Interaction with multiple widgets Bokeh - python-3.x

Question

EDIT: Some users have mentioned that the question is unclear. My objective is to keep track of previous states.
I am trying to create a plot that can be modified using 3 widgets. However, every new widget change does not take into consideration previous widget selections (for example, if a selection is made using widget 1 and then widget 2 is modified, the modification of widget 2 considers the original graph and not the changes made with widget 1).
I am trying to avoid using Custom_JS as I have no experience with Javascript. Is there any way to combine the functions so that any change in the widgets takes into consideration previous widget interactions?
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import matplotlib
from datetime import date
from ipywidgets import interact
from bokeh.io import push_notebook, show, output_notebook, curdoc
from bokeh.plotting import figure
from bokeh.layouts import column, layout, widgetbox, row
from bokeh.models import ColumnDataSource, HoverTool, CustomJS, Panel
from bokeh.layouts import widgetbox
from bokeh.models.widgets import RangeSlider, Slider, Select,
DateRangeSlider, Tabs
df = pd.read_csv("/Users/danielmontillanavas/Desktop/Tiller/00_Data/SF_may_correct_decimal.csv", sep =',',decimal=',')
df = df.drop(['Unnamed: 0'], axis=1)
df.rename(columns = {'Stamped phone from HS':'phone','Contact Email':'Email','Account Name':'Account_name',
'Opportunity ID':'ID', 'Close Date':'Close_date','Stamped-date of closed (DO NOT USE)':'Stamped_date',
'Quote Amount':'Quote_Amount', 'Lead Source':'Source','Desired activation date':'Activ_date'},
inplace=True)
df.Close_date = pd.to_datetime(df.Close_date, format='%Y-%m-%d')
cols_num = ['Quote_Amount','DISCOUNT']
df[cols_num] = df[cols_num].apply(pd.to_numeric)
df_closed = df[df['Stage']=='Closed']
df_closed.fillna("Unknown", inplace=True)
start_point = min(df['Quote_Amount'])
end_point = max(df['Quote_Amount'])
TOOLS = 'pan,wheel_zoom,box_zoom,reset,tap,save,box_select,lasso_select'
source = ColumnDataSource(df_closed)
hover = HoverTool(
tooltips=[
("Quote", "$x"),
("Discount", "$y")
]
)
p = figure(title='Quotes per Source - Closed deals',tools=[hover,TOOLS],
plot_height=800, plot_width=800)
p.circle('Quote_Amount','DISCOUNT',source=source, size = 8, color = 'CornflowerBlue', alpha = 0.6)
N = 20000
slider = Slider(start=start_point, end=end_point, step=10, value=N,
title='Select Quote Amount Cutoff')
dfList = df_closed.Source.unique().tolist()
All_view = ['All']
source_options = All_view + dfList
menu = Select(title = "Select Lead Source",options=source_options, value = 'All')
first_date = min(df['Close_date'])
last_date = max(df['Close_date'])
date_range_slider = DateRangeSlider(title="Select Date Range ", start=first_date, end=date.today(), value=(date(2017, 9, 7), date(2017, 10, 15)), step=1)
def slider_callback(attr, old, new):
N = new # this works also with slider.value but new is more explicit
new1 = ColumnDataSource(df_closed.loc[(df_closed.Quote_Amount < N)])
source.data = new1.data
slider.on_change('value',slider_callback)
def menu_callback(attr, old, new):
if menu.value == 'All': new2 = ColumnDataSource(df_closed)
else: new2 = ColumnDataSource(df_closed.loc[(df_closed.Source == menu.value)])
source.data = new2.data
menu.on_change('value',menu_callback)
def date_callback(attr, old, new):
start = date_range_slider.value_as_datetime[0].strftime("%Y-%m-%d")
end = date_range_slider.value_as_datetime[1].strftime("%Y-%m-%d")
df_closed_new = df_closed[df_closed['Close_date'] >= start]
df_closed_new = df_closed[df_closed['Close_date'] <= end]
new3 = ColumnDataSource(df_closed_new)
source.data = new3.data
date_range_slider.on_change('value',date_callback)
# Put controls in a single element
controls = widgetbox(menu, slider, date_range_slider)
# Create a row layout
layout = row(controls, p)
curdoc().add_root(layout)

Answer 1

You question is not very clear to me. Are you talking about the previous state of widgets? The callbacks have access to the current state of all the other widgets so if you want to maintain a history of their previous states you'll have to explicitly keep track of that.
However I immediately notice on thing that should not be done, so I am going to post an answer just to draw attention to it. Don't create new CDS objects just to use their .data attribute and throw them away:
new1 = ColumnDataSource(df_closed.loc[(df_closed.Quote_Amount < N)])
source.data = new1.data
There is alot of machinery under the covers that affords all the automatic synchronization other features of Bokeh. CDS in particular are extremely heavyweight, complicated objects, and doing this above is a known anti-pattern that can break things. Instead, if you just need a new suitable .data dict, then use from_df:
new_data = ColumnDataSource.from_df(df_closed.loc[(df_closed.Quote_Amount < N)])
source.data = new_data