Improve Legend support for Layout and add documentation

[hoxbro]

closes #5833

This PR I want to implement the following:

• Add show_legends and legend_position to .opts for a Layout Plot. (Note that show_legends is plural)
• Add documentation for sync_legends and show_legends in a Layout plot.
• Add unit test for util.select_legends.
• Maybe rename util.select_legends to util.show_legends.

Example of show_legends:

import holoviews as hv
import hvplot.pandas
import numpy as np
import pandas as pd

df = pd.DataFrame(np.arange(10)[:, None] * np.array([1, 2, 3]), columns=list("ABC"))
plot = (df.hvplot() + df.hvplot() + df.hvplot() + df.hvplot()).cols(2)
plot.opts(sync_legends=True, show_legends=0, legend_position="top_left")

[codecov-commenter]

Codecov Report

Merging #5852 (1484cf8) into main (5ba6537) will increase coverage by 0.02%.
Report is 1 commits behind head on main.
The diff coverage is 100.00%.

@@            Coverage Diff             @@
##             main    #5852      +/-   ##
==========================================
+ Coverage   88.23%   88.26%   +0.02%     
==========================================
  Files         309      309              
  Lines       63915    63939      +24     
==========================================
+ Hits        56396    56436      +40     
+ Misses       7519     7503      -16     

Flag	Coverage Δ
ui-tests	23.37% <50.00%> (+<0.01%)	⬆️

Flags with carried forward coverage won't be shown. Click here to find out more.

Files Changed	Coverage Δ
holoviews/plotting/bokeh/plot.py	92.49% <100.00%> (+0.06%)	⬆️
holoviews/plotting/bokeh/util.py	68.86% <100.00%> (+1.96%)	⬆️
holoviews/tests/plotting/bokeh/test_utils.py	100.00% <100.00%> (ø)

... and 3 files with indirect coverage changes

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[philippjfr]

Looks good to me!

[hoxbro]

I have changed show_legends to None to not change current behavior like this should not show the legend of the first plot.

import holoviews as hv
import hvplot.pandas
import numpy as np
import pandas as pd

df = pd.DataFrame(np.arange(10)[:, None] * np.array([1, 2, 3]), columns=list("ABC"))
plot = (df.hvplot().opts(show_legend=False) + df.hvplot() + df.hvplot() + df.hvplot()).cols(2)
plot

[philippjfr]

Latest changes seem reasonable to me. Happy to see this merged.

[github-actions]

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