Jeroen Janssens - Data Science at the Command Line. Second Edition (2021)

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Data Science at the Command Line. Second Edition
Автор: Jeroen Janssens (2021)

Praise for Data Science at the Command Line

Traditional computer and data science curricula all too often mistake the command line as an obsolete relic instead of teaching it as the modern and vital toolset that it is. Only well into my career did I come to grasp the elegance and power of the command line for easily exploring messy datasets and even creating reproducible data pipelines for work. The first edition of Data Science at the Command Line was one of the most comprehensive and clear references when I was a novice in the art, and now with the second edition, I’m again learning new tools and applications from it.
Dan Nguyen, data scientist, former news application developer at ProPublica, and former Lorry I. Lokey Visiting Professor in Professional Journalism at Stanford University

The Unix philosophy of simple tools, each doing one job well, then cleverly piped together, is embodied by the command line. Jeroen expertly discusses how to bring that philosophy into your work in data science, illustrating how the command line is not only the world of file input/output, but also the world of data manipulation, exploration, and even modeling.
Chris H. Wiggins, associate professor in the department of applied physics and applied mathematics at Columbia University, and chief data scientist at The New York Times

This book explains how to integrate common data science tasks into a coherent workflow. It’s not just about tactics for breaking down problems, it’s also about strategies for assembling the pieces of the solution.
John D. Cook, consultant in applied mathematics, statistics, and technical computing

Despite what you may hear, most practical data science is still focused on interesting visualizations and insights derived from flat files. Jeroen’s book leans into this reality, and helps reduce complexity for data practitioners by showing how time-tested command-line tools can be repurposed for data science.
Paige Bailey, principal product manager code intelligence at Microsoft, GitHub

It’s amazing how fast so much data work can be performed at the command line before ever pulling the data into R, Python, or a database. Older technologies like sed and awk are still incredibly powerful and versatile. Until I read Data Science at the Command Line, I had only heard of these tools but never saw their full power. Thanks to Jeroen, it’s like I now have a secret weapon for working with large data.
Jared Lander, chief data scientist at Lander Analytics, organizer of the New York Open Statistical Programming Meetup, and author of R for Everyone

The command line is an essential tool in every data scientist’s toolbox, and knowing it well makes it easy to translate questions you have of your data to real-time insights. Jeroen not only explains the basic Unix philosophy of how to chain together single-purpose tools to arrive at simple solutions for complex problems, but also introduces new command-line tools for data cleaning, analysis, visualization, and modeling.
Jake Hofman, senior principal researcher at Microsoft Research, and adjunct assistant