diff --git a/pandas/core/indexes/base.py b/pandas/core/indexes/base.py
index 26d25645b02c6..2246384f41b76 100644
--- a/pandas/core/indexes/base.py
+++ b/pandas/core/indexes/base.py
@@ -21,6 +21,7 @@
TypeVar,
Union,
cast,
+ overload,
)
import warnings
@@ -165,6 +166,8 @@
)
if TYPE_CHECKING:
+ from typing import Literal
+
from pandas import (
CategoricalIndex,
DataFrame,
@@ -3380,7 +3383,7 @@ def get_loc(self, key, method=None, tolerance=None):
@final
def get_indexer(
self, target, method=None, limit=None, tolerance=None
- ) -> np.ndarray:
+ ) -> np.ndarray[np.intp]:
method = missing.clean_reindex_fill_method(method)
target = ensure_index(target)
@@ -3405,7 +3408,7 @@ def get_indexer(
def _get_indexer(
self, target: Index, method=None, limit=None, tolerance=None
- ) -> np.ndarray:
+ ) -> np.ndarray[np.intp]:
if tolerance is not None:
tolerance = self._convert_tolerance(tolerance, target)
@@ -3735,7 +3738,9 @@ def _validate_can_reindex(self, indexer: np.ndarray) -> None:
if not self._index_as_unique and len(indexer):
raise ValueError("cannot reindex from a duplicate axis")
- def reindex(self, target, method=None, level=None, limit=None, tolerance=None):
+ def reindex(
+ self, target, method=None, level=None, limit=None, tolerance=None
+ ) -> Tuple[Index, Optional[np.ndarray[np.intp]]]:
"""
Create index with target's values.
@@ -3863,9 +3868,31 @@ def _reindex_non_unique(self, target):
# --------------------------------------------------------------------
# Join Methods
+ @overload
+ def join(
+ self,
+ other: Index,
+ how: str_t = "left",
+ level=None,
+ return_indexers: Literal[True] = ...,
+ sort: bool = False,
+ ) -> Tuple[Index, Optional[np.ndarray[np.intp]], Optional[np.ndarray[np.intp]]]:
+ ...
+
+ @overload
def join(
self,
- other,
+ other: Index,
+ how: str_t = "left",
+ level=None,
+ return_indexers: Literal[False] = ...,
+ sort: bool = False,
+ ) -> Index:
+ ...
+
+ def join(
+ self,
+ other: Index,
how: str_t = "left",
level=None,
return_indexers: bool = False,
@@ -3915,7 +3942,7 @@ def join(
if len(other) == 0 and how in ("left", "outer"):
join_index = self._view()
if return_indexers:
- rindexer = np.repeat(-1, len(join_index))
+ rindexer = -1 * np.ones(len(join_index), dtype=np.intp)
return join_index, None, rindexer
else:
return join_index
@@ -3923,7 +3950,7 @@ def join(
if len(self) == 0 and how in ("right", "outer"):
join_index = other._view()
if return_indexers:
- lindexer = np.repeat(-1, len(join_index))
+ lindexer = -1 * np.ones(len(join_index), dtype=np.intp)
return join_index, lindexer, None
else:
return join_index
@@ -3996,16 +4023,32 @@ def join(
lindexer = None
else:
lindexer = self.get_indexer(join_index)
+ lindexer = ensure_platform_int(lindexer)
if join_index is other:
rindexer = None
else:
rindexer = other.get_indexer(join_index)
+ rindexer = ensure_platform_int(rindexer)
return join_index, lindexer, rindexer
else:
return join_index
+ @overload
+ def _join_multi(
+ self, other: Index, how: str = "left", return_indexers: Literal[True] = ...
+ ) -> Tuple[
+ MultiIndex, Optional[np.ndarray[np.intp]], Optional[np.ndarray[np.intp]]
+ ]:
+ ...
