From 936c94b66787514d9b43fcf5d026a8634423859c Mon Sep 17 00:00:00 2001
From: MomIsBestFriend <>
Date: Wed, 25 Dec 2019 03:56:54 +0200
Subject: [PATCH 01/11] TYP: Annotations in pandas/core/nanops.py

---
 pandas/core/nanops.py | 135 ++++++++++++++++++++++++++++++++----------
 1 file changed, 105 insertions(+), 30 deletions(-)

diff --git a/pandas/core/nanops.py b/pandas/core/nanops.py
index 1079f516a4e40..2692948e8d329 100644
--- a/pandas/core/nanops.py
+++ b/pandas/core/nanops.py
@@ -1,13 +1,14 @@
 import functools
 import itertools
 import operator
-from typing import Any, Optional, Tuple, Union
+from typing import Any, Callable, Optional, Tuple, Union
 
 import numpy as np
 
 from pandas._config import get_option
 
 from pandas._libs import NaT, Timedelta, Timestamp, iNaT, lib
+from pandas._typing import Dtype, Scalar
 from pandas.compat._optional import import_optional_dependency
 
 from pandas.core.dtypes.cast import _int64_max, maybe_upcast_putmask
@@ -37,7 +38,7 @@
 _USE_BOTTLENECK = False
 
 
-def set_use_bottleneck(v=True):
+def set_use_bottleneck(v: bool = True) -> None:
     # set/unset to use bottleneck
     global _USE_BOTTLENECK
     if _BOTTLENECK_INSTALLED:
@@ -55,7 +56,7 @@ def __init__(self, *dtypes):
     def check(self, obj) -> bool:
         return hasattr(obj, "dtype") and issubclass(obj.dtype.type, self.dtypes)
 
-    def __call__(self, f):
+    def __call__(self, f) -> Callable:
         @functools.wraps(f)
         def _f(*args, **kwargs):
             obj_iter = itertools.chain(args, kwargs.values())
@@ -80,11 +81,11 @@ def _f(*args, **kwargs):
 
 
 class bottleneck_switch:
-    def __init__(self, name=None, **kwargs):
+    def __init__(self, name: Optional[str] = None, **kwargs):
         self.name = name
         self.kwargs = kwargs
 
-    def __call__(self, alt):
+    def __call__(self, alt: Callable) -> Callable:
         bn_name = self.name or alt.__name__
 
         try:
@@ -93,7 +94,9 @@ def __call__(self, alt):
             bn_func = None
 
         @functools.wraps(alt)
-        def f(values, axis=None, skipna=True, **kwds):
+        def f(
+            values: np.ndarray, axis: Optional[int] = None, skipna: bool = True, **kwds
+        ):
             if len(self.kwargs) > 0:
                 for k, v in self.kwargs.items():
                     if k not in kwds:
@@ -129,7 +132,7 @@ def f(values, axis=None, skipna=True, **kwds):
         return f
 
 
-def _bn_ok_dtype(dt, name: str) -> bool:
+def _bn_ok_dtype(dt: Dtype, name: str) -> bool:
     # Bottleneck chokes on datetime64
     if not is_object_dtype(dt) and not (
         is_datetime_or_timedelta_dtype(dt) or is_datetime64tz_dtype(dt)
@@ -163,7 +166,9 @@ def _has_infs(result) -> bool:
         return False
 
 
-def _get_fill_value(dtype, fill_value=None, fill_value_typ=None):
+def _get_fill_value(
+    dtype: Dtype, fill_value: Any = None, fill_value_typ: Optional[str] = None
+):
     """ return the correct fill value for the dtype of the values """
     if fill_value is not None:
         return fill_value
@@ -326,12 +331,12 @@ def _get_values(
     return values, mask, dtype, dtype_max, fill_value
 
 
-def _na_ok_dtype(dtype):
+def _na_ok_dtype(dtype) -> bool:
     # TODO: what about datetime64tz?  PeriodDtype?
     return not issubclass(dtype.type, (np.integer, np.timedelta64, np.datetime64))
 
 
-def _wrap_results(result, dtype, fill_value=None):
+def _wrap_results(result, dtype: Dtype, fill_value=None):
     """ wrap our results if needed """
 
     if is_datetime64_dtype(dtype) or is_datetime64tz_dtype(dtype):
@@ -362,7 +367,9 @@ def _wrap_results(result, dtype, fill_value=None):
     return result
 
 
-def _na_for_min_count(values, axis: Optional[int]):
+def _na_for_min_count(
+    values: np.ndarray, axis: Optional[int]
+) -> Union[Scalar, np.ndarray]:
     """
     Return the missing value for `values`.
 
