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.
This open book is licensed under a Creative Commons License (CC BY-NC-ND). Free download in PDF format is not available. You can read Data Science at the Command Line book online for free.