From d6356206ab681f6732e1a7d270a689a667c69f08 Mon Sep 17 00:00:00 2001
From: jbrockmendel <jbrockmendel@gmail.com>
Date: Wed, 2 Oct 2019 10:09:58 -0500
Subject: [PATCH 01/13] TST: More maybe_promote xfails

---
 pandas/core/dtypes/cast.py               | 15 ++++++++++++---
 pandas/tests/dtypes/cast/test_promote.py | 11 -----------
 2 files changed, 12 insertions(+), 14 deletions(-)

diff --git a/pandas/core/dtypes/cast.py b/pandas/core/dtypes/cast.py
index 5801384bf8db9..1b5340468034a 100644
--- a/pandas/core/dtypes/cast.py
+++ b/pandas/core/dtypes/cast.py
@@ -348,12 +348,21 @@ def maybe_promote(dtype, fill_value=np.nan):
                 dtype = np.dtype(np.object_)
             fill_value = np.nan
 
+        if dtype == np.object_ or dtype.kind in ["U", "S"]:
+            # We treat string-like dtypes as object, and _always_ fill
+            #  with np.nan
+            fill_value = np.nan
+
     # returns tuple of (dtype, fill_value)
     if issubclass(dtype.type, np.datetime64):
-        try:
-            fill_value = tslibs.Timestamp(fill_value).to_datetime64()
-        except (TypeError, ValueError):
+        if isinstance(fill_value, datetime) and fill_value.tzinfo is not None:
+            # Trying to insert tzaware into tznaive, have to cast to object
             dtype = np.dtype(np.object_)
+        else:
+            try:
+                fill_value = tslibs.Timestamp(fill_value).to_datetime64()
+            except (TypeError, ValueError):
+                dtype = np.dtype(np.object_)
     elif issubclass(dtype.type, np.timedelta64):
         try:
             fv = tslibs.Timedelta(fill_value)
diff --git a/pandas/tests/dtypes/cast/test_promote.py b/pandas/tests/dtypes/cast/test_promote.py
index 1b7de9b20f42f..d80004b674dbc 100644
--- a/pandas/tests/dtypes/cast/test_promote.py
+++ b/pandas/tests/dtypes/cast/test_promote.py
@@ -484,9 +484,6 @@ def test_maybe_promote_any_numpy_dtype_with_datetimetz(
     fill_dtype = DatetimeTZDtype(tz=tz_aware_fixture)
     boxed, box_dtype = box  # read from parametrized fixture
 
-    if dtype.kind == "M" and not boxed:
-        pytest.xfail("Comes back as M8 instead of object")
-
     fill_value = pd.Series([fill_value], dtype=fill_dtype)[0]
 
     # filling any numpy dtype with datetimetz casts to object
@@ -572,11 +569,6 @@ def test_maybe_promote_string_with_any(string_dtype, any_numpy_dtype_reduced, bo
     fill_dtype = np.dtype(any_numpy_dtype_reduced)
     boxed, box_dtype = box  # read from parametrized fixture
 
-    if boxed and box_dtype is None and fill_dtype.kind == "m":
-        pytest.xfail("wrong missing value marker")
-    if boxed and box_dtype is None and fill_dtype.kind == "M":
-        pytest.xfail("wrong missing value marker")
-
     # create array of given dtype; casts "1" to correct dtype
     fill_value = np.array([1], dtype=fill_dtype)[0]
 
@@ -639,9 +631,6 @@ def test_maybe_promote_object_with_any(object_dtype, any_numpy_dtype_reduced, bo
     fill_dtype = np.dtype(any_numpy_dtype_reduced)
     boxed, box_dtype = box  # read from parametrized fixture
 
-    if boxed and box_dtype is None and is_datetime_or_timedelta_dtype(fill_dtype):
-        pytest.xfail("wrong missing value marker")
-
     # create array of given dtype; casts "1" to correct dtype
     fill_value = np.array([1], dtype=fill_dtype)[0]
 

From 677825b9b02c609a490631415866a929a9f2b2a4 Mon Sep 17 00:00:00 2001
From: jbrockmendel <jbrockmendel@gmail.com>
Date: Wed, 2 Oct 2019 10:51:32 -0500
Subject: [PATCH 02/13] cleanup

---
 pandas/core/dtypes/cast.py               |  3 +--
 pandas/tests/dtypes/cast/test_promote.py | 23 +++++++++++------------
 2 files changed, 12 insertions(+), 14 deletions(-)

diff --git a/pandas/core/dtypes/cast.py b/pandas/core/dtypes/cast.py
index 1b5340468034a..7bce86b572f0c 100644
--- a/pandas/core/dtypes/cast.py
+++ b/pandas/core/dtypes/cast.py
@@ -352,6 +352,7 @@ def maybe_promote(dtype, fill_value=np.nan):
             # We treat string-like dtypes as object, and _always_ fill
             #  with np.nan
             fill_value = np.nan
+            dtype = np.dtype(np.object_)
 
