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from typing import Any
import numpy as np
from pandas._typing import npt
class Infinity:
def __eq__(self, other) -> bool: ...
def __ne__(self, other) -> bool: ...
def __lt__(self, other) -> bool: ...
def __le__(self, other) -> bool: ...
def __gt__(self, other) -> bool: ...
def __ge__(self, other) -> bool: ...
class NegInfinity:
def __eq__(self, other) -> bool: ...
def __ne__(self, other) -> bool: ...
def __lt__(self, other) -> bool: ...
def __le__(self, other) -> bool: ...
def __gt__(self, other) -> bool: ...
def __ge__(self, other) -> bool: ...
def unique_deltas(
arr: np.ndarray, # const int64_t[:]
) -> np.ndarray: ... # np.ndarray[np.int64, ndim=1]
def is_lexsorted(list_of_arrays: list[npt.NDArray[np.int64]]) -> bool: ...
def groupsort_indexer(
index: np.ndarray, # const int64_t[:]
ngroups: int,
) -> tuple[
np.ndarray, # ndarray[int64_t, ndim=1]
np.ndarray, # ndarray[int64_t, ndim=1]
]: ...
def kth_smallest(
arr: np.ndarray, # numeric[:]
k: int,
) -> Any: ... # numeric
# ----------------------------------------------------------------------
# Pairwise correlation/covariance
def nancorr(
mat: npt.NDArray[np.float64], # const float64_t[:, :]
cov: bool = ...,
minp: int | None = ...,
) -> npt.NDArray[np.float64]: ... # ndarray[float64_t, ndim=2]
def nancorr_spearman(
mat: npt.NDArray[np.float64], # ndarray[float64_t, ndim=2]
minp: int = ...,
) -> npt.NDArray[np.float64]: ... # ndarray[float64_t, ndim=2]
# ----------------------------------------------------------------------
def validate_limit(nobs: int | None, limit=...) -> int: ...
def get_fill_indexer(
mask: npt.NDArray[np.bool_],
limit: int | None = None,
) -> npt.NDArray[np.intp]: ...
def pad(
old: np.ndarray, # ndarray[numeric_object_t]
new: np.ndarray, # ndarray[numeric_object_t]
limit=...,
) -> npt.NDArray[np.intp]: ... # np.ndarray[np.intp, ndim=1]
def pad_inplace(
values: np.ndarray, # numeric_object_t[:]
mask: np.ndarray, # uint8_t[:]
limit=...,
) -> None: ...
def pad_2d_inplace(
values: np.ndarray, # numeric_object_t[:, :]
mask: np.ndarray, # const uint8_t[:, :]
limit=...,
) -> None: ...
def backfill(
old: np.ndarray, # ndarray[numeric_object_t]
new: np.ndarray, # ndarray[numeric_object_t]
limit=...,
) -> npt.NDArray[np.intp]: ... # np.ndarray[np.intp, ndim=1]
def backfill_inplace(
values: np.ndarray, # numeric_object_t[:]
mask: np.ndarray, # uint8_t[:]
limit=...,
) -> None: ...
def backfill_2d_inplace(
values: np.ndarray, # numeric_object_t[:, :]
mask: np.ndarray, # const uint8_t[:, :]
limit=...,
) -> None: ...
def is_monotonic(
arr: np.ndarray, # ndarray[numeric_object_t, ndim=1]
timelike: bool,
) -> tuple[bool, bool, bool]: ...
# ----------------------------------------------------------------------
# rank_1d, rank_2d
# ----------------------------------------------------------------------
def rank_1d(
values: np.ndarray, # ndarray[numeric_object_t, ndim=1]
labels: np.ndarray | None = ..., # const int64_t[:]=None
is_datetimelike: bool = ...,
ties_method=...,
ascending: bool = ...,
pct: bool = ...,
na_option=...,
mask: npt.NDArray[np.bool_] | None = ...,
) -> np.ndarray: ... # np.ndarray[float64_t, ndim=1]
def rank_2d(
in_arr: np.ndarray, # ndarray[numeric_object_t, ndim=2]
axis: int = ...,
is_datetimelike: bool = ...,
ties_method=...,
ascending: bool = ...,
na_option=...,
pct: bool = ...,
) -> np.ndarray: ... # np.ndarray[float64_t, ndim=1]
def diff_2d(
arr: np.ndarray, # ndarray[diff_t, ndim=2]
out: np.ndarray, # ndarray[out_t, ndim=2]
periods: int,
axis: int,
datetimelike: bool = ...,
) -> None: ...
