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Sarkar Dr Tirthajyoti - Data Wrangling with Python: Creating actionable data from raw sources

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Sarkar Dr Tirthajyoti Data Wrangling with Python: Creating actionable data from raw sources

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Simplify your ETL processes with these hands-on data hygiene 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 like random data generation and data integrity checks
Book Description

For data to be useful and meaningful, it must be curated and refined. Data Wrangling with Python teaches you the core ideas behind these processes and equips you with knowledge of the most popular tools and techniques in the domain.

The book starts with the absolute basics of Python, focusing mainly on data structures. It then delves into the fundamental tools of data wrangling like NumPy and Pandas libraries. Youll explore useful insights into 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. This combination of Python tips and tricks will also demonstrate 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, youll cover how to handle missing or wrong data, and reformat it based on the requirements from the downstream analytics tool. The book will further help you grasp concepts through real-world examples and datasets.

By the end of this book, you will be confident in using a diverse array of sources to extract, clean, transform, and format your data efficiently.

What you will learn
  • Use and manipulate complex and simple data structures
  • Harness the full potential of DataFrames and numpy.array at run time
  • Perform web scraping with BeautifulSoup4 and html5lib
  • Execute advanced string search and manipulation with RegEX
  • Handle outliers and perform data imputation with Pandas
  • Use descriptive statistics and plotting techniques
  • Practice data wrangling and modeling using data generation techniques
Who this book is for

Data Wrangling with Python 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.

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Data Wrangling with Python

Creating actionable data from raw sources

Dr. Tirthajyoti Sarkar and Shubhadeep Roychowdhury

Data Wrangling with Python

Copyright 2019 Packt Publishing

All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.

Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the author, nor Packt Publishing, and its dealers and distributors will be held liable for any damages caused or alleged to be caused directly or indirectly by this book.

Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.

Authors: Dr. Tirthajyoti Sarkar and Shubhadeep Roychowdhury

Managing Editor: Steffi Monteiro

Acquisitions Editor: Kunal Sawant

Production Editor: Nitesh Thakur

Editorial Board: David Barnes, Ewan Buckingham, Shivangi Chatterji, Simon Cox, Manasa Kumar, Alex Mazonowicz, Douglas Paterson, Dominic Pereira, Shiny Poojary, Saman Siddiqui, Erol Staveley, Ankita Thakur, and Mohita Vyas.

First Published: February 2019

Production Reference: 1280219

ISBN: 978-1-78980-011-1

Published by Packt Publishing Ltd.

Livery Place, 35 Livery Street

Birmingham B3 2PB, UK

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