A simple yet powerful Streamlit-based web application that allows users to upload raw CSV files, automatically clean and preprocess them, and then download the cleaned version for further analysis or modeling.
The app performs basic data cleaning operations such as renaming columns, filling missing values, and adding derived columns (like listing gain percentage). Users can preview both raw and cleaned data, view summary statistics, and optionally save cleaned CSVs to the server with unique filenames.
⚙️ Key Features:
📤 Upload any CSV dataset
🧹 Automatic cleaning pipeline (fill NaNs, normalize column names, add computed fields)
💾 Option to save cleaned file on the server or download instantly
📊 Instant preview of raw and cleaned data
📈 Basic descriptive statistics from cleaned data
💡 Use Case:
Ideal for data scientists, analysts, and students who want a quick, no-code solution for cleaning messy CSV datasets before deeper analysis or model training.