+
+ @overload
+ def _join_multi(
+ self, other: Index, how: str = "left", return_indexers: Literal[False] = ...
+ ) -> MultiIndex:
+ ...
+
@final
- def _join_multi(self, other, how, return_indexers=True):
+ def _join_multi(self, other: Index, how: str, return_indexers: bool = True):
from pandas.core.indexes.multi import MultiIndex
from pandas.core.reshape.merge import restore_dropped_levels_multijoin
@@ -4083,8 +4126,22 @@ def _join_multi(self, other, how, return_indexers=True):
return result[0], result[2], result[1]
return result
+ @overload
+ def _join_non_unique(
+ self, other: Index, how: str = "left", return_indexers: Literal[True] = ...
+ ) -> Tuple[Index, Optional[np.ndarray[np.intp]], Optional[np.ndarray[np.intp]]]:
+ ...
+
+ @overload
+ def _join_non_unique(
+ self, other: Index, how: str = "left", return_indexers: Literal[False] = ...
+ ) -> Index:
+ ...
+
@final
- def _join_non_unique(self, other, how="left", return_indexers=False):
+ def _join_non_unique(
+ self, other: Index, how: str = "left", return_indexers: bool = False
+ ):
from pandas.core.reshape.merge import get_join_indexers
# We only get here if dtypes match
@@ -4111,9 +4168,38 @@ def _join_non_unique(self, other, how="left", return_indexers=False):
else:
return join_index
+ @overload
+ def _join_level(
+ self,
+ other: Index,
+ level,
+ how: str = "left",
+ return_indexers: bool = False,
+ keep_order: bool = True,
+ ) -> Tuple[
+ MultiIndex, Optional[np.ndarray[np.intp]], Optional[np.ndarray[np.intp]]
+ ]:
+ ...
+
+ @overload
+ def _join_level(
+ self,
+ other: Index,
+ level,
+ how: str = "left",
+ return_indexers: bool = False,
+ keep_order: bool = True,
+ ) -> MultiIndex:
+ ...
+
@final
def _join_level(
- self, other, level, how="left", return_indexers=False, keep_order=True
+ self,
+ other: Index,
+ level,
+ how: str = "left",
+ return_indexers: bool = False,
+ keep_order: bool = True,
):
"""
The join method *only* affects the level of the resulting
@@ -4253,8 +4339,20 @@ def _get_leaf_sorter(labels):
else:
return join_index
+ @overload
+ def _join_monotonic(
+ self, other, how: str = "left", return_indexers: Literal[True] = ...
+ ) -> Tuple[Index, Optional[np.ndarray[np.intp]], Optional[np.ndarray[np.intp]]]:
+ ...
+
+ @overload
+ def _join_monotonic(
+ self, other, how: str = "left", return_indexers: Literal[False] = ...
+ ) -> Index:
+ ...
+
@final
- def _join_monotonic(self, other, how="left", return_indexers=False):
+ def _join_monotonic(self, other, how: str = "left", return_indexers: bool = False):
# We only get here with matching dtypes
assert other.dtype == self.dtype
@@ -5236,6 +5334,18 @@ def get_indexer_for(self, target, **kwargs):
indexer, _ = self.get_indexer_non_unique(target)
return indexer
+ @overload
+ def _get_indexer_non_comparable(
+ self, target: Index, method, unique: Literal[True] = ...
+ ) -> np.ndarray[np.intp]:
+ ...
+
+ @overload
+ def _get_indexer_non_comparable(
+ self, target: Index, method, unique: Literal[False] = ...
+ ) -> Tuple[np.ndarray[np.intp], np.ndarray[np.intp]]:
+ ...
