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I am creating an interactive scatter chart that includes dropdowns for x and y axes.

However, currently it will work only when the x and y axes source columns are numericals or date objects etc. In case of string columns nothing will get displayed.

How do I alter the script so it automatically changes the axis type from nominal to ordinal - and vice versa - depending on current dropdown selection?

# -*- coding: utf-8 -*-

from os.path import dirname, join
import numpy as np
import pandas.io.sql as psql
import sqlite3 as sql
import pandas as pd

from bokeh.plotting import figure
from bokeh.layouts import layout, widgetbox
from bokeh.models import ColumnDataSource, Div
from bokeh.models.widgets import Slider, Select, TextInput
from bokeh.io import curdoc

projects = pd.read_excel('explorer_data.xlsx')

#functions
year = lambda x : x.to_pydatetime().year

axis_map = header:header for header in list(projects)

# Create Input controls
budget = Slider(title="Minimum budget", value=80, start=0, end=200000, step=1000)
start_date = Slider(title="Project start date", start=1940, end=2019, value=1970, step=1)
end_date = Slider(title="Project end date", start=1940, end=2019, value=2019, step=1)

x_axis = Select(title="X Axis", options=sorted(axis_map.keys()), value="Budget")
y_axis = Select(title="Y Axis", options=sorted(axis_map.keys()), value="Spent/Paid")

# Create Column Data Source that will be used by the plot
source = ColumnDataSource(data=dict(x=, y=, number=, title=, year=, revenue=, alpha=))

TOOLTIPS=[
 ("ID", "@number")
# ("Year", "@year"),
# ("$", "@revenue")
]

p = figure(plot_height=600, plot_width=700, title="", toolbar_location=None, tools = "pan,wheel_zoom,box_zoom,reset", tooltips=TOOLTIPS)
p.circle(x="x", y="y", source=source, size=7)

def select_projects():
 selected = projects[

 (projects['Budget'] >= budget.value) &
 (projects['Start Date'].map(year) >= start_date.value) &
 (projects['End Date'].map(year) <= end_date.value)
 ]

 return selected


def update():
 df = select_projects()
 x_name = axis_map[x_axis.value]
 y_name = axis_map[y_axis.value]

 p.xaxis.axis_label = x_axis.value
 p.yaxis.axis_label = y_axis.value
 p.title.text = "%d projects selected" % len(df)
 source.data = dict(
 x=df[x_name],
 y=df[y_name],
 number=df['Project ID'],
 )

controls = [budget, start_date, end_date, x_axis, y_axis]
for control in controls:
 control.on_change('value', lambda attr, old, new: update())

sizing_mode = 'fixed' # 'scale_width' also looks nice with this example

inputs = widgetbox(*controls, sizing_mode=sizing_mode)
l = layout([
# [desc],
 [inputs, p],
], sizing_mode=sizing_mode)

update() # initial load of the data

curdoc().add_root(l)
curdoc().title = "Projects"