     # returns tuple of (dtype, fill_value)
     if issubclass(dtype.type, np.datetime64):
@@ -424,8 +425,6 @@ def maybe_promote(dtype, fill_value=np.nan):
     # in case we have a string that looked like a number
     if is_extension_array_dtype(dtype):
         pass
-    elif is_datetime64tz_dtype(dtype):
-        pass
     elif issubclass(np.dtype(dtype).type, (bytes, str)):
         dtype = np.object_
 
diff --git a/pandas/tests/dtypes/cast/test_promote.py b/pandas/tests/dtypes/cast/test_promote.py
index d80004b674dbc..1881ce295a4a2 100644
--- a/pandas/tests/dtypes/cast/test_promote.py
+++ b/pandas/tests/dtypes/cast/test_promote.py
@@ -332,18 +332,17 @@ def test_maybe_promote_any_with_datetime64(
     dtype = np.dtype(any_numpy_dtype_reduced)
     boxed, box_dtype = box  # read from parametrized fixture
 
-    if is_datetime64_dtype(dtype):
-        if boxed and (
-            box_dtype == object
-            or (box_dtype is None and not is_datetime64_dtype(type(fill_value)))
-        ):
-            pytest.xfail("falsely upcasts to object")
-    else:
-        if boxed and (
-            box_dtype == "dt_dtype"
-            or (box_dtype is None and is_datetime64_dtype(type(fill_value)))
-        ):
-            pytest.xfail("mix of lack of upcasting, resp. wrong missing value")
+    if boxed:
+        if is_datetime64_dtype(dtype):
+            if box_dtype == object:
+                pytest.xfail("falsely upcasts to object")
+            elif box_dtype is None and not is_datetime64_dtype(type(fill_value)):
+                pytest.xfail("falsely upcasts to object")
+        else:
+            if box_dtype == "dt_dtype":
+                pytest.xfail("mix of lack of upcasting, resp. wrong missing value")
+            elif box_dtype is None and is_datetime64_dtype(type(fill_value)):
+                pytest.xfail("mix of lack of upcasting, resp. wrong missing value")
 
     # special case for box_dtype
     box_dtype = np.dtype(datetime64_dtype) if box_dtype == "dt_dtype" else box_dtype

From ac2cb8713884f12ba14e057936376d0cba23daf8 Mon Sep 17 00:00:00 2001
From: jbrockmendel <jbrockmendel@gmail.com>
Date: Wed, 2 Oct 2019 10:52:40 -0500
Subject: [PATCH 03/13] trim xfail cases

---
 pandas/tests/dtypes/cast/test_promote.py | 8 ++------
 1 file changed, 2 insertions(+), 6 deletions(-)

diff --git a/pandas/tests/dtypes/cast/test_promote.py b/pandas/tests/dtypes/cast/test_promote.py
index 1881ce295a4a2..6a4c10fd2eaa9 100644
--- a/pandas/tests/dtypes/cast/test_promote.py
+++ b/pandas/tests/dtypes/cast/test_promote.py
@@ -334,14 +334,10 @@ def test_maybe_promote_any_with_datetime64(
 
     if boxed:
         if is_datetime64_dtype(dtype):
-            if box_dtype == object:
-                pytest.xfail("falsely upcasts to object")
-            elif box_dtype is None and not is_datetime64_dtype(type(fill_value)):
+            if box_dtype is None and not is_datetime64_dtype(type(fill_value)):
                 pytest.xfail("falsely upcasts to object")
         else:
-            if box_dtype == "dt_dtype":
-                pytest.xfail("mix of lack of upcasting, resp. wrong missing value")
-            elif box_dtype is None and is_datetime64_dtype(type(fill_value)):
+            if box_dtype is None and is_datetime64_dtype(type(fill_value)):
                 pytest.xfail("mix of lack of upcasting, resp. wrong missing value")
 
     # special case for box_dtype

From 7137dda9c5597d4021e8c3457b7abb296705fa41 Mon Sep 17 00:00:00 2001
From: jbrockmendel <jbrockmendel@gmail.com>
Date: Wed, 2 Oct 2019 11:21:54 -0500
Subject: [PATCH 04/13] cleanup

---
 pandas/tests/dtypes/cast/test_promote.py | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/pandas/tests/dtypes/cast/test_promote.py b/pandas/tests/dtypes/cast/test_promote.py
index 6a4c10fd2eaa9..66bf73758b000 100644
--- a/pandas/tests/dtypes/cast/test_promote.py
+++ b/pandas/tests/dtypes/cast/test_promote.py
@@ -332,12 +332,12 @@ def test_maybe_promote_any_with_datetime64(
     dtype = np.dtype(any_numpy_dtype_reduced)
     boxed, box_dtype = box  # read from parametrized fixture
 
