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A dropdown for sales by country

As you were working away at your desk, the global sales manager from the e-commerce company stopped by with a new challenge. She liked the recent sales graphs you created, but wants to filter by country and see the category data update live.

She emphasized using the approved country names: United Kingdom, Germany, France, Australia, and Hong Kong.

🛑 Note: You may need to enter Full screen mode to view the dashboard correctly with all elements side-by-side.

This exercise is part of the course

Building Dashboards with Dash and Plotly

View Course

Exercise instructions

  • Add a dropdown component called dcc.Dropdown with an identifier of country_dd below line 16 to be used in a callback.
  • Set the input and output of the callback below line 30 to connect the country_dd dropdown to the major_cat graph.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

from dash import Dash, dcc, html, Input, Output, callback
import plotly.express as px
import pandas as pd
ecom_sales = pd.read_csv('/usr/local/share/datasets/ecom_sales.csv')
logo_link = 'https://assets.datacamp.com/production/repositories/5893/datasets/fdbe0accd2581a0c505dab4b29ebb66cf72a1803/e-comlogo.png'

app = Dash()

app.layout = [
    html.Img(src=logo_link, style={'margin': '30px 0px 0px 0px'}),
    html.H1('Sales breakdowns'),
    html.Div([
        html.H2('Controls'),
        html.Br(),
        html.H3('Country Select'),
        # Add a dropdown with identifier
        dcc.____(
            ____='country_dd',
            options=['United Kingdom', 'Germany', 'France', 'Australia', 'Hong Kong'],
            style={'width': '200px', 'margin': '0 auto'})],
      	style={'width': '350px', 'height': '350px', 'display': 'inline-block', 'vertical-align': 'top', 'border': '1px solid black', 'padding': '20px'}),
    html.Div([
        dcc.Graph(id='major_cat'),
        html.H2('Major Category', style={'border': '2px solid black', 'width': '200px', 'margin': '0 auto'})],
        style={'width': '700px', 'display': 'inline-block'})
]


@callback(
    # Set the input and output of the callback to link the dropdown to the graph
    ____(component_id='____', component_property='____'),
    ____(component_id='____', component_property='____')
)

def update_plot(input_country):
    country_filter = 'All Countries'
    sales = ecom_sales.copy(deep=True)
    if input_country:
        country_filter = input_country
        sales = sales[sales['Country'] == country_filter]
    ecom_bar_major_cat = sales.groupby('Major Category')['OrderValue'].agg('sum').reset_index(name='Total Sales ($)')
    bar_fig_major_cat = px.bar(
        title=f'Sales in {country_filter}', data_frame=ecom_bar_major_cat, x='Total Sales ($)', y='Major Category', color='Major Category',
                 color_discrete_map={'Clothes':'blue','Kitchen':'red','Garden':'green','Household':'yellow'})
    return bar_fig_major_cat


if __name__ == '__main__':
    app.run(debug=True)
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