Merge branch 'master' into feature/generalized_window_operations

Author: Matt Roeschke

pandas/core/frame.py

@@ -5269,7 +5269,7 @@ def _arith_op(left, right):
             with np.errstate(all="ignore"):
                 res_values = _arith_op(this.values, other.values)
             new_data = dispatch_fill_zeros(func, this.values, other.values, res_values)
-        return this._construct_result(other, new_data, _arith_op)
+        return this._construct_result(new_data)
 
     def _combine_match_index(self, other, func, level=None):
         left, right = self.align(other, join="outer", axis=0, level=level, copy=False)
@@ -5282,44 +5282,31 @@ def _combine_match_index(self, other, func, level=None):
             # fastpath --> operate directly on values
             with np.errstate(all="ignore"):
                 new_data = func(left.values.T, right.values).T
-        return left._construct_result(other, new_data, func)
+        return left._construct_result(new_data)
 
     def _combine_match_columns(self, other: Series, func, level=None):
         left, right = self.align(other, join="outer", axis=1, level=level, copy=False)
         # at this point we have `left.columns.equals(right.index)`
         new_data = ops.dispatch_to_series(left, right, func, axis="columns")
-        return left._construct_result(right, new_data, func)
+        return left._construct_result(new_data)
 
-    def _combine_const(self, other, func):
-        # scalar other or np.ndim(other) == 0
-        new_data = ops.dispatch_to_series(self, other, func)
-        return self._construct_result(other, new_data, func)
-
-    def _construct_result(self, other, result, func):
+    def _construct_result(self, result) -> "DataFrame":
         """
         Wrap the result of an arithmetic, comparison, or logical operation.
 
         Parameters
         ----------
-        other : object
         result : DataFrame
-        func : binary operator
 
         Returns
         -------
         DataFrame
-
-        Notes
-        -----
-        `func` is included for compat with SparseDataFrame signature, is not
-        needed here.
         """
         out = self._constructor(result, index=self.index, copy=False)
         # Pin columns instead of passing to constructor for compat with
         #  non-unique columns case
         out.columns = self.columns
         return out
-        # TODO: finalize?  we do for SparseDataFrame
 
     def combine(self, other, func, fill_value=None, overwrite=True):
         """

pandas/core/ops/__init__.py

@@ -892,7 +892,8 @@ def f(self, other, axis=default_axis, level=None, fill_value=None):
             if fill_value is not None:
                 self = self.fillna(fill_value)
 
-            return self._combine_const(other, op)
+            new_data = dispatch_to_series(self, other, op)
+            return self._construct_result(new_data)
 
     f.__name__ = op_name
 
@@ -926,15 +927,16 @@ def f(self, other, axis=default_axis, level=None):
             if not self._indexed_same(other):
                 self, other = self.align(other, "outer", level=level, copy=False)
             new_data = dispatch_to_series(self, other, na_op, str_rep)
-            return self._construct_result(other, new_data, na_op)
+            return self._construct_result(new_data)
 
         elif isinstance(other, ABCSeries):
             return _combine_series_frame(
                 self, other, na_op, fill_value=None, axis=axis, level=level
             )
         else:
             # in this case we always have `np.ndim(other) == 0`
-            return self._combine_const(other, na_op)
+            new_data = dispatch_to_series(self, other, na_op)
+            return self._construct_result(new_data)
 
     f.__name__ = op_name
 
@@ -957,7 +959,7 @@ def f(self, other):
                     "Can only compare identically-labeled DataFrame objects"
                 )
             new_data = dispatch_to_series(self, other, func, str_rep)
-            return self._construct_result(other, new_data, func)
+            return self._construct_result(new_data)
 
         elif isinstance(other, ABCSeries):
             return _combine_series_frame(
@@ -967,8 +969,8 @@ def f(self, other):
 
             # 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)
-            return res
+            new_data = dispatch_to_series(self, other, func)
+            return self._construct_result(new_data)
 
     f.__name__ = op_name
 

pandas/core/series.py

@@ -1131,7 +1131,9 @@ def _get_with(self, key):
         elif isinstance(key, tuple):
             try:
                 return self._get_values_tuple(key)
-            except Exception:
+            except ValueError:
+                # if we don't have a MultiIndex, we may still be able to handle
+                #  a 1-tuple.  see test_1tuple_without_multiindex
                 if len(key) == 1:
                     key = key[0]
                     if isinstance(key, slice):
@@ -1186,7 +1188,9 @@ def _get_values(self, indexer):
             return self._constructor(
                 self._data.get_slice(indexer), fastpath=True
             ).__finalize__(self)
-        except Exception:
+        except ValueError:
+            # mpl compat if we look up e.g. ser[:, np.newaxis];
+            #  see tests.series.timeseries.test_mpl_compat_hack
             return self._values[indexer]
 
     def _get_value(self, label, takeable: bool = False):

pandas/tests/indexing/test_iloc.py

@@ -8,6 +8,7 @@
 import pandas as pd
 from pandas import DataFrame, Series, concat, date_range, isna
 from pandas.api.types import is_scalar
+from pandas.core.indexing import IndexingError
 from pandas.tests.indexing.common import Base
 from pandas.util import testing as tm
 
@@ -722,7 +723,7 @@ def test_iloc_mask(self):
                         else:
                             accessor = df
                         ans = str(bin(accessor[mask]["nums"].sum()))
-                    except Exception as e:
+                    except (ValueError, IndexingError, NotImplementedError) as e:
                         ans = str(e)
 
                     key = tuple([idx, method])

pandas/tests/indexing/test_indexing.py

@@ -1202,3 +1202,12 @@ def test_readonly_indices():
     result = df["data"].iloc[indices]
     expected = df["data"].loc[[1, 3, 6]]
     tm.assert_series_equal(result, expected)
+
+
+def test_1tuple_without_multiindex():
+    ser = pd.Series(range(5))
+    key = (slice(3),)
+
+    result = ser[key]
+    expected = ser[key[0]]
+    tm.assert_series_equal(result, expected)

pandas/tests/io/pytables/test_pytables.py

@@ -37,7 +37,6 @@
 import pandas.util.testing as tm
 from pandas.util.testing import assert_frame_equal, assert_series_equal, set_timezone
 
-from pandas.io.formats.printing import pprint_thing
 from pandas.io.pytables import (
     ClosedFileError,
     HDFStore,
@@ -3415,14 +3414,9 @@ def test_string_select(self):
             expected = df[df.x == "none"]
             assert_frame_equal(result, expected)
 
-            try:
-                result = store.select("df", "x!=none")
-                expected = df[df.x != "none"]
-                assert_frame_equal(result, expected)
-            except Exception as detail:
-                pprint_thing("[{0}]".format(detail))
-                pprint_thing(store)
-                pprint_thing(expected)
+            result = store.select("df", "x!=none")
+            expected = df[df.x != "none"]
+            assert_frame_equal(result, expected)
 
             df2 = df.copy()
             df2.loc[df2.x == "", "x"] = np.nan

pandas/util/testing.py

@@ -9,7 +9,6 @@
 from shutil import rmtree
 import string
 import tempfile
-import traceback
 from typing import Union, cast
 import warnings
 import zipfile
@@ -2291,10 +2290,7 @@ def wrapper(*args, **kwargs):
                     " and error {error}".format(error=e)
                 )
 
-            try:
-                e_str = traceback.format_exc(e)
-            except Exception:
-                e_str = str(e)
+            e_str = str(e)
 
             if any(m.lower() in e_str.lower() for m in _skip_on_messages):
                 skip(