@@ -393,7 +400,12 @@ def _na_for_min_count(values, axis: Optional[int]):
         return result
 
 
-def nanany(values, axis=None, skipna: bool = True, mask=None):
+def nanany(
+    values: np.ndarray,
+    axis: Optional[int] = None,
+    skipna: bool = True,
+    mask: Optional[np.ndarray] = None,
+) -> bool:
     """
     Check if any elements along an axis evaluate to True.
 
@@ -425,7 +437,12 @@ def nanany(values, axis=None, skipna: bool = True, mask=None):
     return values.any(axis)
 
 
-def nanall(values, axis=None, skipna: bool = True, mask=None):
+def nanall(
+    values: np.ndarray,
+    axis: Optional[int] = None,
+    skipna: bool = True,
+    mask: Optional[np.ndarray] = None,
+) -> bool:
     """
     Check if all elements along an axis evaluate to True.
 
@@ -458,7 +475,13 @@ def nanall(values, axis=None, skipna: bool = True, mask=None):
 
 
 @disallow("M8")
-def nansum(values, axis=None, skipna=True, min_count=0, mask=None):
+def nansum(
+    values: np.ndarray,
+    axis: Optional[int] = None,
+    skipna: bool = True,
+    min_count: int = 0,
+    mask: Optional[np.ndarray] = None,
+) -> Dtype:
     """
     Sum the elements along an axis ignoring NaNs
 
@@ -629,7 +652,7 @@ def _get_counts_nanvar(
     mask: Optional[np.ndarray],
     axis: Optional[int],
     ddof: int,
-    dtype=float,
+    dtype: Dtype = float,
 ) -> Tuple[Union[int, np.ndarray], Union[int, np.ndarray]]:
     """ Get the count of non-null values along an axis, accounting
     for degrees of freedom.
@@ -776,7 +799,13 @@ def nanvar(values, axis=None, skipna=True, ddof=1, mask=None):
 
 
 @disallow("M8", "m8")
-def nansem(values, axis=None, skipna=True, ddof=1, mask=None):
+def nansem(
+    values: np.ndarray,
+    axis: Optional[int] = None,
+    skipna: bool = True,
+    ddof: int = 1,
+    mask: Optional[np.ndarray] = None,
+) -> float:
     """
     Compute the standard error in the mean along given axis while ignoring NaNs
 
@@ -819,9 +848,14 @@ def nansem(values, axis=None, skipna=True, ddof=1, mask=None):
     return np.sqrt(var) / np.sqrt(count)
 
 
-def _nanminmax(meth, fill_value_typ):
+def _nanminmax(meth: str, fill_value_typ: str) -> Callable:
     @bottleneck_switch(name="nan" + meth)
-    def reduction(values, axis=None, skipna=True, mask=None):
+    def reduction(
+        values: np.ndarray,
+        axis: Optional[int] = None,
+        skipna: bool = True,
+        mask: Optional[np.ndarray] = None,
+    ) -> np.ndarray:
 
         values, mask, dtype, dtype_max, fill_value = _get_values(
             values, skipna, fill_value_typ=fill_value_typ, mask=mask
@@ -847,7 +881,12 @@ def reduction(values, axis=None, skipna=True, mask=None):
 
 
 @disallow("O")
-def nanargmax(values, axis=None, skipna=True, mask=None):
+def nanargmax(
+    values: np.ndarray,
+    axis: Optional[int] = None,
+    skipna: bool = True,
+    mask: Optional[np.ndarray] = None,
+) -> int:
     """
     Parameters
     ----------
@@ -878,7 +917,12 @@ def nanargmax(values, axis=None, skipna=True, mask=None):
 
 
 @disallow("O")
-def nanargmin(values, axis=None, skipna=True, mask=None):
+def nanargmin(
+    values: np.ndarray,
+    axis: Optional[int] = None,
+    skipna: bool = True,
+    mask: Optional[np.ndarray] = None,
+) -> int:
     """
     Parameters
     ----------
@@ -909,7 +953,12 @@ def nanargmin(values, axis=None, skipna=True, mask=None):
 
 
 @disallow("M8", "m8")
-def nanskew(values, axis=None, skipna=True, mask=None):
+def nanskew(
+    values: np.ndarray,
+    axis: Optional[int] = None,
+    skipna: bool = True,
+    mask: Optional[np.ndarray] = None,
+) -> float:
     """ Compute the sample skewness.
 
