HoverTool for multiple data series in bokeh scatter plot

Question

I have the following small example script making use of numpy and bokeh:

import numpy as np
import bokeh.plotting as bp
from bokeh.objects import HoverTool 
bp.output_file('test.html')

fig = bp.figure(tools="reset,hover")
x = np.linspace(0,2*np.pi)
y1 = np.sin(x)
y2 = np.cos(x)
s1 = fig.scatter(x=x,y=y1,color='#0000ff',size=10,legend='sine')
s1.select(dict(type=HoverTool)).tooltips = {"x":"$x", "y":"$y"}
s2 = fig.scatter(x=x,y=y2,color='#ff0000',size=10,legend='cosine')
s2.select(dict(type=HoverTool)).tooltips = {"x":"$x", "y":"$y"}
bp.show()

The problem is that the hover tool only works for the cosine curve but not for the sine.

I know that one option would be to plot both series togehter and change the color of the cosine data points:

import numpy as np
import bokeh.plotting as bp
from bokeh.objects import HoverTool 
bp.output_file('test.html')

fig = bp.figure(tools="reset,hover")
x = np.linspace(0,2*np.pi)

y1 = np.sin(x)
y2 = np.cos(x)

x = np.array([x,x]).flatten()
y = np.array([y1,y2]).flatten()

blue = np.array('#0000ff').flatten()
red = np.array('#ff0000').flatten()
colors = np.array([blue.repeat(len(y1)),red.repeat(len(y1))]).flatten()

s1 = fig.scatter(x=x,y=y,color=colors,size=10,legend='sine & cosine')
s1.select(dict(type=HoverTool)).tooltips = {"x":"$x", "y":"$y"}
bp.show()

But then I loose the legend entry for the second color.

How do I manage to be able to hover over both data sets and see the corresponding tooltip?

Thanks!

Max

Answer 1

Edit: Note that the approach below is necessary only if you want different tooltips for different glyphs. If you want the same tooltips for all glyphs, see the answer above.

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If you want to have multiple hover tools, you need to add multiple hover tools, each configured for a different renderer. You can add them this way:

p = figure()

r1 = p.circle([1,2,3], [4,5,6], color="blue")
p.add_tools(HoverTool(renderers=[r1], tooltips=TIPS))

r2 = p.square([4,5,6], [1,2,3], color="red")
p.add_tools(HoverTool(renderers=[r2], tooltips=TIPS))

Answer 2

The original answer was ancient and outdated, here is how to accomplish this with any modern version of Bokeh:

from bokeh.plotting import figure, show
import numpy as np

x = np.linspace(0, 2*np.pi)
y1 = np.sin(x)
y2 = np.cos(x)

fig = figure(tools="reset", tooltips=[("x", "$x"), ("y", "$y")])
s1 = fig.scatter(x, y1, color='#0000ff', size=10, legend_label='sine')
s2 = fig.scatter(x, y2, color='#ff0000', size=10, legend_label='cosine')

show(fig)