Welcome to the TweetMetrics repository! This project is a comprehensive analysis of tweet engagement metrics, employing various tools and technologies for data manipulation, querying, and analysis. Whether you're interested in Pandas, MySQL, or SQLAlchemy, this repository has you covered.

• Description: Python script for migrating data to MySQL database.
• Usage: Execute this script to transfer the dataset into a MySQL database.

• Description: Jupyter Notebook showcasing data analysis and querying using Pandas.
• Usage: Explore Pandas functionality and answers to project questions interactively.

• Description: A text file containing the project questions for reference.
• Usage: Find the list of questions that guided the analysis in this project.

• Description: SQL script for analysis and querying using MySQL.
• Usage: Execute this script in a MySQL environment to perform SQL-based analysis.

• Description: Jupyter Notebook demonstrating analysis and querying using SQLAlchemy-MySQL.
• Usage: Explore SQLAlchemy functionality and answers to project questions interactively.

• Description: Original dataset containing tweet engagement metrics.
• Usage: The raw data used for analysis, in CSV format.

• Description: Cleaned version of the dataset.
• Usage: A cleaned version of the dataset after preprocessing steps.

1. Clone this repository to your local machine.
2. Explore the provided Jupyter Notebooks for Pandas and SQLAlchemy-MySQL analyses.
3. Run the mysqlMigration.py script to migrate data to a MySQL database.
4. Execute the SQL scripts (SQLAnalysis.sql) for additional analysis.
5. Refer to the questions.txt file for project-related inquiries.

Feel free to explore, analyze, and learn from the TweetMetrics repository. Enjoy your data journey! 🚀