CLN: Have pd.pivot mirror pivot instead of pivot_simple

pandas/core/frame.py

@@ -5346,8 +5346,7 @@ def update(self, other, join='left', overwrite=True, filter_func=None,
     # ----------------------------------------------------------------------
     # Data reshaping
 
-    def pivot(self, index=None, columns=None, values=None):
-        """
+    _shared_docs['pivot'] = """
         Return reshaped DataFrame organized by given index / column values.
 
         Reshape data (produce a "pivot" table) based on column values. Uses
@@ -5449,7 +5448,11 @@ def pivot(self, index=None, columns=None, values=None):
            ...
         ValueError: Index contains duplicate entries, cannot reshape
         """
-        from pandas.core.reshape.reshape import pivot
+
+    @Substitution('')
+    @Appender(_shared_docs['pivot'])
+    def pivot(self, index=None, columns=None, values=None):
+        from pandas.core.reshape.pivot import pivot
         return pivot(self, index=index, columns=columns, values=values)
 
     _shared_docs['pivot_table'] = """

pandas/core/reshape/api.py

@@ -2,7 +2,7 @@
 
 from pandas.core.reshape.concat import concat
 from pandas.core.reshape.melt import melt, lreshape, wide_to_long
-from pandas.core.reshape.reshape import pivot_simple as pivot, get_dummies
+from pandas.core.reshape.reshape import get_dummies
 from pandas.core.reshape.merge import merge, merge_ordered, merge_asof
-from pandas.core.reshape.pivot import pivot_table, crosstab
+from pandas.core.reshape.pivot import pivot_table, pivot, crosstab
 from pandas.core.reshape.tile import cut, qcut

pandas/core/reshape/pivot.py

@@ -10,7 +10,7 @@
 from pandas.core.series import Series
 from pandas.core.groupby import Grouper
 from pandas.core.reshape.util import cartesian_product
-from pandas.core.index import Index, _get_objs_combined_axis
+from pandas.core.index import Index, MultiIndex, _get_objs_combined_axis
 from pandas.compat import range, lrange, zip
 from pandas import compat
 import pandas.core.common as com
@@ -368,6 +368,29 @@ def _convert_by(by):
         by = list(by)
     return by
 
+@Substitution('\ndata : DataFrame')
+@Appender(_shared_docs['pivot'], indents=1)
+def pivot(data, index=None, columns=None, values=None):
+    if values is None:
+        cols = [columns] if index is None else [index, columns]
+        append = index is None
+        indexed = data.set_index(cols, append=append)
+    else:
+        if index is None:
+            index = data.index
+        else:
+            index = data[index]
+        index = MultiIndex.from_arrays([index, data[columns]])
+
+        if is_list_like(values) and not isinstance(values, tuple):
+            # Exclude tuple because it is seen as a single column name
+            indexed = data._constructor(data[values].values, index=index,
+                                        columns=values)
+        else:
+            indexed = data._constructor_sliced(data[values].values,
+                                               index=index)
+    return indexed.unstack(columns)
+
 
 def crosstab(index, columns, values=None, rownames=None, colnames=None,
              aggfunc=None, margins=False, margins_name='All', dropna=True,

pandas/core/reshape/reshape.py

@@ -383,31 +383,6 @@ def _unstack_multiple(data, clocs, fill_value=None):
     return unstacked
 
 
-def pivot(self, index=None, columns=None, values=None):
-    """
-    See DataFrame.pivot
-    """
-    if values is None:
-        cols = [columns] if index is None else [index, columns]
-        append = index is None
-        indexed = self.set_index(cols, append=append)
-    else:
-        if index is None:
-            index = self.index
-        else:
-            index = self[index]
-        index = MultiIndex.from_arrays([index, self[columns]])
-
-        if is_list_like(values) and not isinstance(values, tuple):
-            # Exclude tuple because it is seen as a single column name
-            indexed = self._constructor(self[values].values, index=index,
-                                        columns=values)
-        else:
-            indexed = self._constructor_sliced(self[values].values,
-                                               index=index)
-    return indexed.unstack(columns)
-
-
 def pivot_simple(index, columns, values):
     """
     Produce 'pivot' table based on 3 columns of this DataFrame.