Welcome to the Netflix Stock Analysis project! This repository contains a time-series dataset of Netflix stock values spanning five years, from 2018 to 2022. The project involves analyzing, visualizing, and deriving insights from the dataset to understand trends, patterns, and stock performance over time.
This dataset provides comprehensive information on Netflix's stock performance. The key columns are:
- Date: The date on which a particular stock value was recorded.
- Open: The stock's opening price on that day.
- High: The highest price of the stock during the day.
- Low: The lowest price of the stock during the day.
- Close: The stock's closing price at the end of the day.
- Adj Close: The adjusted closing price, reflecting the stock’s value after accounting for corporate actions such as splits or dividends.
- Volume: The total number of shares traded during the day.
This project aims to explore and analyze the Netflix stock data to:
- Visualize Trends: Examine how stock prices and trading volume changed over five years.
- Identify Patterns: Spot any seasonal or cyclical trends in Netflix's stock performance.
- Stock Performance Insights: Analyze key performance metrics like price volatility, moving averages, and growth rates.
- Correlation Analysis: Understand the relationship between trading volume and stock price movements.
Programming Language: Python
Libraries:
- pandas for data manipulation and analysis.
- matplotlib and seaborn for data visualization.
- numpy for numerical computations.
- statsmodels and scipy for advanced time-series analysis.