Holoview Dataset: Independent Axes Range with multiple Plots hv.Path

HoloViews
1

I would like to plot a Dataset with hv.Path but scale the y_axis independently for each appended plot.
Whatever I tried it seems all y_axes will be set to one option only. Is there any way to define the y axis according to a value in a column?

plot_column = pn.Column()

# Iterate through unique values of 'measurand' and create a separate plot for each
for measurand_value, group_df in selected_columns.groupby('measurand'):
    group_df = group_df.sort_values(by='frequency', ascending=True)  # Sort by 'frequency' in ascending order
    dataset = hv.Dataset(group_df, kdims=['frequency', 'signal'], vdims=['ID'])

    if measurand_value in ('LOW', 'VERYLOW'):
        y_range = (-0.005, 0.005)
    else:
        y_range = (-0.001, 0.001)

    path_plot = hv.Path(dataset, label=f"'measurand': {measurand_value}").opts(
        width=1280, height=600
    )
    plot_column.append(path_plot)

Edit: I have made some progress with: opts(shared_axes=False) so at least the axes are independent now

2

It works like this:

for measurand_value, group_df in filtered_df.groupby('measurand'):
    group_df = group_df.sort_values(by='frequency', ascending=True)
    dataset = hv.Dataset(group_df, kdims=['frequency', 'signal'], vdims=['ID'])
    # Define y_range based on the condition
    if measurand_value in ('BC1x', 'BC1y', 'BC1z'):
        y_range = (-0.01, 0.01)
    else:
        y_range = (-0.1, 0.1)
    path_plot = hv.Path(dataset, label=f"'measurand': {measurand_value}").opts(
        width=1280, height=600, shared_axes=False, ylim=y_range
    )
    plot_column.append(path_plot)