r

How to convert a factor to integer\numeric without loss of information?

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See the Warning section of ?factor: In particular, as.numeric applied to a factor is meaningless, and may happen by implicit coercion. To transform a factor f to approximately its original numeric values, as.numeric(levels(f))[f] is recommended and slightly more efficient than as.numeric(as.character(f)). The FAQ on R has similar advice. Why is as.numeric(levels(f))[f] more efficent than as.numeric(as.character(f))? … Read more

Rotating and spacing axis labels in ggplot2

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Change the last line to q + theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1)) By default, the axes are aligned at the center of the text, even when rotated. When you rotate +/- 90 degrees, you usually want it to be aligned at the edge instead: The image above is from this blog … Read more

data.table vs dplyr: can one do something well the other can’t or does poorly?

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We need to cover at least these aspects to provide a comprehensive answer/comparison (in no particular order of importance): Speed, Memory usage, Syntax and Features. My intent is to cover each one of these as clearly as possible from data.table perspective. Note: unless explicitly mentioned otherwise, by referring to dplyr, we refer to dplyr’s data.frame … Read more

Drop data frame columns by name

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You can use a simple list of names : DF <- data.frame( x=1:10, y=10:1, z=rep(5,10), a=11:20 ) drops <- c(“x”,”z”) DF[ , !(names(DF) %in% drops)] Or, alternatively, you can make a list of those to keep and refer to them by name : keeps <- c(“y”, “a”) DF[keeps] EDIT : For those still not acquainted … Read more

Remove rows with all or some NAs (missing values) in data.frame

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Also check complete.cases : > final[complete.cases(final), ] gene hsap mmul mmus rnor cfam 2 ENSG00000199674 0 2 2 2 2 6 ENSG00000221312 0 1 2 3 2 na.omit is nicer for just removing all NA‘s. complete.cases allows partial selection by including only certain columns of the dataframe: > final[complete.cases(final[ , 5:6]),] gene hsap mmul mmus … Read more

Grouping functions (tapply, by, aggregate) and the *apply family

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R has many *apply functions which are ably described in the help files (e.g. ?apply). There are enough of them, though, that beginning useRs may have difficulty deciding which one is appropriate for their situation or even remembering them all. They may have a general sense that “I should be using an *apply function here”, … Read more

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