Merge remote-tracking branch 'upstream/master' into typing

Author: simonjayhawkins

ci/deps/travis-36-cov.yaml

@@ -29,7 +29,7 @@ dependencies:
   - python-snappy
   - python=3.6.*
   - pytz
-  - s3fs
+  - s3fs<0.3
   - scikit-learn
   - scipy
   - sqlalchemy

ci/deps/travis-36-slow.yaml

@@ -18,7 +18,7 @@ dependencies:
   - python-dateutil
   - python=3.6.*
   - pytz
-  - s3fs
+  - s3fs<0.3
   - scipy
   - sqlalchemy
   - xlrd

ci/deps/travis-37.yaml

@@ -17,7 +17,7 @@ dependencies:
   - pytest-xdist>=1.29.0
   - pytest-mock
   - hypothesis>=3.58.0
-  - s3fs
+  - s3fs<0.3
   - pip
   - pyreadstat
   - pip:

doc/source/whatsnew/v1.0.0.rst

@@ -199,7 +199,7 @@ Timezones
 Numeric
 ^^^^^^^
 - Bug in :meth:`DataFrame.quantile` with zero-column :class:`DataFrame` incorrectly raising (:issue:`23925`)
--
+- :class:`DataFrame` inequality comparisons with object-dtype and ``complex`` entries failing to raise ``TypeError`` like their :class:`Series` counterparts (:issue:`28079`)
 -
 
 Conversion
@@ -279,6 +279,7 @@ Reshaping
 
 - Bug in :meth:`DataFrame.apply` that caused incorrect output with empty :class:`DataFrame` (:issue:`28202`, :issue:`21959`)
 - Bug in :meth:`DataFrame.stack` not handling non-unique indexes correctly when creating MultiIndex (:issue: `28301`)
+- Bug :func:`merge_asof` could not use :class:`datetime.timedelta` for ``tolerance`` kwarg (:issue:`28098`)
 
 Sparse
 ^^^^^^

pandas/_libs/tslibs/conversion.pyx

@@ -519,7 +519,7 @@ cdef _TSObject convert_str_to_tsobject(object ts, object tz, object unit,
             try:
                 ts = parse_datetime_string(ts, dayfirst=dayfirst,
                                            yearfirst=yearfirst)
-            except Exception:
+            except (ValueError, OverflowError):
                 raise ValueError("could not convert string to Timestamp")
 
     return convert_to_tsobject(ts, tz, unit, dayfirst, yearfirst)

pandas/_libs/tslibs/parsing.pyx

@@ -309,9 +309,9 @@ cdef parse_datetime_string_with_reso(date_string, freq=None, dayfirst=False,
         parsed, reso = dateutil_parse(date_string, _DEFAULT_DATETIME,
                                       dayfirst=dayfirst, yearfirst=yearfirst,
                                       ignoretz=False, tzinfos=None)
-    except Exception as e:
+    except (ValueError, OverflowError) as err:
         # TODO: allow raise of errors within instead
-        raise DateParseError(e)
+        raise DateParseError(err)
     if parsed is None:
         raise DateParseError("Could not parse {dstr}".format(dstr=date_string))
     return parsed, parsed, reso

pandas/core/arrays/datetimes.py

@@ -1918,6 +1918,9 @@ def sequence_to_dt64ns(
     tz = validate_tz_from_dtype(dtype, tz)
 
     if isinstance(data, ABCIndexClass):
+        if data.nlevels > 1:
+            # Without this check, data._data below is None
+            raise TypeError("Cannot create a DatetimeArray from a MultiIndex.")
         data = data._data
 
     # By this point we are assured to have either a numpy array or Index

pandas/core/indexes/datetimelike.py

@@ -198,7 +198,11 @@ def equals(self, other):
         elif not isinstance(other, type(self)):
             try:
                 other = type(self)(other)
-            except Exception:
+            except (ValueError, TypeError, OverflowError):
+                # e.g.
+                #  ValueError -> cannot parse str entry, or OutOfBoundsDatetime
+                #  TypeError  -> trying to convert IntervalIndex to DatetimeIndex
+                #  OverflowError -> Index([very_large_timedeltas])
                 return False
 
         if not is_dtype_equal(self.dtype, other.dtype):