-    if boxed:
+    if boxed and box_dtype is None:
         if is_datetime64_dtype(dtype):
-            if box_dtype is None and not is_datetime64_dtype(type(fill_value)):
+            if not is_datetime64_dtype(type(fill_value)):
                 pytest.xfail("falsely upcasts to object")
         else:
-            if box_dtype is None and is_datetime64_dtype(type(fill_value)):
+            if is_datetime64_dtype(type(fill_value)):
                 pytest.xfail("mix of lack of upcasting, resp. wrong missing value")
 
     # special case for box_dtype

From 5ac4da58593421f27b1f68512dec57faf170b20e Mon Sep 17 00:00:00 2001
From: jbrockmendel <jbrockmendel@gmail.com>
Date: Wed, 2 Oct 2019 11:29:19 -0500
Subject: [PATCH 05/13] cleanup box xfails

---
 pandas/tests/dtypes/cast/test_promote.py | 18 +++++++++---------
 1 file changed, 9 insertions(+), 9 deletions(-)

diff --git a/pandas/tests/dtypes/cast/test_promote.py b/pandas/tests/dtypes/cast/test_promote.py
index 66bf73758b000..bd1abc716c8e8 100644
--- a/pandas/tests/dtypes/cast/test_promote.py
+++ b/pandas/tests/dtypes/cast/test_promote.py
@@ -524,15 +524,15 @@ def test_maybe_promote_any_with_timedelta64(
     dtype = np.dtype(any_numpy_dtype_reduced)
     boxed, box_dtype = box  # read from parametrized fixture
 
-    if is_timedelta64_dtype(dtype):
-        if boxed and (
-            box_dtype == object
-            or (box_dtype is None and not is_timedelta64_dtype(type(fill_value)))
-        ):
-            pytest.xfail("falsely upcasts to object")
-    else:
-        if boxed and box_dtype is None and is_timedelta64_dtype(type(fill_value)):
-            pytest.xfail("does not upcast correctly")
+    if boxed:
+        if is_timedelta64_dtype(dtype):
+            if box_dtype == object:
+                pytest.xfail("falsely upcasts to object")
+            elif box_dtype is None and not is_timedelta64_dtype(type(fill_value)):
+                pytest.xfail("falsely upcasts to object")
+        else:
+            if box_dtype is None and is_timedelta64_dtype(type(fill_value)):
+                pytest.xfail("does not upcast correctly")
 
     # special case for box_dtype
     box_dtype = np.dtype(timedelta64_dtype) if box_dtype == "td_dtype" else box_dtype

From 7fe25bc56632ecb63b4e3e730551078ce51140cc Mon Sep 17 00:00:00 2001
From: jbrockmendel <jbrockmendel@gmail.com>
Date: Wed, 2 Oct 2019 11:31:05 -0500
Subject: [PATCH 06/13] clean up not-boxed xfails

---
 pandas/tests/dtypes/cast/test_promote.py | 28 +++++++++---------------
 1 file changed, 10 insertions(+), 18 deletions(-)

diff --git a/pandas/tests/dtypes/cast/test_promote.py b/pandas/tests/dtypes/cast/test_promote.py
index bd1abc716c8e8..0c30cfb3d5e71 100644
--- a/pandas/tests/dtypes/cast/test_promote.py
+++ b/pandas/tests/dtypes/cast/test_promote.py
@@ -678,24 +678,16 @@ def test_maybe_promote_any_numpy_dtype_with_na(
     dtype = np.dtype(any_numpy_dtype_reduced)
     boxed, box_dtype = box  # read from parametrized fixture
 
-    if (
-        dtype == bytes
-        and not boxed
-        and fill_value is not None
-        and fill_value is not NaT
-    ):
-        pytest.xfail("does not upcast to object")
-    elif dtype == "uint64" and not boxed and fill_value == iNaT:
-        pytest.xfail("does not upcast correctly")
-    # below: opinionated that iNaT should be interpreted as missing value
-    elif (
-        not boxed
-        and (is_float_dtype(dtype) or is_complex_dtype(dtype))
-        and fill_value == iNaT
-    ):
-        pytest.xfail("does not cast to missing value marker correctly")
-    elif (is_string_dtype(dtype) or dtype == bool) and not boxed and fill_value == iNaT:
-        pytest.xfail("does not cast to missing value marker correctly")
+    if not boxed:
+        if dtype == bytes and fill_value is not None and fill_value is not NaT:
+            pytest.xfail("does not upcast to object")
+        elif dtype == "uint64" and fill_value == iNaT:
+            pytest.xfail("does not upcast correctly")
+        # below: opinionated that iNaT should be interpreted as missing value
+        elif (is_float_dtype(dtype) or is_complex_dtype(dtype)) and fill_value == iNaT:
+            pytest.xfail("does not cast to missing value marker correctly")
+        elif (is_string_dtype(dtype) or dtype == bool) and fill_value == iNaT:
+            pytest.xfail("does not cast to missing value marker correctly")
 
     if is_integer_dtype(dtype) and dtype == "uint64" and fill_value == iNaT:
         # uint64 + negative int casts to object; iNaT is considered as missing

