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Paperback
January 2018
9781683922179
More details
- Publisher
Mercury Learning and Information - Published
24th January 2018 - ISBN 9781683922179
- Language English
- Pages 188 pp.
- Size 6" x 9"
$39.95
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January 2018
9781683922186
More details
- Publisher
Mercury Learning and Information - Published
16th January 2018 - ISBN 9781683922186
- Language English
- Pages 188 pp.
- Size 6" x 9"
$39.95
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January 2018
9781683922759
More details
- Publisher
Mercury Learning and Information - Published
24th January 2018 - ISBN 9781683922759
- Language English
- Pages 188 pp.
- Size 6" x 9"
$124.95
As part of the best selling Pocket Primer series, this book is an effort to give programmers sufficient knowledge of data cleaning to be able to work on their own projects. It is designed as a practical introduction to using flexible, powerful (and free) Unix / Linux shell commands to perform common data cleaning tasks. The book is packed with realistic examples and numerous commands that illustrate both the syntax and how the commands work together. Companion files with source code are available for downloading from the publisher.
Features:
- A practical introduction to using flexible, powerful (and free) Unix / Linux shell commands to perform common data cleaning tasks
- Includes the concept of piping data between commands, regular expression substitution, and the sed and awk commands
- Packed with realistic examples and numerous commands that illustrate both the syntax and how the commands work together
- Assumes the reader has no prior experience, but the topic is covered comprehensively enough to teach a pro some new tricks
- Includes companion files with all of the source code examples (download from the publisher).
1: Introduction
2: Useful Commands
3: Filtering Data with grep
4: Transforming Data with sed
5: Doing Everything Else with awk
Appendix: Other Code Samples
Index
Oswald Campesato
Oswald Campesato specializes in Deep Learning, Python, Data Science, and generative AI. He is the author/co-author of over forty-five books including Google Gemini for Python, Large Language Models, and GPT-4 for Developers (all Mercury Learning).