CODEWITHSUNDEEP
pythonpython-3.xhoverbokeh
thosphor
thosphor

Reputation: 2781

Multiple HoverTools for different lines (bokeh)

I have more than one line on a bokeh plot, and I want the HoverTool to show the value for each line, but using the method from a previous stackoverflow answer isn't working:

https://stackoverflow.com/a/27549243/3087409

Here's the relevant code snippet from that answer:

fig = bp.figure(tools="reset,hover")
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')
fig.select(dict(type=HoverTool)).tooltips = {"x":"$x", "y":"$y"}

And here's my code:

from bokeh.models import HoverTool
from bokeh.plotting import figure

source = ColumnDataSource(data=dict(
    x = [list of datetimes]
    wind = [some list]
    coal = [some other list]
    )
)

hover = HoverTool(mode = "vline")

plot = figure(tools=[hover], toolbar_location=None,
    x_axis_type='datetime')

plot.line('x', 'wind')
plot.select(dict(type=HoverTool)).tooltips = {"y":"@wind"}
plot.line('x', 'coal')
plot.select(dict(type=HoverTool)).tooltips = {"y":"@coal"}

As far as I can tell, it's equivalent to the code in the answer I linked to, but when I hover over the figure, both hover tools boxes show the same value, that of the wind.

Upvotes: 7

Views: 7380

Answers (1)

Space Impact
Space Impact

Reputation: 13255

You need to add renderers for each plot. Check this. Also do not use samey label for both values change the names.

from bokeh.models import HoverTool
from bokeh.plotting import figure

source = ColumnDataSource(data=df)

plot = figure(x_axis_type='datetime',plot_width=800, plot_height=300)

plot1 =plot.line(x='x',y= 'wind',source=source,color='blue')
plot.add_tools(HoverTool(renderers=[plot1], tooltips=[('wind',"@wind")],mode='vline'))

plot2 = plot.line(x='x',y= 'coal',source=source,color='red')
plot.add_tools(HoverTool(renderers=[plot2], tooltips=[("coal","@coal")],mode='vline'))

show(plot)

The output look like this. OUTPUT

Upvotes: 17

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