Sharon Machlis

About the Author Sharon Machlis


Beginner’s guide to R: Introduction

R is hot. Whether measured by more than 10,000 add-on packages, the 95,000+ members of LinkedIn’s R group or the  more than 400 R Meetup groups currently in existence, there can be little doubt that interest in the R statistics language, especially for data analysis, is soaring.

Why R? It’s free, open source, powerful and highly extensible. “You have a lot of prepackaged stuff that’s already available, so you’re standing on the shoulders of giants,” Google‘s chief economist told The New York Times back in 2009.

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22 free tools for data visualization and analysis

You may not think you’ve got much in common with an investigative journalist or an academic medical researcher. But if you’re trying to extract useful information from an ever-increasing inflow of data, you’ll likely find visualization useful — whether it’s to show patterns or trends with graphics instead of mountains of numbers, or to try to explain complex issues to a nontechnical audience.

There are many tools around to help turn data into graphics, but they can carry hefty price tags. The cost can make sense for professionals whose primary job is to find meaning in mountains of information, but you might not be able to justify such an expense if you or your users only need a graphics application from time to time, or if your budget for new tools is somewhat limited. If one of the higher-priced options is out of your reach, there are a surprising number of highly robust tools for data visualization and analysis that are available at no charge.

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