Title
Python Data Cleaning Cookbook: Modern techniques and Python tools to detect and remove dirty data and extract key insights,Used
Delivery time: 8-12 business days (International)
Discover how to describe your data in detail, identify data issues, and find out how to solve them using commonly used techniques and tips and tricksKey features Get wellversed with various data cleaning techniques to reveal key insights Manipulate data of different complexities to shape them into the right form as per your business needs Clean, monitor, and validate large data volumes to diagnose problems before moving on to data analysisBook DescriptionGetting clean data to reveal insights is essential, as directly jumping into data analysis without proper data cleaning may lead to incorrect results. This book shows you tools and techniques that you can apply to clean and handle data with Python. You'll begin by getting familiar with the shape of data by using practices that can be deployed routinely with most data sources. Then, the book teaches you how to manipulate data to get it into a useful form. You'll also 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. Moving on, you'll perform key tasks, such as handling missing values, validating errors, removing duplicate data, monitoring high volumes of data, and handling outliers and invalid dates. Next, you'll cover recipes on using supervised learning and Naive Bayes analysis to identify unexpected values and classification errors, and generate visualizations for exploratory data analysis (EDA) to visualize 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 Python book, you'll be equipped with all the key skills that you need to clean data and diagnose problems within it.What you will learn Find out how to read and analyze data from a variety of sources Produce summaries of the attributes of data frames, columns, and rows Filter data and select columns of interest that satisfy given criteria Address messy data issues, including working with dates and missing values Improve your productivity in Python pandas by using method chaining Use visualizations to gain additional insights and identify potential data issues Enhance your ability to learn what is going on in your data Build userdefined functions and classes to automate data cleaningWho this book is forThis book is for anyone looking for ways to handle messy, duplicate, and poor data using different Python tools and techniques. The book takes a recipebased approach to help you to learn how to clean and manage data. Working knowledge of Python programming is all you need to get the most out of the book.
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Shipping & Returns
Shipping
We ship your order within 2–3 business days for USA deliveries and 5–8 business days for international shipments. Once your package has been dispatched from our warehouse, you'll receive an email confirmation with a tracking number, allowing you to track the status of your delivery.
Returns
To facilitate a smooth return process, a Return Authorization (RA) Number is required for all returns. Returns without a valid RA number will be declined and may incur additional fees. You can request an RA number within 15 days of the original delivery date. For more details, please refer to our Return & Refund Policy page.
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Warranty
We provide a 2-year limited warranty, from the date of purchase for all our products.
If you believe you have received a defective product, or are experiencing any problems with your product, please contact us.
This warranty strictly does not cover damages that arose from negligence, misuse, wear and tear, or not in accordance with product instructions (dropping the product, etc.).
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