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"""gr.BarPlot() component."""
from __future__ import annotations
from typing import Any, Callable, Literal
import altair as alt
import pandas as pd
from gradio_client.documentation import document, set_documentation_group
from gradio.components.plot import AltairPlot, AltairPlotData, Plot
set_documentation_group("component")
from gradio.events import Dependency
@document()
class BarPlot(Plot):
"""
Create a bar plot.
Preprocessing: this component does *not* accept input.
Postprocessing: expects a pandas dataframe with the data to plot.
Demos: bar_plot, chicago-bikeshare-dashboard
"""
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,
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.
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. Queue must be enabled. 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.
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,
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 | None = None,
width: int | 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."""
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
chart = (
alt.Chart(value) # type: ignore
.mark_bar() # type: ignore
.encode(**encodings)
.properties(background="transparent", **properties)
)
if interactive:
chart = chart.interactive()
return chart
def postprocess(
self, value: pd.DataFrame | dict | None
) -> AltairPlotData | dict | None:
# if None or update
if value is None or isinstance(value, dict):
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_inputs(self) -> dict[str, Any]:
return {}
def preprocess(self, payload: AltairPlotData) -> AltairPlotData:
return payload |