Netflix Stock Price Trend Analysis Project

Welcome to the Netflix Stock Price Trend Analysis project! This project aims to analyze the historical trends of Netflix stock prices using Python and data analysis techniques. By examining the stock price data, we can gain insights into price fluctuations, patterns, and potential trends, which can be valuable for investors and financial analysis.

Project Overview

In this project, we analyze the historical stock price data of Netflix using the yfinance library. We focus on visualizing the stock price trends, identifying patterns, and exploring potential insights that can assist in making informed investment decisions.

Getting Started

Follow these steps to get started with the project:

1. Clone the Repository: Clone this repository to your local machine using the following command:

   git clone https://github.com/yourusername/Netflix-Stock-Price-Trend-Analysis.git
   

2. Install Dependencies: Install the required dependencies by running:

   pip install -r requirements.txt
   

3. Fetching Data: Use the provided Jupyter notebook to fetch historical Netflix stock price data using the yfinance library.

4. Data Analysis: Analyze the stock price data using various techniques like plotting time series graphs, calculating moving averages, and identifying trends.

5. Visualization: Create visualizations to showcase stock price trends, volume changes, and any interesting patterns that emerge from the data.

6. Insights: Interpret the visualized data to derive insights into historical stock price behavior and potential investment opportunities.

Project Structure

The project repository is organized as follows:

├── LICENSE
├── README.md           <- README .
├── notebooks           <- Folder containing the final reports/results of this project.
│   │
│   └── Netflix_Stock_Price_Trend_Analysis.ipynb   <- Final notebook for the project.
├── reports            <- Folder containing the final reports/results of this project.
│   │
│   └── Report.pdf     <- Final analysis report in PDF.
│   
├── src                <- Source for this project.
│   │
│   └── data           <- Datasets used and collected for this project.
|   └── model          <- Model.

License

This project is licensed under the MIT License.

Author

• ©2023 Tushar Aggarwal. All rights reserved
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Contact me!

If you have any questions, suggestions, or just want to say hello, you can reach out to us at Tushar Aggarwal. We would love to hear from you!