2839 search results for "ggplot2"

Simply creating various scatter plots with ggplot #rstats

February 28, 2014
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Simply creating various scatter plots with ggplot #rstats

Inspired by these two postings, I thought about including a function in my package for simply creating scatter plots. In my package, there’s a function called sjp.scatter for creating scatter plots. To reproduce these examples, first load the package and then attach the sample data set: The simplest function call is by just providing two

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The tf-idf-Statistic For Keyword Extraction

February 27, 2014
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The tf-idf-Statistic For Keyword Extraction

The tf-idf-statistic (“term frequency – inverse document frequency”) is a common tool for the purpose of extracting keywords from a document by not just considering a single document but all documents from the corpus. In terms of tf-idf a word … Continue reading → The post The tf-idf-Statistic For Keyword Extraction appeared first on joy...

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Easily generate correlated variables from any distribution

February 27, 2014
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Easily generate correlated variables from any distribution

In this post I will demonstrate in R how to draw correlated random variables from any distributionThe idea is simple.  1. Draw any number of variables from a joint normal distribution. 2. Apply the univariate normal CDF of variables to derive pro...

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Type I error rates in test of normality by simulation

February 26, 2014
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Type I error rates in test of normality by simulation

This simulation tests the type I error rates of the Shapiro-Wilk test of normality in R and SAS. First, we run a simulation in R. Notice the simulation is vectorized: there are no "for" loops that clutter the code and slow the simulation. # type I erroralpha <- 0.05# number of simulationsn.simulations <- 10000#...

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Unemployment revisited

February 23, 2014
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Unemployment revisited

Approximately a year ago I made a post graphing unemployment in Europe and other locations. I have always wanted to do this again, not because the R-code would be so interesting, but just because I wanted to see the plots. As time progressed I attempte...

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The gap between data mining and predictive models

February 20, 2014
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The gap between data mining and predictive models

The Facebook data science blog shared some fun data explorations this Valentine’s Day in Carlos Greg Diuk’s “The Formation of Love”. They are rightly receiving positive interest in and positive reviews of their work (for example Robinson Meyer’s Atlantic article). The finding is also a great opportunity to discuss the gap between cool data mining Related posts:

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Shapefile Polygons Plotted on Google Maps Using ggmap in R – Throw some, throw some STATS on that map…(Part 2)

February 20, 2014
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Shapefile Polygons Plotted on Google Maps Using ggmap in R – Throw some, throw some STATS on that map…(Part 2)

Well it’s been long enough since my last post. Had a few things on my plate (vacation, holidays, another holiday, some more holidays, and quite a lot of research). March is almost here but the good news is that I have plenty of work stored up to start serving out some intuitive approaches for learning

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Function to Simplify Loading and Installing Packages

February 20, 2014
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One of the more tedious parts of working with R is maintaining my R library. To make my R scripts reproducible and sharable, I will install packages if they are not available. For example, the top of my R scripts tend to look something like this: if(!require(devtools) | !require(ggplot2) | !require(psych) | !require(lme4) | !require(benchmark)) { install.packages(c('devtools','ggplot2','psych','lme4','benchmark')) } This has worked fine for...

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R and (Software) Relatives

February 18, 2014
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R and (Software) Relatives

Post also available with code executed inline at rpubs.com. O'Reilly recently published the results of a survey from attendees of the Strata Conference related to tool usage and salary.  The entire survey is available for download.  In the survey results, R was heralded as second only to SQL as a tool used by conference attendees.  An chart from the...

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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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