Squashed commit of the following:

commit c9d6e89
Author: Tom Augspurger <[email protected]>
Date:   Thu Oct 4 08:34:22 2018 -0500

    xpass -> skip

commit 95d5cbf
Author: Tom Augspurger <[email protected]>
Date:   Thu Oct 4 08:22:17 2018 -0500

    typo, import

commit 4e9b7f0
Author: Tom Augspurger <[email protected]>
Date:   Thu Oct 4 08:18:40 2018 -0500

    doc update

commit cc2bfc8
Merge: 11a0d93 fe67b94
Author: Tom Augspurger <[email protected]>
Date:   Thu Oct 4 08:15:46 2018 -0500

    Merge remote-tracking branch 'upstream/master' into ea-divmod

commit fe67b94
Author: Tom Augspurger <[email protected]>
Date:   Thu Oct 4 06:55:09 2018 -0500

    Update type for PeriodDtype / DatetimeTZDtype / IntervalDtype (pandas-dev#22938)

commit b12e5ba
Author: Tom Augspurger <[email protected]>
Date:   Thu Oct 4 06:30:29 2018 -0500

    Safer is dtype (pandas-dev#22975)

commit c19c805
Author: Tom Augspurger <[email protected]>
Date:   Thu Oct 4 06:27:54 2018 -0500

    Catch Exception in combine (pandas-dev#22936)

commit d553ab3
Author: Anjali2019 <[email protected]>
Date:   Thu Oct 4 13:24:06 2018 +0200

    TST: Fixturize series/test_combine_concat.py (pandas-dev#22964)

commit 4c78b97
Author: Anjali2019 <[email protected]>
Date:   Thu Oct 4 13:23:39 2018 +0200

    TST: Fixturize series/test_constructors.py (pandas-dev#22965)

commit 45d3bb7
Author: Anjali2019 <[email protected]>
Date:   Thu Oct 4 13:23:20 2018 +0200

    TST: Fixturize series/test_datetime_values.py (pandas-dev#22966)

commit f1a22ff
Author: Anjali2019 <[email protected]>
Date:   Thu Oct 4 13:22:21 2018 +0200

    TST: Fixturize series/test_dtypes.py (pandas-dev#22967)

commit abf68fd
Author: Anjali2019 <[email protected]>
Date:   Thu Oct 4 13:21:45 2018 +0200

    TST: Fixturize series/test_io.py (pandas-dev#22972)

commit e6b0c29
Author: Anjali2019 <[email protected]>
Date:   Thu Oct 4 13:20:46 2018 +0200

    TST: Fixturize series/test_missing.py (pandas-dev#22973)

commit 9b405b8
Author: Joris Van den Bossche <[email protected]>
Date:   Thu Oct 4 13:16:28 2018 +0200

    CLN: values is required argument in _shallow_copy_with_infer (pandas-dev#22983)

commit c282e31
Author: h-vetinari <[email protected]>
Date:   Thu Oct 4 03:34:35 2018 +0200

    Fix ASV import error (pandas-dev#22978)

commit 11a0d93
Author: Tom Augspurger <[email protected]>
Date:   Wed Oct 3 14:26:34 2018 -0500

    typerror

commit a0cd5e7
Author: Tom Augspurger <[email protected]>
Date:   Wed Oct 3 14:25:38 2018 -0500

    TypeError for Series

commit 2247461
Author: Tom Augspurger <[email protected]>
Date:   Wed Oct 3 13:29:29 2018 -0500

    Test op(Series[EA], EA])

commit c9fe5d3
Author: Tom Augspurger <[email protected]>
Date:   Wed Oct 3 13:21:33 2018 -0500

    make strict

commit 7ef697c
Author: Tom Augspurger <[email protected]>
Date:   Wed Oct 3 13:14:52 2018 -0500

    Use super

commit 35d4213
Merge: 0671e7d ee80803
Author: Tom Augspurger <[email protected]>
Date:   Wed Oct 3 13:11:05 2018 -0500

    Merge remote-tracking branch 'upstream/master' into ea-divmod

commit 0671e7d
Author: Tom Augspurger <[email protected]>
Date:   Tue Oct 2 11:10:42 2018 -0500