From 44a616214977a8029f9e34d7e26ba59b2565f07b Mon Sep 17 00:00:00 2001
From: Terji Petersen <contribute@tensortable.com>
Date: Thu, 3 Oct 2019 07:56:10 +0100
Subject: [PATCH 07/13] DEPR: Deprecate Index.set_value (#28621)

---
 doc/source/reference/indexing.rst |  1 -
 doc/source/whatsnew/v1.0.0.rst    |  4 +++-
 pandas/core/indexes/base.py       | 14 +++++++++++++-
 pandas/tests/indexes/test_base.py | 13 +++++++++----
 4 files changed, 25 insertions(+), 7 deletions(-)

diff --git a/doc/source/reference/indexing.rst b/doc/source/reference/indexing.rst
index 576f734d517aa..dd59a99b3df9e 100644
--- a/doc/source/reference/indexing.rst
+++ b/doc/source/reference/indexing.rst
@@ -166,7 +166,6 @@ Selecting
    Index.get_slice_bound
    Index.get_value
    Index.get_values
-   Index.set_value
    Index.isin
    Index.slice_indexer
    Index.slice_locs
diff --git a/doc/source/whatsnew/v1.0.0.rst b/doc/source/whatsnew/v1.0.0.rst
index 2668734031ee1..16d23d675a8bb 100644
--- a/doc/source/whatsnew/v1.0.0.rst
+++ b/doc/source/whatsnew/v1.0.0.rst
@@ -123,7 +123,9 @@ Documentation Improvements
 Deprecations
 ~~~~~~~~~~~~
 
--
+- ``Index.set_value`` has been deprecated. For a given index ``idx``, array ``arr``,
+  value in ``idx`` of ``idx_val`` and a new value of ``val``, ``idx.set_value(arr, idx_val, val)``
+  is equivalent to ``arr[idx.get_loc(idx_val)] = val``, which should be used instead (:issue:`28621`).
 -
 
 .. _whatsnew_1000.prior_deprecations:
diff --git a/pandas/core/indexes/base.py b/pandas/core/indexes/base.py
index 0b5f9fb61fce8..afa4f1a5a8c76 100644
--- a/pandas/core/indexes/base.py
+++ b/pandas/core/indexes/base.py
@@ -205,7 +205,9 @@ class Index(IndexOpsMixin, PandasObject):
     """
 
     # tolist is not actually deprecated, just suppressed in the __dir__
-    _deprecations = DirNamesMixin._deprecations | frozenset(["tolist", "dtype_str"])
+    _deprecations = DirNamesMixin._deprecations | frozenset(
+        ["tolist", "dtype_str", "set_value"]
+    )
 
     # To hand over control to subclasses
     _join_precedence = 1
@@ -4680,10 +4682,20 @@ def set_value(self, arr, key, value):
         """
         Fast lookup of value from 1-dimensional ndarray.
 
+        .. deprecated:: 1.0
+
         Notes
         -----
         Only use this if you know what you're doing.
         """
+        warnings.warn(
+            (
+                "The 'set_value' method is deprecated, and "
+                "will be removed in a future version."
+            ),
+            FutureWarning,
+            stacklevel=2,
+        )
         self._engine.set_value(
             com.values_from_object(arr), com.values_from_object(key), value
         )
diff --git a/pandas/tests/indexes/test_base.py b/pandas/tests/indexes/test_base.py
index d1ed79118d2fa..82d5ddd1ac358 100644
--- a/pandas/tests/indexes/test_base.py
+++ b/pandas/tests/indexes/test_base.py
@@ -1908,16 +1908,21 @@ def test_is_monotonic_incomparable(self, attr):
         index = Index([5, datetime.now(), 7])
         assert not getattr(index, attr)
 
-    def test_get_set_value(self):
+    def test_set_value_deprecated(self):
+        # GH 28621
+        idx = self.create_index()
+        arr = np.array([1, 2, 3])
+        with tm.assert_produces_warning(FutureWarning):
+            idx.set_value(arr, idx[1], 80)
+        assert arr[1] == 80
+
+    def test_get_value(self):
         # TODO: Remove function? GH 19728
         values = np.random.randn(100)
         date = self.dateIndex[67]
 
         assert_almost_equal(self.dateIndex.get_value(values, date), values[67])
 
-        self.dateIndex.set_value(values, date, 10)
-        assert values[67] == 10
-
     @pytest.mark.parametrize("values", [["foo", "bar", "quux"], {"foo", "bar", "quux"}])
     @pytest.mark.parametrize(
         "index,expected",

From 624dc21921e8fd88b5a90c0da86d7c8c79b4fbe5 Mon Sep 17 00:00:00 2001
From: Tirth Jain <jaintirth24@gmail.com>
Date: Thu, 3 Oct 2019 22:41:45 +0530
Subject: [PATCH 08/13] CLN: Centralised _check_percentile (#27584)

---
 pandas/core/algorithms.py  |  3 ---
 pandas/core/frame.py       |  8 ++++++--
 pandas/core/generic.py     | 23 ++++++-----------------
 pandas/core/series.py      |  4 ++--