+
@final
def _get_indexer_non_comparable(self, target: Index, method, unique: bool = True):
"""
diff --git a/pandas/core/indexes/category.py b/pandas/core/indexes/category.py
index 62941a23c6459..81766576a8edb 100644
--- a/pandas/core/indexes/category.py
+++ b/pandas/core/indexes/category.py
@@ -3,6 +3,7 @@
Hashable,
List,
Optional,
+ Tuple,
)
import warnings
@@ -386,7 +387,9 @@ def unique(self, level=None):
# of result, not self.
return type(self)._simple_new(result, name=self.name)
- def reindex(self, target, method=None, level=None, limit=None, tolerance=None):
+ def reindex(
+ self, target, method=None, level=None, limit=None, tolerance=None
+ ) -> Tuple[Index, Optional[np.ndarray[np.intp]]]:
"""
Create index with target's values (move/add/delete values as necessary)
@@ -394,7 +397,7 @@ def reindex(self, target, method=None, level=None, limit=None, tolerance=None):
-------
new_index : pd.Index
Resulting index
- indexer : np.ndarray or None
+ indexer : np.ndarray[np.intp] or None
Indices of output values in original index
"""
@@ -484,7 +487,7 @@ def _maybe_cast_indexer(self, key) -> int:
def _get_indexer(
self, target: Index, method=None, limit=None, tolerance=None
- ) -> np.ndarray:
+ ) -> np.ndarray[np.intp]:
if self.equals(target):
return np.arange(len(self), dtype="intp")
@@ -492,11 +495,15 @@ def _get_indexer(
return self._get_indexer_non_unique(target._values)[0]
@Appender(_index_shared_docs["get_indexer_non_unique"] % _index_doc_kwargs)
- def get_indexer_non_unique(self, target):
+ def get_indexer_non_unique(
+ self, target
+ ) -> Tuple[np.ndarray[np.intp], np.ndarray[np.intp]]:
target = ibase.ensure_index(target)
return self._get_indexer_non_unique(target._values)
- def _get_indexer_non_unique(self, values: ArrayLike):
+ def _get_indexer_non_unique(
+ self, values: ArrayLike
+ ) -> Tuple[np.ndarray[np.intp], np.ndarray[np.intp]]:
"""
get_indexer_non_unique but after unrapping the target Index object.
"""
@@ -515,7 +522,7 @@ def _get_indexer_non_unique(self, values: ArrayLike):
codes = self.categories.get_indexer(values)
indexer, missing = self._engine.get_indexer_non_unique(codes)
- return ensure_platform_int(indexer), missing
+ return ensure_platform_int(indexer), ensure_platform_int(missing)
@doc(Index._convert_list_indexer)
def _convert_list_indexer(self, keyarr):
diff --git a/pandas/core/indexes/datetimelike.py b/pandas/core/indexes/datetimelike.py
index 0e32e5c5d2762..fed1158df5b75 100644
--- a/pandas/core/indexes/datetimelike.py
+++ b/pandas/core/indexes/datetimelike.py
@@ -828,7 +828,7 @@ def _union(self, other, sort):
def join(
self,
- other,
+ other: Index,
how: str = "left",
level=None,
return_indexers: bool = False,
diff --git a/pandas/core/indexes/interval.py b/pandas/core/indexes/interval.py
index 86ff95a588217..82bc2b8ec3bc0 100644
--- a/pandas/core/indexes/interval.py
+++ b/pandas/core/indexes/interval.py
@@ -700,7 +700,7 @@ def _get_indexer(
method: Optional[str] = None,
limit: Optional[int] = None,
tolerance: Optional[Any] = None,
- ) -> np.ndarray:
+ ) -> np.ndarray[np.intp]:
if isinstance(target, IntervalIndex):
# equal indexes -> 1:1 positional match
@@ -732,7 +732,9 @@ def _get_indexer(
return ensure_platform_int(indexer)
@Appender(_index_shared_docs["get_indexer_non_unique"] % _index_doc_kwargs)
- def get_indexer_non_unique(self, target: Index) -> Tuple[np.ndarray, np.ndarray]:
+ def get_indexer_non_unique(
+ self, target: Index
+ ) -> Tuple[np.ndarray[np.intp], np.ndarray[np.intp]]:
target = ensure_index(target)
if isinstance(target, IntervalIndex) and not self._should_compare(target):
@@ -751,7 +753,9 @@ def get_indexer_non_unique(self, target: Index) -> Tuple[np.ndarray, np.ndarray]
return ensure_platform_int(indexer), ensure_platform_int(missing)
- def _get_indexer_pointwise(self, target: Index) -> Tuple[np.ndarray, np.ndarray]:
+ def _get_indexer_pointwise(
+ self, target: Index
+ ) -> Tuple[np.ndarray[np.intp], np.ndarray[np.intp]]:
"""
pointwise implementation for get_indexer and get_indexer_non_unique.
