for i in range(modin_df.shape[x])]
 
-    modin_result = modin_df.set_axis(labels, axis=axis, inplace=False)
-    pandas_result = pandas_df.set_axis(labels, axis=axis, inplace=False)
-    df_equals(modin_result, pandas_result)
+    kw = {"copy": True}
+    if PandasCompatVersion.CURRENT == PandasCompatVersion.PY36:
+        kw = {"inplace": False}
+    eval_general(modin_df, pandas_df, lambda df: df.set_axis(labels, axis=axis, **kw))
 
     modin_df_copy = modin_df.copy()
-    modin_df.set_axis(labels, axis=axis, inplace=True)
+    if "copy" in kw:
+        kw["copy"] = False
+    modin_df = modin_df.set_axis(labels, axis=axis, **kw)
 
     # Check that the copy and original are different
     try:
@@ -1232,7 +1235,7 @@ def test_set_axis(data, axis):
     else:
         assert False
 
-    pandas_df.set_axis(labels, axis=axis, inplace=True)
+    pandas_df = pandas_df.set_axis(labels, axis=axis, **kw)
     df_equals(modin_df, pandas_df)