I am new to python and want to make an interactive chart with a dataset given in class. I want to be able to simply display the data associated with the point I select with the TapTool in Bokeh. The data is too dense to jsut simply use the hovertool though. It seems the hovertool did not require javascript, but apparently getting the tap tool requires knowing a whole other coding language. I am not familiar with python as it is, so adding a javascript callback is making things a bit complicated.

Right now I have this figure plotted with my dataframe using data from the California Housing dataset from sci-kit. I also have the US_states sampledata from bokeh to plot too.

from bokeh.layouts import layout
from bokeh.plotting import figure, show, output_file
from bokeh.models import Circle, Div, ColumnDataSource, CustomJS, MultiChoice, HoverTool, LinearColorMapper, ColorBar
from bokeh.io import output_notebook
from bokeh.sampledata import us_states
from bokeh.transform import transform
from bokeh.models.tools import *

#US state sample data
us_states = us_states.data.copy()
us_states = us_states["CA"]



#Creating figure and adding california basemap
color = LinearColorMapper(palette = 'Viridis256',
                      low = df.MedInc.min(),
                      high = df.MedInc.max())
color2 = LinearColorMapper(palette = 'Inferno256',
                      low = df.price.min(),
                      high = df.price.max())

cal = figure(title = "California Housing Data Geographic Distribution",
         plot_width = 1000)

cal.circle('Longitude','Latitude',source = geo_source, 
       color= transform('MedInc', color),size =2,
       alpha = 0.2,legend_label = "Median Income")

cal.circle('Longitude','Latitude',source = geo_source, 
       color= transform('price', color2),size =1,
       alpha = 0.2,legend_label = "House Price")



 color_bar = ColorBar(color_mapper = color,
                 label_standoff = 14,
                 location = (0,0),
                 title = 'Median Income')

 color_bar2 = ColorBar(color_mapper = color2,
                 label_standoff = 14,
                 location = (0,0),
                 title = 'House Price')

 cal.add_layout(color_bar,'right')
 cal.add_layout(color_bar2,'right')

 cal.legend.location = "top_right"
 cal.legend.click_policy="hide"
                      

I have no clue what to write for the JS callback for the TapTool though since I'm not really sure how it works, how the variables transfer, etc.

callback = CustomJS(args=dict(source=geo_source), code="""
//Insert JS code here
""")

taptool = TapTool(callback=callback)
geo_source.selected.js_on_change('indices', callback)
cal.add_tools(taptool)