| # |
| # Licensed to the Apache Software Foundation (ASF) under one |
| # or more contributor license agreements. See the NOTICE file |
| # distributed with this work for additional information |
| # regarding copyright ownership. The ASF licenses this file |
| # to you under the Apache License, Version 2.0 (the |
| # "License"); you may not use this file except in compliance |
| # with the License. You may obtain a copy of the License at |
| # |
| # http://www.apache.org/licenses/LICENSE-2.0 |
| # |
| # Unless required by applicable law or agreed to in writing, |
| # software distributed under the License is distributed on an |
| # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY |
| # KIND, either express or implied. See the License for the |
| # specific language governing permissions and limitations |
| # under the License. |
| |
| # This Protocol reuses core Pandas annotation. |
| # Overall pipeline looks as follows |
| # - Stubgen pandas.core.frame |
| # - Add Protocol as a base class |
| # - Replace imports with Any |
| |
| import numpy.ma as np # type: ignore[import] |
| from typing import Any, Hashable, IO, Iterable, List, Optional, Sequence, Tuple, Union |
| from typing_extensions import Protocol |
| from .series import SeriesLike |
| |
| Axes = Any |
| Dtype = Any |
| Index = Any |
| Renamer = Any |
| Axis = Any |
| Level = Any |
| |
| class DataFrameLike(Protocol): |
| def __init__( |
| self, |
| data: Any = ..., |
| index: Optional[Axes] = ..., |
| columns: Optional[Axes] = ..., |
| dtype: Optional[Dtype] = ..., |
| copy: bool = ..., |
| ) -> None: ... |
| @property |
| def axes(self) -> List[Index]: ... |
| @property |
| def shape(self) -> Tuple[int, int]: ... |
| @property |
| def style(self) -> Any: ... |
| def items(self) -> Iterable[Tuple[Optional[Hashable], SeriesLike]]: ... |
| def iteritems(self) -> Iterable[Tuple[Optional[Hashable], SeriesLike]]: ... |
| def iterrows(self) -> Iterable[Tuple[Optional[Hashable], SeriesLike]]: ... |
| def itertuples(self, index: bool = ..., name: str = ...): ... |
| def __len__(self) -> int: ... |
| def dot(self, other: Any): ... |
| def __matmul__(self, other: Any): ... |
| def __rmatmul__(self, other: Any): ... |
| @classmethod |
| def from_dict( |
| cls: Any, data: Any, orient: Any = ..., dtype: Any = ..., columns: Any = ... |
| ) -> DataFrameLike: ... |
| def to_numpy(self, dtype: Any = ..., copy: Any = ...) -> np.ndarray: ... |
| def to_dict(self, orient: str = ..., into: Any = ...): ... |
| def to_gbq( |
| self, |
| destination_table: Any, |
| project_id: Any = ..., |
| chunksize: Any = ..., |
| reauth: Any = ..., |
| if_exists: Any = ..., |
| auth_local_webserver: Any = ..., |
| table_schema: Any = ..., |
| location: Any = ..., |
| progress_bar: Any = ..., |
| credentials: Any = ..., |
| ) -> None: ... |
| @classmethod |
| def from_records( |
| cls: Any, |
| data: Any, |
| index: Any = ..., |
| exclude: Any = ..., |
| columns: Any = ..., |
| coerce_float: Any = ..., |
| nrows: Any = ..., |
| ) -> DataFrameLike: ... |
| def to_records( |
| self, index: Any = ..., column_dtypes: Any = ..., index_dtypes: Any = ... |
| ) -> np.recarray: ... |
| def to_stata( |
| self, |
| path: Any, |
