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Merge pull request #170 from pandas-dev/master
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‎.pre-commit-config.yaml

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@@ -206,3 +206,8 @@ repos:
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files: ^pandas/core/
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exclude: ^pandas/core/api\.py$
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types: [python]
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- id: no-bool-in-core-generic
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name: Use bool_t instead of bool in pandas/core/generic.py
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entry: python scripts/no_bool_in_generic.py
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language: python
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files: ^pandas/core/generic\.py$

‎LICENSES/PYUPGRADE_LICENSE

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Copyright (c) 2017 Anthony Sottile
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal
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in the Software without restriction, including without limitation the rights
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to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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copies of the Software, and to permit persons to whom the Software is
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furnished to do so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included in
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all copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
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THE SOFTWARE.

‎pandas/_libs/algos.pyi

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# Note: this covers algos.pyx and algos_common_helper but NOT algos_take_helper
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from typing import Any
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import numpy as np
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class Infinity:
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"""
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Provide a positive Infinity comparison method for ranking.
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"""
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def __eq__(self, other) -> bool: ...
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def __ne__(self, other) -> bool: ...
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def __lt__(self, other) -> bool: ...
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def __le__(self, other) -> bool: ...
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def __gt__(self, other) -> bool: ...
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def __ge__(self, other) -> bool: ...
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class NegInfinity:
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"""
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Provide a negative Infinity comparison method for ranking.
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"""
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def __eq__(self, other) -> bool: ...
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def __ne__(self, other) -> bool: ...
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def __lt__(self, other) -> bool: ...
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def __le__(self, other) -> bool: ...
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def __gt__(self, other) -> bool: ...
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def __ge__(self, other) -> bool: ...
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def unique_deltas(
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arr: np.ndarray, # const int64_t[:]
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) -> np.ndarray: ... # np.ndarray[np.int64, ndim=1]
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def is_lexsorted(list_of_arrays: list[np.ndarray]) -> bool: ...
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def groupsort_indexer(
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index: np.ndarray, # const int64_t[:]
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ngroups: int,
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) -> tuple[
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np.ndarray, # ndarray[int64_t, ndim=1]
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np.ndarray, # ndarray[int64_t, ndim=1]
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]:
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...
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def kth_smallest(
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a: np.ndarray, # numeric[:]
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k: int,
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) -> Any: ... # numeric
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# ----------------------------------------------------------------------
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# Pairwise correlation/covariance
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def nancorr(
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mat: np.ndarray, # const float64_t[:, :]
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cov: bool = False,
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minp=None,
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) -> np.ndarray: # np.ndarray[float64_t, ndim=2]
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...
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def nancorr_spearman(
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mat: np.ndarray, # ndarray[float64_t, ndim=2]
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minp: int = 1,
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) -> np.ndarray: # np.ndarray[np.float64, ndim=2]
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...
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def nancorr_kendall(
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mat: np.ndarray, # ndarray[float64_t, ndim=2]
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minp: int = 1,
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) -> np.ndarray: # np.ndarray[float64, ndim=2]
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...
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# ----------------------------------------------------------------------
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# ctypedef fused algos_t:
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# float64_t
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# float32_t
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# object
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# int64_t
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# int32_t
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# int16_t
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# int8_t
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# uint64_t
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# uint32_t
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# uint16_t
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# uint8_t
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def validate_limit(nobs: int | None, limit=None) -> int: ...
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def pad(
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old: np.ndarray, # ndarray[algos_t]
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new: np.ndarray, # ndarray[algos_t]
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limit=None,
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) -> np.ndarray: ... # np.ndarray[np.intp, ndim=1]
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def pad_inplace(
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values: np.ndarray, # algos_t[:]
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mask: np.ndarray, # uint8_t[:]
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limit=None,
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) -> None: ...
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def pad_2d_inplace(
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values: np.ndarray, # algos_t[:, :]
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mask: np.ndarray, # const uint8_t[:, :]
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limit=None,
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) -> None:
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...
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def backfill(
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old: np.ndarray, # ndarray[algos_t]
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new: np.ndarray, # ndarray[algos_t]
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limit=None,
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) -> np.ndarray: # np.ndarray[np.intp, ndim=1]
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...
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def backfill_inplace(
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values: np.ndarray, # algos_t[:]
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mask: np.ndarray, # uint8_t[:]
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limit=None,
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) -> None: ...
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def backfill_2d_inplace(
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values: np.ndarray, # algos_t[:, :]
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mask: np.ndarray, # const uint8_t[:, :]
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limit=None,
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) -> None: ...
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def is_monotonic(
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arr: np.ndarray, # ndarray[algos_t, ndim=1]
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timelike: bool
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) -> tuple[bool, bool, bool]:
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...
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# ----------------------------------------------------------------------
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# rank_1d, rank_2d
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# ----------------------------------------------------------------------
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# ctypedef fused rank_t:
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# object
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# float64_t
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# uint64_t
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# int64_t
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def rank_1d(
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values: np.ndarray, # ndarray[rank_t, ndim=1]
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labels: np.ndarray, # const int64_t[:]
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is_datetimelike: bool = ...,
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ties_method=...,
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ascending: bool = ...,
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pct: bool = ...,
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na_option=...,
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) -> np.ndarray: ... # np.ndarray[float64_t, ndim=1]
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def rank_2d(
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in_arr: np.ndarray, # ndarray[rank_t, ndim=2]
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axis: int = ...,
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is_datetimelike: bool = ...,
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ties_method=...,
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ascending: bool = ...,
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na_option=...,
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pct: bool = ...,
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) -> np.ndarray: ... # np.ndarray[float64_t, ndim=1]
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def diff_2d(
