In Bokeh, how do I add tooltips to a Timeseries chart (hover tool)?

Below is what I came up with.

Its not pretty but it works.

Im still new to Bokeh (& Python for that matter) so if anyone wants to suggest a better way to do this, please feel free.

import pandas as pdimport numpy as npfrom bokeh.charts import TimeSeriesfrom bokeh.models import HoverToolfrom bokeh.plotting import showtoy_df = pd.DataFrame(data=np.random.rand(5,3), columns = ('a', 'b' ,'c'), index = pd.DatetimeIndex(start='01-01-2015',periods=5, freq='d'))        _tools_to_show = 'box_zoom,pan,save,hover,resize,reset,tap,wheel_zoom'        p = figure(width=1200, height=900, x_axis_type="datetime", tools=_tools_to_show)# FIRST plot ALL lines (This is a hack to get it working, why can't i pass in a dataframe to multi_line?)   # It's not pretty but it works. # what I want to do!: p.multi_line(df)ts_list_of_list = []for i in range(0,len(toy_df.columns)):    ts_list_of_list.append(toy_df.index.T)vals_list_of_list = toy_df.values.T.tolist()# Define colors because otherwise multi_line will use blue for all lines...cols_to_use =  ['Black', 'Red', 'Lime']p.multi_line(ts_list_of_list, vals_list_of_list, line_color=cols_to_use)# THEN put  scatter one at a time on top of each one to get tool tips (HACK! lines with tooltips not yet supported by Bokeh?) for (name, series) in toy_df.iteritems():    # need to repmat the name to be same dimension as index    name_for_display = np.tile(name, [len(toy_df.index),1])    source = ColumnDataSource({'x': toy_df.index, 'y': series.values, 'series_name': name_for_display, 'Date': toy_df.index.format()})    # trouble formating x as datestring, so pre-formating and using an extra column. It's not pretty but it works.    p.scatter('x', 'y', source = source, fill_alpha=0, line_alpha=0.3, line_color="grey")         hover = p.select(dict(type=HoverTool))    hover.tooltips = [("Series", "@series_name"), ("Date", "@Date"),  ("Value", "@y{0.00%}"),]    hover.mode = 'mouse'show(p)

I’m not familiar with Pandas，I just use python list to show the very example of how to add tooltips to muti_lines, show series names ,and properly display date/time。Below is the result.Thanks to @bs123's answer and @tterry's answer in Bokeh Plotting: Enable tooltips for only some glyphs

my result

# -*- coding: utf-8 -*-from bokeh.plotting import figure, output_file, show, ColumnDataSourcefrom bokeh.models import  HoverToolfrom datetime import datetimedateX_str = ['2016-11-14','2016-11-15','2016-11-16']#conver the string of datetime to python  datetime objectdateX = [datetime.strptime(i, "%Y-%m-%d") for i in dateX_str]v1= [10,13,5]v2 = [8,4,14]v3= [14,9,6]v = [v1,v2,v3]names = ['v1','v2','v3']colors = ['red','blue','yellow']output_file('example.html',title = 'example of add tooltips to multi_timeseries')tools_to_show = 'hover,box_zoom,pan,save,resize,reset,wheel_zoom'p = figure(x_axis_type="datetime", tools=tools_to_show)#to show the tooltip for multi_lines,you need use the ColumnDataSource which define the data source of glyph#the key is to use the same column name for each data source of the glyph#so you don't have to add tooltip for each glyph,the tooltip is added to the figure#plot each timeseries line glyphfor i in xrange(3):# bokeh can't show datetime object in tooltip properly,so we use string instead    source = ColumnDataSource(data={                'dateX': dateX, # python datetime object as X axis                'v': v[i],                'dateX_str': dateX_str, #string of datetime for display in tooltip                'name': [names[i] for n in xrange(3)]            })    p.line('dateX', 'v',source=source,legend=names[i],color = colors[i])    circle = p.circle('dateX', 'v',source=source, fill_color="white", size=8, legend=names[i],color = colors[i])    #to avoid some strange behavior(as shown in the picture at the end), only add the circle glyph to the renders of hover tool    #so tooltip only takes effect on circle glyph    p.tools[0].renderers.append(circle)# show the tooltiphover = p.select(dict(type=HoverTool))hover.tooltips = [("value", "@v"), ("name", "@name"), ("date", "@dateX_str")]hover.mode = 'mouse'show(p)

tooltips with some strange behavior,two tips displayed at the same time

Here is my solution. I inspected the glyph render data source to see what are the names on it. Then I use those names on the hoover tooltips. You can see the resulting plot here.

import numpy as npfrom bokeh.charts import TimeSeriesfrom bokeh.models import HoverToolfrom bokeh.plotting import showtoy_df = pd.DataFrame(data=np.random.rand(5,3), columns = ('a', 'b' ,'c'), index = pd.DatetimeIndex(start='01-01-2015',periods=5, freq='d'))   #Bockeh display dates as numbers so convert to string tu show correctlytoy_df.index = toy_df.index.astype(str) p = TimeSeries(toy_df, tools='hover')  #Next 3 lines are to inspect how are names on gliph to call them with @name on hover#glyph_renderers = p.select(dict(type=GlyphRenderer))#bar_source = glyph_renderers[0].data_source#print(bar_source.data)  #Here we can inspect names to call on hoverhover = p.select(dict(type=HoverTool))hover.tooltips = [        ("Series", "@series"),        ("Date", "@x_values"),        ("Value", "@y_values"),        ]show(p)