# CSV Cleaner and Parser 🧹📊

This project provides a lightweight and effective Python script for cleaning and parsing CSV files. It's ideal for preprocessing raw datasets during data engineering workflows.

## 🔧 Features

- ✅ Removes duplicate rows
- ✅ Drops rows with all missing values
- ✅ Strips whitespace and standardizes string columns (lowercase)
- ✅ Fills missing values with `"missing"`
- ✅ Generates a log file for data cleaning activity

## 📁 File Structure

CSV_Parsing/ ├── cleaner.py # Main Python script for cleaning CSVs ├── raw.csv # Example input CSV (for demo/testing) ├── cleaned.csv # Cleaned output CSV ├── logs/ │ └── clean_log.txt # Logs for cleaning steps and file status └── README.md # Project documentation

## 🚀 Getting Started

### 🔨 Requirements

- Python 3.x
- pandas

Install dependencies:
```bash
pip install pandas

⚙️ How to Use

1. Clone the Repository

git clone https://github.com/trishita-26/CSV_Parsing.git
cd CSV_Parsing

2. Run the Script

python cleaner.py --input raw.csv --output cleaned.csv

This will:

• Clean the data from raw.csv
• Save the output to cleaned.csv
• Log the process in logs/clean_log.txt

📝 Make sure the logs/ directory exists. The script creates it automatically if missing.

🧪 Sample Input (raw.csv)

Name,Age,Email
alice,25.0,alice@example.com
bob,,bob@example.com
charlie,30.0,
alice,25.0,alice@example.com
david,28.0,david@sample.com
eve,22.0,eve@example.com

✅ Sample Output (cleaned.csv)

Name,Age,Email
alice,25.0,alice@example.com
bob,missing,bob@example.com
charlie,30.0,missing
david,28.0,david@sample.com
eve,22.0,eve@example.com

💡 Use Cases

• Initial data cleaning before loading into a database or data warehouse
• Preprocessing CSV files before analysis or visualization
• Learning and showcasing data engineering practices

🧑‍💻 Author

👤 Trishita
Engineering student with a passion for building data pipelines and automation tools.

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📬 Feedback

If you found this useful or have suggestions to improve, feel free to open an issue or star the repo ⭐

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