def ensure_platform_int(arr: object) -> npt.NDArray[np.intp]: ...
def ensure_object(arr: object) -> npt.NDArray[np.object_]: ...
def ensure_float64(arr: object) -> npt.NDArray[np.float64]: ...
def ensure_int8(arr: object) -> npt.NDArray[np.int8]: ...
def ensure_int16(arr: object) -> npt.NDArray[np.int16]: ...
def ensure_int32(arr: object) -> npt.NDArray[np.int32]: ...
def ensure_int64(arr: object) -> npt.NDArray[np.int64]: ...
def ensure_uint64(arr: object) -> npt.NDArray[np.uint64]: ...
def take_1d_int8_int8(
values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=...
) -> None: ...
def take_1d_int8_int32(
values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=...
) -> None: ...
def take_1d_int8_int64(
values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=...
) -> None: ...
def take_1d_int8_float64(
values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=...
) -> None: ...
def take_1d_int16_int16(
values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=...
) -> None: ...
def take_1d_int16_int32(
values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=...
) -> None: ...
def take_1d_int16_int64(
values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=...
) -> None: ...
def take_1d_int16_float64(
values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=...
) -> None: ...
def take_1d_int32_int32(
values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=...
) -> None: ...
def take_1d_int32_int64(
values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=...
) -> None: ...
def take_1d_int32_float64(
values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=...
) -> None: ...
def take_1d_int64_int64(
values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=...
) -> None: ...
def take_1d_int64_float64(
values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=...
) -> None: ...
def take_1d_float32_float32(
values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=...
) -> None: ...
def take_1d_float32_float64(
values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=...
) -> None: ...
def take_1d_float64_float64(
values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=...
) -> None: ...
def take_1d_object_object(
values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=...
) -> None: ...
def take_1d_bool_bool(
values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=...
) -> None: ...
def take_1d_bool_object(
values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=...
) -> None: ...
def take_2d_axis0_int8_int8(
values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=...
) -> None: ...
def take_2d_axis0_int8_int32(
values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=...
) -> None: ...
def take_2d_axis0_int8_int64(
values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=...
) -> None: ...
def take_2d_axis0_int8_float64(
values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=...
) -> None: ...
def take_2d_axis0_int16_int16(
values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=...
) -> None: ...
def take_2d_axis0_int16_int32(
values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=...
) -> None: ...
def take_2d_axis0_int16_int64(
values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=...
) -> None: ...
def take_2d_axis0_int16_float64(
values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=...
) -> None: ...
def take_2d_axis0_int32_int32(
values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=...
) -> None: ...
def take_2d_axis0_int32_int64(
values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=...
) -> None: ...
def take_2d_axis0_int32_float64(
values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=...
) -> None: ...
def take_2d_axis0_int64_int64(
values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=...
) -> None: ...
def take_2d_axis0_int64_float64(
values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=...
) -> None: ...
def take_2d_axis0_float32_float32(
values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=...
) -> None: ...
def take_2d_axis0_float32_float64(
values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=...
) -> None: ...
def take_2d_axis0_float64_float64(
values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=...
) -> None: ...
def take_2d_axis0_object_object(
values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=...
) -> None: ...
def take_2d_axis0_bool_bool(
values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=...
) -> None: ...
def take_2d_axis0_bool_object(
values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=...
) -> None: ...
def take_2d_axis1_int8_int8(
values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=...
) -> None: ...
def take_2d_axis1_int8_int32(
values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=...
) -> None: ...
def take_2d_axis1_int8_int64(
values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=...
) -> None: ...
def take_2d_axis1_int8_float64(
values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=...