    Fixup

commit 1b4261f
Merge: c92a4a8 1d9f76c
Author: Tom Augspurger <[email protected]>
Date:   Tue Oct 2 10:58:43 2018 -0500

    Merge remote-tracking branch 'upstream/master' into ea-divmod

commit c92a4a8
Author: Tom Augspurger <[email protected]>
Date:   Mon Oct 1 16:56:15 2018 -0500

    Update old test

commit 52538fa
Author: Tom Augspurger <[email protected]>
Date:   Mon Oct 1 16:51:48 2018 -0500

    BUG: divmod return type

Author: TomAugspurger

.travis.yml

@@ -53,18 +53,20 @@ matrix:
     - dist: trusty
       env:
         - JOB="3.6, coverage" ENV_FILE="ci/travis-36.yaml" TEST_ARGS="--skip-slow --skip-network" PANDAS_TESTING_MODE="deprecate" COVERAGE=true DOCTEST=true
-    # In allow_failures
-    - dist: trusty
-      env:
-        - JOB="3.6, slow" ENV_FILE="ci/travis-36-slow.yaml" SLOW=true
-    # In allow_failures
+
     - dist: trusty
       env:
         - JOB="3.7, NumPy dev" ENV_FILE="ci/travis-37-numpydev.yaml" TEST_ARGS="--skip-slow --skip-network -W error" PANDAS_TESTING_MODE="deprecate"
       addons:
         apt:
           packages:
           - xsel
+
+    # In allow_failures
+    - dist: trusty
+      env:
+        - JOB="3.6, slow" ENV_FILE="ci/travis-36-slow.yaml" SLOW=true
+
     # In allow_failures
     - dist: trusty
       env:
@@ -73,13 +75,6 @@ matrix:
       - dist: trusty
         env:
           - JOB="3.6, slow" ENV_FILE="ci/travis-36-slow.yaml" SLOW=true
-      - dist: trusty
-        env:
-          - JOB="3.7, NumPy dev" ENV_FILE="ci/travis-37-numpydev.yaml" TEST_ARGS="--skip-slow --skip-network -W error" PANDAS_TESTING_MODE="deprecate"
-        addons:
-          apt:
-            packages:
-            - xsel
       - dist: trusty
         env:
           - JOB="3.6, doc" ENV_FILE="ci/travis-36-doc.yaml" DOC=true

asv_bench/benchmarks/indexing.py

@@ -2,10 +2,10 @@
 
 import numpy as np
 import pandas.util.testing as tm
-from pandas import (Series, DataFrame, MultiIndex, Int64Index, Float64Index,
-                    IntervalIndex, CategoricalIndex,
-                    IndexSlice, concat, date_range)
-from .pandas_vb_common import setup, Panel  # noqa
+from pandas import (Series, DataFrame, MultiIndex, Panel,
+                    Int64Index, Float64Index, IntervalIndex,
+                    CategoricalIndex, IndexSlice, concat, date_range)
+from .pandas_vb_common import setup  # noqa
 
 
 class NumericSeriesIndexing(object):

asv_bench/benchmarks/join_merge.py

@@ -3,14 +3,15 @@
 
 import numpy as np
 import pandas.util.testing as tm
-from pandas import (DataFrame, Series, MultiIndex, date_range, concat, merge,
-                    merge_asof)
+from pandas import (DataFrame, Series, Panel, MultiIndex,
+                    date_range, concat, merge, merge_asof)
+
 try:
     from pandas import merge_ordered
 except ImportError:
     from pandas import ordered_merge as merge_ordered
 
-from .pandas_vb_common import Panel, setup  # noqa
+from .pandas_vb_common import setup  # noqa
 
 
 class Append(object):

asv_bench/benchmarks/panel_ctor.py

@@ -1,9 +1,9 @@
 import warnings
 from datetime import datetime, timedelta
 
-from pandas import DataFrame, DatetimeIndex, date_range
+from pandas import DataFrame, Panel, DatetimeIndex, date_range
 
-from .pandas_vb_common import Panel, setup  # noqa
+from .pandas_vb_common import setup  # noqa
 
 
 class DifferentIndexes(object):

asv_bench/benchmarks/panel_methods.py

@@ -1,8 +1,9 @@
 import warnings
 
 import numpy as np
+from pandas import Panel
 
-from .pandas_vb_common import Panel, setup  # noqa
+from .pandas_vb_common import setup  # noqa
 
 
 class PanelMethods(object):

doc/source/extending.rst

@@ -167,11 +167,11 @@ your ``MyExtensionArray`` class, as follows:
    element one-by-one, this might not be as performant as implementing your own
    version of the associated operators directly on the ``ExtensionArray``.
 
