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 100 Unix power 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, 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
Manage your data science workflow
Create your own tools from one-liners and existing Python or R code
Parallelize and distribute data-intensive pipelines
Model data with dimensionality reduction, regression, and classification algorithms
Leverage the command line from Python, Jupyter, R, RStudio, and Apache Spark