code: def update():
      ages.data = df[
          (df.Location == location.value) & (df.Year == int(year.value))
      ]
  
      pop = (
          df[df.Location == location.value].groupby(df.Year).Value.sum()
      )
      new_known = pop[pop.index <= 2010]
      new_predicted = pop[pop.index >= 2010]
      known.data = dict(x=new_known.index.map(str), y=new_known.values)
      predicted.data = dict(
          x=new_predicted.index.map(str), y=new_predicted.values
      )
  
file_path: bokeh/examples/server/app/population.py
imports: from math import pi
  from bokeh.io import curdoc
  from bokeh.layouts import column, row
  from bokeh.models import ColumnDataSource, CustomJSTickFormatter, CustomJSTransform, Select
  from bokeh.plotting import figure
  from bokeh.sampledata.population import data
  from bokeh.transform import factor_cmap, transform
label_desc: Use image node_id 1 for calling a global function with example usage: update() without return types