WIP: Panel Transpose Cleanup

pandas/compat/numpy/function.py

@@ -282,23 +282,6 @@ def validate_take_with_convert(convert, args, kwargs):
                                      method='both', max_fname_arg_count=0)
 
 
-def validate_transpose_for_generic(inst, kwargs):
-    try:
-        validate_transpose(tuple(), kwargs)
-    except ValueError as e:
-        klass = type(inst).__name__
-        msg = str(e)
-
-        # the Panel class actual relies on the 'axes' parameter if called
-        # via the 'numpy' library, so let's make sure the error is specific
-        # about saying that the parameter is not supported for particular
-        # implementations of 'transpose'
-        if "the 'axes' parameter is not supported" in msg:
-            msg += " for {klass} instances".format(klass=klass)
-
-        raise ValueError(msg)
-
-
 def validate_window_func(name, args, kwargs):
     numpy_args = ('axis', 'dtype', 'out')
     msg = ("numpy operations are not "

pandas/core/frame.py

@@ -2545,7 +2545,7 @@ def memory_usage(self, index=True, deep=False):
                             index=['Index']).append(result)
         return result
 
-    def transpose(self, *args, **kwargs):
+    def transpose(self, copy=False):
         """
         Transpose index and columns.
 
@@ -2558,9 +2558,6 @@ def transpose(self, *args, **kwargs):
         copy : bool, default False
             If True, the underlying data is copied. Otherwise (default), no
             copy is made if possible.
-        *args, **kwargs
-            Additional keywords have no effect but might be accepted for
-            compatibility with numpy.
 
         Returns
         -------
@@ -2640,8 +2637,7 @@ def transpose(self, *args, **kwargs):
         1    object
         dtype: object
         """
-        nv.validate_transpose(args, dict())
-        return super(DataFrame, self).transpose(1, 0, **kwargs)
+        return super().transpose(copy)
 
     T = property(transpose)
 

pandas/core/generic.py

@@ -306,9 +306,8 @@ def _construct_axes_from_arguments(
         supplied; useful to distinguish when a user explicitly passes None
         in scenarios where None has special meaning.
         """
-
-        # construct the args
         args = list(args)
+        # construct the args
         for a in self._AXIS_ORDERS:
 
             # if we have an alias for this axis
@@ -651,32 +650,24 @@ def _set_axis(self, axis, labels):
         self._data.set_axis(axis, labels)
         self._clear_item_cache()
 
-    def transpose(self, *args, **kwargs):
+    def transpose(self, copy, valid_axes=[1, 0]):
         """
         Permute the dimensions of the %(klass)s
 
         Parameters
         ----------
-        args : %(args_transpose)s
         copy : boolean, default False
             Make a copy of the underlying data. Mixed-dtype data will
             always result in a copy
-        **kwargs
-            Additional keyword arguments will be passed to the function.
+        valid_axes : list of str or int
+            Names / aliases for axes to be transposed.
 
         Returns
         -------
         y : same as input
-
-        Examples
-        --------
-        >>> p.transpose(2, 0, 1)
-        >>> p.transpose(2, 0, 1, copy=True)
         """
-
         # construct the args
-        axes, kwargs = self._construct_axes_from_arguments(args, kwargs,
-                                                           require_all=True)
+        axes, kwargs = self._construct_axes_from_arguments(valid_axes, dict())
         axes_names = tuple(self._get_axis_name(axes[a])
                            for a in self._AXIS_ORDERS)
         axes_numbers = tuple(self._get_axis_number(axes[a])
@@ -689,10 +680,9 @@ def transpose(self, *args, **kwargs):
         new_axes = self._construct_axes_dict_from(self, [self._get_axis(x)
                                                          for x in axes_names])
         new_values = self.values.transpose(axes_numbers)
-        if kwargs.pop('copy', None) or (len(args) and args[-1]):
+        if copy:
             new_values = new_values.copy()
 
-        nv.validate_transpose_for_generic(self, kwargs)
         return self._constructor(new_values, **new_axes).__finalize__(self)
 
     def swapaxes(self, axis1, axis2, copy=True):

pandas/core/panel.py

@@ -1264,25 +1264,6 @@ def reindex_axis(self, labels, axis=0, method=None, level=None, copy=True,
                                                copy=copy, limit=limit,
                                                fill_value=fill_value)
 
-    @Substitution(**_shared_doc_kwargs)
-    @Appender(NDFrame.transpose.__doc__)
-    def transpose(self, *args, **kwargs):
-        # check if a list of axes was passed in instead as a
-        # single *args element
-        if (len(args) == 1 and hasattr(args[0], '__iter__') and
-                not is_string_like(args[0])):
-            axes = args[0]
-        else:
-            axes = args
-
-        if 'axes' in kwargs and axes:
-            raise TypeError("transpose() got multiple values for "
-                            "keyword argument 'axes'")
-        elif not axes:
-            axes = kwargs.pop('axes', ())
-
-        return super(Panel, self).transpose(*axes, **kwargs)
-
     @Substitution(**_shared_doc_kwargs)
     @Appender(NDFrame.fillna.__doc__)
     def fillna(self, value=None, method=None, axis=None, inplace=False,