Monthly Archives: March 2009

Identify Data Points in Off-Screen R Graphics Devices

March 16, 2009
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Today Ruya Gokhan Kocer asked me how to use the R function identify() in off-screen graphics devices. Actually it’s pretty easy as long as we obtain the list returned by identify(pos = TRUE). For example, # open a windows device x11() x = rnorm(20) y = rnorm(20) plot(x, y) # identify 5 points id = identify(x, y, n = 5, pos =

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2009 March Madness Half Marathon in Cary

March 15, 2009
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This morning it was once more time for the annual March Madness Half Marathon in Cary. This race is basically the start of the running season in Chicagoland. And we could not have asked for better weather. After a really cold and long winter, and a short snapback to really cold temperatures this week, it started to warm up a little yesterday...

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Color: The Cinderella of dataviz

March 13, 2009
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Color:  The Cinderella of dataviz

“Avoiding catastrophe becomes the first principle in bringing color to information: Above all, do no harm.”  — Envisioning Information, Edward Tufte, Graphics Press, 1990    Color is one of the most abused and neglected tools in data visualization. It is abused when we make poor color choices; it is neglected when we rely on poor software

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Visulization of correlation matrix

March 12, 2009
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Color Imagedata(mtcars)fit = lm(mpg ~ ., mtcars)cor = summary(fit, correlation = TRUE)$correlationcor2 = t(cor)colors = c("#A50F15", "#DE2D26", "#FB6A4A", "#FCAE91", "#FEE5D9","white", "#EFF3FF", "#BDD7E7", "#6BAED6", "#3182BD", "#08519C")image(1:11, 1:11, cor2, axes = FALSE, ann = F, col = colors)text(rep(1:11, 11), rep(1:11, each = 11), round(100 * cor2))Ellipseslibrary(ellipse)col =

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Visulization of correlation matrix

March 12, 2009
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Color Imagedata(mtcars)fit = lm(mpg ~ ., mtcars)cor = summary(fit, correlation = TRUE)$correlationcor2 = t(cor)colors = c("#A50F15", "#DE2D26", "#FB6A4A", "#FCAE91", "#FEE5D9","white", "#EFF3FF", "#BDD7E7", "#6BAED6", "#3182BD", "#08519C")image(1:11, 1:11, cor2, axes = FALSE, ann = F, col = colors)text(rep(1:11, 11), rep(1:11, each = 11), round(100 * cor2))Ellipseslibrary(ellipse)col =

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no “Infinities”

March 12, 2009
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no “Infinities”

Thanks to  Pierre-Yves for the below useful tip!if you have a dataset from which you want the max or min but they have to be real number and not "Inf" or "-Inf" there is a way to do it:data <- c(-Inf, 1,2,3,4,5,6,7,8,9,10, Inf)max(data)# Return...

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Andrews’ Curve And Parallel Coordinate Graph

March 11, 2009
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Unison graph and parallel coordinate graph share similar thought in visualising the difference of multidimensional data, thought the former is much more complicated. Based on iris data, we can see their performance.Parallel coordinate graphAndrews' Cur...

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Andrews’ Curve And Parallel Coordinate Graph

March 11, 2009
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Unison graph and parallel coordinate graph share similar thought in visualising the difference of multidimensional data, thought the former is much more complicated. Based on iris data, we can see their performance.Parallel coordinate graphAndrews' Cur...

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Scatterplots

March 11, 2009
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There are many types of scatterplots in R, here are some examples based on the famous Iris data.pairs() and coplot() in package graphics.gpairs() in package YaleToolkit.scatterplot.matrix() or spm() in package car.splom() in package lattice.

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Scatterplots

March 11, 2009
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There are many types of scatterplots in R, here are some examples based on the famous Iris data.pairs() and coplot() in package graphics.gpairs() in package YaleToolkit.scatterplot.matrix() or spm() in package car.splom() in package lattice.

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