Data Science at the Command Line: Obtain, Scrub, Explore, and Model Data with UNIX Power Tools Paperback
ZAR 1019
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Learn how to greatly improve your data science workflow by leveraging the command line's power.
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What Stands Out
Product Details
- Learn how to use command-line tools to efficiently obtain, scrub, explore, and model data
- Access a Docker image containing over 100 Unix power tools for Windows, macOS, or Linux
- Discover the agility, scalability, and extensibility of the command line technology
- Improve data science workflow by integrating command-line power with Python or R processing
- Ideal for data scientists, analysts, engineers, system administrators, and researchers
- Explore operations such as obtaining data from various sources, data scrubbing, visualization, and modeling
| Book format | Paperback |
| Fiction/nonfiction | Non-Fiction |
| Genre | Computing & Internet |
| Pages | 280 |
| Reading level | Professional and Scholarly |
| Subgenre | Computers |
| Edition | 2 |
| Publisher | O'Reilly Media |
| Original languages | English |
| Language | English |
| Assembled product height | 9.19 in (23.3 cm) |
| Assembled product weight | 1 lb (450 grams) |
| Bisac subject heading | Computers |
Who Should Buy?
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Data Enthusiasts
Individuals eager to enhance their data manipulation skills using command line tools for better efficiency.
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UNIX Users
Users familiar with UNIX who want to apply command line techniques to data science tasks effectively.
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Self-Learners
Individuals motivated to learn data science independently through practical examples and hands-on exercises.
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Beginners
Complete newcomers to data science without UNIX knowledge may struggle to grasp the concepts presented in this book.
Product Description
Data Science at the Command Line: Obtain, Scrub, Explore, and Model Data with UNIX Power Tools Paperback
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ZAR 1019
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Features & Benefits
- Learn how to combine small yet powerful command-line tools to quickly obtain, scrub, explore, and model your data.
- Ideal for data scientists, analysts, engineers, system administrators, and researchers.
- Obtain data from websites, APIs, databases, and spreadsheets.
- Perform scrub operations on text, CSV, HTML, XML, and JSON files.
- Explore data, compute descriptive statistics, and create visualizations.
- Leverage the command line from Python, Jupyter, R, RStudio, and Apache Spark.
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