A PyQT GUI application for converting InfoLease report outputs into Excel files. Handles parsing and summarizing. Learns where files are meant to be store and compiles monthly and yearly summaries.
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InfoLeaseExtract/venv/Lib/site-packages/pandas/_libs/join.pyi

93 lines
3.3 KiB

import numpy as np
from pandas._typing import npt
def inner_join(
left: np.ndarray, # const intp_t[:]
right: np.ndarray, # const intp_t[:]
max_groups: int,
) -> tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]]: ...
def left_outer_join(
left: np.ndarray, # const intp_t[:]
right: np.ndarray, # const intp_t[:]
max_groups: int,
sort: bool = ...,
) -> tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]]: ...
def full_outer_join(
left: np.ndarray, # const intp_t[:]
right: np.ndarray, # const intp_t[:]
max_groups: int,
) -> tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]]: ...
def ffill_indexer(
indexer: np.ndarray, # const intp_t[:]
) -> npt.NDArray[np.intp]: ...
def left_join_indexer_unique(
left: np.ndarray, # ndarray[join_t]
right: np.ndarray, # ndarray[join_t]
) -> npt.NDArray[np.intp]: ...
def left_join_indexer(
left: np.ndarray, # ndarray[join_t]
right: np.ndarray, # ndarray[join_t]
) -> tuple[
np.ndarray, # np.ndarray[join_t]
npt.NDArray[np.intp],
npt.NDArray[np.intp],
]: ...
def inner_join_indexer(
left: np.ndarray, # ndarray[join_t]
right: np.ndarray, # ndarray[join_t]
) -> tuple[
np.ndarray, # np.ndarray[join_t]
npt.NDArray[np.intp],
npt.NDArray[np.intp],
]: ...
def outer_join_indexer(
left: np.ndarray, # ndarray[join_t]
right: np.ndarray, # ndarray[join_t]
) -> tuple[
np.ndarray, # np.ndarray[join_t]
npt.NDArray[np.intp],
npt.NDArray[np.intp],
]: ...
def asof_join_backward_on_X_by_Y(
left_values: np.ndarray, # asof_t[:]
right_values: np.ndarray, # asof_t[:]
left_by_values: np.ndarray, # by_t[:]
right_by_values: np.ndarray, # by_t[:]
allow_exact_matches: bool = ...,
tolerance: np.number | int | float | None = ...,
) -> tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]]: ...
def asof_join_forward_on_X_by_Y(
left_values: np.ndarray, # asof_t[:]
right_values: np.ndarray, # asof_t[:]
left_by_values: np.ndarray, # by_t[:]
right_by_values: np.ndarray, # by_t[:]
allow_exact_matches: bool = ...,
tolerance: np.number | int | float | None = ...,
) -> tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]]: ...
def asof_join_nearest_on_X_by_Y(
left_values: np.ndarray, # asof_t[:]
right_values: np.ndarray, # asof_t[:]
left_by_values: np.ndarray, # by_t[:]
right_by_values: np.ndarray, # by_t[:]
allow_exact_matches: bool = ...,
tolerance: np.number | int | float | None = ...,
) -> tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]]: ...
def asof_join_backward(
left_values: np.ndarray, # asof_t[:]
right_values: np.ndarray, # asof_t[:]
allow_exact_matches: bool = ...,
tolerance: np.number | int | float | None = ...,
) -> tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]]: ...
def asof_join_forward(
left_values: np.ndarray, # asof_t[:]
right_values: np.ndarray, # asof_t[:]
allow_exact_matches: bool = ...,
tolerance: np.number | int | float | None = ...,
) -> tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]]: ...
def asof_join_nearest(
left_values: np.ndarray, # asof_t[:]
right_values: np.ndarray, # asof_t[:]
allow_exact_matches: bool = ...,
tolerance: np.number | int | float | None = ...,
) -> tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]]: ...