# Python Scripts Collection

## Overview
This repository serves as a collection of Python scripts, Jupyter notebooks, and data analysis projects. It showcases various data science techniques and programming approaches.

## Repository Contents
- **email_campaign_case_study_20190703.ipynb**: 
  - Detailed analysis of email marketing campaign data
  - Includes data visualization and performance metrics
  - Demonstrates Python data analysis workflow

- **s3_csv_handler.py**:
  - Utility script for working with CSV files in AWS S3 buckets
  - Features include uploading, downloading, and listing CSV files
  - Includes functions for direct pandas DataFrame integration
  - Command-line interface for easy use

## Technologies Used
- Python 3.x
- Jupyter Notebooks
- Pandas for data manipulation
- Matplotlib/Seaborn for visualization
- Boto3 for AWS S3 integration

## How to Use

### Jupyter Notebooks
1. Clone this repository
2. Ensure you have Python and required libraries installed
3. Open the notebooks in Jupyter Lab/Notebook
4. Run the cells to see the analysis in action

### S3 CSV Handler
```
# Install required dependencies
pip install boto3 pandas

# Upload a CSV file to S3
python s3_csv_handler.py --upload local_file.csv s3://bucket-name/path/

# Download a CSV file from S3
python s3_csv_handler.py --download s3://bucket-name/path/file.csv local_directory/

# List CSV files in an S3 bucket
python s3_csv_handler.py --list s3://bucket-name/path/
```

## Future Additions
- More data analysis projects
- Machine learning examples
- Data visualization techniques
- Additional AWS integration utilities

Feel free to explore the scripts and notebooks and provide feedback or suggestions for improvement!