This thoroughly revised guide demonstrates how the flexibility of the command line can help you become a more efficient and productive data scientist. You’ll learn how to combine small yet powerful command-line tools to quickly obtain, scrub, explore, and model your data. To get you started, author Jeroen Janssens provides a Docker image packed with over 80 tools—useful whether you work with Windows, macOS, or Linux.
You’ll quickly discover why the command line is an agile, scalable, and extensible technology. Even if you’re comfortable processing data with Python or R, you’ll learn how to greatly improve your data science workflow by leveraging the command line’s power. This book is ideal for data scientists, analysts, and engineers; software and machine learning engineers; and system administrators.
- Obtain data from websites, APIs, databases, and spreadsheets
- Perform scrub operations on text, CSV, HTM, XML, and JSON files
- Explore data, compute descriptive statistics, and create visualizations
- Manage your data science workflow
- Create reusable command-line tools from one-liners and existing Python or R code
- Parallelize and distribute data-intensive pipelines
- Model data with dimensionality reduction, clustering, regression, and classification algorithms
Table of contents
- Data Science is OSEMN
- Intermezzo Chapters
- What is the Command Line?
- Why Data Science at the Command Line?
- A Real-world Use Case
- Further Reading
- 2. Getting Started
- Title: Data Science at the Command Line, 2nd Edition
- Release date: September 2021
- Publisher(s): O'Reilly Media, Inc.
- ISBN: 9781492087847
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