CSV Cleaner

Struggling with Excel and Tableau for data cleaning ? Don’t sweat it! This CSV Cleaner is your one-click solution to effortless data preparation!

Overview

CSV Cleaner is a Python-based tool designed to help users clean and preprocess CSV files. It offers several operations, including removing null values, handling 'NA' values, removing duplicate rows, cleaning special characters, and managing outliers. The tool features a user-friendly GUI built with Tkinter, allowing users to easily select operations and save the cleaned data.

Features

• Remove null values from the dataset.
• Handle 'NA' values efficiently.
• Remove duplicate rows.
• Clean special characters from both column names and data entries.
• Handle outliers based on IQR (Interquartile Range).
• Simple and intuitive GUI for user interaction.

Requirements

• Python 3.x
• Pandas
• NumPy
• Tkinter
• Regular expressions (re)

Installation

1. Clone this repository:

   git clone https://github.com/ohnogaurav/csvcleaner.git

2. Navigate to the project directory:

   cd csvcleaner

3. Install the required packages (if not already installed):

   pip install pandas numpy

Usage

1. Run the CSV Cleaner script:

   python csv_cleaner.py

2. The program will prompt you to select a CSV file.

3. Based on the contents of the selected file, it will enable relevant cleaning operations.

4. Choose the operations you wish to perform and specify a location to save the cleaned file.

Contributing

Contributions are welcome! Please feel free to submit a pull request or open an issue if you have suggestions for improvements.