CLN: remove unused try_cast kwarg from ops

pandas/core/frame.py

@@ -4971,14 +4971,14 @@ def _combine_match_index(self, other, func, level=None):
                                      index=left.index, columns=self.columns,
                                      copy=False)
 
-    def _combine_match_columns(self, other, func, level=None, try_cast=True):
+    def _combine_match_columns(self, other, func, level=None):
         assert isinstance(other, Series)
         left, right = self.align(other, join='outer', axis=1, level=level,
                                  copy=False)
         assert left.columns.equals(right.index)
         return ops.dispatch_to_series(left, right, func, axis="columns")
 
-    def _combine_const(self, other, func, errors='raise', try_cast=True):
+    def _combine_const(self, other, func, errors='raise'):
         assert lib.is_scalar(other) or np.ndim(other) == 0
         return ops.dispatch_to_series(self, other, func)
 

pandas/core/ops.py

@@ -1726,10 +1726,10 @@ def column_op(a, b):
 
 
 def _combine_series_frame(self, other, func, fill_value=None, axis=None,
-                          level=None, try_cast=True):
+                          level=None):
     """
     Apply binary operator `func` to self, other using alignment and fill
-    conventions determined by the fill_value, axis, level, and try_cast kwargs.
+    conventions determined by the fill_value, axis, and level kwargs.
 
     Parameters
     ----------
@@ -1739,7 +1739,6 @@ def _combine_series_frame(self, other, func, fill_value=None, axis=None,
     fill_value : object, default None
     axis : {0, 1, 'columns', 'index', None}, default None
     level : int or None, default None
-    try_cast : bool, default True
 
     Returns
     -------
@@ -1754,8 +1753,7 @@ def _combine_series_frame(self, other, func, fill_value=None, axis=None,
         if axis == 0:
             return self._combine_match_index(other, func, level=level)
         else:
-            return self._combine_match_columns(other, func, level=level,
-                                               try_cast=try_cast)
+            return self._combine_match_columns(other, func, level=level)
     else:
         if not len(other):
             return self * np.nan
@@ -1766,8 +1764,7 @@ def _combine_series_frame(self, other, func, fill_value=None, axis=None,
                                      columns=self.columns)
 
         # default axis is columns
-        return self._combine_match_columns(other, func, level=level,
-                                           try_cast=try_cast)
+        return self._combine_match_columns(other, func, level=level)
 
 
 def _align_method_FRAME(left, right, axis):
@@ -1867,13 +1864,13 @@ def f(self, other, axis=default_axis, level=None, fill_value=None):
             pass_op = op if axis in [0, "columns", None] else na_op
             return _combine_series_frame(self, other, pass_op,
                                          fill_value=fill_value, axis=axis,
-                                         level=level, try_cast=True)
+                                         level=level)
         else:
             if fill_value is not None:
                 self = self.fillna(fill_value)
 
             assert np.ndim(other) == 0
-            return self._combine_const(other, op, try_cast=True)
+            return self._combine_const(other, op)
 
     f.__name__ = op_name
 
@@ -1909,9 +1906,10 @@ def f(self, other, axis=default_axis, level=None):
         elif isinstance(other, ABCSeries):
             return _combine_series_frame(self, other, na_op,
                                          fill_value=None, axis=axis,
-                                         level=level, try_cast=False)
+                                         level=level)
         else:
-            return self._combine_const(other, na_op, try_cast=False)
+            assert np.ndim(other) == 0, other
+            return self._combine_const(other, na_op)
 
     f.__name__ = op_name
 
@@ -1937,14 +1935,13 @@ def f(self, other):
         elif isinstance(other, ABCSeries):
             return _combine_series_frame(self, other, func,
                                          fill_value=None, axis=None,
-                                         level=None, try_cast=False)
+                                         level=None)
         else:
 
             # straight boolean comparisons we want to allow all columns
             # (regardless of dtype to pass thru) See #4537 for discussion.
             res = self._combine_const(other, func,
-                                      errors='ignore',
-                                      try_cast=False)
+                                      errors='ignore')
             return res.fillna(True).astype(bool)
 
     f.__name__ = op_name
@@ -1991,13 +1988,13 @@ def f(self, other, axis=None):
             self._get_axis_number(axis)
 
         if isinstance(other, self._constructor):
-            return self._compare_constructor(other, na_op, try_cast=False)
+            return self._compare_constructor(other, na_op)
         elif isinstance(other, (self._constructor_sliced, ABCDataFrame,
                                 ABCSeries)):
             raise Exception("input needs alignment for this object [{object}]"
                             .format(object=self._constructor))
         else:
-            return self._combine_const(other, na_op, try_cast=False)
+            return self._combine_const(other, na_op)
 
     f.__name__ = op_name
 

pandas/core/panel.py

@@ -330,7 +330,7 @@ def _init_matrix(self, data, axes, dtype=None, copy=False):
     # ----------------------------------------------------------------------
     # Comparison methods
 
-    def _compare_constructor(self, other, func, try_cast=True):
+    def _compare_constructor(self, other, func):
         if not self._indexed_same(other):
             raise Exception('Can only compare identically-labeled '
                             'same type objects')
@@ -745,13 +745,13 @@ def _combine(self, other, func, axis=0):
                 "{otype!s} is not supported in combine operation with "
                 "{selftype!s}".format(otype=type(other), selftype=type(self)))
 
-    def _combine_const(self, other, func, try_cast=True):
+    def _combine_const(self, other, func):
         with np.errstate(all='ignore'):
             new_values = func(self.values, other)
         d = self._construct_axes_dict()
         return self._constructor(new_values, **d)
 
-    def _combine_frame(self, other, func, axis=0, try_cast=True):
+    def _combine_frame(self, other, func, axis=0):
         index, columns = self._get_plane_axes(axis)
         axis = self._get_axis_number(axis)
 
@@ -770,7 +770,7 @@ def _combine_frame(self, other, func, axis=0, try_cast=True):
         return self._constructor(new_values, self.items, self.major_axis,
                                  self.minor_axis)
 
-    def _combine_panel(self, other, func, try_cast=True):
+    def _combine_panel(self, other, func):
         items = self.items.union(other.items)
         major = self.major_axis.union(other.major_axis)
         minor = self.minor_axis.union(other.minor_axis)

pandas/core/sparse/frame.py

@@ -618,7 +618,7 @@ def _combine_match_index(self, other, func, level=None):
             new_data, index=new_index, columns=self.columns,
             default_fill_value=fill_value).__finalize__(self)
 
-    def _combine_match_columns(self, other, func, level=None, try_cast=True):
+    def _combine_match_columns(self, other, func, level=None):
         # patched version of DataFrame._combine_match_columns to account for
         # NumPy circumventing __rsub__ with float64 types, e.g.: 3.0 - series,
         # where 3.0 is numpy.float64 and series is a SparseSeries. Still
@@ -642,7 +642,7 @@ def _combine_match_columns(self, other, func, level=None, try_cast=True):
             new_data, index=self.index, columns=union,
             default_fill_value=self.default_fill_value).__finalize__(self)
 
-    def _combine_const(self, other, func, errors='raise', try_cast=True):
+    def _combine_const(self, other, func, errors='raise'):
         return self._apply_columns(lambda x: func(x, other))
 
     def _reindex_index(self, index, method, copy, level, fill_value=np.nan,