Book Image

Hands-On Data Science with the Command Line

By : Jason Morris, Chris McCubbin, Raymond Page
Book Image

Hands-On Data Science with the Command Line

By: Jason Morris, Chris McCubbin, Raymond Page

Overview of this book

The Command Line has been in existence on UNIX-based OSes in the form of Bash shell for over 3 decades. However, very little is known to developers as to how command-line tools can be OSEMN (pronounced as awesome and standing for Obtaining, Scrubbing, Exploring, Modeling, and iNterpreting data) for carrying out simple-to-advanced data science tasks at speed. This book will start with the requisite concepts and installation steps for carrying out data science tasks using the command line. You will learn to create a data pipeline to solve the problem of working with small-to medium-sized files on a single machine. You will understand the power of the command line, learn how to edit files using a text-based and an. You will not only learn how to automate jobs and scripts, but also learn how to visualize data using the command line. By the end of this book, you will learn how to speed up the process and perform automated tasks using command-line tools.
Table of Contents (8 chapters)

awk, sed, and tr

In this section, we will be looking at awk, sed, and tr.

awk

awk (including the gnu implementation, gawk) is designed for streaming text processing, data extraction, and reporting. An awk program is structured as a set of patterns that are matched, and actions to take when those patterns are matched:

pattern {action}
pattern {action}
pattern {action}

For each record (usually each line of text passed to awk), each pattern is tested to see whether the record matches, and if so, the action is taken. Additionally, each record is automatically split into a list of fields by a delimiter (any run of whitespace by default). The default action, if none is given, is to print the record. The default pattern is...