-This implementation will try to reconstruct a new ``ExtensionArray`` with the
-result of the element-wise operation. Whether or not that succeeds depends on
-whether the operation returns a result that's valid for the ``ExtensionArray``.
-If an ``ExtensionArray`` cannot be reconstructed, a list containing the scalars
-returned instead.
+For arithmetic operations, this implementation will try to reconstruct a new
+``ExtensionArray`` with the result of the element-wise operation. Whether
+or not that succeeds depends on whether the operation returns a result
+that's valid for the ``ExtensionArray``. If an ``ExtensionArray`` cannot
+be reconstructed, an ndarray containing the scalars returned instead.
 
 .. _extending.extension.testing:
 

pandas/core/arrays/base.py

@@ -781,20 +781,24 @@ def convert_values(param):
             # a TypeError should be raised
             res = [op(a, b) for (a, b) in zip(lvalues, rvalues)]
 
-            if coerce_to_dtype:
-                if op.__name__ in {'divmod', 'rdivmod'}:
+            def _maybe_convert(arr):
+                if coerce_to_dtype:
+                    # https://github.com/pandas-dev/pandas/issues/22850
+                    # We catch all regular exceptions here, and fall back
+                    # to an ndarray.
                     try:
-                        a, b = zip(*res)
-                        res = (self._from_sequence(a),
-                               self._from_sequence(b))
+                        res = self._from_sequence(arr)
                     except Exception:
-                        pass
+                        res = np.asarray(arr)
                 else:
-                    try:
-                        res = self._from_sequence(res)
-                    except Exception:
-                        pass
+                    res = np.asarray(arr)
+                return res
 
+            if op.__name__ in {'divmod', 'rdivmod'}:
+                a, b = zip(*res)
+                res = _maybe_convert(a), _maybe_convert(b)
+            else:
+                res = _maybe_convert(res)
             return res
 
         op_name = ops._get_op_name(op, True)

pandas/core/dtypes/base.py

@@ -2,6 +2,7 @@
 import numpy as np
 
 from pandas import compat
+from pandas.core.dtypes.generic import ABCSeries, ABCIndexClass, ABCDataFrame
 from pandas.errors import AbstractMethodError
 
 
@@ -83,7 +84,12 @@ def is_dtype(cls, dtype):
         """
         dtype = getattr(dtype, 'dtype', dtype)
 
-        if isinstance(dtype, np.dtype):
+        if isinstance(dtype, (ABCSeries, ABCIndexClass,
+                              ABCDataFrame, np.dtype)):
+            # https://github.com/pandas-dev/pandas/issues/22960
+            # avoid passing data to `construct_from_string`. This could
+            # cause a FutureWarning from numpy about failing elementwise
+            # comparison from, e.g., comparing DataFrame == 'category'.
             return False
         elif dtype is None:
             return False

pandas/core/frame.py

@@ -4908,7 +4908,8 @@ def _combine_match_index(self, other, func, level=None):
             return ops.dispatch_to_series(left, right, func)
         else:
             # fastpath --> operate directly on values
-            new_data = func(left.values.T, right.values).T
+            with np.errstate(all="ignore"):
+                new_data = func(left.values.T, right.values).T
             return self._constructor(new_data,
                                      index=left.index, columns=self.columns,
                                      copy=False)

pandas/core/indexes/base.py

@@ -540,7 +540,7 @@ def _shallow_copy(self, values=None, **kwargs):
 
         return self._simple_new(values, **attributes)
 