| convert_dates: Optional[Any] = ..., |
| write_index: bool = ..., |
| byteorder: Optional[Any] = ..., |
| time_stamp: Optional[Any] = ..., |
| data_label: Optional[Any] = ..., |
| variable_labels: Optional[Any] = ..., |
| version: int = ..., |
| convert_strl: Optional[Any] = ..., |
| ) -> None: ... |
| def to_feather(self, path: Any) -> None: ... |
| def to_markdown( |
| self, buf: Optional[IO[str]] = ..., mode: Optional[str] = ..., **kwargs: Any |
| ) -> Optional[str]: ... |
| def to_parquet( |
| self, |
| path: Any, |
| engine: Any = ..., |
| compression: Any = ..., |
| index: Any = ..., |
| partition_cols: Any = ..., |
| **kwargs: Any |
| ) -> None: ... |
| def to_html( |
| self, |
| buf: Optional[Any] = ..., |
| columns: Optional[Any] = ..., |
| col_space: Optional[Any] = ..., |
| header: bool = ..., |
| index: bool = ..., |
| na_rep: str = ..., |
| formatters: Optional[Any] = ..., |
| float_format: Optional[Any] = ..., |
| sparsify: Optional[Any] = ..., |
| index_names: bool = ..., |
| justify: Optional[Any] = ..., |
| max_rows: Optional[Any] = ..., |
| max_cols: Optional[Any] = ..., |
| show_dimensions: bool = ..., |
| decimal: str = ..., |
| bold_rows: bool = ..., |
| classes: Optional[Any] = ..., |
| escape: bool = ..., |
| notebook: bool = ..., |
| border: Optional[Any] = ..., |
| table_id: Optional[Any] = ..., |
| render_links: bool = ..., |
| encoding: Optional[Any] = ..., |
| ): ... |
| def info( |
| self, |
| verbose: Any = ..., |
| buf: Any = ..., |
| max_cols: Any = ..., |
| memory_usage: Any = ..., |
| null_counts: Any = ..., |
| ) -> None: ... |
| def memory_usage(self, index: Any = ..., deep: Any = ...) -> SeriesLike: ... |
| def transpose(self, *args: Any, copy: bool = ...) -> DataFrameLike: ... |
| T: Any = ... |
| def __getitem__(self, key: Any): ... |
| def __setitem__(self, key: Any, value: Any): ... |
| def query(self, expr: Any, inplace: bool = ..., **kwargs: Any): ... |
| def eval(self, expr: Any, inplace: bool = ..., **kwargs: Any): ... |
| def select_dtypes( |
| self, include: Any = ..., exclude: Any = ... |
| ) -> DataFrameLike: ... |
| def insert( |
| self, loc: Any, column: Any, value: Any, allow_duplicates: Any = ... |
| ) -> None: ... |
| def assign(self, **kwargs: Any) -> DataFrameLike: ... |
| def lookup(self, row_labels: Any, col_labels: Any) -> np.ndarray: ... |
| def align( |
| self, |
| other: Any, |
| join: Any = ..., |
| axis: Any = ..., |
| level: Any = ..., |
| copy: Any = ..., |
| fill_value: Any = ..., |
| method: Any = ..., |
| limit: Any = ..., |
| fill_axis: Any = ..., |
| broadcast_axis: Any = ..., |
| ) -> DataFrameLike: ... |
| def reindex(self, *args: Any, **kwargs: Any) -> DataFrameLike: ... |
| def drop( |
| self, |
| labels: Optional[Any] = ..., |
| axis: int = ..., |
| index: Optional[Any] = ..., |
| columns: Optional[Any] = ..., |
| level: Optional[Any] = ..., |
| inplace: bool = ..., |
| errors: str = ..., |
| ): ... |
| def rename( |
| self, |
| mapper: Optional[Renamer] = ..., |
| *, |
| index: Optional[Renamer] = ..., |
| columns: Optional[Renamer] = ..., |
| axis: Optional[Axis] = ..., |
| copy: bool = ..., |
| inplace: bool = ..., |
| level: Optional[Level] = ..., |
| errors: str = ... |
