Posts Tagged ‘ plyr ’

Good riddance to Excel pivot tables

January 30, 2011
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Good riddance to Excel pivot tables

Excel pivot tables have been how I have reorganized data...up until now. These are just a couple of examples why R is superior to Excel for reorganizing data:################ Good riddance to pivot tables ############library(reshape2)library(plyr)&nbsp...

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ClusterProfiles

October 12, 2010
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ClusterProfiles

It is very common to cluster genes based on their expression profiles, and also very common to integrate Gene Ontology to observe the distribution of biological processes, molecular functions and cellular components for a given gene list. But, what if the two in combination? The Gene Ontology distributions across a variety of gene clusters may give us a...

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Using the {plyr} (1.2) package parallel processing backend with windows

September 11, 2010
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Hadley Wickham has just announced the release of a new R package “reshape2” which is (as Hadley wrote) “a reboot of the reshape package”. Alongside, Hadley announced the release of plyr 1.2.1 (now faster and with support to parallel computation!). Both releases are exciting due to a significant speed increase they have now gained. Yet in case of the new plyr...

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New versions for ggplot2 (0.8.8) and plyr (1.0) were released today

July 6, 2010
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New versions for ggplot2 (0.8.8) and plyr (1.0) were released today

As prolific as the CRAN website is of packages, there are several packages to R that succeeds in standing out for their wide spread use (and quality), Hadley Wickhams ggplot2 and plyr are two such packages. And today (through twitter) Hadley has updates the rest of us with the news: just released new versions of plyr and ggplot2. source...

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Struggling with apply() in R

December 11, 2009
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Struggling with apply() in R

It’s common knowledge that I struggle wrapping my head around the apply functions in R. That is illustrated very clearly in the following discussion on Stack Overflow: Dirk’s comment is actually spot on. I’ve asked the same damn question at least 4-5 times. Only I didn’t really understand it was the same question. That’s one of

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brew: Creating Repetitive Reports

September 9, 2009
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brew: Creating Repetitive Reports

United Nations report World Population Prospects: The 2008 Revision (highlights available here) provides data about the historical and forecasted population of the country. In exploring the future and past population trends it is relatively easy to subset the dataset by your selected variable. > file <- c("UNdata_Population.csv") > population <- read.csv(file) > names(population) <- c("code", "country", "year", +

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A Fast Intro to PLYR for R

August 27, 2009
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A Fast Intro to PLYR for R

I’m not dead yet! Although it has been rumored that I am. The new job is going great and I’m thrilled to be with a new firm doing interesting work alongside smart people. It makes me seem smarter by simple association. There’s been a lot going on recently in the R user community. There was an

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Sometimes, you just need to use a plyr

July 10, 2009
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Sometimes, you just need to use a plyr

I haven’t posted anything about R-nerdery in quite some time. But I have to pause for a moment, and sing the praises of a relatively new package that has made my life exponentially easier. The plyr package. R has the capability to apply a single function to a vector or list using apply or mapply,

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R: Calculating all possible linear regression models for a given set of predictors

February 6, 2009
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R: Calculating all possible linear regression models for a given set of predictors

Although the graphic at the left might not seem a 100% appropriate, it gives a hint to what I am about to do. I want to calculate all possible linear regression models with one dependent and several independent variables. I do not want to address bias and fitting issues or the question if this

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R: Combining vectors or data frames of unequal length into one data frame

January 23, 2009
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R: Combining vectors or data frames of unequal length into one data frame

Today I will treat a problem I encounter every once in a while. Let’s suppose we have several dataframes or vectors of unequel length but with partly matching column names,  just like the following ones: df1 <- data.frame(Intercept = .4, x1=.4, x2=.2, x3=.7) df2 <- data.frame(Intercept = .5,        x2=.8       ) This for example may occur when fitting several

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