This document presents a time series analysis project on stock market data. The project analyzes the daily returns of stocks in the S&P 500 index over a week, compares closing prices of companies, and checks for correlations between stocks. Various Python libraries like Numpy, Pandas, and Matplotlib are used. Plots of moving averages and closing prices for Apple stock are generated. A heatmap is also used to visualize correlations between different stock returns. The conclusion finds correlations mean linked percentage changes between some stock prices. Future work could include comparing more stocks and adding more visualizations.