First cleanup pass for pandas.core.arrays

pandas/core/arrays/array_.py

@@ -1,8 +1,13 @@
+from typing import Optional, Sequence, Union
+
+import numpy as np
+
 from pandas._libs import lib, tslibs
 
+from pandas.core.arrays.base import ExtensionArray
 from pandas.core.dtypes.common import (
     is_datetime64_ns_dtype, is_extension_array_dtype, is_timedelta64_ns_dtype)
-from pandas.core.dtypes.dtypes import registry
+from pandas.core.dtypes.dtypes import ExtensionDtype, registry
 
 from pandas import compat
 

pandas/core/arrays/base.py

@@ -6,6 +6,7 @@
    without warning.
 """
 import operator
+from typing import Any, Callable, Optional, Sequence, Tuple, Union
 
 import numpy as np
 
@@ -15,6 +16,7 @@
 from pandas.util._decorators import Appender, Substitution
 
 from pandas.core.dtypes.common import is_list_like
+from pandas.core.dtypes.dtypes import ExtensionDtype
 from pandas.core.dtypes.generic import ABCIndexClass, ABCSeries
 from pandas.core.dtypes.missing import isna
 
@@ -365,7 +367,7 @@ def isna(self):
         raise AbstractMethodError(self)
 
     def _values_for_argsort(self):
-        # type: () -> ndarray
+        # type: () -> np.ndarray
         """
         Return values for sorting.
 
@@ -597,7 +599,7 @@ def searchsorted(self, value, side="left", sorter=None):
         return arr.searchsorted(value, side=side, sorter=sorter)
 
     def _values_for_factorize(self):
-        # type: () -> Tuple[ndarray, Any]
+        # type: () -> Tuple[np.ndarray, Any]
         """
         Return an array and missing value suitable for factorization.
 
@@ -622,7 +624,7 @@ def _values_for_factorize(self):
         return self.astype(object), np.nan
 
     def factorize(self, na_sentinel=-1):
-        # type: (int) -> Tuple[ndarray, ExtensionArray]
+        # type: (int) -> Tuple[np.ndarray, ExtensionArray]
         """
         Encode the extension array as an enumerated type.
 

pandas/core/arrays/datetimelike.py

@@ -2,15 +2,17 @@
 from datetime import datetime, timedelta
 import operator
 import warnings
+from typing import Union, Sequence, Tuple
 
 import numpy as np
 
 from pandas._libs import NaT, algos, iNaT, lib
+from pandas._libs.tslibs.nattype import NaTType
 from pandas._libs.tslibs.period import (
     DIFFERENT_FREQ, IncompatibleFrequency, Period)
 from pandas._libs.tslibs.timedeltas import Timedelta, delta_to_nanoseconds
 from pandas._libs.tslibs.timestamps import (
-    RoundTo, maybe_integer_op_deprecated, round_nsint64)
+    RoundTo, maybe_integer_op_deprecated, round_nsint64, Timestamp)
 import pandas.compat as compat
 from pandas.compat.numpy import function as nv
 from pandas.errors import (
@@ -350,7 +352,7 @@ def __iter__(self):
 
     @property
     def asi8(self):
-        # type: () -> ndarray
+        # type: () -> np.ndarray
         """
         Integer representation of the values.
 

pandas/core/arrays/datetimes.py

@@ -2,6 +2,7 @@
 from datetime import datetime, time, timedelta
 import textwrap
 import warnings
+from typing import Union
 
 import numpy as np
 from pytz import utc

pandas/core/arrays/integer.py

@@ -510,7 +510,7 @@ def value_counts(self, dropna=True):
         return Series(array, index=index)
 
     def _values_for_argsort(self):
-        # type: () -> ndarray
+        # type: () -> np.ndarray
         """Return values for sorting.
 
         Returns

pandas/core/arrays/period.py

@@ -1,17 +1,21 @@
 # -*- coding: utf-8 -*-
 from datetime import timedelta
 import operator
+from typing import Any, Callable, List, Optional, Sequence, Union
 
 import numpy as np
 
 from pandas._libs.tslibs import (
     NaT, frequencies as libfrequencies, iNaT, period as libperiod)
+from pandas._libs.tslibs.nattype import NaTType
 from pandas._libs.tslibs.fields import isleapyear_arr
 from pandas._libs.tslibs.period import (
     DIFFERENT_FREQ, IncompatibleFrequency, Period, get_period_field_arr,
     period_asfreq_arr)
 from pandas._libs.tslibs.timedeltas import Timedelta, delta_to_nanoseconds
 import pandas.compat as compat
+from pandas.core.arrays.base import ExtensionArray
+from pandas.core.indexes.base import Index
 from pandas.util._decorators import Appender, cache_readonly
 
 from pandas.core.dtypes.common import (
@@ -132,7 +136,7 @@ class PeriodArray(dtl.DatetimeLikeArrayMixin, dtl.DatelikeOps):
     _scalar_type = Period
 
     # Names others delegate to us
-    _other_ops = []
+    _other_ops = []     # type: List[str]
     _bool_ops = ['is_leap_year']
     _object_ops = ['start_time', 'end_time', 'freq']
     _field_ops = ['year', 'month', 'day', 'hour', 'minute', 'second',

pandas/core/arrays/sparse.py

@@ -7,12 +7,13 @@
 import operator
 import re
 import warnings
+from typing import Any, Callable, Type, Union
 
 import numpy as np
 
 from pandas._libs import index as libindex, lib
 import pandas._libs.sparse as splib
-from pandas._libs.sparse import BlockIndex, IntIndex
+from pandas._libs.sparse import BlockIndex, IntIndex, SparseIndex
 from pandas._libs.tslibs import NaT
 import pandas.compat as compat
 from pandas.compat.numpy import function as nv
@@ -79,7 +80,7 @@ class SparseDtype(ExtensionDtype):
     _metadata = ('_dtype', '_fill_value', '_is_na_fill_value')
 
     def __init__(self, dtype=np.float64, fill_value=None):
-        # type: (Union[str, np.dtype, 'ExtensionDtype', type], Any) -> None
+        # type: (Union[str, np.dtype, 'ExtensionDtype', Type], Any) -> None
         from pandas.core.dtypes.missing import na_value_for_dtype
         from pandas.core.dtypes.common import (
             pandas_dtype, is_string_dtype, is_scalar
@@ -372,7 +373,7 @@ def _subtype_with_str(self):
 
 
 def _get_fill(arr):
-    # type: (SparseArray) -> ndarray
+    # type: (SparseArray) -> np.ndarray
     """
     Create a 0-dim ndarray containing the fill value
 

pandas/core/arrays/timedeltas.py

@@ -4,6 +4,7 @@
 from datetime import timedelta
 import textwrap
 import warnings
+from typing import List
 
 import numpy as np
 
@@ -134,8 +135,8 @@ class TimedeltaArray(dtl.DatetimeLikeArrayMixin, dtl.TimelikeOps):
     _scalar_type = Timedelta
     __array_priority__ = 1000
     # define my properties & methods for delegation
-    _other_ops = []
-    _bool_ops = []
+    _other_ops = []     # type: List[str]
+    _bool_ops = []      # type: List[str]
     _object_ops = ['freq']
     _field_ops = ['days', 'seconds', 'microseconds', 'nanoseconds']
     _datetimelike_ops = _field_ops + _object_ops + _bool_ops