) -> None: ...
def take_2d_axis1_int16_int16(
values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=...
) -> None: ...
def take_2d_axis1_int16_int32(
values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=...
) -> None: ...
def take_2d_axis1_int16_int64(
values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=...
) -> None: ...
def take_2d_axis1_int16_float64(
values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=...
) -> None: ...
def take_2d_axis1_int32_int32(
values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=...
) -> None: ...
def take_2d_axis1_int32_int64(
values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=...
) -> None: ...
def take_2d_axis1_int32_float64(
values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=...
) -> None: ...
def take_2d_axis1_int64_int64(
values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=...
) -> None: ...
def take_2d_axis1_int64_float64(
values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=...
) -> None: ...
def take_2d_axis1_float32_float32(
values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=...
) -> None: ...
def take_2d_axis1_float32_float64(
values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=...
) -> None: ...
def take_2d_axis1_float64_float64(
values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=...
) -> None: ...
def take_2d_axis1_object_object(
values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=...
) -> None: ...
def take_2d_axis1_bool_bool(
values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=...
) -> None: ...
def take_2d_axis1_bool_object(
values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=...
) -> None: ...
def take_2d_multi_int8_int8(
values: np.ndarray,
indexer: tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]],
out: np.ndarray,
fill_value=...,
) -> None: ...
def take_2d_multi_int8_int32(
values: np.ndarray,
indexer: tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]],
out: np.ndarray,
fill_value=...,
) -> None: ...
def take_2d_multi_int8_int64(
values: np.ndarray,
indexer: tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]],
out: np.ndarray,
fill_value=...,
) -> None: ...
def take_2d_multi_int8_float64(
values: np.ndarray,
indexer: tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]],
out: np.ndarray,
fill_value=...,
) -> None: ...
def take_2d_multi_int16_int16(
values: np.ndarray,
indexer: tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]],
out: np.ndarray,
fill_value=...,
) -> None: ...
def take_2d_multi_int16_int32(
values: np.ndarray,
indexer: tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]],
out: np.ndarray,
fill_value=...,
) -> None: ...
def take_2d_multi_int16_int64(
values: np.ndarray,
indexer: tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]],
out: np.ndarray,
fill_value=...,
) -> None: ...
def take_2d_multi_int16_float64(
values: np.ndarray,
indexer: tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]],
out: np.ndarray,
fill_value=...,
) -> None: ...
def take_2d_multi_int32_int32(
values: np.ndarray,
indexer: tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]],
out: np.ndarray,
fill_value=...,
) -> None: ...
def take_2d_multi_int32_int64(
values: np.ndarray,
indexer: tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]],
out: np.ndarray,
fill_value=...,
) -> None: ...
def take_2d_multi_int32_float64(
values: np.ndarray,
indexer: tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]],
out: np.ndarray,
fill_value=...,
) -> None: ...
def take_2d_multi_int64_float64(
values: np.ndarray,
indexer: tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]],
out: np.ndarray,
fill_value=...,
) -> None: ...
def take_2d_multi_float32_float32(
values: np.ndarray,
indexer: tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]],
out: np.ndarray,
fill_value=...,
) -> None: ...
def take_2d_multi_float32_float64(
values: np.ndarray,
indexer: tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]],
out: np.ndarray,
fill_value=...,
) -> None: ...
def take_2d_multi_float64_float64(
values: np.ndarray,
indexer: tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]],
out: np.ndarray,
fill_value=...,
) -> None: ...
def take_2d_multi_object_object(
values: np.ndarray,
indexer: tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]],
out: np.ndarray,
fill_value=...,
) -> None: ...
def take_2d_multi_bool_bool(
values: np.ndarray,
indexer: tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]],
out: np.ndarray,
fill_value=...,
) -> None: ...
def take_2d_multi_bool_object(
values: np.ndarray,
indexer: tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]],
out: np.ndarray,
fill_value=...,
) -> None: ...
def take_2d_multi_int64_int64(
values: np.ndarray,
indexer: tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]],
out: np.ndarray,
fill_value=...,
) -> None: ...
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