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arr: np.ndarray, # ndarray[diff_t, ndim=2]
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out: np.ndarray, # ndarray[out_t, ndim=2]
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periods: int,
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axis: int,
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datetimelike: bool = ...,
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) -> None: ...
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def ensure_platform_int(arr: object) -> np.ndarray: ...
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def ensure_object(arr: object) -> np.ndarray: ...
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def ensure_float64(arr: object, copy=True) -> np.ndarray: ...
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def ensure_float32(arr: object, copy=True) -> np.ndarray: ...
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def ensure_int8(arr: object, copy=True) -> np.ndarray: ...
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def ensure_int16(arr: object, copy=True) -> np.ndarray: ...
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def ensure_int32(arr: object, copy=True) -> np.ndarray: ...
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def ensure_int64(arr: object, copy=True) -> np.ndarray: ...
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def ensure_uint8(arr: object, copy=True) -> np.ndarray: ...
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def ensure_uint16(arr: object, copy=True) -> np.ndarray: ...
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def ensure_uint32(arr: object, copy=True) -> np.ndarray: ...
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def ensure_uint64(arr: object, copy=True) -> np.ndarray: ...
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def take_1d_int8_int8(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
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def take_1d_int8_int32(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
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def take_1d_int8_int64(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
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def take_1d_int8_float64(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
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def take_1d_int16_int16(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
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def take_1d_int16_int32(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
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def take_1d_int16_int64(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
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def take_1d_int16_float64(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
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def take_1d_int32_int32(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
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def take_1d_int32_int64(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
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def take_1d_int32_float64(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
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def take_1d_int64_int64(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
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def take_1d_int64_float64(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
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def take_1d_float32_float32(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
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def take_1d_float32_float64(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
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def take_1d_float64_float64(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
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def take_1d_object_object(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
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def take_1d_bool_bool(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
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def take_1d_bool_object(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
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def take_2d_axis0_int8_int8(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
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def take_2d_axis0_int8_int32(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
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def take_2d_axis0_int8_int64(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
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def take_2d_axis0_int8_float64(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
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def take_2d_axis0_int16_int16(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
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def take_2d_axis0_int16_int32(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
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def take_2d_axis0_int16_int64(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
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def take_2d_axis0_int16_float64(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
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def take_2d_axis0_int32_int32(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
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def take_2d_axis0_int32_int64(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
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def take_2d_axis0_int32_float64(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
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def take_2d_axis0_int64_int64(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
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def take_2d_axis0_int64_float64(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
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def take_2d_axis0_float32_float32(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
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def take_2d_axis0_float32_float64(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
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def take_2d_axis0_float64_float64(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
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def take_2d_axis0_object_object(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
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def take_2d_axis0_bool_bool(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
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def take_2d_axis0_bool_object(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
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def take_2d_axis1_int8_int8(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
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def take_2d_axis1_int8_int32(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
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def take_2d_axis1_int8_int64(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
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def take_2d_axis1_int8_float64(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
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def take_2d_axis1_int16_int16(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
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def take_2d_axis1_int16_int32(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
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def take_2d_axis1_int16_int64(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
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def take_2d_axis1_int16_float64(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
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def take_2d_axis1_int32_int32(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
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def take_2d_axis1_int32_int64(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
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def take_2d_axis1_int32_float64(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
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def take_2d_axis1_int64_int64(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
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def take_2d_axis1_int64_float64(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
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def take_2d_axis1_float32_float32(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
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def take_2d_axis1_float32_float64(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
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def take_2d_axis1_float64_float64(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
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def take_2d_axis1_object_object(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
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def take_2d_axis1_bool_bool(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
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def take_2d_axis1_bool_object(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
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def take_2d_multi_int8_int8(values: np.ndarray, indexer, out: np.ndarray, fill_value=...) -> None: ...
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def take_2d_multi_int8_int32(values: np.ndarray, indexer, out: np.ndarray, fill_value=...) -> None: ...
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def take_2d_multi_int8_int64(values: np.ndarray, indexer, out: np.ndarray, fill_value=...) -> None: ...
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def take_2d_multi_int8_float64(values: np.ndarray, indexer, out: np.ndarray, fill_value=...) -> None: ...
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def take_2d_multi_int16_int16(values: np.ndarray, indexer, out: np.ndarray, fill_value=...) -> None: ...
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def take_2d_multi_int16_int32(values: np.ndarray, indexer, out: np.ndarray, fill_value=...) -> None: ...
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def take_2d_multi_int16_int64(values: np.ndarray, indexer, out: np.ndarray, fill_value=...) -> None: ...
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def take_2d_multi_int16_float64(values: np.ndarray, indexer, out: np.ndarray, fill_value=...) -> None: ...
283+
def take_2d_multi_int32_int32(values: np.ndarray, indexer, out: np.ndarray, fill_value=...) -> None: ...
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def take_2d_multi_int32_int64(values: np.ndarray, indexer, out: np.ndarray, fill_value=...) -> None: ...
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def take_2d_multi_int32_float64(values: np.ndarray, indexer, out: np.ndarray, fill_value=...) -> None: ...
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def take_2d_multi_int64_float64(values: np.ndarray, indexer, out: np.ndarray, fill_value=...) -> None: ...
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def take_2d_multi_float32_float32(values: np.ndarray, indexer, out: np.ndarray, fill_value=...) -> None: ...
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def take_2d_multi_float32_float64(values: np.ndarray, indexer, out: np.ndarray, fill_value=...) -> None: ...
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def take_2d_multi_float64_float64(values: np.ndarray, indexer, out: np.ndarray, fill_value=...) -> None: ...
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def take_2d_multi_object_object(values: np.ndarray, indexer, out: np.ndarray, fill_value=...) -> None: ...
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def take_2d_multi_bool_bool(values: np.ndarray, indexer, out: np.ndarray, fill_value=...) -> None: ...
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def take_2d_multi_bool_object(values: np.ndarray, indexer, out: np.ndarray, fill_value=...) -> None: ...
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def take_2d_multi_int64_int64(values: np.ndarray, indexer, out: np.ndarray, fill_value=...) -> None: ...

