Bad Data Handbook
Q. Ethan Mccallum
Sold by Rarewaves USA, OSWEGO, IL, U.S.A.
AbeBooks Seller since 10 June 2025
New - Soft cover
Condition: New
Ships within U.S.A.
Quantity: Over 20 available
Add to basketSold by Rarewaves USA, OSWEGO, IL, U.S.A.
AbeBooks Seller since 10 June 2025
Condition: New
Quantity: Over 20 available
Add to basketWelcome to data science's dirty secret: real-world data is messy. Data scientists must spend a good deal of time playing software developer, writing code to clean up data before they can actually do anything constructive with it. It's a necessary evil, but you can still make the most of it. This practical book walks you through several real-world examples to demonstrate the theory and practice behind working with and cleaning up dirty data. No one tool solves all of the problems well. Wise data scientists learn many tools and learn where each one shines. To that end, this book takes a polyglot approach: most examples will involve R and Python, but expect the occasional smattering of Groovy and sed/awk fun.
Seller Inventory # LU-9781449321888
What is bad data? Some people consider it a technical phenomenon, like missing values or malformed records, but bad data includes a lot more. In this handbook, data expert Q. Ethan McCallum has gathered 19 colleagues from every corner of the data arena to reveal how they've recovered from nasty data problems.
From cranky storage to poor representation to misguided policy, there are many paths to bad data. Bottom line? Bad data is data that gets in the way. This book explains effective ways to get around it.
Among the many topics covered, you'll discover how to:
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