Python Data Cleaning Cookbook PDF

Python Data Cleaning Cookbook PDF
Python Data Cleaning Cookbook PDF
eBook: Python Data Cleaning Cookbook PDF : Modern techniques and Python tools to detect and remove dirty data and extract key insights by Michael Walker

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Getting clean data to reveal insights is important, 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 optimize and turn data into a useful information. 

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. This eBook is curated from github and the web. So, what are you waiting for? Download Python Data Cleaning Cookbook free pdf from the below given link.

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October 18, 2021


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