     The statistic computed here is the adjusted Fisher-Pearson standardized
@@ -987,7 +1036,12 @@ def nanskew(values, axis=None, skipna=True, mask=None):
 
 
 @disallow("M8", "m8")
-def nankurt(values, axis=None, skipna=True, mask=None):
+def nankurt(
+    values: np.ndarray,
+    axis: Optional[int] = None,
+    skipna: bool = True,
+    mask: Optional[np.ndarray] = None,
+) -> float:
     """
     Compute the sample excess kurtosis
 
@@ -1075,7 +1129,13 @@ def nankurt(values, axis=None, skipna=True, mask=None):
 
 
 @disallow("M8", "m8")
-def nanprod(values, axis=None, skipna=True, min_count=0, mask=None):
+def nanprod(
+    values: np.ndarray,
+    axis: Optional[int] = None,
+    skipna: bool = True,
+    min_count: int = 0,
+    mask: Optional[np.ndarray] = None,
+) -> Dtype:
     """
     Parameters
     ----------
@@ -1138,7 +1198,7 @@ def _get_counts(
     values_shape: Tuple[int],
     mask: Optional[np.ndarray],
     axis: Optional[int],
-    dtype=float,
+    dtype: Dtype = float,
 ) -> Union[int, np.ndarray]:
     """ Get the count of non-null values along an axis
 
@@ -1218,7 +1278,12 @@ def _zero_out_fperr(arg):
 
 
 @disallow("M8", "m8")
-def nancorr(a, b, method="pearson", min_periods=None):
+def nancorr(
+    a: np.ndarray,
+    b: np.ndarray,
+    method: str = "pearson",
+    min_periods: Optional[int] = None,
+):
     """
     a, b: ndarrays
     """
@@ -1240,7 +1305,7 @@ def nancorr(a, b, method="pearson", min_periods=None):
     return f(a, b)
 
 
-def get_corr_func(method):
+def get_corr_func(method: str):
     if method in ["kendall", "spearman"]:
         from scipy.stats import kendalltau, spearmanr
     elif callable(method):
@@ -1262,7 +1327,7 @@ def _spearman(a, b):
 
 
 @disallow("M8", "m8")
-def nancov(a, b, min_periods=None):
+def nancov(a: np.ndarray, b: np.ndarray, min_periods: Optional[int] = None):
     if len(a) != len(b):
         raise AssertionError("Operands to nancov must have same size")
 
@@ -1308,7 +1373,7 @@ def _ensure_numeric(x):
 # NA-friendly array comparisons
 
 
-def make_nancomp(op):
+def make_nancomp(op) -> Callable:
     def f(x, y):
         xmask = isna(x)
         ymask = isna(y)
@@ -1335,7 +1400,9 @@ def f(x, y):
 nanne = make_nancomp(operator.ne)
 
 
-def _nanpercentile_1d(values, mask, q, na_value, interpolation):
+def _nanpercentile_1d(
+    values: np.ndarray, mask: np.ndarray, q, na_value: Scalar, interpolation: str
+) -> Union[Scalar, np.ndarray]:
     """
     Wrapper for np.percentile that skips missing values, specialized to
     1-dimensional case.
@@ -1366,7 +1433,15 @@ def _nanpercentile_1d(values, mask, q, na_value, interpolation):
     return np.percentile(values, q, interpolation=interpolation)
 
 
-def nanpercentile(values, q, axis, na_value, mask, ndim, interpolation):
+def nanpercentile(
+    values: np.ndarray,
+    q,
+    axis: int,
+    na_value,
+    mask: np.ndarray,
+    ndim: int,
+    interpolation: str,
+):
     """
     Wrapper for np.percentile that skips missing values.
 