‎pandas/_libs/algos.pyx

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -563,7 +563,7 @@ ctypedef fused algos_t:
563563
uint8_t
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565565

566-
def validate_limit(nobs: int, limit=None) -> int:
566+
def validate_limit(nobs: int | None, limit=None) -> int:
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"""
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Check that the `limit` argument is a positive integer.
569569

‎pandas/_libs/internals.pyi

Lines changed: 12 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -6,7 +6,10 @@ from typing import (
66

77
import numpy as np
88

9-
from pandas._typing import ArrayLike
9+
from pandas._typing import (
10+
ArrayLike,
11+
T,
12+
)
1013

1114
def slice_len(slc: slice, objlen: int = ...) -> int: ...
1215

@@ -50,9 +53,16 @@ class BlockPlacement:
5053
def append(self, others: list[BlockPlacement]) -> BlockPlacement: ...
5154

5255

53-
class Block:
56+
class SharedBlock:
5457
_mgr_locs: BlockPlacement
5558
ndim: int
5659
values: ArrayLike
5760

5861
def __init__(self, values: ArrayLike, placement: BlockPlacement, ndim: int): ...
62+
63+
class NumpyBlock(SharedBlock):
64+
values: np.ndarray
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def getitem_block_index(self: T, slicer: slice) -> T: ...
66+
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class Block(SharedBlock):
68+
...

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