Python Data Cleaning Cookbook: Detect and remove dirty data and extract key insights with pandas, machine learning and ChatGPT- Second Edition

by Michael Walker

The book shows you how to clean, wrangle, and view data from multiple perspectives, including dataset and column attributes.

Key benefits

• Get to grips with new techniques for data preprocessing and cleaning for machine learning and NLP models

• Use new and updated AI tools and techniques for data cleaning tasks

• Clean, monitor, and validate large data volumes to diagnose problems using cutting-edge methodologies including Machine learning and AI

Description

Jumping into data analysis without proper data cleaning will certainly lead to incorrect results. The Python Data Cleaning Cookbook – Second Edition will show you tools and techniques for cleaning and handling data with Python for better outcomes. Fully updated to the latest version of Python and all relevant tools, this book will teach you how to manipulate and clean data to get it into a useful form. he current edition focuses on advanced techniques like machine learning and AI-specific approaches and tools for data cleaning along with the conventional ones. The book also delves into tips and techniques to process and clean data for ML, AI, and NLP models. You will learn how to filter and summarize data to gain insights and better understand what makes sense and what does not, along with discovering how to operate on data to address the issues you’ve identified. Next, you’ll cover recipes for using supervised learning and Naive Bayes analysis to identify unexpected values and classification errors and generate visualizations for exploratory data analysis (EDA) to identify unexpected values. Finally, you’ll build functions and classes that you can reuse without modification when you have new data. By the end of this Data Cleaning book, you’ll know how to clean data and diagnose problems within it.

Who is this book for?

This book is for anyone looking for ways to handle messy, duplicate, and poor data using different Python tools and techniques. It takes a recipe-based approach to help you to learn how to clean and …