-    def _shallow_copy_with_infer(self, values=None, **kwargs):
+    def _shallow_copy_with_infer(self, values, **kwargs):
         """
         create a new Index inferring the class with passed value, don't copy
         the data, use the same object attributes with passed in attributes
@@ -553,8 +553,6 @@ def _shallow_copy_with_infer(self, values=None, **kwargs):
         values : the values to create the new Index, optional
         kwargs : updates the default attributes for this Index
         """
-        if values is None:
-            values = self.values
         attributes = self._get_attributes_dict()
         attributes.update(kwargs)
         attributes['copy'] = False

pandas/core/indexes/multi.py

@@ -556,7 +556,7 @@ def view(self, cls=None):
         result._id = self._id
         return result
 
-    def _shallow_copy_with_infer(self, values=None, **kwargs):
+    def _shallow_copy_with_infer(self, values, **kwargs):
         # On equal MultiIndexes the difference is empty.
         # Therefore, an empty MultiIndex is returned GH13490
         if len(values) == 0:

pandas/core/indexes/period.py

@@ -252,17 +252,10 @@ def _from_ordinals(cls, values, name=None, freq=None, **kwargs):
         result = cls._simple_new(data, name=name)
         return result
 
-    def _shallow_copy(self, values=None, **kwargs):
+    def _shallow_copy(self, values, **kwargs):
         # TODO: simplify, figure out type of values
-        if values is None:
-            # Note: this is the Index implementation.
-            # slightly different from AttributesMixin implementation which
-            # defaults to self._ndarray_values
-            values = self.values
-        else:
-            # this differs too
-            if not isinstance(values, PeriodArray):
-                values = PeriodArray._from_ordinals(values, freq=self.freq)
+        if not isinstance(values, PeriodArray):
+            values = PeriodArray._from_ordinals(values, freq=self.freq)
 
         # I don't like overloading shallow_copy with freq changes.
         # See if it's used anywhere outside of test_resample_empty_dataframe

pandas/core/series.py

@@ -4228,7 +4228,7 @@ def _try_cast(arr, take_fast_path):
         try:
             # gh-15832: Check if we are requesting a numeric dype and
             # that we can convert the data to the requested dtype.
-            if is_float_dtype(dtype) or is_integer_dtype(dtype):
+            if is_integer_dtype(dtype):
                 subarr = maybe_cast_to_integer_array(arr, dtype)
 
             subarr = maybe_cast_to_datetime(arr, dtype)

pandas/tests/dtypes/test_dtypes.py

@@ -815,3 +815,23 @@ def test_registry_find(dtype, expected):
      ('datetime64[ns, US/Eastern]', DatetimeTZDtype('ns', 'US/Eastern'))])
 def test_pandas_registry_find(dtype, expected):
     assert _pandas_registry.find(dtype) == expected
+
+
+@pytest.mark.parametrize("check", [
+    is_categorical_dtype,
+    is_datetime64tz_dtype,
+    is_period_dtype,
+    is_datetime64_ns_dtype,
+    is_datetime64_dtype,
+    is_interval_dtype,
+    is_datetime64_any_dtype,
+    is_string_dtype,
+    is_bool_dtype,
+])
+def test_is_dtype_no_warning(check):
+    data = pd.DataFrame({"A": [1, 2]})
+    with tm.assert_produces_warning(None):
+        check(data)
+
+    with tm.assert_produces_warning(None):
+        check(data["A"])

pandas/tests/extension/decimal/test_decimal.py

@@ -102,7 +102,7 @@ class TestInterface(BaseDecimal, base.BaseInterfaceTests):
 
 class TestConstructors(BaseDecimal, base.BaseConstructorsTests):
 
-    @pytest.mark.xfail(reason="not implemented constructor from dtype")
+    @pytest.mark.skip(reason="not implemented constructor from dtype")
     def test_from_dtype(self, data):
         # construct from our dtype & string dtype
         pass

pandas/tests/extension/json/test_json.py

@@ -131,8 +131,7 @@ def test_custom_asserts(self):
 
 class TestConstructors(BaseJSON, base.BaseConstructorsTests):
 
