88 lines
2.3 KiB
Python
88 lines
2.3 KiB
Python
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from collections.abc import (
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Hashable,
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Sequence,
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)
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from typing import (
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Any,
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Literal,
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)
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from matplotlib.axes import Axes
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from matplotlib.colors import Colormap
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from matplotlib.figure import Figure
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from matplotlib.table import Table
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import numpy as np
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from pandas.core.frame import DataFrame
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from pandas.core.series import Series
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from typing_extensions import TypeAlias
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from pandas._typing import (
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HashableT,
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npt,
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)
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_Color: TypeAlias = str | Sequence[float]
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def table(
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ax: Axes,
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data: DataFrame | Series,
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**kwargs,
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) -> Table: ...
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def register() -> None: ...
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def deregister() -> None: ...
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def scatter_matrix(
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frame: DataFrame,
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alpha: float = 0.5,
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figsize: tuple[float, float] | None = None,
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ax: Axes | None = None,
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grid: bool = False,
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diagonal: Literal["hist", "kde"] = "hist",
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marker: str = ".",
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density_kwds: dict[str, Any] | None = None,
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hist_kwds: dict[str, Any] | None = None,
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range_padding: float = 0.05,
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**kwargs,
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) -> npt.NDArray[np.object_]: ...
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def radviz(
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frame: DataFrame,
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class_column: Hashable,
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ax: Axes | None = None,
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color: _Color | Sequence[_Color] | None = None,
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colormap: str | Colormap | None = None,
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**kwds,
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) -> Axes: ...
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def andrews_curves(
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frame: DataFrame,
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class_column: Hashable,
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ax: Axes | None = None,
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samples: int = 200,
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color: _Color | Sequence[_Color] | None = None,
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colormap: str | Colormap | None = None,
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**kwargs,
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) -> Axes: ...
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def bootstrap_plot(
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series: Series,
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fig: Figure | None = None,
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size: int = 50,
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samples: int = 500,
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**kwds,
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) -> Figure: ...
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def parallel_coordinates(
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frame: DataFrame,
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class_column: Hashable,
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cols: list[HashableT] | None = None,
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ax: Axes | None = None,
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color: _Color | Sequence[_Color] | None = None,
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use_columns: bool = False,
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xticks: Sequence[float] | None = None,
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colormap: str | Colormap | None = None,
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axvlines: bool = True,
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axvlines_kwds: dict[str, Any] | None = None,
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sort_labels: bool = False,
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**kwargs,
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) -> Axes: ...
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def lag_plot(series: Series, lag: int = 1, ax: Axes | None = None, **kwds) -> Axes: ...
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def autocorrelation_plot(series: Series, ax: Axes | None = None, **kwargs) -> Axes: ...
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plot_params: dict[str, Any]
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