venv/Lib/site-packages/gradio/components/bar_plot.pyi

"""gr.BarPlot() component."""

from __future__ import annotations

from typing import TYPE_CHECKING, Any, Callable, Literal

from gradio_client.documentation import document

from gradio.components.plot import AltairPlot, AltairPlotData, Plot

if TYPE_CHECKING:
    import pandas as pd

from gradio.events import Dependency

@document()
class BarPlot(Plot):
    """
    Creates a bar plot component to display data from a pandas DataFrame (as output). As this component does
    not accept user input, it is rarely used as an input component.

    Demos: bar_plot
    """

    data_model = AltairPlotData

    def __init__(
        self,
        value: pd.DataFrame | Callable | None = None,
        x: str | None = None,
        y: str | None = None,
        *,
        color: str | None = None,
        vertical: bool = True,
        group: str | None = None,
        title: str | None = None,
        tooltip: list[str] | str | None = None,
        x_title: str | None = None,
        y_title: str | None = None,
        x_label_angle: float | None = None,
        y_label_angle: float | None = None,
        color_legend_title: str | None = None,
        group_title: str | None = None,
        color_legend_position: Literal[
            "left",
            "right",
            "top",
            "bottom",
            "top-left",
            "top-right",
            "bottom-left",
            "bottom-right",
            "none",
        ]
        | None = None,
        height: int | str | None = None,
        width: int | str | None = None,
        y_lim: list[int] | None = None,
        caption: str | None = None,
        interactive: bool | None = True,
        label: str | None = None,
        show_label: bool | None = None,
        container: bool = True,
        scale: int | None = None,
        min_width: int = 160,
        every: float | None = None,
        visible: bool = True,
        elem_id: str | None = None,
        elem_classes: list[str] | str | None = None,
        render: bool = True,
        key: int | str | None = None,
        sort: Literal["x", "y", "-x", "-y"] | None = None,
        show_actions_button: bool = False,
    ):
        """
        Parameters:
            value: The pandas dataframe containing the data to display in a scatter plot. If a callable is provided, the function will be called whenever the app loads to set the initial value of the plot.
            x: Column corresponding to the x axis.
            y: Column corresponding to the y axis.
            color: The column to determine the bar color. Must be categorical (discrete values).
            vertical: If True, the bars will be displayed vertically. If False, the x and y axis will be switched, displaying the bars horizontally. Default is True.
            group: The column with which to split the overall plot into smaller subplots.
            title: The title to display on top of the chart.
            tooltip: The column (or list of columns) to display on the tooltip when a user hovers over a bar.
            x_title: The title given to the x axis. By default, uses the value of the x parameter.
            y_title: The title given to the y axis. By default, uses the value of the y parameter.
            x_label_angle: The angle (in degrees) of the x axis labels. Positive values are clockwise, and negative values are counter-clockwise.
            y_label_angle: The angle (in degrees) of the y axis labels. Positive values are clockwise, and negative values are counter-clockwise.
            color_legend_title: The title given to the color legend. By default, uses the value of color parameter.
            group_title: The label displayed on top of the subplot columns (or rows if vertical=True). Use an empty string to omit.
            color_legend_position: The position of the color legend. If the string value 'none' is passed, this legend is omitted. For other valid position values see: https://vega.github.io/vega/docs/legends/#orientation.
            height: The height of the plot, specified in pixels if a number is passed, or in CSS units if a string is passed.
            width: The width of the plot, specified in pixels if a number is passed, or in CSS units if a string is passed.
            y_lim: A tuple of list containing the limits for the y-axis, specified as [y_min, y_max].
            caption: The (optional) caption to display below the plot.
            interactive: Whether users should be able to interact with the plot by panning or zooming with their mouse or trackpad.
            label: The (optional) label to display on the top left corner of the plot.
            show_label: Whether the label should be displayed.
            every: If `value` is a callable, run the function 'every' number of seconds while the client connection is open. Has no effect otherwise. The event can be accessed (e.g. to cancel it) via this component's .load_event attribute.
            visible: Whether the plot should be visible.
            elem_id: An optional string that is assigned as the id of this component in the HTML DOM. Can be used for targeting CSS styles.
            elem_classes: An optional list of strings that are assigned as the classes of this component in the HTML DOM. Can be used for targeting CSS styles.
            render: If False, component will not render be rendered in the Blocks context. Should be used if the intention is to assign event listeners now but render the component later.
            key: if assigned, will be used to assume identity across a re-render. Components that have the same key across a re-render will have their value preserved.
            sort: Specifies the sorting axis as either "x", "y", "-x" or "-y". If None, no sorting is applied.
            show_actions_button: Whether to show the actions button on the top right corner of the plot.
        """
        self.x = x
        self.y = y
        self.color = color
        self.vertical = vertical
        self.group = group
        self.group_title = group_title
        self.tooltip = tooltip
        self.title = title
        self.x_title = x_title
        self.y_title = y_title
        self.x_label_angle = x_label_angle
        self.y_label_angle = y_label_angle
        self.color_legend_title = color_legend_title
        self.group_title = group_title
        self.color_legend_position = color_legend_position
        self.y_lim = y_lim
        self.caption = caption
        self.interactive_chart = interactive
        self.width = width
        self.height = height
        self.sort = sort
        self.show_actions_button = show_actions_button
        super().__init__(
            value=value,
            label=label,
            show_label=show_label,
            container=container,
            scale=scale,
            min_width=min_width,
            visible=visible,
            elem_id=elem_id,
            elem_classes=elem_classes,
            render=render,
            key=key,
            every=every,
        )

    def get_block_name(self) -> str:
        return "plot"