"""
diff --git a/pandas/core/indexes/multi.py b/pandas/core/indexes/multi.py
index 7bb3dc5ab4545..565773993084c 100644
--- a/pandas/core/indexes/multi.py
+++ b/pandas/core/indexes/multi.py
@@ -2509,7 +2509,9 @@ def sortlevel(
return new_index, indexer
- def reindex(self, target, method=None, level=None, limit=None, tolerance=None):
+ def reindex(
+ self, target, method=None, level=None, limit=None, tolerance=None
+ ) -> Tuple[Index, Optional[np.ndarray[np.intp]]]:
"""
Create index with target's values (move/add/delete values as necessary)
@@ -2517,7 +2519,7 @@ def reindex(self, target, method=None, level=None, limit=None, tolerance=None):
-------
new_index : pd.MultiIndex
Resulting index
- indexer : np.ndarray or None
+ indexer : np.ndarray[np.intp] or None
Indices of output values in original index.
"""
@@ -2672,7 +2674,7 @@ def _get_partial_string_timestamp_match_key(self, key):
def _get_indexer(
self, target: Index, method=None, limit=None, tolerance=None
- ) -> np.ndarray:
+ ) -> np.ndarray[np.intp]:
# empty indexer
if not len(target):
diff --git a/pandas/core/indexes/range.py b/pandas/core/indexes/range.py
index 05bb32dad6cab..5797390b66f4e 100644
--- a/pandas/core/indexes/range.py
+++ b/pandas/core/indexes/range.py
@@ -395,7 +395,9 @@ def get_loc(self, key, method=None, tolerance=None):
raise KeyError(key)
return super().get_loc(key, method=method, tolerance=tolerance)
- def _get_indexer(self, target: Index, method=None, limit=None, tolerance=None):
+ def _get_indexer(
+ self, target: Index, method=None, limit=None, tolerance=None
+ ) -> np.ndarray[np.intp]:
if com.any_not_none(method, tolerance, limit):
return super()._get_indexer(
target, method=method, tolerance=tolerance, limit=limit
diff --git a/pandas/core/series.py b/pandas/core/series.py
index 9feec7acae4c6..ba49db4760b92 100644
--- a/pandas/core/series.py
+++ b/pandas/core/series.py
@@ -4220,7 +4220,13 @@ def _reduce(
with np.errstate(all="ignore"):
return op(delegate, skipna=skipna, **kwds)
- def _reindex_indexer(self, new_index, indexer, copy):
+ def _reindex_indexer(
+ self,
+ new_index: Optional[Index],
+ indexer: Optional[np.ndarray[np.intp]],
+ copy: bool,
+ ) -> Series:
+ # Note: new_index is None iff indexer is None
if indexer is None:
if copy:
return self.copy()
@@ -4231,7 +4237,7 @@ def _reindex_indexer(self, new_index, indexer, copy):
)
return self._constructor(new_values, index=new_index)
- def _needs_reindex_multi(self, axes, method, level):
+ def _needs_reindex_multi(self, axes, method, level) -> bool:
"""
Check if we do need a multi reindex; this is for compat with
higher dims.