 pandas/util/_validators.py | 35 +++++++++++++++++++++++++++++++++++
 5 files changed, 49 insertions(+), 24 deletions(-)

diff --git a/pandas/core/algorithms.py b/pandas/core/algorithms.py
index 5a479667f0227..4073ede84c6f6 100644
--- a/pandas/core/algorithms.py
+++ b/pandas/core/algorithms.py
@@ -246,7 +246,6 @@ def _get_hashtable_algo(values):
 
 
 def _get_data_algo(values, func_map):
-
     if is_categorical_dtype(values):
         values = values._values_for_rank()
 
@@ -297,7 +296,6 @@ def match(to_match, values, na_sentinel=-1):
     result = table.lookup(to_match)
 
     if na_sentinel != -1:
-
         # replace but return a numpy array
         # use a Series because it handles dtype conversions properly
         from pandas import Series
@@ -1163,7 +1161,6 @@ def compute(self, method):
 
         # slow method
         if n >= len(self.obj):
-
             reverse_it = self.keep == "last" or method == "nlargest"
             ascending = method == "nsmallest"
             slc = np.s_[::-1] if reverse_it else np.s_[:]
diff --git a/pandas/core/frame.py b/pandas/core/frame.py
index 67360122ed021..1ab62d7a9e3bf 100644
--- a/pandas/core/frame.py
+++ b/pandas/core/frame.py
@@ -31,7 +31,11 @@
     deprecate_kwarg,
     rewrite_axis_style_signature,
 )
-from pandas.util._validators import validate_axis_style_args, validate_bool_kwarg
+from pandas.util._validators import (
+    validate_axis_style_args,
+    validate_bool_kwarg,
+    validate_percentile,
+)
 
 from pandas.core.dtypes.cast import (
     cast_scalar_to_array,
@@ -8178,7 +8182,7 @@ def quantile(self, q=0.5, axis=0, numeric_only=True, interpolation="linear"):
         C        1 days 12:00:00
         Name: 0.5, dtype: object
         """
-        self._check_percentile(q)
+        validate_percentile(q)
 
         data = self._get_numeric_data() if numeric_only else self
         axis = self._get_axis_number(axis)
diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index cb21588c8ba1a..ddbdb48ab0441 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -32,7 +32,11 @@
 from pandas.compat.numpy import function as nv
 from pandas.errors import AbstractMethodError
 from pandas.util._decorators import Appender, Substitution, rewrite_axis_style_signature
-from pandas.util._validators import validate_bool_kwarg, validate_fillna_kwargs
+from pandas.util._validators import (
+    validate_bool_kwarg,
+    validate_fillna_kwargs,
+    validate_percentile,
+)
 
 from pandas.core.dtypes.common import (
     ensure_int64,
@@ -10168,7 +10172,7 @@ def describe(self, percentiles=None, include=None, exclude=None):
             percentiles = list(percentiles)
 
             # get them all to be in [0, 1]
-            self._check_percentile(percentiles)
+            validate_percentile(percentiles)
 
             # median should always be included
             if 0.5 not in percentiles:
@@ -10272,21 +10276,6 @@ def describe_1d(data):
         d.columns = data.columns.copy()
         return d
 
-    def _check_percentile(self, q):
-        """
-        Validate percentiles (used by describe and quantile).
-        """
-
-        msg = "percentiles should all be in the interval [0, 1]. Try {0} instead."
-        q = np.asarray(q)
-        if q.ndim == 0:
-            if not 0 <= q <= 1:
-                raise ValueError(msg.format(q / 100.0))
-        else:
-            if not all(0 <= qs <= 1 for qs in q):
-                raise ValueError(msg.format(q / 100.0))
-        return q
-
     _shared_docs[
         "pct_change"
     ] = """
diff --git a/pandas/core/series.py b/pandas/core/series.py
index 44a29f73c51e7..97e8a2dbac7f5 100644
--- a/pandas/core/series.py
+++ b/pandas/core/series.py
@@ -16,7 +16,7 @@
 from pandas.compat import PY36
 from pandas.compat.numpy import function as nv
 from pandas.util._decorators import Appender, Substitution, deprecate
-from pandas.util._validators import validate_bool_kwarg
+from pandas.util._validators import validate_bool_kwarg, validate_percentile
 
 from pandas.core.dtypes.common import (
     _is_unorderable_exception,
@@ -2317,7 +2317,7 @@ def quantile(self, q=0.5, interpolation="linear"):
         dtype: float64
         """
 