| ) -> Optional[DataFrameLike]: ... |
| def fillna( |
| self, |
| value: Any = ..., |
| method: Any = ..., |
| axis: Any = ..., |
| inplace: Any = ..., |
| limit: Any = ..., |
| downcast: Any = ..., |
| ) -> Optional[DataFrameLike]: ... |
| def replace( |
| self, |
| to_replace: Optional[Any] = ..., |
| value: Optional[Any] = ..., |
| inplace: bool = ..., |
| limit: Optional[Any] = ..., |
| regex: bool = ..., |
| method: str = ..., |
| ): ... |
| def shift( |
| self, |
| periods: Any = ..., |
| freq: Any = ..., |
| axis: Any = ..., |
| fill_value: Any = ..., |
| ) -> DataFrameLike: ... |
| def set_index( |
| self, |
| keys: Any, |
| drop: bool = ..., |
| append: bool = ..., |
| inplace: bool = ..., |
| verify_integrity: bool = ..., |
| ): ... |
| def reset_index( |
| self, |
| level: Optional[Union[Hashable, Sequence[Hashable]]] = ..., |
| drop: bool = ..., |
| inplace: bool = ..., |
| col_level: Hashable = ..., |
| col_fill: Optional[Hashable] = ..., |
| ) -> Optional[DataFrameLike]: ... |
| def isna(self) -> DataFrameLike: ... |
| def isnull(self) -> DataFrameLike: ... |
| def notna(self) -> DataFrameLike: ... |
| def notnull(self) -> DataFrameLike: ... |
| def dropna( |
| self, |
| axis: int = ..., |
| how: str = ..., |
| thresh: Optional[Any] = ..., |
| subset: Optional[Any] = ..., |
| inplace: bool = ..., |
| ): ... |
| def drop_duplicates( |
| self, |
| subset: Optional[Union[Hashable, Sequence[Hashable]]] = ..., |
| keep: Union[str, bool] = ..., |
| inplace: bool = ..., |
| ignore_index: bool = ..., |
| ) -> Optional[DataFrameLike]: ... |
| def duplicated( |
| self, |
| subset: Optional[Union[Hashable, Sequence[Hashable]]] = ..., |
| keep: Union[str, bool] = ..., |
| ) -> SeriesLike: ... |
| def sort_values( |
| self, |
| by: Any, |
| axis: int = ..., |
| ascending: bool = ..., |
| inplace: bool = ..., |
| kind: str = ..., |
| na_position: str = ..., |
| ignore_index: bool = ..., |
| ): ... |
| def sort_index( |
| self, |
| axis: Any = ..., |
| level: Any = ..., |
| ascending: Any = ..., |
| inplace: Any = ..., |
| kind: Any = ..., |
| na_position: Any = ..., |
| sort_remaining: Any = ..., |
| ignore_index: bool = ..., |
| ) -> Any: ... |
| def nlargest(self, n: Any, columns: Any, keep: Any = ...) -> DataFrameLike: ... |
| def nsmallest(self, n: Any, columns: Any, keep: Any = ...) -> DataFrameLike: ... |
| def swaplevel( |
| self, i: Any = ..., j: Any = ..., axis: Any = ... |
| ) -> DataFrameLike: ... |
| def reorder_levels(self, order: Any, axis: Any = ...) -> DataFrameLike: ... |
| def combine( |
| self, |
| other: DataFrameLike, |
| func: Any, |
| fill_value: Any = ..., |
| overwrite: Any = ..., |
| ) -> DataFrameLike: ... |
| def combine_first(self, other: DataFrameLike) -> DataFrameLike: ... |
| def update( |
| self, |
| other: Any, |
| join: Any = ..., |
| overwrite: Any = ..., |
| filter_func: Any = ..., |
| errors: Any = ..., |
| ) -> None: ... |
| def groupby( |
| self, |
| by: Any = ..., |
| axis: Any = ..., |
| level: Any = ..., |
| as_index: bool = ..., |
| sort: bool = ..., |
| group_keys: bool = ..., |
| squeeze: bool = ..., |
| observed: bool = ..., |
| ) -> Any: ... |
| def pivot( |
| self, index: Any = ..., columns: Any = ..., values: Any = ... |
