TYP: Annotations in core/indexes/

pandas/core/indexers.py

@@ -144,8 +144,9 @@ def validate_indices(indices: np.ndarray, n: int) -> None:
     if len(indices):
         min_idx = indices.min()
         if min_idx < -1:
-            msg = f"'indices' contains values less than allowed ({min_idx} < -1)"
-            raise ValueError(msg)
+            raise ValueError(
+                f"'indices' contains values less than allowed ({min_idx} < -1)"
+            )
 
         max_idx = indices.max()
         if max_idx >= n:

pandas/core/indexes/accessors.py

@@ -26,8 +26,7 @@ class Properties(PandasDelegate, PandasObject, NoNewAttributesMixin):
     def __init__(self, data, orig):
         if not isinstance(data, ABCSeries):
             raise TypeError(
-                f"cannot convert an object of type {type(data)} to a "
-                "datetimelike index"
+                f"cannot convert an object of type {type(data)} to a datetimelike index"
             )
 
         self._parent = data
@@ -91,9 +90,8 @@ def _delegate_property_get(self, name):
 
     def _delegate_property_set(self, name, value, *args, **kwargs):
         raise ValueError(
-            "modifications to a property of a datetimelike "
-            "object are not supported. Change values on the "
-            "original."
+            "modifications to a property of a datetimelike object are not supported. "
+            "Change values on the original."
         )
 
     def _delegate_method(self, name, *args, **kwargs):
@@ -222,7 +220,7 @@ def to_pytimedelta(self):
 
         Returns
         -------
-        a : numpy.ndarray
+        numpy.ndarray
             Array of 1D containing data with `datetime.timedelta` type.
 
         See Also
@@ -314,8 +312,7 @@ def __new__(cls, data):
 
         if not isinstance(data, ABCSeries):
             raise TypeError(
-                f"cannot convert an object of type {type(data)} to a "
-                "datetimelike index"
+                f"cannot convert an object of type {type(data)} to a datetimelike index"
             )
 
         orig = data if is_categorical_dtype(data) else None

pandas/core/indexes/api.py

@@ -124,7 +124,6 @@ def _get_combined_index(
     -------
     Index
     """
-
     # TODO: handle index names!
     indexes = _get_distinct_objs(indexes)
     if len(indexes) == 0:
@@ -273,7 +272,6 @@ def get_consensus_names(indexes):
     list
         A list representing the consensus 'names' found.
     """
-
     # find the non-none names, need to tupleify to make
     # the set hashable, then reverse on return
     consensus_names = {tuple(i.names) for i in indexes if com.any_not_none(*i.names)}

pandas/core/indexes/base.py

@@ -804,11 +804,10 @@ def _assert_take_fillable(
         # only fill if we are passing a non-None fill_value
         if allow_fill and fill_value is not None:
             if (indices < -1).any():
-                msg = (
+                raise ValueError(
                     "When allow_fill=True and fill_value is not None, "
                     "all indices must be >= -1"
                 )
-                raise ValueError(msg)
             taken = algos.take(
                 values, indices, allow_fill=allow_fill, fill_value=na_value
             )
@@ -1324,8 +1323,7 @@ def set_names(self, names, level=None, inplace=False):
             raise ValueError("Level must be None for non-MultiIndex")
 
         if level is not None and not is_list_like(level) and is_list_like(names):
-            msg = "Names must be a string when a single level is provided."
-            raise TypeError(msg)
+            raise TypeError("Names must be a string when a single level is provided.")
 
         if not is_list_like(names) and level is None and self.nlevels > 1:
             raise TypeError("Must pass list-like as `names`.")
@@ -1421,8 +1419,8 @@ def _validate_index_level(self, level):
         if isinstance(level, int):
             if level < 0 and level != -1:
                 raise IndexError(
-                    f"Too many levels: Index has only 1 level,"
-                    f" {level} is not a valid level number"
+                    "Too many levels: Index has only 1 level, "
+                    f"{level} is not a valid level number"
                 )
             elif level > 0:
                 raise IndexError(

pandas/core/indexes/category.py

@@ -715,9 +715,7 @@ def _convert_list_indexer(self, keyarr, kind=None):
         indexer = self.categories.get_indexer(np.asarray(keyarr))
         if (indexer == -1).any():
             raise KeyError(
-                "a list-indexer must only "
-                "include values that are "
-                "in the categories"
+                "a list-indexer must only include values that are in the categories"
             )
 
         return self.get_indexer(keyarr)

pandas/core/indexes/datetimelike.py

@@ -2,7 +2,7 @@
 Base and utility classes for tseries type pandas objects.
 """
 import operator
-from typing import Set
+from typing import List, Set
 
 import numpy as np
 
@@ -73,7 +73,7 @@ def method(self, other):
 
 class DatetimeIndexOpsMixin(ExtensionOpsMixin):
     """
-    common ops mixin to support a unified interface datetimelike Index
+    Common ops mixin to support a unified interface datetimelike Index.
     """
 
     _data: ExtensionArray
@@ -336,7 +336,7 @@ def _convert_tolerance(self, tolerance, target):
             raise ValueError("list-like tolerance size must match target index size")
         return tolerance
 
-    def tolist(self):
+    def tolist(self) -> List:
         """
         Return a list of the underlying data.
         """
@@ -661,11 +661,12 @@ def _summary(self, name=None):
         Parameters
         ----------
         name : str
-            name to use in the summary representation
+            Name to use in the summary representation.
 
