🧪 1-Hour Data Analysis Quiz

Welcome! In this quiz, you’ll review:

• Forking a GitHub repository
• Using a provided Python function
• Performing a simple data transformation
• Creating a basic plot
• Committing your work back to GitHub

You have 60 minutes to complete all tasks. Good luck!

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📁 Repository Files (Available together with this README)

• sales.csv — A small dataset of product sales
• helpers.py — Contains add_revenue function to help with your analysis

❗ Do not modify these files. Create new files for your work.

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📋 Your Tasks

1. Fork this repository to your GitHub account.
2. Clone your fork to your local machine.
3. Create a new Python script called run_analysis.py that does the following:
   • Loads sales.csv using pandas
   • Columns: product,units,price
   • Task: Add a total_revenue column (units * price).
   • Imports and uses the add_revenue() function from helpers.py
   • Saves the updated data as sales_with_revenue.csv
   • Creates a simple bar plot of product vs revenue and saves it as revenue_plot.png
4. Run your script to generate the output files.
5. Deliverables (Must Be in Your Fork by Deadline):
   • Python script: run_analysis.py
   • Updated CSV: sales_with_revenue.csv with total_revenue column
   • Plot image: revenue_plot.png

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Uploads are time-stamped by GitHub. Do not re-upload after deadline.

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💡 Starter Code (Put this in run_analysis.py)

# You can modify this file if you want
import pandas as pd
import matplotlib.pyplot as plt
from helpers import add_revenue

# Load data
df = pd.read_csv('sales.csv')

# Add revenue column using the provided function
df = add_revenue(df)

# Save updated CSV
df.to_csv('sales_with_revenue.csv', index=False)

# Create and save a simple bar plot
plt.figure(figsize=(8, 5))
plt.bar(df['product'], df['revenue'])
plt.title('Revenue by Product')
plt.ylabel('Revenue ($)')
plt.xticks(rotation=45)
plt.tight_layout()
plt.savefig('revenue_plot.png')

print("✅ Done! Check for sales_with_revenue.csv and revenue_plot.png")