Bash for Data Scientists / / Oswald Campesato.

This book introduces an assortment of powerful command line utilities that can be combined to create simple, yet powerful shell scripts for processing datasets. The code samples and scripts use the bash shell, and typically involve small datasets so you can focus on understanding the features of gre...

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Place / Publishing House:Dulles, VA : : Mercury Learning and Information, , [2022]
©2022
Year of Publication:2022
Language:English
Online Access:
Physical Description:1 online resource (276 p.)
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100 1 |a Campesato, Oswald,   |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
245 1 0 |a Bash for Data Scientists /  |c Oswald Campesato. 
264 1 |a Dulles, VA :   |b Mercury Learning and Information,   |c [2022] 
264 4 |c ©2022 
300 |a 1 online resource (276 p.) 
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505 0 0 |t Frontmatter --   |t CONTENTS --   |t Preface --   |t Chapter 1: Introduction --   |t Chapter 2: Files and Directories --   |t Chapter 3: Useful Commands --   |t Chapter 4: Conditional Logic and Loops --   |t Chapter 5: Processing Datasets with grep and sed --   |t Chapter 6: Processing Datasets with awk --   |t Chapter 7: Processing Datasets (Pandas) --   |t Chapter 8: NoSQL, SQLite, and Python --   |t Index 
506 0 |a restricted access  |u http://purl.org/coar/access_right/c_16ec  |f online access with authorization  |2 star 
520 |a This book introduces an assortment of powerful command line utilities that can be combined to create simple, yet powerful shell scripts for processing datasets. The code samples and scripts use the bash shell, and typically involve small datasets so you can focus on understanding the features of grep, sed, and awk. Companion files with code are available for downloading from the publisher. FEATURES:Provides the reader with power­ful command line utilities that can be combined to create simple yet powerful shell scripts for processing datasetsContains a variety of code fragments and shell scripts for data scientists, data analysts, and those who want shell-based solutions to “clean” various types of datasetsCompanion files with code 
530 |a Issued also in print. 
538 |a Mode of access: Internet via World Wide Web. 
546 |a In English. 
588 0 |a Description based on online resource; title from PDF title page (publisher's Web site, viewed 08. Aug 2023) 
650 4 |a Data. 
650 4 |a Programming. 
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653 |a Computer Science. 
653 |a Data Science. 
653 |a Pandas. 
653 |a Programming. 
653 |a Python. 
653 |a UNIX. 
653 |a awk. 
653 |a data mining. 
653 |a grep. 
653 |a sed. 
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776 0 |c print  |z 9781683929734 
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