-        self._check_percentile(q)
+        validate_percentile(q)
 
         # We dispatch to DataFrame so that core.internals only has to worry
         #  about 2D cases.
diff --git a/pandas/util/_validators.py b/pandas/util/_validators.py
index 8d5f9f7749682..f5a472596f58f 100644
--- a/pandas/util/_validators.py
+++ b/pandas/util/_validators.py
@@ -2,8 +2,11 @@
 Module that contains many useful utilities
 for validating data or function arguments
 """
+from typing import Iterable, Union
 import warnings
 
+import numpy as np
+
 from pandas.core.dtypes.common import is_bool
 
 
@@ -370,3 +373,35 @@ def validate_fillna_kwargs(value, method, validate_scalar_dict_value=True):
         raise ValueError("Cannot specify both 'value' and 'method'.")
 
     return value, method
+
+
+def validate_percentile(q: Union[float, Iterable[float]]) -> np.ndarray:
+    """
+    Validate percentiles (used by describe and quantile).
+
+    This function checks if the given float oriterable of floats is a valid percentile
+    otherwise raises a ValueError.
+
+    Parameters
+    ----------
+    q: float or iterable of floats
+        A single percentile or an iterable of percentiles.
+
+    Returns
+    -------
+    ndarray
+        An ndarray of the percentiles if valid.
+
+    Raises
+    ------
+    ValueError if percentiles are not in given interval([0, 1]).
+    """
+    msg = "percentiles should all be in the interval [0, 1]. Try {0} instead."
+    q_arr = np.asarray(q)
+    if q_arr.ndim == 0:
+        if not 0 <= q_arr <= 1:
+            raise ValueError(msg.format(q_arr / 100.0))
+    else:
+        if not all(0 <= qs <= 1 for qs in q_arr):
+            raise ValueError(msg.format(q_arr / 100.0))
+    return q_arr

From b209aefb0e9c62d8bc8c87e38c9fea8523af91a0 Mon Sep 17 00:00:00 2001
From: jbrockmendel <jbrockmendel@gmail.com>
Date: Thu, 3 Oct 2019 12:47:45 -0500
Subject: [PATCH 09/13] remove iNaT case

---
 pandas/tests/dtypes/cast/test_promote.py | 13 +------------
 1 file changed, 1 insertion(+), 12 deletions(-)

diff --git a/pandas/tests/dtypes/cast/test_promote.py b/pandas/tests/dtypes/cast/test_promote.py
index 0c30cfb3d5e71..0df55f7090b1b 100644
--- a/pandas/tests/dtypes/cast/test_promote.py
+++ b/pandas/tests/dtypes/cast/test_promote.py
@@ -669,7 +669,7 @@ def test_maybe_promote_any_with_object(any_numpy_dtype_reduced, object_dtype, bo
     )
 
 
-@pytest.mark.parametrize("fill_value", [None, np.nan, NaT, iNaT])
+@pytest.mark.parametrize("fill_value", [None, np.nan, NaT])
 # override parametrization due to to many xfails; see GH 23982 / 25425
 @pytest.mark.parametrize("box", [(False, None)])
 def test_maybe_promote_any_numpy_dtype_with_na(
@@ -678,17 +678,6 @@ def test_maybe_promote_any_numpy_dtype_with_na(
     dtype = np.dtype(any_numpy_dtype_reduced)
     boxed, box_dtype = box  # read from parametrized fixture
 
-    if not boxed:
-        if dtype == bytes and fill_value is not None and fill_value is not NaT:
-            pytest.xfail("does not upcast to object")
-        elif dtype == "uint64" and fill_value == iNaT:
-            pytest.xfail("does not upcast correctly")
-        # below: opinionated that iNaT should be interpreted as missing value
-        elif (is_float_dtype(dtype) or is_complex_dtype(dtype)) and fill_value == iNaT:
-            pytest.xfail("does not cast to missing value marker correctly")
-        elif (is_string_dtype(dtype) or dtype == bool) and fill_value == iNaT:
-            pytest.xfail("does not cast to missing value marker correctly")
-
     if is_integer_dtype(dtype) and dtype == "uint64" and fill_value == iNaT:
         # uint64 + negative int casts to object; iNaT is considered as missing
         expected_dtype = np.dtype(object)

From c718d98690d754d72986e7aea8a377d37b7a98bb Mon Sep 17 00:00:00 2001
From: jbrockmendel <jbrockmendel@gmail.com>
Date: Thu, 3 Oct 2019 12:49:36 -0500
Subject: [PATCH 10/13] remove another iNaT case

---
 pandas/tests/dtypes/cast/test_promote.py | 26 +++++-------------------
 1 file changed, 5 insertions(+), 21 deletions(-)

diff --git a/pandas/tests/dtypes/cast/test_promote.py b/pandas/tests/dtypes/cast/test_promote.py
index 0df55f7090b1b..42c019e19b8f4 100644
