Dumbbell

simple_dumbbell(data, title='Dumbbell plot', marker_size=16, marker_line_width=8, plotly_kwargs=None, size=None, show_legend=None, show=True, write_html_path=None)

Creates a dumbbell plot. These are useful to show the difference between two sets of data which have the same categories. For instance, it can be used to compare two binary classifiers by plotting the various classification metrics.

Example:

from blitzly.plots.dumbbell import simple_dumbbell
import numpy as np
import pandas as pd

data = {
    "foo": np.random.randn(10),
    "bar": np.random.randn(10),
}
index = [f"category_{i+1}" for i in range(10)]
df = pd.DataFrame(data, index=index)

simple_dumbbell(df)

Parameters:

Name	Type	Description	Default
data	Union[pd.DataFrame, NDArray]	Data to plot.	required
title	str	Title of the plot.	'Dumbbell plot'
marker_size	int	Size of the circular marker of the dumbbells.	16
marker_line_width	int	Thickness of the line joining the markers.	8
plotly_kwargs	Optional[dict]	Additional keyword arguments to pass to Plotly go.Scatter.	None
size	Optional[Tuple[int, int]	Size of the plot.	None
show_legend	Optional[bool]	Whether to show the legend.	None
show	bool	Whether to show the figure.	True
write_html_path	Optional[str]	The path to which the histogram should be written as an HTML file. If None, the histogram will not be saved.	None

Returns:

Name	Type	Description
BaseFigure	BaseFigure	The dumbbell plot.

Source code in blitzly/plots/dumbbell.py

def simple_dumbbell(
    data: Union[pd.DataFrame, NDArray],
    title: str = "Dumbbell plot",
    marker_size: int = 16,
    marker_line_width: int = 8,
    plotly_kwargs: Optional[dict] = None,
    size: Optional[Tuple[int, int]] = None,
    show_legend: Optional[bool] = None,
    show: bool = True,
    write_html_path: Optional[str] = None,
) -> BaseFigure:
    """Creates a dumbbell plot. These are useful to show the difference between
    two sets of data which have the same categories. For instance, it can be
    used to compare two binary classifiers by plotting the various
    classification metrics.

    Example:
    ```python
    from blitzly.plots.dumbbell import simple_dumbbell
    import numpy as np
    import pandas as pd

    data = {
        "foo": np.random.randn(10),
        "bar": np.random.randn(10),
    }
    index = [f"category_{i+1}" for i in range(10)]
    df = pd.DataFrame(data, index=index)

    simple_dumbbell(df)
    ```

    Args:
        data (Union[pd.DataFrame, NDArray]): Data to plot.
        title (str): Title of the plot.
        marker_size (int): Size of the circular marker of the dumbbells.
        marker_line_width (int): Thickness of the line joining the markers.
        plotly_kwargs (Optional[dict]): Additional keyword arguments to pass to Plotly `go.Scatter`.
        size (Optional[Tuple[int, int]): Size of the plot.
        show_legend (Optional[bool]): Whether to show the legend.
        show (bool): Whether to show the figure.
        write_html_path (Optional[str]): The path to which the histogram should be written as an HTML file.
            If None, the histogram will not be saved.

    Returns:
        BaseFigure: The dumbbell plot.
    """

    data = check_data(data, min_rows=1, min_columns=2, max_columns=2, as_pandas=True)

    fig = go.Figure()

    for index, row in data.iterrows():
        fig.add_trace(
            go.Scatter(
                x=[row.iloc[0], row.iloc[1]],
                y=[index, index],
                mode="lines",
                showlegend=False,
                line={
                    "color": "black",
                    "width": marker_line_width,
                },
            )
        )

    for column_idx, column_name in enumerate(data.columns):
        fig.add_trace(
            go.Scatter(
                x=data.iloc[:, column_idx],
                y=data.index,
                mode="markers",
                name=column_name,
                **plotly_kwargs if plotly_kwargs else {},
            )
        )

    fig.update_traces(
        marker=dict(size=marker_size),
    )

    fig = update_figure_layout(fig, title, size, show_legend)
    return save_show_return(fig, write_html_path, show)