Python Intern Assignment

Time: 60 minutes

⚠️ Important: Use of AI tools (ChatGPT, GitHub Copilot, etc.) is not allowed for this exercise

Task

Create a Python script that analyses customer support ticket data.

What You Get

• tickets.csv file with columns: ticket_id, category, priority, resolution_hours, satisfaction, agent

What You Build

Create analyzer.py with three functions:

Function 1: Basic Stats

def get_summary():
    # Calculate and return:
    # - Total number of tickets
    # - Average resolution time
    # - Average satisfaction score

Function 2: Category Analysis

def analyze_categories():
    # For each category (Technical, Billing, Account), return:
    # - Number of tickets
    # - Average resolution time
    # - Average satisfaction score

Function 3: Agent Performance

def analyze_agents():
    # For each agent, return:
    # - Number of tickets handled
    # - Average resolution time
    # - Average satisfaction score

Expected Output

Total Tickets: 95
Average Resolution: 12.5 hours
Average Satisfaction: 3.8/5

Categories:
Technical: 32 tickets, 18.2h avg, 3.4/5
Billing: 25 tickets, 7.1h avg, 4.2/5  
Account: 38 tickets, 11.8h avg, 3.9/5

Agents:
Alice: 28 tickets, 14.1h avg, 4.0/5
Bob: 35 tickets, 11.8h avg, 3.7/5
Carol: 32 tickets, 12.0h avg, 3.8/5

Submit

Fork this repo and share the forked repo URL at hello@digilake.io

Requirements:

1. Working analyzer.py file
2. Simple README with usage instructions
3. Push to GitHub

Note: Please maintain a git history so that we can analyse how the solution was evolved
For any question/doubt, please reach out to hello@digilake.io
Bonus: Follow code quality best practices (linting, formatting, type hints) and set up GitHub Actions to automatically check code quality (extra credit)

That's it! Keep it simple and focus on getting it working.