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Data Science at the Command Line by Jeroen Janssens

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Chapter 3. Obtaining Data

This chapter deals with the first step of the OSEMN model: obtaining data. After all, without any data, there is not much data science that we can do. We assume that the data that is needed to solve the data science problem at hand already exists at some location in some form. Our goal is to get this data onto your computer (or into your Data Science Toolbox) in a form that we can work with.

According to the Unix philosophy, text is a universal interface. Almost every command-line tool takes text as input, produces text as output, or both. This is the main reason why command-line tools can work so well together. However, as we’ll see, even just text can come in multiple forms.

Data can be obtained in several ways—for example by downloading it from a server, by querying a database, or by connecting to a web API. Sometimes, the data comes in a compressed form or in a binary format such as Microsoft Excel. In this chapter, we discuss several tools that help tackle this from the command line, including: curl (Stenberg, 2012), in2csv (Groskopf, 2014), sql2csv (Groskopf, 2014), and tar (Bailey, Eggert, & Poznyakoff, 2014).

Overview

In this chapter, you’ll learn how to:

  • Download data from the Internet

  • Query databases

  • Connect to web APIs

  • Decompress files

  • Convert Microsoft Excel spreadsheets into usable data

Copying Local Files to the Data Science Toolbox

A common situation is that you already have the necessary files on your own computer. This ...

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