Bokeh source change - bokeh

Question

I am trying to update the data source for a Bokeh scatter plot using a function.
But instead of plotting only the new data, the plot shows all of it.
I think I'm passing a new data source to the plot, but the old plotted points persist.
How would you update the scatterplot with just new data?
Also, is there any way of retrieving the current selection in the dropdown menu without interacting with it? (i.e. without a callback that uses on_change)
import numpy as np
import pandas as pd
from bokeh.models import ColumnDataSource
from bokeh.models.widgets import Tabs, Select
from bokeh.layouts import column, row, Spacer
from bokeh.io import curdoc
from bokeh.plotting import figure, curdoc, show
#Plotting points on initial chart.
df_AB = pd.DataFrame(np.random.randint(0,100,size=(500, 2)), columns=list('AB'), index=[str(i) for i in range(1,500+1)])
pointchart=figure(plot_width=800, plot_height=700, tools=['lasso_select','box_select'],title="Point scatter")
pointchart_source= ColumnDataSource(df_AB[["A","B"]])
pointchart_glyph= pointchart.circle("A","B",source=pointchart_source)
#Dropdown
selectoroptions=['','new selection', 'other selection']
Xselector = Select(title="Dropdown:", value="", options=selectoroptions)
#Callback to update data source
def Xdropdownchange(attrname, old, new):
pointchart_glyph= pointchart.circle("X","Y",source=make_updated_source())
Xselector.on_change("value", Xdropdownchange)
#Making new/updated data source based on dropdowns.
df_XY = pd.DataFrame(np.random.randint(0,100,size=(500, 2)), columns=list('XY'), index=[str(i) for i in range(1,500+1)])
def make_updated_source():
new_x=pd.Series(list(df_XY.iloc[0:100]["X"]),name="X")
new_y=pd.Series(list(df_XY.iloc[0:100]["Y"]),name="Y")
sourcedf=pd.DataFrame([new_x,new_y]).T
pointchart_source= ColumnDataSource(sourcedf)
return pointchart_source
#Show
layout=row(column(Xselector, Spacer(width=400, height=500)),pointchart)
curdoc().add_root(layout)
!powershell -command {'bokeh serve --show Dropdown_sourcechange.ipynb'}

Answer 1

I changed some things in your code and it now shows your original data if you select the empty value in your dropdown or a randomly generated dataset when you select one of the other values in the dropdown. Retrieving the current selection in the dropdown without using a callback is also possible with print(Xselector.value)
import numpy as np
import pandas as pd
from bokeh.models import ColumnDataSource
from bokeh.models.widgets import Tabs, Select
from bokeh.layouts import column, row, Spacer
from bokeh.io import curdoc
from bokeh.plotting import figure, curdoc, show
#Plotting points on initial chart.
df_AB = pd.DataFrame(np.random.randint(0,100,size=(500, 2)), columns=list('XY'), index=[str(i) for i in range(1,500+1)])
pointchart=figure(plot_width=800, plot_height=700, tools=['lasso_select','box_select','wheel_zoom'],title="Point scatter")
source= ColumnDataSource(df_AB[["X","Y"]])
pointchart.circle("X","Y",source=source)
#Dropdown
selectoroptions=['','new selection', 'other selection']
Xselector = Select(title="Dropdown:", value="", options=selectoroptions)
def make_updated_source(attr, old, new):
if new == '':
source.data = ColumnDataSource(df_AB[["X","Y"]]).data
else:
df_XY = pd.DataFrame(np.random.randint(0,100,size=(500, 2)), columns=list('XY'), index=[str(i) for i in range(1,500+1)])
new_x=pd.Series(list(df_XY.iloc[0:100]["X"]),name="X")
new_y=pd.Series(list(df_XY.iloc[0:100]["Y"]),name="Y")
sourcedf=pd.DataFrame([new_x,new_y]).T
source.data = ColumnDataSource(sourcedf).data
Xselector.on_change("value", make_updated_source)
#Retrieve selection in dropdown withoud on_change
print(Xselector.value)
#Show
layout=row(column(Xselector, Spacer(width=400, height=500)),pointchart)
curdoc().add_root(layout)
!powershell -command {'bokeh serve --show Dropdown_sourcechange.ipynb'}