Upload my_dashboard.py

my_dashboard.py

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+#!/usr/bin/env python
+# coding: utf-8
+
+# In[13]:
+
+
+import altair as alt
+import pandas as pd
+import panel as pn
+
+# Load the Panel extension
+
+pn.extension('vega')
+
+
+# Load the dataset
+data = pd.read_csv("/Users/kenzabaddou/Downloads/archive/marketing_campaign.csv", sep=";")
+
+# Data cleaning
+data = data.rename(columns=lambda x: x.strip())  # Remove leading and trailing spaces from column names
+data = data.dropna(subset=['Income'])
+mean_income = data['Income'].mean()
+data['Income'] = data['Income'].fillna(mean_income)
+data['total_spent'] = data[['MntWines', 'MntFruits', 'MntMeatProducts', 'MntFishProducts', 'MntSweetProducts', 'MntGoldProds']].sum(axis=1)
+
+# Define widgets
+education_dropdown = alt.binding_select(options=sorted(data['Education'].unique()), name='Education Level:')
+education_select = alt.selection_single(fields=['Education'], bind=education_dropdown, name='Select')
+
+# New widget: marital status dropdown
+marital_status_dropdown = alt.binding_select(options=sorted(data['Marital_Status'].unique()), name='Marital Status:')
+marital_status_select = alt.selection_single(fields=['Marital_Status'], bind=marital_status_dropdown, name='Select')
+
+# New widget: range slider for number of web visits
+num_web_visits_slider = alt.binding_range(min=0, max=data['NumWebVisitsMonth'].max(), step=1, name='Web Visits per Month:')
+num_web_visits_select = alt.selection_single(fields=['NumWebVisitsMonth'], bind=num_web_visits_slider, name='Select')
+
+# Add new widgets for product selection
+products = ['MntWines', 'MntFruits', 'MntMeatProducts', 'MntFishProducts', 'MntSweetProducts', 'MntGoldProds']
+product_x_dropdown = alt.binding_select(options=products, name='Product X:')
+product_x_select = alt.selection_single(fields=['x_product'], bind=product_x_dropdown, init={'x_product': 'MntWines'})
+product_y_dropdown = alt.binding_select(options=products, name='Product Y:')
+product_y_select = alt.selection_single(fields=['y_product'], bind=product_y_dropdown, init={'y_product': 'MntMeatProducts'})
+
+
+# Define views
+
+# View 1: Bar chart of customer distribution by education level
+education_chart = alt.Chart(data).mark_bar().encode(
+    x=alt.X('Education:N', title='Education Level'),
+    y=alt.Y('count():Q', title='Number of Customers'),
+    color='Education:N'
+).properties(title='Customer Distribution by Education Level')
+
+
+# Define widgets
+education_dropdown = alt.binding_select(options=sorted(data['Education'].unique()), name='Education Level:')
+education_select = alt.selection_single(fields=['Education'], bind=education_dropdown, name='Select')
+income_slider = alt.binding_range(min=0, max=data['Income'].max(), step=1000, name='Annual Income:')
+income_select = alt.selection_single(fields=['Income'], bind=income_slider, name='Select')
+
+# View 2: Scatter plot of customer annual income and total amount spent on products (with interaction)
+scatter_chart = alt.Chart(data).mark_circle().encode(
+    x=alt.X('Income:Q', title='Annual Income'),
+    y=alt.Y('total_spent:Q', title='Total Amount Spent on Products'),
+    color='Education:N',
+    tooltip=[
+        alt.Tooltip('Education'),
+        alt.Tooltip('Marital_Status'),
+        alt.Tooltip('Income', format='$,.0f'),
+        alt.Tooltip('total_spent', format='$,.0f')
+    ]
+).properties(title='Customer Annual Income vs Amount Spent on Products').add_selection(
+    education_select, income_select, marital_status_select, num_web_visits_select
+).transform_filter(
+    education_select
+).transform_filter(
+    income_select
+).transform_filter(
+    marital_status_select
+).transform_filter(
+    num_web_visits_select
+)
+
+
+# Define linked selection
+brush = alt.selection(type='interval')
+
+# View 5: Bar chart - Average Total Spending per Education Level (linked to scatter chart)
+avg_spending_by_education = alt.Chart(data).mark_bar().encode(
+    x=alt.X('Education:N', title='Education Level'),
+    y=alt.Y('mean(total_spent):Q', title='Average Total Spending'),
+    tooltip=['Education', 'mean(total_spent):Q']
+).properties(title='Average Total Spending per Education Level').add_selection(
+    brush
+).transform_filter(
+    education_select
+)
+
+# View 6: Yearly Total Amount Spent on Products (linked to enrollment chart)
+yearly_total_spent_chart = alt.Chart(data).mark_line().encode(
