000			03583cam a2200301zu 4500
001			88900538
003			FRCYB88900538
005			20250107233357.0
006			m o d
007			cr un
008			250108s2020 fr | o|||||0|0|||eng d
020			_a9781839215001
035			_aFRCYB88900538
040			_aFR-PaCSA _ben _c _erda
100	1		_aLipp, Brian
245	0	1	_aThe Data Wrangling Workshop _c['Lipp, Brian', 'Roychowdhury, Shubhadeep', 'Sarkar, Dr. Tirthajyoti']
264		1	_bPackt Publishing _c2020
300			_a p.
336			_btxt _2rdacontent
337			_bc _2rdamdedia
338			_bc _2rdacarrier
650		0	_a
700	0		_aLipp, Brian
700	0		_aRoychowdhury, Shubhadeep
700	0		_aSarkar, Dr. Tirthajyoti
856	4	0	_2Cyberlibris _uhttps://international.scholarvox.com/netsen/book/88900538 _qtext/html _a
520			_aA beginner's guide to simplifying Extract, Transform, Load (ETL) processes with the help of hands-on tips, tricks, and best practices, in a fun and interactive way Key Features Explore data wrangling with the help of real-world examples and business use cases Study various ways to extract the most value from your data in minimal time Boost your knowledge with bonus topics, such as random data generation and data integrity checks Book Description While a 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. If you're a beginner, then The Data Wrangling Workshop will help to break down the process for you. You'll start with the basics and build your knowledge, progressing from the core aspects behind data wrangling, to using the most popular tools and techniques. This book starts by showing you how to work with data structures using Python. Through examples and activities, you'll understand why you should stay away from traditional methods of data cleaning used in other languages and take advantage of the specialized pre-built routines in Python. Later, you'll learn how to use the same Python backend to extract and 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 book teaches you how to handle missing or incorrect data, and reformat it based on the requirements from your downstream analytics tool. By the end of this book, you will have developed a solid understanding of how to perform data wrangling with Python, and learned several techniques and best practices 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 Understand 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 into commonly-used Python data science libraries Become well-versed with how to handle and compensate for missing data Who this book is for The Data Wrangling Workshop is designed for developers, data analysts, and business analysts who are looking to pursue a career as a full-fledged data scientist or analytics expert. Although this book is for beginners who want to start data wrangling, prior working knowledge of the Python programming language is necessary to easily grasp the concepts covered here. It will also help to have a rudimentary knowledge of relational databases and SQL.
999			_c73175 _d73175