Getting Started With R: A Beginner’s Guide, Part 1

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If you want to create data visualizations, Tableau is an amazing tool. With a few mouse clicks you can create anything from a bar chart to a heat map. The graphics it produces are beautiful and you don’t need to know any programming. Plus, if you don’t mind your work being public, it’s available at no cost. But these advantages come at a price. Tableau is not a full-featured programming language, it is primarily a tool for visualization. You can do some calculations within Tableau, but you will eventually need to solve a problem that it just can’t handle. In addition, everything you do in Tableau is done through mouse clicks. This makes it difficult to create a record of what you have done, and very difficult for someone else to duplicate your work.

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关键词：beginner Started getting beginn Guide beautiful available anything produces amazing

SAS is arguably the gold standard of statistical software, but I may be a tiny bit biased in saying that. After all, I’m taking classes that are taught in SAS Hall. Base SAS gives you a very powerful set of analytical tools, and it can be expanded with add-on programs for working in specialized fields or doing complex graphics. Virtually any statistical, analytical, or visualization that you can conceive of can be created in SAS. The big downside here is the price. A SAS license is not inexpensive, and by the time you include a couple of the add-on packages, it can be very expensive. If you want to learn SAS, there are free courses available and they include access to a web-based version of the software, but to use it for other purposes, you’ll need a license.

Python is another alternative. It’s free, it’s powerful, and there is a lot of support available on the web. The downside here is a steep learning curve. If you aren’t already a programmer, getting started with Python can be difficult. On the other hand, it is ubiquitous in the analytics community. At a Research Triangle Analysts Unconference last spring, at least 75% of the presentations involved the use of Python. After attending that Unconference, I decided it was time for me to learn Python. If you already know another programming language, then it’s really not that hard. - See more at: http://geraldbelton.com/getting-started-with-r-a-beginners-guide-part-1/#sthash.2eZ27wbS.dpuf

A KD Nuggets Poll suggests that Python is second only to R in popularity for data science or analytics. But it’s still second. R is a full-featured programming language, it’s easy to learn, it’s powerful, and since it is so popular, there is a ton of support available. - See more at:

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