What do you get with Print?

Instant access to your digital eBook copy whilst your Print order is Shipped

Black & white paperback book shipped to your address

Download this book in EPUB and PDF formats

Access this title in our online reader with advanced features

DRM FREE - Read whenever, wherever and however you want

Buy Now

Advanced Analytics with R and Tableau

Chapter 1. Advanced Analytics with R and Tableau

Moving from data visualization into deeper, more advanced analytics? This book will intensify data skills for a data-savvy user who wants to move into analytics and data science in order to make a difference to their businesses, by harnessing the analytical power of R and the stunning visualization capabilities of Tableau.

Together, Tableau and R offer accessible analytics by allowing a combination of easy-to-use data visualization along with industry-standard, robust statistical computation. Readers will come across a wide range of machine learning algorithms and learn how descriptive, prescriptive, and predictive visually appealing analytical solutions can be designed solutions with R and Tableau.

Let's get ready to start our transition from being a data-savvy user to a data analyst using sound statistical tools to perform advanced analytics. To do this, we need to get the tools ready. In this topic, we will commence our journey of conducting Tableau analytics with the industry-standard, statistical prowess of R. As the first step on our journey, we will cover the installation of R, including key points about ensuring the right bitness before we start. In order to create R scripts easily, we will install RStudio for ease of use.

We need to get R and Tableau to communicate, and to achieve this communication, we will install and configure Rserve.

Installing R for Windows

The following steps shows how to download and install R on windows:

The first step is to download your required version of R from the CRAN website [http://www.rproject.org/].
Go to the official R website, which you can find at https://www.r-project.org/.
The download link can be found on the left-hand side of the page.
The next option is for you to choose the location of the server that holds R. The best option is to choose the mirror that is geographically closest to you. For example, if you are based in the UK, then you might choose the mirror that is located in Bristol.
Once you click on the link, there is a section at the top of the page called Download and Install R. There is a different link for each operating system. To download the Windows-specific version of R, there is a link that specifies Download R for Windows. When you click on it, the download links will appear on the next page to download R.
On the next page, there are a number of options, but it is easier to select the option that specifies install R for the first time.
Finally, there is an option at the top of the page that allows you to download the latest R installation package. The install package is wrapped up in an EXE file, and both 32 bit and 64 bit options are wrapped up in the same file.
Now that R is downloaded, the next step is to install R. The instructions are given here:
Double-click on the R executable file, and select the language. In this example, we will use English. Choose your preferred language, and click OK to proceed:
The Welcome page will appear, and you should click Next to continue:
The next item is the general license agreement. Click Next to continue:
The next step is to specify the destination location for R's files. In this example, the default is selected. Once the destination has been selected, click Next to proceed:
In the next step, the components of R are configured. If you have a 32-bit machine, then you will need to select the 32-bit option from the drop-down list.
In the next screenshot, the 64-bit User Installation option has been selected:
The next option is to customize the startup options. Here, the default is selected. Click Next to continue.
The next option is to select the Start Menu folder configuration. Select the default, and click Next:
Next, it's possible to configure some of R's options, such as the creation of a desktop icon. Here, let's choose the default options and click Next:
In the next step, the R files are copied to the computer. This step should only take a few moments:
Finally, R is installed, and you should receive a final window. Click Finish:
Once completed, launch RGui from the shortcut, or you can locate RGui.exe from your installation path. The default path for Windows is C:\Program Files\R\R- 2.15.1\bin\x64\Rgui.exe.
Type help.start() at the R-Console prompt and press Enter. If you can see the help server page then you have successfully installed and configured your R package.

Key benefits

A comprehensive guide that will bring out the creativity in you to visualize the results of complex calculations using Tableau and R

Combine Tableau analytics and visualization with the power of R using this step-by-step guide

Wondering how R can be used with Tableau? This book is your one-stop solution.

Description

Tableau and R offer accessible analytics by allowing a combination of easy-to-use data visualization along with industry-standard, robust statistical computation. Moving from data visualization into deeper, more advanced analytics? This book will intensify data skills for data viz-savvy users who want to move into analytics and data science in order to enhance their businesses by harnessing the analytical power of R and the stunning visualization capabilities of Tableau. Readers will come across a wide range of machine learning algorithms and learn how descriptive, prescriptive, predictive, and visually appealing analytical solutions can be designed with R and Tableau. In order to maximize learning, hands-on examples will ease the transition from being a data-savvy user to a data analyst using sound statistical tools to perform advanced analytics. By the end of this book, you will get to grips with advanced calculations in R and Tableau for analytics and prediction with the help of use cases and hands-on examples.

What you will learn

Integrate Tableau s analytics with the industry-standard, statistical prowess of R. Make R function calls in Tableau, and visualize R functions with Tableau using RServe. Use the CRISP-DM methodology to create a roadmap for analytics investigations. Implement various supervised and unsupervised learning algorithms in R to return values to Tableau. Make quick, cogent, and data-driven decisions for your business using advanced analytical techniques such as forecasting, predictions, association rules, clustering, classification, and other advanced Tableau/R calculated field functions.

What do you get with Print?