Styjun

I am learning to use the Bokeh library on Python. What I have right now is this:

source = ColumnDataSource(data=dict(x=x, counts=rates))

My x value is an array of tuples, something like this:

x = [('A' ,'1'), ('B', '1'), ('C', '1'), ('A', '2'), ('B', '2'), ('C', '2')]

What I want is to have a tooltip in my graph that will display the second value of the tuple (the 1 or the 2, whichever corresponds). I created my tooltip like this:

TOOLTIPS = [("Rate", "@counts"), ("Value", "@x")]

The first one (Rate) is working fine and shows the value that I want, but the second one shows both values (A, 1) and I only want to show one of them (1). For the record this is how I am creating the figure:

p = figure(x_range=FactorRange(*x), sizing_mode='stretch_both', title="Test",toolbar_location=None, tools="", tooltips=TOOLTIPS)

Is this possible?

You can just split the x-array into two separate arrays so that...

x = [('A' ,'1'), ('B', '1'), ('C', '1'), ('A', '2'), ('B', '2'), ('C', '2')]

...becomes...

x_1 = ["A","B","C","A","B","C"]
x_2 = ["1","1","1","2","2","2"]

and then supply these arrays to the CDS.

Then in your tooltip you just reference x_2 like...

TOOLTIPS = [("Rate", "@counts"), ("Value", "@x_2")]

You could use HoverTool callback like this (Bokeh v1.0.4):

from bokeh.plotting import figure, show
from bokeh.models import ColumnDataSource, FactorRange, HoverTool, CustomJS

x = [('A' , '1'), ('B', '1'), ('C', '1'), ('A', '2'), ('B', '2'), ('C', '2')]
rates = [1, 2, 3, 4, 5, 6]

source = ColumnDataSource(data = dict(x = x, counts = rates))

TOOLTIPS = [("Rate", "@counts"), ("Value", "@x")]
p = figure(x_range = FactorRange(*x), sizing_mode = 'stretch_both', title = "Test", toolbar_location = None, tools = "")
p.vbar(x = 'x', top = 'counts', width = 0.2, source = source)

code = ''' if (cb_data.index.indices.length > 0) 
 index = cb_data.index.indices[0];
 x1 = source.data.x[index][1]
 hover.tooltips[1] = ['Value', x1]; 
 '''
hover = HoverTool()
hover.tooltips = TOOLTIPS
hover.callback = CustomJS(args = dict(source = source, hover = hover), code = code)
p.add_tools(hover)

show(p)

Result: