2 - Setting up the Tools
from PART ONE - GETTING STARTED
Published online by Cambridge University Press: 15 September 2017
Summary
It is time to start working. Here, I share with you the ways in which Python and R, and their associated tools, should be installed on your computer. For most of this book, and for this chapter in particular, you need to be connected to the Internet. If you are a Windows, Linux, or Mac OS X user, each installation requires the usual steps for your system, which in general requires that you accept every option; however, I give you some suggestions when necessary.
Installing R
To download R, you need to visit https://cran.r-project.org/. That webpage clearly indicates the options for Windows, Mac, or Linux users. Windows and Mac users need to visit the appropriate link and get the file you need, checking if the version offered is the right one for your operating system. As Linux users may expect, after they go to the Linux link, R will ask you to choose among the Debian, redhat, suse, or ubuntu options.
After you download the file from R, you need to install it. This is simply done by clicking the file you downloaded to your computer. Just run it and keep all the default settings. The Linux versions have particular instructions to run in the terminal once the right file is chosen. You do not need to run R now (if you opened it, just close it). We will run R always from RStudio.
Installing RStudio. To get RStudio, just go visit the downloads website.
Once in that webpage, you will find links to the different desktop versions available (as opposed to the server versions, which you do not need). The webpage with the installers looks like Figure 2.1. Download the version you need according to your machine, install it, and accept all the default options. Now, when you start RStudio, you will see a graphical user interface (GUI), composed of a set of windows as shown in Figure 2.2.
The RStudio GUI has four windows. You may have a different set of windows in RStudio, so Figure 2.2 should be only a reference.
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- Information
- Introduction to Data Science for Social and Policy ResearchCollecting and Organizing Data with R and Python, pp. 12 - 23Publisher: Cambridge University PressPrint publication year: 2017