This project performs data analysis on wage data for IT positions in various tech companies. The data includes fields such as company name, rank, location, specialization, and compensation details, allowing us to break down compensation by multiple factors and make comparisons.
Company: The tech company (e.g., Facebook, Google).
Rank: The job level or rank within the company (e.g., E3, L3/T3).
Location: The primary city for the position.
State: The state in which the position is located.
Specialism: The area of technical specialization (e.g., Mobile, Distributed Systems).
Total Compensation: The total annual compensation including salary, stock, and bonus.
Base: Base salary.
Stock: Stock component of the compensation.
Bonus: Bonus component of the compensation.
Descriptive Analysis: Summarizes and visualizes average compensation by company, specialization, and location.
Comparative Analysis: Compares total compensation across different specialisms and locations.
Exploratory Data Analysis (EDA): Provides insights into the distribution of compensation packages in the tech industry.
Location-Based Insights: Analyzes wage differences between California, Washington, and other key tech hubs.
Requirements: Python 3.8+ Packages: pandas, matplotlib, seaborn
Data Preprocessing: Load and clean the dataset. Compensation Analysis: Analyze total compensation and its components by various factors. Visualization: Generate plots to visualize the distribution of salaries, stock options, and bonuses.
The project outputs charts and tables showing:
Average compensation by company and rank.
Highest-paying specializations.
Location-based wage comparisons.
Feel free to fork this project and create pull requests if you have ideas for improvement. Make sure to follow the standard code of conduct for contributing.