         Returns
         -------
-        String with a summarized representation of the index
+        str
+            Summarized representation of the index.
         """
         formatter = self._formatter_func
         if len(self) > 0:

pandas/core/indexes/datetimes.py

@@ -45,9 +45,10 @@
 
 
 def _new_DatetimeIndex(cls, d):
-    """ This is called upon unpickling, rather than the default which doesn't
-    have arguments and breaks __new__ """
-
+    """
+    This is called upon unpickling, rather than the default which doesn't
+    have arguments and breaks __new__
+    """
     if "data" in d and not isinstance(d["data"], DatetimeIndex):
         # Avoid need to verify integrity by calling simple_new directly
         data = d.pop("data")
@@ -100,9 +101,9 @@ class DatetimeIndex(DatetimeIndexOpsMixin, Int64Index, DatetimeDelegateMixin):
 
     Parameters
     ----------
-    data  : array-like (1-dimensional), optional
+    data : array-like (1-dimensional), optional
         Optional datetime-like data to construct index with.
-    copy  : bool
+    copy : bool
         Make a copy of input ndarray.
     freq : str or pandas offset object, optional
         One of pandas date offset strings or corresponding objects. The string
@@ -273,7 +274,7 @@ def __new__(
     @classmethod
     def _simple_new(cls, values, name=None, freq=None, tz=None, dtype=None):
         """
-        we require the we have a dtype compat for the values
+        We require the we have a dtype compat for the values
         if we are passed a non-dtype compat, then coerce using the constructor
         """
         if isinstance(values, DatetimeArray):
@@ -345,7 +346,13 @@ def tz(self, value):
 
     @cache_readonly
     def _is_dates_only(self) -> bool:
-        """Return a boolean if we are only dates (and don't have a timezone)"""
+        """
+        Return a boolean if we are only dates (and don't have a timezone)
+
+        Returns
+        -------
+        bool
+        """
         from pandas.io.formats.format import _is_dates_only
 
         return _is_dates_only(self.values) and self.tz is None
@@ -360,7 +367,9 @@ def __reduce__(self):
         return _new_DatetimeIndex, (type(self), d), None
 
     def __setstate__(self, state):
-        """Necessary for making this object picklable"""
+        """
+        Necessary for making this object picklable.
+        """
         if isinstance(state, dict):
             super().__setstate__(state)
 
@@ -393,7 +402,9 @@ def __setstate__(self, state):
     _unpickle_compat = __setstate__
 
     def _convert_for_op(self, value):
-        """ Convert value to be insertable to ndarray """
+        """
+        Convert value to be insertable to ndarray.
+        """
         if self._has_same_tz(value):
             return _to_M8(value)
         raise ValueError("Passed item and index have different timezone")
@@ -461,7 +472,7 @@ def _union(self, other, sort):
 
     def union_many(self, others):
         """
-        A bit of a hack to accelerate unioning a collection of indexes
+        A bit of a hack to accelerate unioning a collection of indexes.
         """
         this = self
 
@@ -489,7 +500,7 @@ def union_many(self, others):
                     this._data._dtype = dtype
         return this
 
-    def _can_fast_union(self, other):
+    def _can_fast_union(self, other) -> bool:
         if not isinstance(other, DatetimeIndex):
             return False
 
@@ -581,7 +592,7 @@ def intersection(self, other, sort=False):
 
         Returns
         -------
-        y : Index or DatetimeIndex or TimedeltaIndex
+        Index or DatetimeIndex or TimedeltaIndex
         """
         return super().intersection(other, sort=sort)
 
@@ -699,7 +710,9 @@ def snap(self, freq="S"):
         # we know it conforms; skip check
         return DatetimeIndex._simple_new(snapped, name=self.name, tz=self.tz, freq=freq)
 
-    def join(self, other, how="left", level=None, return_indexers=False, sort=False):
+    def join(
+        self, other, how: str = "left", level=None, return_indexers=False, sort=False
+    ):
         """
         See Index.join
         """
@@ -840,9 +853,8 @@ def _parsed_string_to_bounds(self, reso, parsed):
         if parsed.tzinfo is not None:
             if self.tz is None:
                 raise ValueError(
-                    "The index must be timezone aware "
-                    "when indexing with a date string with a "
-                    "UTC offset"
+                    "The index must be timezone aware when indexing "
+                    "with a date string with a UTC offset"
                 )
             start = start.tz_localize(parsed.tzinfo).tz_convert(self.tz)
             end = end.tz_localize(parsed.tzinfo).tz_convert(self.tz)
@@ -851,7 +863,16 @@ def _parsed_string_to_bounds(self, reso, parsed):
             end = end.tz_localize(self.tz)
         return start, end
 
-    def _partial_date_slice(self, reso, parsed, use_lhs=True, use_rhs=True):
+    def _partial_date_slice(
+        self, reso: str, parsed, use_lhs: bool = True, use_rhs: bool = True
+    ):
+        """
+        Parameters
+        ----------
+        reso : str
+        use_lhs : bool, default True
+        use_rhs : bool, default True
+        """
         is_monotonic = self.is_monotonic
         if (
             is_monotonic

pandas/core/indexes/frozen.py

@@ -35,7 +35,7 @@ def union(self, other) -> "FrozenList":
 
         Returns
         -------
-        diff : FrozenList
+        FrozenList
             The collection difference between self and other.
         """
         if isinstance(other, tuple):
@@ -53,7 +53,7 @@ def difference(self, other) -> "FrozenList":
 
         Returns
         -------
-        diff : FrozenList
+        FrozenList
             The collection difference between self and other.
         """
         other = set(other)
@@ -92,7 +92,9 @@ def __hash__(self):
         return hash(tuple(self))
 
     def _disabled(self, *args, **kwargs):
-        """This method will not function because object is immutable."""
+        """
+        This method will not function because object is immutable.
+        """
         raise TypeError(f"'{type(self).__name__}' does not support mutable operations.")
 
     def __str__(self) -> str: