▶Book Description
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.
▶What You Will Learn
⦁ Understand how to set up the command line for data science
⦁ Use AWK programming language commands to search quickly in large datasets.
⦁ Work with files and APIs using the command line
⦁ Share and collect data with CLI tools
⦁ Perform visualization with commands and functions
⦁ Uncover machine-level programming practices with a modern approach to data science
▶Key Features
⦁ Perform string processing, numerical computations, and more using CLI tools
⦁ Understand the essential components of data science development workflow
⦁ Automate data pipeline scripts and visualization with the command line
▶Who This Book Is For
Hands-On Data Science with the Command Line provides useful tips and tricks on how to use the command line for everyday data problems. This book is aimed for the reader that has little to no command-line experience but has worked in the field of computer science and/or has experience with modern data science problems.
You'll learn how to set up the command line on multiple platforms and configure it to your liking, learn how to find help with commands, and learn how to create reusable scripts.
You will also learn how to obtain an actual dataset, perform some analytics, and learn how to visualize the data. Towards the end of the book, we touch on some of the advanced features of the command line and where to go from there.
In addition, all of the code examples are available to download in Packt's GitHub account. Any updates to this book will be made available to you by the Packt platform.
▶What this book covers
⦁ Chapter 1, Data Science at the Command line and Setting It up, covers how to install and configure the command line on multiple platforms of your choosing.
⦁ Chapter 2, Essential Commands, is a hands-on demo on using the basics of the command line and where to find help if needed.
⦁ Chapter 3, Shell Workflows, and Data Acquisition and Massaging, really gets into performing some basic data science exercises with a live dataset and customizing your command-line environment as you see fit.
⦁ Chapter 4, Reusable Bash and Developing Reusable Code in Bash, builds on the previous chapters and gets more advanced with creating reusable scripts and visualizations.
⦁ Chapter 5, Loops, Functions, and String Processing, is an advanced hands-on exercise on iterating over data using loops and exploring with regular expressions.
⦁ Chapter 6, SQL, Math, and Wrapping it up, is an advanced hands-on exercise to use what you've learned over the last chapters, and we introduce databases, streaming, and working with APIs.