--- a/pandas/tests/dtypes/cast/test_promote.py
+++ b/pandas/tests/dtypes/cast/test_promote.py
@@ -7,7 +7,7 @@
 import numpy as np
 import pytest
 
-from pandas._libs.tslibs import NaT, iNaT
+from pandas._libs.tslibs import NaT
 from pandas.compat import is_platform_windows
 
 from pandas.core.dtypes.cast import maybe_promote
@@ -19,7 +19,6 @@
     is_integer_dtype,
     is_object_dtype,
     is_scalar,
-    is_string_dtype,
     is_timedelta64_dtype,
 )
 from pandas.core.dtypes.dtypes import DatetimeTZDtype
@@ -432,7 +431,7 @@ def test_maybe_promote_datetimetz_with_datetimetz(
     )
 
 
-@pytest.mark.parametrize("fill_value", [None, np.nan, NaT, iNaT])
+@pytest.mark.parametrize("fill_value", [None, np.nan, NaT])
 # override parametrization due to to many xfails; see GH 23982 / 25425
 @pytest.mark.parametrize("box", [(False, None)])
 def test_maybe_promote_datetimetz_with_na(tz_aware_fixture, fill_value, box):
@@ -440,14 +439,7 @@ def test_maybe_promote_datetimetz_with_na(tz_aware_fixture, fill_value, box):
     dtype = DatetimeTZDtype(tz=tz_aware_fixture)
     boxed, box_dtype = box  # read from parametrized fixture
 
-    # takes the opinion that DatetimeTZ should have single na-marker
-    # using iNaT would lead to errors elsewhere -> NaT
-    if not boxed and fill_value == iNaT:
-        # TODO: are we sure iNaT _should_ be cast to NaT?
-        pytest.xfail("wrong missing value marker")
-
     expected_dtype = dtype
-    # DatetimeTZDtype does not use iNaT as missing value marker
     exp_val_for_scalar = NaT
     exp_val_for_array = NaT
 
@@ -678,25 +670,17 @@ def test_maybe_promote_any_numpy_dtype_with_na(
     dtype = np.dtype(any_numpy_dtype_reduced)
     boxed, box_dtype = box  # read from parametrized fixture
 
-    if is_integer_dtype(dtype) and dtype == "uint64" and fill_value == iNaT:
-        # uint64 + negative int casts to object; iNaT is considered as missing
-        expected_dtype = np.dtype(object)
-        exp_val_for_scalar = np.nan
-    elif is_integer_dtype(dtype) and fill_value == iNaT:
-        # other integer + iNaT casts to int64
-        expected_dtype = np.int64
-        exp_val_for_scalar = iNaT
-    elif is_integer_dtype(dtype) and fill_value is not NaT:
+    if is_integer_dtype(dtype) and fill_value is not NaT:
         # integer + other missing value (np.nan / None) casts to float
         expected_dtype = np.float64
         exp_val_for_scalar = np.nan
-    elif is_object_dtype(dtype) and (fill_value == iNaT or fill_value is NaT):
+    elif is_object_dtype(dtype) and fill_value is NaT:
         # inserting into object does not cast the value
         # but *does* cast None to np.nan
         expected_dtype = np.dtype(object)
         exp_val_for_scalar = fill_value
     elif is_datetime_or_timedelta_dtype(dtype):
-        # datetime / timedelta cast all missing values to iNaT
+        # datetime / timedelta cast all missing values to dtyped NaT
         expected_dtype = dtype
         exp_val_for_scalar = dtype.type("NaT", "ns")
     elif fill_value is NaT:

From 11603ad83432ab5ce00bcbeefba6d12608a8f409 Mon Sep 17 00:00:00 2001
From: jbrockmendel <jbrockmendel@gmail.com>
Date: Thu, 3 Oct 2019 13:48:56 -0500
Subject: [PATCH 11/13] Fix floatt32 case

---
 pandas/core/dtypes/cast.py               | 5 ++++-
 pandas/tests/dtypes/cast/test_promote.py | 3 ---
 2 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/pandas/core/dtypes/cast.py b/pandas/core/dtypes/cast.py
index 7bce86b572f0c..94a9f62f1fafe 100644
--- a/pandas/core/dtypes/cast.py
+++ b/pandas/core/dtypes/cast.py
@@ -385,7 +385,10 @@ def maybe_promote(dtype, fill_value=np.nan):
         if issubclass(dtype.type, np.bool_):
             dtype = np.object_
         elif issubclass(dtype.type, np.integer):
-            dtype = np.float64
+            dtype = np.dtype(np.float64)
+            if not isna(fill_value):
+                # TODO: use specific NAN instead of np.nan?
+                fill_value = dtype.type(fill_value)
     elif is_bool(fill_value):
         if not issubclass(dtype.type, np.bool_):
             dtype = np.object_
diff --git a/pandas/tests/dtypes/cast/test_promote.py b/pandas/tests/dtypes/cast/test_promote.py
