BUG: Make DataFrame not hardcode it's own constructor in the code. Issue

Changed all occurrences of `return DataFrame` to `return
self._constructor` and changed the latter to return `self.__class__`
rather than `DataFrame` by default.

Also made static methods like `DataFrame.from_dict` work on the
`cls` passed to them rather than on hard-coded `DataFrame`.

This is a minimal quick win on the cases described in Issue pandas-dev#2859.
A formal approach to make classes friendly to subclassing might still be
needed, see discussion in the case.

Author: lukauskas

pandas/core/frame.py

@@ -565,7 +565,7 @@ def axes(self):
 
     @property
     def _constructor(self):
-        return DataFrame
+        return self.__class__
 
     # Fancy indexing
     _ix = None
@@ -855,15 +855,15 @@ def dot(self, other):
                                 (lvals.shape, rvals.shape))
 
         if isinstance(other, DataFrame):
-            return DataFrame(np.dot(lvals, rvals),
+            return self._constructor(np.dot(lvals, rvals),
                              index=left.index,
                              columns=other.columns)
         elif isinstance(other, Series):
             return Series(np.dot(lvals, rvals), index=left.index)
         elif isinstance(rvals, np.ndarray):
             result = np.dot(lvals, rvals)
             if result.ndim == 2:
-                return DataFrame(result, index=left.index)
+                return self._constructor(result, index=left.index)
             else:
                 return Series(result, index=left.index)
         else:  # pragma: no cover
@@ -902,7 +902,7 @@ def from_dict(cls, data, orient='columns', dtype=None):
         elif orient != 'columns':  # pragma: no cover
             raise ValueError('only recognize index or columns for orient')
 
-        return DataFrame(data, index=index, columns=columns, dtype=dtype)
+        return cls(data, index=index, columns=columns, dtype=dtype)
 
     def to_dict(self, outtype='dict'):
         """
@@ -969,15 +969,15 @@ def from_records(cls, data, index=None, exclude=None, columns=None,
 
         if com.is_iterator(data):
             if nrows == 0:
-                return DataFrame()
+                return cls()
 
             try:
                 if py3compat.PY3:
                     first_row = next(data)
                 else:
                     first_row = data.next()
             except StopIteration:
-                return DataFrame(index=index, columns=columns)
+                return cls(index=index, columns=columns)
 
             dtype = None
             if hasattr(first_row, 'dtype') and first_row.dtype.names:
@@ -1067,7 +1067,7 @@ def from_records(cls, data, index=None, exclude=None, columns=None,
         mgr = _arrays_to_mgr(arrays, arr_columns, result_index,
                              columns)
 
-        return DataFrame(mgr)
+        return cls(mgr)
 
     def to_records(self, index=True, convert_datetime64=True):
         """
@@ -2061,7 +2061,7 @@ def _slice(self, slobj, axis=0):
     def _box_item_values(self, key, values):
         items = self.columns[self.columns.get_loc(key)]
         if values.ndim == 2:
-            return DataFrame(values.T, columns=items, index=self.index)
+            return self._constructor(values.T, columns=items, index=self.index)
         else:
             return Series.from_array(values, index=self.index, name=items)
 
@@ -2647,7 +2647,7 @@ def _reindex_multi(self, new_index, new_columns, copy, fill_value):
         if row_indexer is not None and col_indexer is not None:
             new_values = com.take_2d_multi(self.values, row_indexer,
                                            col_indexer, fill_value=fill_value)
-            return DataFrame(new_values, index=new_index, columns=new_columns)
+            return self._constructor(new_values, index=new_index, columns=new_columns)
         elif row_indexer is not None:
             return self._reindex_with_indexers(new_index, row_indexer,
                                                None, None, copy, fill_value)
@@ -2695,7 +2695,7 @@ def _reindex_with_indexers(self, index, row_indexer, columns, col_indexer,
         if copy and new_data is self._data:
             new_data = new_data.copy()
 
