🔥 Pandas Scenario-Based Interview Question 🐼

📊 Scenario:

You have an orders dataset with:
order_id
customer_id
order_date
category
sales

🎯 Task:

Find the top-selling category for each month based on total sales.

✅ Pandas Solution:

import pandas as pd

# Convert to datetime
df['order_date'] = pd.to_datetime(df['order_date'])

# Extract month
df['month'] = df['order_date'].dt.strftime('%b-%Y')

# Total sales by month & category
sales_summary = (
df.groupby(['month', 'category'])['sales']
.sum()
.reset_index()
)

# Rank categories within each month
sales_summary['rank'] = (
sales_summary.groupby('month')['sales']
.rank(method='dense', ascending=False)
)

# Top category per month
result = sales_summary[sales_summary['rank'] == 1]

print(result)

💡 Concepts Tested:

✔️ groupby()
✔️ Date handling
✔️ Aggregation
✔️ Ranking within groups

React ♥️ for more interview questions