| ) -> DataFrameLike: ... |
| def pivot_table( |
| self, |
| values: Any = ..., |
| index: Any = ..., |
| columns: Any = ..., |
| aggfunc: Any = ..., |
| fill_value: Any = ..., |
| margins: Any = ..., |
| dropna: Any = ..., |
| margins_name: Any = ..., |
| observed: Any = ..., |
| ) -> DataFrameLike: ... |
| def stack(self, level: int = ..., dropna: bool = ...): ... |
| def explode(self, column: Union[str, Tuple]) -> DataFrameLike: ... |
| def unstack(self, level: int = ..., fill_value: Optional[Any] = ...): ... |
| def melt( |
| self, |
| id_vars: Any = ..., |
| value_vars: Any = ..., |
| var_name: Any = ..., |
| value_name: Any = ..., |
| col_level: Any = ..., |
| ) -> DataFrameLike: ... |
| def diff(self, periods: Any = ..., axis: Any = ...) -> DataFrameLike: ... |
| def aggregate(self, func: Any, axis: int = ..., *args: Any, **kwargs: Any): ... |
| agg: Any = ... |
| def transform( |
| self, func: Any, axis: Any = ..., *args: Any, **kwargs: Any |
| ) -> DataFrameLike: ... |
| def apply( |
| self, |
| func: Any, |
| axis: int = ..., |
| raw: bool = ..., |
| result_type: Optional[Any] = ..., |
| args: Any = ..., |
| **kwds: Any |
| ): ... |
| def applymap(self, func: Any) -> DataFrameLike: ... |
| def append( |
| self, |
| other: Any, |
| ignore_index: Any = ..., |
| verify_integrity: Any = ..., |
| sort: Any = ..., |
| ) -> DataFrameLike: ... |
| def join( |
| self, |
| other: Any, |
| on: Any = ..., |
| how: Any = ..., |
| lsuffix: Any = ..., |
| rsuffix: Any = ..., |
| sort: Any = ..., |
| ) -> DataFrameLike: ... |
| def merge( |
| self, |
| right: Any, |
| how: Any = ..., |
| on: Any = ..., |
| left_on: Any = ..., |
| right_on: Any = ..., |
| left_index: Any = ..., |
| right_index: Any = ..., |
| sort: Any = ..., |
| suffixes: Any = ..., |
| copy: Any = ..., |
| indicator: Any = ..., |
| validate: Any = ..., |
| ) -> DataFrameLike: ... |
| def round( |
| self, decimals: Any = ..., *args: Any, **kwargs: Any |
| ) -> DataFrameLike: ... |
| def corr(self, method: Any = ..., min_periods: Any = ...) -> DataFrameLike: ... |
| def cov(self, min_periods: Any = ...) -> DataFrameLike: ... |
| def corrwith( |
| self, other: Any, axis: Any = ..., drop: Any = ..., method: Any = ... |
| ) -> SeriesLike: ... |
| def count( |
| self, axis: int = ..., level: Optional[Any] = ..., numeric_only: bool = ... |
| ): ... |
| def nunique(self, axis: Any = ..., dropna: Any = ...) -> SeriesLike: ... |
| def idxmin(self, axis: Any = ..., skipna: Any = ...) -> SeriesLike: ... |
| def idxmax(self, axis: Any = ..., skipna: Any = ...) -> SeriesLike: ... |
| def mode( |
| self, axis: Any = ..., numeric_only: Any = ..., dropna: Any = ... |
| ) -> DataFrameLike: ... |
| def quantile( |
| self, |
| q: float = ..., |
| axis: int = ..., |
| numeric_only: bool = ..., |
| interpolation: str = ..., |
| ): ... |
| def to_timestamp( |
| self, freq: Any = ..., how: Any = ..., axis: Any = ..., copy: Any = ... |
| ) -> DataFrameLike: ... |
| def to_period( |
| self, freq: Any = ..., axis: Any = ..., copy: Any = ... |
| ) -> DataFrameLike: ... |
| def isin(self, values: Any) -> DataFrameLike: ... |
| plot: Any = ... |
| hist: Any = ... |
| boxplot: Any = ... |
| sparse: Any = ... |