From 3f07a8fe6c45e353b95d671fe5cae14e33c882ad Mon Sep 17 00:00:00 2001
From: MomIsBestFriend <>
Date: Sun, 29 Dec 2019 13:50:57 +0200
Subject: [PATCH 02/11] Fixes for jbrockmendel review

---
 pandas/core/nanops.py | 19 +++++++++----------
 1 file changed, 9 insertions(+), 10 deletions(-)

diff --git a/pandas/core/nanops.py b/pandas/core/nanops.py
index 2692948e8d329..c91262b24dd4e 100644
--- a/pandas/core/nanops.py
+++ b/pandas/core/nanops.py
@@ -167,7 +167,9 @@ def _has_infs(result) -> bool:
 
 
 def _get_fill_value(
-    dtype: Dtype, fill_value: Any = None, fill_value_typ: Optional[str] = None
+    dtype: Dtype,
+    fill_value: Optional[Scalar] = None,
+    fill_value_typ: Optional[str] = None,
 ):
     """ return the correct fill value for the dtype of the values """
     if fill_value is not None:
@@ -652,7 +654,7 @@ def _get_counts_nanvar(
     mask: Optional[np.ndarray],
     axis: Optional[int],
     ddof: int,
-    dtype: Dtype = float,
+    dtype=float,
 ) -> Tuple[Union[int, np.ndarray], Union[int, np.ndarray]]:
     """ Get the count of non-null values along an axis, accounting
     for degrees of freedom.
@@ -1135,7 +1137,7 @@ def nanprod(
     skipna: bool = True,
     min_count: int = 0,
     mask: Optional[np.ndarray] = None,
-) -> Dtype:
+):
     """
     Parameters
     ----------
@@ -1148,7 +1150,7 @@ def nanprod(
 
     Returns
     -------
-    result : dtype
+    The product of all elements on a given axis. ( NaNs are treated as 1)
 
     Examples
     --------
@@ -1156,10 +1158,6 @@ def nanprod(
     >>> s = pd.Series([1, 2, 3, np.nan])
     >>> nanops.nanprod(s)
     6.0
-
-    Returns
-    -------
-    The product of all elements on a given axis. ( NaNs are treated as 1)
     """
     mask = _maybe_get_mask(values, skipna, mask)
 
@@ -1305,8 +1303,9 @@ def nancorr(
     return f(a, b)
 
 
-def get_corr_func(method: str):
-    if method in ["kendall", "spearman"]:
+def get_corr_func(method) -> Callable:
+    if method in ["kendall", "spearman", "pearson"]:
+        import scipy.stats
         from scipy.stats import kendalltau, spearmanr
     elif callable(method):
         return method

From 0b6b26fdd2da49de1d18953d879c41e3b720ff9a Mon Sep 17 00:00:00 2001
From: MomIsBestFriend <>
Date: Sun, 29 Dec 2019 16:01:30 +0200
Subject: [PATCH 03/11] Added scipy to dep list of azure-macOS and
 azure-36-32bit

---
 ci/deps/azure-36-32bit.yaml | 1 +
 ci/deps/azure-macos-36.yaml | 1 +
 pandas/core/nanops.py       | 1 -
 3 files changed, 2 insertions(+), 1 deletion(-)

diff --git a/ci/deps/azure-36-32bit.yaml b/ci/deps/azure-36-32bit.yaml
index cf3fca307481f..fa294be78b731 100644
--- a/ci/deps/azure-36-32bit.yaml
+++ b/ci/deps/azure-36-32bit.yaml
@@ -18,6 +18,7 @@ dependencies:
   - numpy=1.14.*
   - python-dateutil
   - pytz=2017.2
+  - scipy>=1.1
 
   # see comment above
   - pip
diff --git a/ci/deps/azure-macos-36.yaml b/ci/deps/azure-macos-36.yaml
index f393ed84ecf63..ea0083d1c8308 100644
--- a/ci/deps/azure-macos-36.yaml
+++ b/ci/deps/azure-macos-36.yaml
@@ -26,6 +26,7 @@ dependencies:
   - pytables
   - python-dateutil==2.6.1
   - pytz
+  - scipy>=1.1
   - xarray
   - xlrd
   - xlsxwriter
diff --git a/pandas/core/nanops.py b/pandas/core/nanops.py
index c91262b24dd4e..bc3eacff468d8 100644
--- a/pandas/core/nanops.py
+++ b/pandas/core/nanops.py
@@ -1305,7 +1305,6 @@ def nancorr(
 
 def get_corr_func(method) -> Callable:
     if method in ["kendall", "spearman", "pearson"]:
-        import scipy.stats
         from scipy.stats import kendalltau, spearmanr
     elif callable(method):
         return method

