Pandas Dataframe and ipywidgets dropdown

import pandas as pd
import numpy as np
import ipywidgets as widgets
from ipywidgets import Layout, AppLayout
from IPython.display import display
import functools


# Initially, we will get the data and load it into a dataframe:
# Updated data frame to load in our test data
data = {'year': ['2000', '2000','2000','2000','2001','2001','2001','2001', '2002',  '2002', '2002', '2002',
                 '2003','2003','2003','2003','2004', '2004','2004','2004', '2005', '2005', '2005', '2005',
                 '2006', '2006', '2006', '2006', '2006', '2007', '2007', '2007', '2007', '2008', '2008', '2008', '2008',
                 '2009', '2009', '2009', '2009'],

        'purpose':['Holiday', 'Business', 'VFR', 'Study', 'Holiday', 'Business', 'VFR', 'Study', 'Holiday', 'Business',
                   'VFR', 'Study', 'Holiday', 'Business', 'VFR', 'Study', 'Holiday', 'Business', 'VFR', 'Study', 'Holiday',
                   'Business', 'VFR', 'Study', 'Holiday', 'Business', 'VFR', 'Study', 'Holiday', 'Business', 'VFR', 'Study',
                   'Holiday', 'Business', 'VFR', 'Study', 'Holiday', 'Business', 'VFR', 'Study', 'Holiday'
                  ],

        'market':['Belgium', 'Luxembourg', 'France', 'Spain', 'Norway', 'Sweden', 'Germany', 'Austria', 'Denmark',
                  'Portugal', 'Greece', 'Croatia', 'Belgium', 'Luxembourg', 'France', 'Spain', 'Norway', 'Sweden',
                  'Germany', 'Austria', 'Denmark', 'Portugal', 'Greece', 'Croatia', 'Belgium', 'Luxembourg', 'France',
                  'Spain', 'Norway', 'Sweden', 'Germany', 'Austria', 'Denmark', 'Portugal', 'Greece', 'Croatia', 'Belgium',
                  'Luxembourg', 'France', 'Spain', 'Norway'
                 ]}

df_london = pd.DataFrame (data, columns = ['year','purpose', 'market'])

#df_london = pd.read_csv(file, encoding = 'ISO-8859-1')

# Example of when the dropdown year is selected a new text box is
# displayed to show the purpose filter

# Setup our List boxes to filter results based on filter choices
ALL = 'ALL'
def unique_sorted_values_plus_ALL(array):
    unique = array.unique().tolist()
    unique.sort()
    unique.insert(0, ALL)
    return unique

# variable to store the common output for the dropdowns
output = widgets.Output()

# Here are the three dropdowns:
dropdown_year = widgets.Dropdown(description='Year',
                                  options = unique_sorted_values_plus_ALL(df_london.year))

dropdown_purpose = widgets.Dropdown(description='Purpose',
                                     options = unique_sorted_values_plus_ALL(df_london.purpose))

dropdown_market = widgets.Dropdown(description='Market',
                                    options = unique_sorted_values_plus_ALL(df_london.market))

# Function to filter our dropdown listboxes
def common_filtering(year,purpose, market):

    # Make a copy of our data frame
    df = df_london.copy()

    # Initialise our empty list
    filters = []

    # Evaluate our dropdown list boxes and return booleans for our selections
    if year is not ALL:
        filters.append(df['year'] == year)
    if purpose is not ALL:
        filters.append(df['purpose'] == purpose)
    if market is not ALL:
        filters.append(df['market'] == market)

    # Ensure that we dont append our results to the cell
    # but overwrite the old results with the new
    output.clear_output()


    with output:
        if filters:
            # Create a pandas Array of True/False for each of teh entries
            df_filter = functools.reduce(lambda x,y: x&y, filters)
            # Using dataframe.loc show our filtered results
            display(df.loc[df_filter])
        else:
            # Otherwise display everything
            display(df)

# We amend the event handlers to call the common_filtering function and pass the change.new value as well as the
# current value of the other dropdown:

def dropdown_year_eventhandler(change):
    common_filtering(change.new, dropdown_purpose.value, dropdown_market.value)

def dropdown_purpose_eventhandler(change):
    common_filtering(dropdown_year.value, change.new, dropdown_market.value,)

def dropdown_market_eventhandler(change):
    common_filtering(dropdown_year.value, dropdown_purpose.value, change.new)

# We bind the handlers to the dropdowns, and that’s it!
dropdown_year.observe(dropdown_year_eventhandler, names='value')
dropdown_purpose.observe(dropdown_purpose_eventhandler, names='value')
dropdown_market.observe(dropdown_market_eventhandler, names='value')

# Setup our Hbox to display the list boxes in a line
box_layout = widgets.Layout(display = 'inline-flex',
                           flex_flow = 'row',
                           align_items = 'stretch',
                           border = 'solid',
                           width = '100%')
# Wrap up our widgets in a variable and assign them the box_layout style
ui = widgets.HBox([dropdown_year, dropdown_purpose, dropdown_market], layout=box_layout)

# Display our dropdown boxes and the output from the selection
display(ui, output)