Brian Lipp - The Data Wrangling Workshop: Create Actionable Data from Raw Sources, 2nd Edition
Here you can read online Brian Lipp - The Data Wrangling Workshop: Create Actionable Data from Raw Sources, 2nd Edition full text of the book (entire story) in english for free. Download pdf and epub, get meaning, cover and reviews about this ebook. year: 2020, publisher: Packt Publishing, genre: Home and family. Description of the work, (preface) as well as reviews are available. Best literature library LitArk.com created for fans of good reading and offers a wide selection of genres:
Romance novel
Science fiction
Adventure
Detective
Science
History
Home and family
Prose
Art
Politics
Computer
Non-fiction
Religion
Business
Children
Humor
Choose a favorite category and find really read worthwhile books. Enjoy immersion in the world of imagination, feel the emotions of the characters or learn something new for yourself, make an fascinating discovery.
- Book:The Data Wrangling Workshop: Create Actionable Data from Raw Sources, 2nd Edition
- Author:
- Publisher:Packt Publishing
- Genre:
- Year:2020
- Rating:4 / 5
- Favourites:Add to favourites
- Your mark:
The Data Wrangling Workshop: Create Actionable Data from Raw Sources, 2nd Edition: summary, description and annotation
We offer to read an annotation, description, summary or preface (depends on what the author of the book "The Data Wrangling Workshop: Create Actionable Data from Raw Sources, 2nd Edition" wrote himself). If you haven't found the necessary information about the book — write in the comments, we will try to find it.
Simplify your ETL processes with these hands-on tips, tricks, and best practices
Key Features- Focus on the basics of data wrangling
- Study various ways to extract the most out of your data in less time
- Boost your learning curve with bonus topics, such as random data generation and data integrity checks
Though huge amount of data is readily available to us, it is not useful in its raw form. For data to be meaningful, it must be curated and refined. The Data Wrangling Workshop teaches you the core ideas behind these processes and equips you with knowledge of the most popular tools and techniques in the domain. The workshop begins by demonstrating how to work with data structures using Python. Through examples and activities, youll understand why you should stay away from traditional ways of data cleaning as done in other languages and take advantage of the specialized pre-built routines in Python. As you progress, youll learn how to use the same Python backend and extract/transform data from an array of sources including the Internet, large database vaults, and Excel financial tables. To help you prepare for more challenging scenarios, the workshop teaches you how to handle missing or wrong data, and reformat it based on the requirements from the downstream analytics tool. By the end of the workshop, you would have learned several data wrangling techniques and best practices thatll give you the confidence to extract, clean, transform, and format your data efficiently from a diverse array of sources.
What you will learn- Get to grips with the fundamentals of data wrangling
- Learn how to model data with random data generation and data integrity checks
- Discover how to examine data with descriptive statistics and plotting techniques
- Explore how to search and retrieve information with regular expressions
- Delve deep into the commonly used data science libraries of Python
- Learn how to handle and compensate for missing data
The Data Wrangling Workshop is designed for developers, data analysts, and business analysts who are keen to pursue a career as a full-fledged data scientist or analytics expert. Although, this book is for beginners, prior working knowledge of Python is necessary to easily grasp the concepts covered here. It will also help to have rudimentary knowledge of relational database and SQL.
Brian Lipp: author's other books
Who wrote The Data Wrangling Workshop: Create Actionable Data from Raw Sources, 2nd Edition? Find out the surname, the name of the author of the book and a list of all author's works by series.