index 42c019e19b8f4..fcd87a5814b72 100644
--- a/pandas/tests/dtypes/cast/test_promote.py
+++ b/pandas/tests/dtypes/cast/test_promote.py
@@ -174,9 +174,6 @@ def test_maybe_promote_int_with_float(any_int_dtype, float_dtype, box):
     fill_dtype = np.dtype(float_dtype)
     boxed, box_dtype = box  # read from parametrized fixture
 
-    if float_dtype == "float32" and not boxed:
-        pytest.xfail("falsely upcasts to float64")
-
     # create array of given dtype; casts "1" to correct dtype
     fill_value = np.array([1], dtype=fill_dtype)[0]
 

From 947556d35944f1cf92bdc17afcf42b961dd619af Mon Sep 17 00:00:00 2001
From: jbrockmendel <jbrockmendel@gmail.com>
Date: Tue, 8 Oct 2019 09:58:22 -0700
Subject: [PATCH 12/13] revert

---
 pandas/core/dtypes/cast.py | 1 -
 1 file changed, 1 deletion(-)

diff --git a/pandas/core/dtypes/cast.py b/pandas/core/dtypes/cast.py
index 94a9f62f1fafe..4435b2518e90b 100644
--- a/pandas/core/dtypes/cast.py
+++ b/pandas/core/dtypes/cast.py
@@ -387,7 +387,6 @@ def maybe_promote(dtype, fill_value=np.nan):
         elif issubclass(dtype.type, np.integer):
             dtype = np.dtype(np.float64)
             if not isna(fill_value):
-                # TODO: use specific NAN instead of np.nan?
                 fill_value = dtype.type(fill_value)
     elif is_bool(fill_value):
         if not issubclass(dtype.type, np.bool_):

From b7db096b4f058bbfa8ef99a97e20cb8eebb57bdf Mon Sep 17 00:00:00 2001
From: jbrockmendel <jbrockmendel@gmail.com>
Date: Tue, 8 Oct 2019 10:02:45 -0700
Subject: [PATCH 13/13] remove one xfail

---
 pandas/tests/dtypes/cast/test_promote.py | 37 ++++++++++++++----------
 1 file changed, 21 insertions(+), 16 deletions(-)

diff --git a/pandas/tests/dtypes/cast/test_promote.py b/pandas/tests/dtypes/cast/test_promote.py
index 9f0f58aeeecc6..45dbdf72209b6 100644
--- a/pandas/tests/dtypes/cast/test_promote.py
+++ b/pandas/tests/dtypes/cast/test_promote.py
@@ -658,13 +658,18 @@ def test_maybe_promote_any_with_datetime64(
     dtype = np.dtype(any_numpy_dtype_reduced)
     boxed, box_dtype = box  # read from parametrized fixture
 
-    if boxed and box_dtype is None:
-        if is_datetime64_dtype(dtype):
-            if not is_datetime64_dtype(type(fill_value)):
-                pytest.xfail("falsely upcasts to object")
-        else:
-            if is_datetime64_dtype(type(fill_value)):
-                pytest.xfail("mix of lack of upcasting, resp. wrong missing value")
+    if is_datetime64_dtype(dtype):
+        if boxed and (
+            box_dtype == object
+            or (box_dtype is None and not is_datetime64_dtype(type(fill_value)))
+        ):
+            pytest.xfail("falsely upcasts to object")
+    else:
+        if boxed and (
+            box_dtype == "dt_dtype"
+            or (box_dtype is None and is_datetime64_dtype(type(fill_value)))
+        ):
+            pytest.xfail("mix of lack of upcasting, resp. wrong missing value")
 
     # special case for box_dtype
     box_dtype = np.dtype(datetime64_dtype) if box_dtype == "dt_dtype" else box_dtype
@@ -879,15 +884,15 @@ def test_maybe_promote_any_with_timedelta64(
     dtype = np.dtype(any_numpy_dtype_reduced)
     boxed, box_dtype = box  # read from parametrized fixture
 
-    if boxed:
-        if is_timedelta64_dtype(dtype):
-            if box_dtype == object:
-                pytest.xfail("falsely upcasts to object")
-            elif box_dtype is None and not is_timedelta64_dtype(type(fill_value)):
-                pytest.xfail("falsely upcasts to object")
-        else:
-            if box_dtype is None and is_timedelta64_dtype(type(fill_value)):
-                pytest.xfail("does not upcast correctly")
+    if is_timedelta64_dtype(dtype):
+        if boxed and (
+            box_dtype == object
+            or (box_dtype is None and not is_timedelta64_dtype(type(fill_value)))
+        ):
+            pytest.xfail("falsely upcasts to object")
+    else:
+        if boxed and box_dtype is None and is_timedelta64_dtype(type(fill_value)):
+            pytest.xfail("does not upcast correctly")
 
     # special case for box_dtype
     box_dtype = np.dtype(timedelta64_dtype) if box_dtype == "td_dtype" else box_dtype