From cc210dbccfe320ae586dd411e47d4c689787bc9e Mon Sep 17 00:00:00 2001
From: MomIsBestFriend <>
Date: Tue, 31 Dec 2019 14:02:08 +0200
Subject: [PATCH 04/11] Fixes for review

---
 pandas/core/nanops.py | 15 +++++++++++----
 1 file changed, 11 insertions(+), 4 deletions(-)

diff --git a/pandas/core/nanops.py b/pandas/core/nanops.py
index bc3eacff468d8..00896773d08ee 100644
--- a/pandas/core/nanops.py
+++ b/pandas/core/nanops.py
@@ -857,7 +857,7 @@ def reduction(
         axis: Optional[int] = None,
         skipna: bool = True,
         mask: Optional[np.ndarray] = None,
-    ) -> np.ndarray:
+    ) -> Dtype:
 
         values, mask, dtype, dtype_max, fill_value = _get_values(
             values, skipna, fill_value_typ=fill_value_typ, mask=mask
@@ -1137,7 +1137,7 @@ def nanprod(
     skipna: bool = True,
     min_count: int = 0,
     mask: Optional[np.ndarray] = None,
-):
+) -> Dtype:
     """
     Parameters
     ----------
@@ -1150,7 +1150,8 @@ def nanprod(
 
     Returns
     -------
-    The product of all elements on a given axis. ( NaNs are treated as 1)
+    Dtype
+        The product of all elements on a given axis. ( NaNs are treated as 1)
 
     Examples
     --------
@@ -1242,7 +1243,13 @@ def _maybe_null_out(
     mask: Optional[np.ndarray],
     shape: Tuple,
     min_count: int = 1,
-) -> np.ndarray:
+) -> Dtype:
+    """
+    Returns
+    -------
+    Dtype
+        The product of all elements on a given axis. ( NaNs are treated as 1)
+    """
     if mask is not None and axis is not None and getattr(result, "ndim", False):
         null_mask = (mask.shape[axis] - mask.sum(axis) - min_count) < 0
         if np.any(null_mask):

From ddd4861f14d19ba6dae9a95b1761dc7d82bc1c32 Mon Sep 17 00:00:00 2001
From: MomIsBestFriend <>
Date: Tue, 31 Dec 2019 14:18:34 +0200
Subject: [PATCH 05/11] Added dtype annotation

---
 pandas/core/nanops.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pandas/core/nanops.py b/pandas/core/nanops.py
index 00896773d08ee..e829731393f41 100644
--- a/pandas/core/nanops.py
+++ b/pandas/core/nanops.py
@@ -654,7 +654,7 @@ def _get_counts_nanvar(
     mask: Optional[np.ndarray],
     axis: Optional[int],
     ddof: int,
-    dtype=float,
+    dtype: Dtype = float,
 ) -> Tuple[Union[int, np.ndarray], Union[int, np.ndarray]]:
     """ Get the count of non-null values along an axis, accounting
     for degrees of freedom.

From 074494e12c55a5de65eccfb81d698249280a646b Mon Sep 17 00:00:00 2001
From: MomIsBestFriend <>
Date: Wed, 1 Jan 2020 15:29:13 +0200
Subject: [PATCH 06/11] Removed changes that are not typing related

---
 ci/deps/azure-36-32bit.yaml | 1 -
 ci/deps/azure-macos-36.yaml | 1 -
 pandas/core/nanops.py       | 2 +-
 3 files changed, 1 insertion(+), 3 deletions(-)

diff --git a/ci/deps/azure-36-32bit.yaml b/ci/deps/azure-36-32bit.yaml
index fa294be78b731..cf3fca307481f 100644
--- a/ci/deps/azure-36-32bit.yaml
+++ b/ci/deps/azure-36-32bit.yaml
@@ -18,7 +18,6 @@ dependencies:
   - numpy=1.14.*
   - python-dateutil
   - pytz=2017.2
-  - scipy>=1.1
 
