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- from __future__ import annotations
- from typing import TYPE_CHECKING
- from wandb.plot.custom_chart import plot_table
- if TYPE_CHECKING:
- import wandb
- from wandb.plot.custom_chart import CustomChart
- def bar(
- table: wandb.Table,
- label: str,
- value: str,
- title: str = "",
- split_table: bool = False,
- ) -> CustomChart:
- """Constructs a bar chart from a wandb.Table of data.
- Args:
- table: A table containing the data for the bar chart.
- label: The name of the column to use for the labels of each bar.
- value: The name of the column to use for the values of each bar.
- title: The title of the bar chart.
- split_table: Whether the table should be split into a separate section
- in the W&B UI. If `True`, the table will be displayed in a section named
- "Custom Chart Tables". Default is `False`.
- Returns:
- CustomChart: A custom chart object that can be logged to W&B. To log the
- chart, pass it to `wandb.log()`.
- Example:
- ```python
- import random
- import wandb
- # Generate random data for the table
- data = [
- ["car", random.uniform(0, 1)],
- ["bus", random.uniform(0, 1)],
- ["road", random.uniform(0, 1)],
- ["person", random.uniform(0, 1)],
- ]
- # Create a table with the data
- table = wandb.Table(data=data, columns=["class", "accuracy"])
- # Initialize a W&B run and log the bar plot
- with wandb.init(project="bar_chart") as run:
- # Create a bar plot from the table
- bar_plot = wandb.plot.bar(
- table=table,
- label="class",
- value="accuracy",
- title="Object Classification Accuracy",
- )
- # Log the bar chart to W&B
- run.log({"bar_plot": bar_plot})
- ```
- """
- return plot_table(
- data_table=table,
- vega_spec_name="wandb/bar/v0",
- fields={"label": label, "value": value},
- string_fields={"title": title},
- split_table=split_table,
- )
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