-    # TODO: Should this be pytest.mark.skip?
-    @pytest.mark.xfail(reason="not implemented constructor from dtype")
+    @pytest.mark.skip(reason="not implemented constructor from dtype")
     def test_from_dtype(self, data):
         # construct from our dtype & string dtype
         pass
@@ -147,13 +146,11 @@ class TestGetitem(BaseJSON, base.BaseGetitemTests):
 
 
 class TestMissing(BaseJSON, base.BaseMissingTests):
-    # TODO: Should this be pytest.mark.skip?
-    @pytest.mark.xfail(reason="Setting a dict as a scalar")
+    @pytest.mark.skip(reason="Setting a dict as a scalar")
     def test_fillna_series(self):
         """We treat dictionaries as a mapping in fillna, not a scalar."""
 
-    # TODO: Should this be pytest.mark.skip?
-    @pytest.mark.xfail(reason="Setting a dict as a scalar")
+    @pytest.mark.skip(reason="Setting a dict as a scalar")
     def test_fillna_frame(self):
         """We treat dictionaries as a mapping in fillna, not a scalar."""
 
@@ -204,8 +201,7 @@ def test_combine_add(self, data_repeated):
 
 
 class TestCasting(BaseJSON, base.BaseCastingTests):
-    # TODO: Should this be pytest.mark.skip?
-    @pytest.mark.xfail(reason="failing on np.array(self, dtype=str)")
+    @pytest.mark.skip(reason="failing on np.array(self, dtype=str)")
     def test_astype_str(self):
         """This currently fails in NumPy on np.array(self, dtype=str) with
 

pandas/tests/extension/test_categorical.py

@@ -140,11 +140,11 @@ def test_take_series(self):
     def test_reindex_non_na_fill_value(self):
         pass
 
-    @pytest.mark.xfail(reason="Categorical.take buggy")
+    @pytest.mark.skip(reason="Categorical.take buggy")
     def test_take_empty(self):
         pass
 
-    @pytest.mark.xfail(reason="test not written correctly for categorical")
+    @pytest.mark.skip(reason="test not written correctly for categorical")
     def test_reindex(self):
         pass
 

pandas/tests/frame/test_operators.py

@@ -1030,3 +1030,9 @@ def test_alignment_non_pandas(self):
             align(df, val, 'index')
         with pytest.raises(ValueError):
             align(df, val, 'columns')
+
+    def test_no_warning(self, all_arithmetic_operators):
+        df = pd.DataFrame({"A": [0., 0.], "B": [0., None]})
+        b = df['B']
+        with tm.assert_produces_warning(None):
+            getattr(df, all_arithmetic_operators)(b, 0)

pandas/tests/series/test_combine_concat.py

@@ -15,29 +15,28 @@
 from pandas.util.testing import assert_series_equal
 import pandas.util.testing as tm
 
-from .common import TestData
 
+class TestSeriesCombine():
 
-class TestSeriesCombine(TestData):
-
-    def test_append(self):
-        appendedSeries = self.series.append(self.objSeries)
+    def test_append(self, datetime_series, string_series, object_series):
+        appendedSeries = string_series.append(object_series)
         for idx, value in compat.iteritems(appendedSeries):
-            if idx in self.series.index:
-                assert value == self.series[idx]
-            elif idx in self.objSeries.index:
-                assert value == self.objSeries[idx]
+            if idx in string_series.index:
+                assert value == string_series[idx]
+            elif idx in object_series.index:
+                assert value == object_series[idx]
             else:
                 raise AssertionError("orphaned index!")
 
-        pytest.raises(ValueError, self.ts.append, self.ts,
+        pytest.raises(ValueError, datetime_series.append, datetime_series,
                       verify_integrity=True)
 
-    def test_append_many(self):
-        pieces = [self.ts[:5], self.ts[5:10], self.ts[10:]]
+    def test_append_many(self, datetime_series):
+        pieces = [datetime_series[:5], datetime_series[5:10],
+                  datetime_series[10:]]
 
         result = pieces[0].append(pieces[1:])
-        assert_series_equal(result, self.ts)
+        assert_series_equal(result, datetime_series)
 
     def test_append_duplicates(self):
         # GH 13677