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.