Smart CSV Cleaner: Hybrid CLI & Natural Language Data Cleaning Tool

A powerful, user-friendly tool for cleaning messy CSV files, accessible via a modern web interface and a powerful command-line interface (CLI). It supports both traditional cleaning operations and advanced transformations, making data cleaning faster and more intuitive.

🚀 Features

1. Interactive Web Interface (GUI)

The primary way to use the Smart CSV Cleaner is through its intuitive web interface.

• Upload & Analyze: Simply upload your CSV file to get an instant analysis, including:
  • Row and column counts
  • A preview of the first 10 rows
  • A count of missing values
• Core Cleaning Operations:
  • Fix Column Names: Standardizes column headers (strips extra spaces, removes special characters, and ensures uniqueness).
  • Handle Missing Data: Choose a strategy (mean, median, mode, or drop rows) to handle empty cells.
  • Remove Outliers: Automatically detect and remove outliers using Z-score or IQR methods.
• Advanced Cleaning Operations:
  • Remove Duplicates: Delete duplicate rows from your dataset.
  • Trim Whitespace: Remove leading/trailing whitespace from all cells.
  • Change Text Case: Convert text to UPPERCASE, lowercase, or Title Case.
  • Find and Replace: Replace specific values throughout the dataset.
  • Drop Columns: Select and remove unwanted columns.
• Post-Cleaning Analysis: After cleaning, see a "Final File Analysis" with updated stats and a preview of the cleaned data.
• Export Options: Download the cleaned data as a .csv or .xlsx file.

2. Command-Line Interface (CLI)

For users who prefer the command line or need to automate cleaning tasks.

• Dual Input Support:
  • Traditional flags: --fix-names, --fix-missing mean, --drop-outliers zscore
  • Natural language commands: "fix column names and remove outliers"
• Comprehensive Operations: All core cleaning operations from the UI are available via the CLI.
• Detailed Logging: Every transformation is timestamped and logged for full traceability.

📦 Installation & Setup

Requirements

• Python 3.7+
• pandas
• click
• tabulate
• openpyxl
• numpy
• Flask

Install Dependencies

pip install pandas click tabulate openpyxl numpy flask

Usage

Running the Web Application

1. Start the Flask server:

   python app.py

2. Open your web browser and navigate to http://127.0.0.1:5000.

Using the CLI

Run the tool from your terminal with the desired flags:

python main.py --input-file your_data.csv --fix-names --fix-missing median --output-file cleaned_data.csv

Or with a natural language command:

python main.py --input-file your_data.csv --nlp-command "fix names and fill missing values with the median"