📊 Project 72 — College Major Salary Analysis (Pandas)

README GENERATED BY AI

📌 Overview

Project 72 is a data analysis script built with Python and pandas that explores salary trends across different undergraduate majors. Using a CSV dataset, the program identifies:

• Majors with the highest and lowest starting salaries
• Majors with the highest mid-career salaries
• Low-risk majors (small salary spread over time)
• High-potential majors (large salary growth over time)

This project focuses on practical data cleaning, analysis, and ranking techniques using pandas.

🛠️ Technologies Used

• Python 3
• pandas

📂 Dataset Requirements

The script expects a file named data.csv in the same directory.

Required columns:

• Undergraduate Major
• Starting Median Salary
• Mid-Career Median Salary
• Mid-Career 90th Percentile Salary

Any rows containing missing values are automatically removed before analysis.

📈 What the Script Does

1. Data Cleaning

• Loads the CSV file
• Removes rows with missing data (dropna())

2. Salary Insights

• Finds the highest starting median salary
• Finds the highest mid-career median salary
• Finds the lowest starting median salary

3. Risk vs Reward Analysis

• Calculates a Spread value:

Spread = Mid-Career 90th Percentile Salary − Starting Median Salary * Uses this spread to determine:

• Top 5 Lowest Risk Majors (smallest spread)
• Top 5 Highest Potential Majors (largest spread)

▶️ How to Run

1. Install pandas if you don’t have it:

bash pip install pandas 2. Make sure data.csv is in the same folder as the script. 3. Run the script:

bash python main.py

📤 Output

The program prints a clear, readable summary directly to the console, showing:

• Major names
• Salary values
• Salary change potential

🎯 Learning Goals

• CSV data handling with pandas
• Data cleaning (dropna)
• Index-based analysis (idxmax, idxmin)
• Sorting and ranking datasets
• Real-world data insights using Python

🚀 Future Improvements

• Visualizations using matplotlib or seaborn
• Export results to a CSV or JSON file
• Interactive CLI options
• Salary normalization for inflation

📄 License

This project is open-source and intended for educational use.