   # see comment above
   - pip
diff --git a/ci/deps/azure-macos-36.yaml b/ci/deps/azure-macos-36.yaml
index ea0083d1c8308..f393ed84ecf63 100644
--- a/ci/deps/azure-macos-36.yaml
+++ b/ci/deps/azure-macos-36.yaml
@@ -26,7 +26,6 @@ dependencies:
   - pytables
   - python-dateutil==2.6.1
   - pytz
-  - scipy>=1.1
   - xarray
   - xlrd
   - xlsxwriter
diff --git a/pandas/core/nanops.py b/pandas/core/nanops.py
index e829731393f41..6bd7e2dbd287d 100644
--- a/pandas/core/nanops.py
+++ b/pandas/core/nanops.py
@@ -1311,7 +1311,7 @@ def nancorr(
 
 
 def get_corr_func(method) -> Callable:
-    if method in ["kendall", "spearman", "pearson"]:
+    if method in ["kendall", "spearman"]:
         from scipy.stats import kendalltau, spearmanr
     elif callable(method):
         return method

From 5c2ecef4ea73bf43588072be383a86e38c14a718 Mon Sep 17 00:00:00 2001
From: MomIsBestFriend <>
Date: Sun, 5 Jan 2020 09:46:39 +0200
Subject: [PATCH 07/11] Removed 'Dtype' as a return type

---
 pandas/core/nanops.py | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/pandas/core/nanops.py b/pandas/core/nanops.py
index c7900ec4fa972..e5737f9efd2e5 100644
--- a/pandas/core/nanops.py
+++ b/pandas/core/nanops.py
@@ -483,7 +483,7 @@ def nansum(
     skipna: bool = True,
     min_count: int = 0,
     mask: Optional[np.ndarray] = None,
-) -> Dtype:
+) -> float:
     """
     Sum the elements along an axis ignoring NaNs
 
@@ -1137,7 +1137,7 @@ def nanprod(
     skipna: bool = True,
     min_count: int = 0,
     mask: Optional[np.ndarray] = None,
-) -> Dtype:
+) -> float:
     """
     Parameters
     ----------
@@ -1243,7 +1243,7 @@ def _maybe_null_out(
     mask: Optional[np.ndarray],
     shape: Tuple,
     min_count: int = 1,
-) -> Dtype:
+) -> float:
     """
     Returns
     -------

From 57d9502a98b2a4dbda5b92a3959ef28354549133 Mon Sep 17 00:00:00 2001
From: MomIsBestFriend <>
Date: Tue, 14 Jan 2020 15:01:52 +0200
Subject: [PATCH 08/11] Reverted typing

---
 pandas/core/nanops.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pandas/core/nanops.py b/pandas/core/nanops.py
index d8090cb58b222..85454e2950546 100644
--- a/pandas/core/nanops.py
+++ b/pandas/core/nanops.py
@@ -1286,7 +1286,7 @@ def _zero_out_fperr(arg):
 def nancorr(
     a: np.ndarray,
     b: np.ndarray,
-    method: str = "pearson",
+    method="pearson",
     min_periods: Optional[int] = None,
 ):
     """

From 6b55a1362affcbccc389d099965ec77c5ba50512 Mon Sep 17 00:00:00 2001
From: MomIsBestFriend <>
Date: Tue, 14 Jan 2020 15:33:04 +0200
Subject: [PATCH 09/11] List issues

---
 pandas/core/nanops.py | 5 +----
 1 file changed, 1 insertion(+), 4 deletions(-)

diff --git a/pandas/core/nanops.py b/pandas/core/nanops.py
index 85454e2950546..51c6d8be50653 100644
--- a/pandas/core/nanops.py
+++ b/pandas/core/nanops.py
@@ -1284,10 +1284,7 @@ def _zero_out_fperr(arg):
 
 @disallow("M8", "m8")
 def nancorr(
-    a: np.ndarray,
-    b: np.ndarray,
-    method="pearson",
-    min_periods: Optional[int] = None,
+    a: np.ndarray, b: np.ndarray, method="pearson", min_periods: Optional[int] = None,
 ):
     """
     a, b: ndarrays

From 328356467eb6d4b636a2e5acf696b059648ce5b5 Mon Sep 17 00:00:00 2001
From: MomIsBestFriend <>
Date: Sat, 18 Jan 2020 23:50:09 +0200
Subject: [PATCH 10/11] Changed the name of "dt" to "dtype"

Ref: https://github.com/pandas-dev/pandas/pull/30461#discussion_r368243516
---
 pandas/core/nanops.py | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/pandas/core/nanops.py b/pandas/core/nanops.py
index 51c6d8be50653..16843caf3f1a1 100644
--- a/pandas/core/nanops.py
+++ b/pandas/core/nanops.py
@@ -132,10 +132,10 @@ def f(
         return f
 
