Conditional dropdown options

A senior purchasing officer in the e-commerce company has posed an interesting problem. Their existing dashboard, showing sales by month for minor categories of items, has a two-level dropdown (major category and minor category) with way too many options in it. It is especially annoying, you are told, that some options appear in the second dropdown that can not be selected.

You assure the stakeholder you can assist - it is an excellent opportunity for you to use chained callbacks to produce a conditional dropdown.

Cet exercice fait partie du cours

Building Dashboards with Dash and Plotly

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Instructions

Create a callback below line 31 to update the minor_cat_dd dropdown options based on the major_cat_dd dropdown value.
Reformat the relevant_minor_options variable (below line 39) into a list of dictionaries with identical label and value keys.
Create another callback below line 43 that updates the sales_line graph figure based on the minor_cat_dd dropdown value.

Exercice interactif pratique

Essayez cet exercice en complétant cet exemple de 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')
major_categories = list(ecom_sales['Major Category'].unique())
minor_categories = list(ecom_sales['Minor Category'].unique())
logo_link = 'https://assets.datacamp.com/production/repositories/5893/datasets/fdbe0accd2581a0c505dab4b29ebb66cf72a1803/e-comlogo.png'
ecom_country = ecom_sales.groupby('Country')['OrderValue'].agg(['sum', 'count']).reset_index().rename(columns={'count':'Sales Volume', 'sum':'Total Sales ($)'})

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('Major Category Select'),
    dcc.Dropdown(
      id='major_cat_dd',
      options=[{'label':category, 'value':category} for category in major_categories],
      style={'width':'200px', 'margin':'0 auto'}),
    html.Br(),
    html.H3('Minor Category Select'),
    dcc.Dropdown(id='minor_cat_dd', style={'width':'200px', 'margin':'0 auto'})],
    style={'width':'350px', 'height':'350px', 'display':'inline-block', 
           'vertical-align':'top', 'border':'1px solid black', 'padding':'20px'}),
  dcc.Graph(id='sales_line',style={'width':'700px', 'height':'650px','display':'inline-block'})
]

# Create a callback from the Major Category dropdown to the Minor Category Dropdown
@callback(
    Output('____', '____'),
    Input('major_cat_dd', 'value'))

def update_minor_dd(major_cat_dd):
    major_minor = ecom_sales[['Major Category', 'Minor Category']].drop_duplicates()
    relevant_minor_options = major_minor[major_minor['Major Category'] == major_cat_dd]['Minor Category'].values.tolist()
    # Set up the Major Category options with the same label and value
    formatted_relevant_minor_options = [{'label':____, 'value':____} for ____ in ____]
    return formatted_relevant_minor_options

# Create a callback for the Minor Category dropdown to update the line plot
@callback(
    Output('____', '____'),
    Input('minor_cat_dd', 'value'))

def update_line(minor_cat):
    minor_cat_title = 'All'
    ecom_line = ecom_sales.copy()
    if minor_cat:
        minor_cat_title = minor_cat
        ecom_line = ecom_line[ecom_line['Minor Category'] == minor_cat]
    ecom_line = ecom_line.groupby('Year-Month')['OrderValue'].agg('sum').reset_index(name='Total Sales ($)')
    line_graph = px.line(ecom_line, x='Year-Month',  y='Total Sales ($)', title=f'Total Sales by Month for Minor Category: {minor_cat_title}')
    return line_graph

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

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