    @staticmethod
    def create_plot(
        value: pd.DataFrame,
        x: str,
        y: str,
        color: str | None = None,
        vertical: bool = True,
        group: str | None = None,
        title: str | None = None,
        tooltip: list[str] | str | None = None,
        x_title: str | None = None,
        y_title: str | None = None,
        x_label_angle: float | None = None,
        y_label_angle: float | None = None,
        color_legend_title: str | None = None,
        group_title: str | None = None,
        color_legend_position: Literal[
            "left",
            "right",
            "top",
            "bottom",
            "top-left",
            "top-right",
            "bottom-left",
            "bottom-right",
            "none",
        ]
        | None = None,
        height: int | str | None = None,
        width: int | str | None = None,
        y_lim: list[int] | None = None,
        interactive: bool | None = True,
        sort: Literal["x", "y", "-x", "-y"] | None = None,
    ):
        """Helper for creating the bar plot."""
        import altair as alt

        interactive = True if interactive is None else interactive
        orientation = (
            {"field": group, "title": group_title if group_title is not None else group}
            if group
            else {}
        )

        x_title = x_title or x
        y_title = y_title or y

        # If horizontal, switch x and y
        if not vertical:
            y, x = x, y
            x = f"sum({x}):Q"
            y_title, x_title = x_title, y_title
            orientation = {"row": alt.Row(**orientation)} if orientation else {}  # type: ignore
            x_lim = y_lim
            y_lim = None
        else:
            y = f"sum({y}):Q"
            x_lim = None
            orientation = {"column": alt.Column(**orientation)} if orientation else {}  # type: ignore

        encodings = dict(
            x=alt.X(
                x,  # type: ignore
                title=x_title,  # type: ignore
                scale=AltairPlot.create_scale(x_lim),  # type: ignore
                axis=alt.Axis(labelAngle=x_label_angle)
                if x_label_angle is not None
                else alt.Axis(),
                sort=sort if vertical and sort is not None else None,
            ),
            y=alt.Y(
                y,  # type: ignore
                title=y_title,  # type: ignore
                scale=AltairPlot.create_scale(y_lim),  # type: ignore
                axis=alt.Axis(labelAngle=y_label_angle)
                if y_label_angle is not None
                else alt.Axis(),
                sort=sort if not vertical and sort is not None else None,
            ),
            **orientation,
        )
        properties = {}
        if title:
            properties["title"] = title
        if height:
            properties["height"] = height
        if width:
            properties["width"] = width

        if color:
            domain = value[color].unique().tolist()
            range_ = list(range(len(domain)))
            encodings["color"] = {
                "field": color,
                "type": "nominal",
                "scale": {"domain": domain, "range": range_},
                "legend": AltairPlot.create_legend(
                    position=color_legend_position, title=color_legend_title or color
                ),
            }

        if tooltip:
            encodings["tooltip"] = tooltip  # type: ignore

        chart = (
            alt.Chart(value)  # type: ignore
            .mark_bar()  # type: ignore
            .encode(**encodings)
            .properties(background="transparent", **properties)
        )
        if interactive:
            chart = chart.interactive()

        return chart

    def preprocess(self, payload: AltairPlotData) -> AltairPlotData:
        """
        Parameters:
            payload: The data to display in a bar plot.
        Returns:
            (Rarely used) passes the data displayed in the bar plot as an AltairPlotData dataclass, which includes the plot information as a JSON string, as well as the type of plot (in this case, "bar").
        """
        return payload

    def postprocess(self, value: pd.DataFrame | None) -> AltairPlotData | None:
        """
        Parameters:
            value: Expects a pandas DataFrame containing the data to display in the bar plot. The DataFrame should contain at least two columns, one for the x-axis (corresponding to this component's `x` argument) and one for the y-axis (corresponding to `y`).
        Returns:
            The data to display in a bar plot, in the form of an AltairPlotData dataclass, which includes the plot information as a JSON string, as well as the type of plot (in this case, "bar").
        """
        # if None or update
        if value is None:
            return value
        if self.x is None or self.y is None:
            raise ValueError("No value provided for required parameters `x` and `y`.")
        chart = self.create_plot(
            value=value,
            x=self.x,
            y=self.y,
            color=self.color,
            vertical=self.vertical,
            group=self.group,
            title=self.title,
            tooltip=self.tooltip,
            x_title=self.x_title,
            y_title=self.y_title,
            x_label_angle=self.x_label_angle,
            y_label_angle=self.y_label_angle,
            color_legend_title=self.color_legend_title,
            color_legend_position=self.color_legend_position,  # type: ignore
            group_title=self.group_title,
            y_lim=self.y_lim,
            interactive=self.interactive_chart,
            height=self.height,
            width=self.width,
            sort=self.sort,  # type: ignore
        )

        return AltairPlotData(type="altair", plot=chart.to_json(), chart="bar")

    def example_payload(self) -> Any:
        return None

    def example_value(self) -> Any:
        import pandas as pd

        return pd.DataFrame({self.x: [1, 2, 3], self.y: [4, 5, 6]})