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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LEADER | 03326nam a22007095i 4500 | ||
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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.) | ||
336 | |a text |b txt |2 rdacontent | ||
337 | |a computer |b c |2 rdamedia | ||
338 | |a online resource |b cr |2 rdacarrier | ||
347 | |a text file |b PDF |2 rda | ||
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. | |
650 | 7 | |a COMPUTERS / Programming Languages / Python. |2 bisacsh | |
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. | ||
776 | 0 | |c EPUB |z 9781683929710 | |
776 | 0 | |c print |z 9781683929734 | |
856 | 4 | 0 | |u https://www.degruyter.com/isbn/9781683929727 |
856 | 4 | 2 | |3 Cover |u https://www.degruyter.com/document/cover/isbn/9781683929727/original |
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