 
-def _bn_ok_dtype(dt: Dtype, name: str) -> bool:
+def _bn_ok_dtype(dtype: Dtype, name: str) -> bool:
     # Bottleneck chokes on datetime64
-    if not is_object_dtype(dt) and not (
-        is_datetime_or_timedelta_dtype(dt) or is_datetime64tz_dtype(dt)
+    if not is_object_dtype(dtype) and not (
+        is_datetime_or_timedelta_dtype(dtype) or is_datetime64tz_dtype(dtype)
     ):
 
         # GH 15507

From 7442310a426f9160abab5e201c10b8ad4590b25d Mon Sep 17 00:00:00 2001
From: MomIsBestFriend <>
Date: Sun, 19 Jan 2020 00:40:44 +0200
Subject: [PATCH 11/11] Removed any newly added annotation of Callable/str

This is because no matter what typing annotation combination of "method"
is being used "Union[Callable, str]" or "Callable" or "str" mypy is
raising errors
---
 pandas/core/nanops.py | 22 ++++++++++------------
 1 file changed, 10 insertions(+), 12 deletions(-)

diff --git a/pandas/core/nanops.py b/pandas/core/nanops.py
index 16843caf3f1a1..2bf2be082f639 100644
--- a/pandas/core/nanops.py
+++ b/pandas/core/nanops.py
@@ -1,7 +1,7 @@
 import functools
 import itertools
 import operator
-from typing import Any, Callable, Optional, Tuple, Union
+from typing import Any, Optional, Tuple, Union
 
 import numpy as np
 
@@ -56,7 +56,7 @@ def __init__(self, *dtypes):
     def check(self, obj) -> bool:
         return hasattr(obj, "dtype") and issubclass(obj.dtype.type, self.dtypes)
 
-    def __call__(self, f) -> Callable:
+    def __call__(self, f):
         @functools.wraps(f)
         def _f(*args, **kwargs):
             obj_iter = itertools.chain(args, kwargs.values())
@@ -81,11 +81,11 @@ def _f(*args, **kwargs):
 
 
 class bottleneck_switch:
-    def __init__(self, name: Optional[str] = None, **kwargs):
+    def __init__(self, name=None, **kwargs):
         self.name = name
         self.kwargs = kwargs
 
-    def __call__(self, alt: Callable) -> Callable:
+    def __call__(self, alt):
         bn_name = self.name or alt.__name__
 
         try:
@@ -167,9 +167,7 @@ def _has_infs(result) -> bool:
 
 
 def _get_fill_value(
-    dtype: Dtype,
-    fill_value: Optional[Scalar] = None,
-    fill_value_typ: Optional[str] = None,
+    dtype: Dtype, fill_value: Optional[Scalar] = None, fill_value_typ=None
 ):
     """ return the correct fill value for the dtype of the values """
     if fill_value is not None:
@@ -850,7 +848,7 @@ def nansem(
     return np.sqrt(var) / np.sqrt(count)
 
 
-def _nanminmax(meth: str, fill_value_typ: str) -> Callable:
+def _nanminmax(meth, fill_value_typ):
     @bottleneck_switch(name="nan" + meth)
     def reduction(
         values: np.ndarray,
@@ -1307,7 +1305,7 @@ def nancorr(
     return f(a, b)
 
 
-def get_corr_func(method) -> Callable:
+def get_corr_func(method):
     if method in ["kendall", "spearman"]:
         from scipy.stats import kendalltau, spearmanr
     elif method in ["pearson"]:
@@ -1381,7 +1379,7 @@ def _ensure_numeric(x):
 # NA-friendly array comparisons
 
 
-def make_nancomp(op) -> Callable:
+def make_nancomp(op):
     def f(x, y):
         xmask = isna(x)
         ymask = isna(y)
@@ -1409,7 +1407,7 @@ def f(x, y):
 
 
 def _nanpercentile_1d(
-    values: np.ndarray, mask: np.ndarray, q, na_value: Scalar, interpolation: str
+    values: np.ndarray, mask: np.ndarray, q, na_value: Scalar, interpolation
 ) -> Union[Scalar, np.ndarray]:
     """
     Wrapper for np.percentile that skips missing values, specialized to
@@ -1448,7 +1446,7 @@ def nanpercentile(
     na_value,
     mask: np.ndarray,
     ndim: int,
-    interpolation: str,
+    interpolation,
 ):
     """
     Wrapper for np.percentile that skips missing values.