-        return DataFrame(new_data)
+        return self._constructor(new_data)
 
     def reindex_like(self, other, method=None, copy=True, limit=None):
         """
@@ -2938,7 +2938,7 @@ def take(self, indices, axis=0):
         if self._is_mixed_type:
             if axis == 0:
                 new_data = self._data.take(indices, axis=1)
-                return DataFrame(new_data)
+                return self._constructor(new_data)
             else:
                 new_columns = self.columns.take(indices)
                 return self.reindex(columns=new_columns)
@@ -2952,7 +2952,7 @@ def take(self, indices, axis=0):
             else:
                 new_columns = self.columns.take(indices)
                 new_index = self.index
-            return DataFrame(new_values, index=new_index,
+            return self._constructor(new_values, index=new_index,
                              columns=new_columns)
 
     #----------------------------------------------------------------------
@@ -4191,7 +4191,7 @@ def _apply_raw(self, func, axis):
 
         # TODO: mixed type case
         if result.ndim == 2:
-            return DataFrame(result, index=self.index,
+            return self._constructor(result, index=self.index,
                              columns=self.columns)
         else:
             return Series(result, index=self._get_agg_axis(axis))
@@ -4622,7 +4622,7 @@ def describe(self, percentile_width=50):
         numdata = self._get_numeric_data()
 
         if len(numdata.columns) == 0:
-            return DataFrame(dict((k, v.describe())
+            return self._constructor(dict((k, v.describe())
                                   for k, v in self.iteritems()),
                              columns=self.columns)
 
@@ -5006,7 +5006,7 @@ def _get_agg_axis(self, axis_num):
     def _get_numeric_data(self):
         if self._is_mixed_type:
             num_data = self._data.get_numeric_data()
-            return DataFrame(num_data, index=self.index, copy=False)
+            return self._constructor(num_data, index=self.index, copy=False)
         else:
             if (self.values.dtype != np.object_ and
                     not issubclass(self.values.dtype.type, np.datetime64)):
@@ -5017,7 +5017,7 @@ def _get_numeric_data(self):
     def _get_bool_data(self):
         if self._is_mixed_type:
             bool_data = self._data.get_bool_data()
-            return DataFrame(bool_data, index=self.index, copy=False)
+            return self._constructor(bool_data, index=self.index, copy=False)
         else:  # pragma: no cover
             if self.values.dtype == np.bool_:
                 return self
@@ -5127,7 +5127,7 @@ def rank(self, axis=0, numeric_only=None, method='average',
             try:
                 ranks = algos.rank(self.values, axis=axis, method=method,
                                    ascending=ascending, na_option=na_option)
-                return DataFrame(ranks, index=self.index, columns=self.columns)
+                return self._constructor(ranks, index=self.index, columns=self.columns)
             except TypeError:
                 numeric_only = True
 
@@ -5137,7 +5137,7 @@ def rank(self, axis=0, numeric_only=None, method='average',
             data = self
         ranks = algos.rank(data.values, axis=axis, method=method,
                            ascending=ascending, na_option=na_option)
-        return DataFrame(ranks, index=data.index, columns=data.columns)
+        return self._constructor(ranks, index=data.index, columns=data.columns)
 
     def to_timestamp(self, freq=None, how='start', axis=0, copy=True):
         """
@@ -5170,7 +5170,7 @@ def to_timestamp(self, freq=None, how='start', axis=0, copy=True):
         else:
             raise ValueError('Axis must be 0 or 1. Got %s' % str(axis))
 
-        return DataFrame(new_data)
+        return self._constructor(new_data)
 
     def to_period(self, freq=None, axis=0, copy=True):
         """
@@ -5204,7 +5204,7 @@ def to_period(self, freq=None, axis=0, copy=True):
         else:
             raise ValueError('Axis must be 0 or 1. Got %s' % str(axis))
 
-        return DataFrame(new_data)
+        return self._constructor(new_data)
 
     #----------------------------------------------------------------------
     # Deprecated stuff