+    x=alt.X('year(Dt_Customer):O', title='Year'),
+    y=alt.Y('sum(total_spent):Q', title='Total Amount Spent'),
+    tooltip=['year(Dt_Customer):O', 'sum(total_spent):Q']
+).transform_filter(
+    education_select
+)
+
+# View 3: Timeline chart of new customer enrollments (with linked highlighting)
+enrollment_chart = alt.Chart(data).mark_line().encode(
+    x=alt.X('year(Dt_Customer):T', title='Year of Enrollment'),
+    y=alt.Y('count():Q', title='Number of New Enrollments'),
+    color='Marital_Status:N').properties(title='New Customer Enrollments Over Time').add_selection(
+    brush, education_select, income_select, marital_status_select, num_web_visits_select).transform_filter(
+    education_select).transform_filter(income_select).transform_filter(marital_status_select).transform_filter(
+    num_web_visits_select)
+
+# New View: Average spending per marital status (with linked highlighting)
+
+avg_spending_by_marital_status = alt.Chart(data).mark_bar().encode(
+x=alt.X('Marital_Status:N', title='Marital Status'),
+y=alt.Y('mean(total_spent):Q', title='Average Total Spending'),
+color='Marital_Status:N',
+tooltip=['Marital_Status', 'mean(total_spent):Q']).properties(title='Average Total Spending per Marital Status').add_selection(brush)
+
+import pandas as pd
+import altair as alt
+
+
+# Convert the 'Dt_Customer' column to datetime format
+data['Dt_Customer'] = pd.to_datetime(data['Dt_Customer'])
+
+# Create 'total_spent' column by summing up spending in different product categories
+data['total_spent'] = data[['MntWines', 'MntFruits', 'MntMeatProducts', 'MntFishProducts', 'MntSweetProducts', 'MntGoldProds']].sum(axis=1)
+
+# Calculate the average spending for each combination of Teenhome, Kidhome, and Marital_Status
+avg_spending = data.groupby(['Teenhome', 'Kidhome', 'Marital_Status'])['total_spent'].mean().reset_index()
+
+# Create a hover selection
+hover = alt.selection_single(on='mouseover', nearest=True, empty='none')
+
+# Create a selection for the dropdown
+marital_status_dropdown = alt.binding_select(options=sorted(data['Marital_Status'].unique()), name='Marital Status:')
+marital_status_select = alt.selection_single(fields=['Marital_Status'], bind=marital_status_dropdown, init={'Marital_Status': 'Married'})
+
+# Create a grouped bar chart for kids
+chart_kids = alt.Chart(avg_spending).mark_bar().encode(
+    x=alt.X('Kidhome:O', title='Number of Kids at Home'),
+    y=alt.Y('total_spent:Q', title='Average Spending'),
+    color=alt.condition(hover, 'Kidhome:O', alt.value('lightgray'), legend=alt.Legend(title='Number of Kids at Home')),
+    tooltip=['Teenhome', 'Kidhome', 'total_spent', 'Marital_Status']
+).properties(title='Average Spending by Number of Kids at Home (Filtered by Marital Status)').add_selection(
+    hover
+)
+
+# Create a grouped bar chart for teens
+chart_teens = alt.Chart(avg_spending).mark_bar().encode(
+    x=alt.X('Teenhome:O', title='Number of Teens at Home'),
+    y=alt.Y('total_spent:Q', title='Average Spending'),
+    color=alt.condition(hover, 'Teenhome:O', alt.value('lightgray'), legend=alt.Legend(title='Number of Teens at Home')),
+    tooltip=['Teenhome', 'Kidhome', 'total_spent', 'Marital_Status']
+).properties(title='Average Spending by Number of Teens at Home (Filtered by Marital Status)').add_selection(
+    hover
+)
+
+# Combine the charts
+concat_chart = alt.hconcat(chart_kids, chart_teens).add_selection(
+    marital_status_select
+).transform_filter(
+    marital_status_select
+)
+
+
+"""scatter_plot = alt.Chart(data).mark_circle().encode(
+    x=alt.X('NumWebVisitsMonth:Q', title='Number of Web Visits per Month'),
+    y=alt.Y('NumWebPurchases:Q', title='Number of Web Purchases'),
+    size=alt.Size('count():Q', scale=alt.Scale(range=[50, 500]), legend=alt.Legend(title='Number of Customers')),
+    color=alt.Color('count():Q', scale=alt.Scale(scheme='viridis'), legend=None),
+    tooltip=['NumWebVisitsMonth', 'NumWebPurchases', 'count()']
+).properties(title='Scatter Plot of Web Visits per Month vs. Web Purchases')
+
+scatter_plot.interactive()"""
+
+# Define dropdown selection for marital status
+marital_status_dropdown = alt.binding_select(options=data['Marital_Status'].unique().tolist(), name='Marital Status: ')
+marital_status_selection = alt.selection_single(fields=['Marital_Status'], bind=marital_status_dropdown, name='Marital_Status', init={'Marital_Status': data['Marital_Status'].iloc[0]})
+
+# Add a scatter plot and filter by marital status
