From 6982fa0ad2a5e08a06bb8ac186a8b77c35c22ff8 Mon Sep 17 00:00:00 2001
From: Matthew Zeitlin <mzeitlin@caltech.edu>
Date: Sat, 11 Sep 2021 11:23:30 -0400
Subject: [PATCH 1/2] TYP: SparseArray

---
 pandas/core/arrays/sparse/array.py | 32 ++++++++++++++++++------------
 pandas/core/arrays/sparse/dtype.py |  2 +-
 2 files changed, 20 insertions(+), 14 deletions(-)

diff --git a/pandas/core/arrays/sparse/array.py b/pandas/core/arrays/sparse/array.py
index 77142ef450487..688e90cce4da6 100644
--- a/pandas/core/arrays/sparse/array.py
+++ b/pandas/core/arrays/sparse/array.py
@@ -98,6 +98,8 @@ class ellipsis(Enum):
 
     from pandas._typing import NumpySorter
 
+    from pandas import Series
+
 else:
     ellipsis = type(Ellipsis)
 
@@ -328,7 +330,7 @@ def __init__(
         fill_value=None,
         kind="integer",
         dtype: Dtype | None = None,
-        copy=False,
+        copy: bool = False,
     ):
 
         if fill_value is None and isinstance(dtype, SparseDtype):
@@ -558,7 +560,7 @@ def __setitem__(self, key, value):
         raise TypeError(msg)
 
     @classmethod
-    def _from_sequence(cls, scalars, *, dtype: Dtype | None = None, copy=False):
+    def _from_sequence(cls, scalars, *, dtype: Dtype | None = None, copy: bool = False):
         return cls(scalars, dtype=dtype)
 
     @classmethod
@@ -606,7 +608,7 @@ def fill_value(self, value):
         self._dtype = SparseDtype(self.dtype.subtype, value)
 
     @property
-    def kind(self) -> str:
+    def kind(self):
         """
         The kind of sparse index for this array. One of {'integer', 'block'}.
         """
@@ -625,10 +627,10 @@ def __len__(self) -> int:
         return self.sp_index.length
 
     @property
-    def _null_fill_value(self):
+    def _null_fill_value(self) -> bool:
         return self._dtype._is_na_fill_value
 
-    def _fill_value_matches(self, fill_value):
+    def _fill_value_matches(self, fill_value) -> bool:
         if self._null_fill_value:
             return isna(fill_value)
         else:
@@ -725,7 +727,7 @@ def fillna(self, value=None, method=None, limit=None):
 
         return self._simple_new(new_values, self._sparse_index, new_dtype)
 
-    def shift(self, periods=1, fill_value=None):
+    def shift(self, periods: int = 1, fill_value=None):
 
         if not len(self) or periods == 0:
             return self.copy()
@@ -794,7 +796,7 @@ def factorize(self, na_sentinel=-1):
         uniques = SparseArray(uniques, dtype=self.dtype)  # type: ignore[assignment]
         return codes, uniques
 
-    def value_counts(self, dropna: bool = True):
+    def value_counts(self, dropna: bool = True) -> Series:
         """
         Returns a Series containing counts of unique values.
 
@@ -909,24 +911,28 @@ def _get_val_at(self, loc):
             val = maybe_box_datetimelike(val, self.sp_values.dtype)
             return val
 
-    def take(self, indices, *, allow_fill=False, fill_value=None) -> SparseArray:
+    def take(
+        self, indices, *, allow_fill: bool = False, fill_value=None
+    ) -> SparseArray:
         if is_scalar(indices):
             raise ValueError(f"'indices' must be an array, not a scalar '{indices}'.")
         indices = np.asarray(indices, dtype=np.int32)
 
+        dtype = None
         if indices.size == 0:
             result = np.array([], dtype="object")
-            kwargs = {"dtype": self.dtype}
+            dtype = self.dtype
         elif allow_fill:
             result = self._take_with_fill(indices, fill_value=fill_value)
-            kwargs = {}
         else:
             # error: Incompatible types in assignment (expression has type
             # "Union[ndarray, SparseArray]", variable has type "ndarray")
             result = self._take_without_fill(indices)  # type: ignore[assignment]
-            kwargs = {"dtype": self.dtype}
+            dtype = self.dtype
 
-        return type(self)(result, fill_value=self.fill_value, kind=self.kind, **kwargs)
+        return type(self)(
+            result, fill_value=self.fill_value, kind=self.kind, dtype=dtype
+        )
 
     def _take_with_fill(self, indices, fill_value=None) -> np.ndarray:
         if fill_value is None:
@@ -1103,7 +1109,7 @@ def _concat_same_type(
 
         return cls(data, sparse_index=sp_index, fill_value=fill_value)
 
-    def astype(self, dtype: AstypeArg | None = None, copy=True):
+    def astype(self, dtype: AstypeArg | None = None, copy: bool = True):
         """
         Change the dtype of a SparseArray.
 
diff --git a/pandas/core/arrays/sparse/dtype.py b/pandas/core/arrays/sparse/dtype.py
index a8f8f10e8716d..6684e559b6f88 100644
--- a/pandas/core/arrays/sparse/dtype.py
+++ b/pandas/core/arrays/sparse/dtype.py
@@ -149,7 +149,7 @@ def fill_value(self):
         return self._fill_value
 
     @property
-    def _is_na_fill_value(self):
+    def _is_na_fill_value(self) -> bool:
         return isna(self.fill_value)
 
     @property

From 07497651b4de85b0d71961ddd63559ff847d48d6 Mon Sep 17 00:00:00 2001
From: Matthew Zeitlin <mzeitlin@caltech.edu>
Date: Sat, 11 Sep 2021 11:25:47 -0400
Subject: [PATCH 2/2] Fix accidental removal

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

diff --git a/pandas/core/arrays/sparse/array.py b/pandas/core/arrays/sparse/array.py
index 688e90cce4da6..58adcc4e31c44 100644
--- a/pandas/core/arrays/sparse/array.py
+++ b/pandas/core/arrays/sparse/array.py
@@ -608,7 +608,7 @@ def fill_value(self, value):
         self._dtype = SparseDtype(self.dtype.subtype, value)
 
     @property
-    def kind(self):
+    def kind(self) -> str:
         """
         The kind of sparse index for this array. One of {'integer', 'block'}.
         """