Blog Archives

Bar charts with percentage labels but counts on the y axis

June 11, 2014
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Bar charts with percentage labels but counts on the y axis

Bar charts and histograms are easily to understand. I often write for non-specialist audiences so I tend to use them a lot. People like percentages too, so a bar chart with counts on the y axis but percentage labels is a useful thing to be able to produce. But how to do them in our

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The apply command 101

May 15, 2014
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The apply command 101

The goal of this blog entry is to introduce basic and essential information about the apply function. Even established R users get confused when considering this family of functions especially when observing how many of the them there are: apply, tapply, lapply, sapply, rapply, eapply, mapply. When I was new to R I was rarely

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Dining in San Francisco – Let R Guide You

May 6, 2014
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Dining in San Francisco – Let R Guide You

I’m frequently asked by newcomers to R to provide an easy to follow generic set of instructions on how to download data, transform it, aggregate it, make graphs, and write it all up for publication in a high impact journal – all by the end of the day ! While such a request is somewhat

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Floating table of contents for your html reports using knitr

April 27, 2014
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If you love knitr and rstudio and use them to produce long reports, you probably know that you can produce a table of contents in your html (and pdf) documents. In the newer rstudio (Version 0.98.801 or later) you do it by requesting a toc in the doc header, something like this. title: "cssTest" output:

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GeoCoding, R, and The Rolling Stones – Part 1

April 12, 2014
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GeoCoding, R, and The Rolling Stones – Part 1

Originally posted on Rolling Your Rs:In this article I discuss a general approach for Geocoding a location from within R, processing XML reports, and using R packages to create interactive maps. There are various ways to accomplish this, though using Google’s GeoCoding service is a good place to start. We’ll also talk a bit…

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GeoCoding, R, and The Rolling Stones – Part 1

April 12, 2014
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GeoCoding, R, and The Rolling Stones – Part 1

Originally posted on Rolling Your Rs:In this article I discuss a general approach for Geocoding a location from within R, processing XML reports, and using R packages to create interactive maps. There are various ways to accomplish this, though using Google’s GeoCoding service is a good place to start. We’ll also talk a bit…

Read more »

Fortran and R – Speed Things Up

April 11, 2014
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Fortran and R – Speed Things Up

If you are a newcomer to R then you are probably quite busy learning the semantics of the language as you experiment with the apply family of commands or come up to speed on the grouping and conditioning capabilities offered by lattice graphics. And, along the way, you might have heard that R has the

Read more »

Fortran and R – Speed Things Up

April 11, 2014
By
Fortran and R – Speed Things Up

If you are a newcomer to R then you are probably quite busy learning the semantics of the language as you experiment with the apply family of commands or come up to speed on the grouping and conditioning capabilities offered by lattice graphics. And, along the way, you might have heard that R has the

Read more »

Conditioning and Grouping with Lattice Graphics

February 17, 2014
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Conditioning and Grouping with Lattice Graphics

Conditioning and grouping are two important concepts in graphing that allow us to rapidly refine our understanding of data under consideration. Conditioning, in particular, allows us to view relationships across “panels” with common scales. Each panel contains a plot whose data is “conditional” upon records drawn from the category that supports that particular panel (an

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Conditioning and Grouping with Lattice Graphics

February 17, 2014
By
Conditioning and Grouping with Lattice Graphics

Conditioning and grouping are two important concepts in graphing that allow us to rapidly refine our understanding of data under consideration. Conditioning, in particular, allows us to view relationships across “panels” with common scales. Each panel contains a plot whose data is “conditional” upon records drawn from the category that supports that particular panel (an

Read more »