+scatter_plot_filtered = alt.Chart(data).mark_circle().encode(
+    x=alt.X('NumWebVisitsMonth:Q', title='Number of Web Visits per Month'),
+    y=alt.Y('NumWebPurchases:Q', title='Number of Web Purchases'),
+    size=alt.Size('count():Q', scale=alt.Scale(range=[50, 500]), legend=alt.Legend(title='Number of Customers')),
+    color=alt.Color('count():Q', scale=alt.Scale(scheme='viridis'), legend=None),
+    tooltip=['NumWebVisitsMonth', 'NumWebPurchases', 'count()']
+).properties(title='Scatter Plot of Web Visits per Month vs. Web Purchases Filtered by Marital Status').transform_filter(
+    marital_status_selection
+)
+
+# Add interactivity and the marital status selection to the scatter plot
+interactive_scatter_plot_filtered = scatter_plot_filtered.interactive().add_selection(marital_status_selection)
+interactive_scatter_plot_filtered
+
+
+# Group by 'Dt_Customer' and calculate average spending for new and returning customers
+new_customers = data[data['NumWebPurchases'] == 0].groupby('Dt_Customer')['total_spent'].mean().reset_index()
+returning_customers = data[data['NumWebPurchases'] > 0].groupby('Dt_Customer')['total_spent'].mean().reset_index()
+
+
+# new_customers and returning_customers DataFrames
+# Create line charts for new and returning customers without filtering
+new_line = alt.Chart(new_customers).mark_line().encode(
+    x=alt.X('Dt_Customer:T', title='Date'),
+    y=alt.Y('total_spent:Q', title='Average Spending'),
+    color=alt.value('blue'),
+    tooltip=['Dt_Customer', 'total_spent']
+).properties(title='New Customers')
+
+returning_line = alt.Chart(returning_customers).mark_line().encode(
+    x=alt.X('Dt_Customer:T', title='Date'),
+    y=alt.Y('total_spent:Q', title='Average Spending'),
+    color=alt.value('green'),
+    tooltip=['Dt_Customer', 'total_spent']
+).properties(title='Returning Customers')
+
+# Display the charts side by side
+combined_chart = alt.hconcat(new_line, returning_line)
+combined_chart
+
+# Merge Marital_Status to new_customers and returning_customers DataFrames
+
+new_customers = new_customers.merge(data[['Dt_Customer', 'Marital_Status']], on='Dt_Customer', how='left')
+returning_customers = returning_customers.merge(data[['Dt_Customer', 'Marital_Status']], on='Dt_Customer', how='left')
+
+# Filter data by marital status using transform_filter within the charts
+new_line_filtered = alt.Chart(new_customers).mark_line().encode(
+    x=alt.X('Dt_Customer:T', title='Date'),
+    y=alt.Y('total_spent:Q', title='Average Spending'),
+    color=alt.value('blue'),
+    tooltip=['Dt_Customer', 'total_spent']
+).properties(title='New Customers').transform_filter(
+    marital_status_selection
+)
+
+returning_line_filtered = alt.Chart(returning_customers).mark_line().encode(
+    x=alt.X('Dt_Customer:T', title='Date'),
+    y=alt.Y('total_spent:Q', title='Average Spending'),
+    color=alt.value('green'),
+    tooltip=['Dt_Customer', 'total_spent']
+).properties(title='Returning Customers').transform_filter(
+    marital_status_selection
+)
+
+# Add interactivity for panning and zooming
+interactive_chart_filtered = alt.layer(new_line_filtered, returning_line_filtered).resolve_scale(y='shared').interactive().add_selection(marital_status_selection)
+
+# Combine the interactive chart, the legend, and the marital status selection
+# Create legend
+legend = alt.Chart(pd.DataFrame({'legend': ['New Customers', 'Returning Customers'], 'color': ['blue', 'green']})).mark_point().encode(
+    x=alt.value(20),
+    y=alt.Y('legend', title=None),
+    color=alt.Color('color', scale=None),
+    tooltip=['legend']
+)
+
+# Combine the interactive chart, the legend, and the marital status selection
+final_chart_filtered = alt.hconcat(interactive_chart_filtered, legend).properties(title='Average Spending of New vs Returning Customers by Marital Status')
+final_chart_filtered
+
+import panel as pn
+pn.extension('vega')
+
+
+# Define dashboard layout
+dashboard = pn.Column(
+    pn.Row(
+        pn.Column(
+            education_chart,
+            avg_spending_by_education,
+            avg_spending_by_marital_status,
+            width=350
+        ),
+        pn.Column(
+            scatter_chart,
+            enrollment_chart,
+            width=700
+        ),
+    ),
+    pn.Row(
+        concat_chart,
+        width=1000
+    ),
+    pn.Row(
+        final_chart_filtered,
+        width=1000
+    ),
+)
+
+
+# Display dashboard
+dashboard.servable()
+
+
+# In[ ]:
+
+
+
+