Data Cleaning and Purification with Python

# Introduction In this project, you will learn how to clean and purify CSV data by removing incomplete, incorrect, and invalid data. The goal is to create a clean dataset from the raw data, which can be used for further analysis or processing. ## 🎯 Tasks In this project, you will learn: - How to set up the project environment and prepare the necessary files - How to import the required libraries for data cleaning - How to read and process the raw data, checking for various types of dirty data - How to write the cleaned data to a new CSV file ## 🏆 Achievements After completing this project, you will be able to: - Use Python and its standard library to work with CSV data - Apply techniques for validating and cleaning data, such as checking for missing values, invalid formats, and unrealistic data - Implement a data cleaning process to create a high-quality dataset - Generate a new CSV file with the cleaned data

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