Overview

This Python script is designed to facilitate the process of reading multiple CSV files, creating a directory, copying these files into the directory, and then uploading the data from these CSV files into a PostgreSQL database. The script uses the Pandas library for handling data and the SQLAlchemy library to connect and interact with the PostgreSQL database.

Prerequisites

Make sure you have the following installed:

Python Pandas library SQLAlchemy library PostgreSQL database

Usage

To utilize the script:

• Scan and compile CSV files from the current directory.
• Create a 'datasets' directory and copy CSV files.
• Read files into Pandas DataFrames, clean table and column names, and upload to a PostgreSQL database. Ensure backups for table replacement.

Notes

• Make sure to install the required libraries using pip install pandas sqlalchemy if you haven't already.
• Modify the database connection details in the script to match your PostgreSQL setup.
• The script assumes that the CSV files are in the same directory as the script.
• Check the PostgreSQL database for successfully uploaded tables.

Feel free to adapt the script according to your specific requirements and data sources.