Description: Further DetailsTitle: Python Data Cleaning CookbookCondition: NewSubtitle: Modern techniques and Python tools to detect and remove dirty data and extract key insightsEAN: 9781800565661ISBN: 9781800565661Publisher: Packt Publishing LimitedFormat: PaperbackRelease Date: 12/11/2020Description: 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 FeaturesGet well-versed with various data cleaning techniques to reveal key insightsManipulate data of different complexities to shape them into the right form as per your business needsClean, monitor, and validate large data volumes to diagnose problems before moving on to data analysisBook Description Getting 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 learnFind out how to read and analyze data from a variety of sourcesProduce summaries of the attributes of data frames, columns, and rowsFilter data and select columns of interest that satisfy given criteriaAddress messy data issues, including working with dates and missing valuesImprove your productivity in Python pandas by using method chainingUse visualizations to gain additional insights and identify potential data issuesEnhance your ability to learn what is going on in your dataBuild user-defined functions and classes to automate data cleaningWho this book is for This book is for anyone looking for ways to handle messy, duplicate, and poor data using different Python tools and techniques. The book takes a recipe-based 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.Language: EnglishCountry/Region of Manufacture: GBItem Height: 93mmItem Length: 75mmAuthor: Michael WalkerGenre: Computing & InternetISBN-10: 1800565666Release Year: 2020 Missing Information?Please contact us if any details are missing and where possible we will add the information to our listing.
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Book Title: Python Data Cleaning Cookbook
Title: Python Data Cleaning Cookbook
Subtitle: Modern techniques and Python tools to detect and remove dirty dat
EAN: 9781800565661
ISBN: 9781800565661
Release Date: 12/11/2020
Release Year: 2020
Country/Region of Manufacture: GB
Item Height: 93mm
Genre: Computing & Internet
ISBN-10: 1800565666
Number of Pages: 436 Pages
Publication Name: Python Data Cleaning Cookbook : Modern Techniques and Python Tools to Detect and Remove Dirty Data and Extract Key Insights
Language: English
Publisher: Packt Publishing, The Limited
Publication Year: 2020
Subject: Data Modeling & Design, Data Processing, Databases / Data Mining, Chemistry / General
Type: Textbook
Subject Area: Computers, Science
Item Length: 3.6 in
Author: Michael Walker
Item Width: 3 in
Format: Trade Paperback
