Automate, Clean, Analyze, Repeat!

🚀 Python Automation Projects

This repository contains my Python scripts and mini-projects focused on automation, bug fixing, file handling, and data cleaning.
All code is written with clarity, proper structure, and real-world use cases in mind.

⭐ All stable and production-ready scripts are available in the main branch.

🫴 What This Repository Offers

The projects here demonstrate my ability to:
• Automate repetitive tasks.
• Handle files and data efficiently.
• Fix and improve buggy Python logic.
• Build small utilities and algorithm-based solutions.
• Convert scripts into usable backend services when needed.

🔹 Folder Structure Overview

📂 Automation/

Scripts to automate repetitive or manual tasks. Examples:

Cleaning CSV files
Renaming multiple files
Simple task automation

📂 BugFix/

Scripts demonstrating bug fixing, logic correction, and safe coding practices. Examples:

Fixing index errors
Correcting logical mistakes
Error handling techniques

📂 DataCleaning/

Scripts for cleaning and preparing data. Examples:

Removing empty rows
Removing duplicate records
Formatting CSV / Excel data

📂 FileHandling/

Scripts related to file operations. Examples:

Reading and writing CSV files
Merging multiple files
Sorting files programmatically

📂 Utilities/

Small helper tools and utility scripts. Examples:

Stopwatch
Logging utility
Common helper functions

🔹 Tech Stack

Language: Python
Version: Python 3.8+
Libraries: Standard library, pandas (where required)

🔹 Code Quality

Clean and readable code
Proper comments for easy understanding
Modular and reusable functions
Tested scripts before upload

🔹 How to Use

⚙️ Installation

•Clone the repository
git clone
https://github.com/anshkunj/python-automation-projects.git
•pip install -r requirements.txt
•Navigate to the required folder
cd python-automation-projects

✅ Run the script using Python
✅ Modify inputs as needed

Each script contains example usage inside comments.

🧠 Why This Repository Matters

• All scripts are practical, not just academic exercises
• Code is written to be simple, readable, and reusable
• Suitable as a portfolio for Python automation & scripting work