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)

Getting set up on Ubuntu Linux

Ubuntu has a full built-in command-line shell and typically uses bash as the default shell. Different window managers have slightly different ways of opening a Terminal window. For example, in the image of Ubuntu 17.10 Artful (located at, open the Terminal by clicking on Activities in the upper-left corner and typing terminal in the dialog:

This will bring up a command-line prompt:

As in other bash shells, this shell doesn't have everything installed, so type the following command to install the installers and command-line tools that we will use in this book:

sudo apt update
sudo apt install jq python-pip gnuplot sqlite3 libsqlite3-dev curl netcat bc
pip install pandas

On Ubuntu, this script installs a few installation tools, including pip. It then uses these tools to install the commands that we use in this book that aren't natively installed, namely jq, gnuplot, sqlite, curl, and pandas.

Getting set up with Docker

What if there were a way to obtain an image with all the commands preinstalled and you were able to run it on most major operating systems without any issues? That's exactly what Docker provides, and you can quickly get up and running in a matter of minutes:

  1. Visit and install the version of Docker for your operating system
  2. Run the following command to obtain the Docker image:
docker run -ivt nextrevtech/commandline-book /bin/bash