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)

Python (pandas, numpy, scikit-learn)

Counting things often gets you to where you need to be, but sometimes more complex tools are required to do the job. Fortunately, we can write our own tools in the UNIX paradigm and use them in our workstream pipes along with our other command-line tools if we so desire.

One such tool is python, along with popular data science libraries such as pandas, numpy, and scikit-learn. This isn't a text on all the great things those libraries can do for you (if you'd like to learn, a good place to start is the official python tutorial (https://docs.python.org/3/tutorial/) and the basics of Pandas data structures in the Pandas documentation (https://pandas.pydata.org/pandas-docs/stable/basics.html). Make sure you have Python, pip, and pandas installed before you continue (see Chapter 1, Data Science at the Command Line and Setting It Up)...