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Is there a R function that applies a function to each pair of columns?

It wouldn’t be faster, but you can use outer to simplify the code. It does require a vectorized function, so here I’ve used Vectorize to make a vectorized version of the function to get the correlation between two columns. df <- data.frame(x=rnorm(100),y=rnorm(100),z=rnorm(100)) n <- ncol(df) corpij <- function(i,j,data) {cor.test(data[,i],data[,j])$p.value} corp <- Vectorize(corpij, vectorize.args=list(“i”,”j”)) outer(1:n,1:n,corp,data=df)

How to strsplit different number of strings in certain column by do function

You’re having troubles because strsplit() returns a list which we then need to apply as.data.frame.list() to each element to get it into the proper format that dplyr requires. Even then it would still require a bit more work to get usable results. Long story short, it doesn’t seem like a suitable operation for do(). I … Read more

Count number of rows by group using dplyr

There’s a special function n() in dplyr to count rows (potentially within groups): library(dplyr) mtcars %>% group_by(cyl, gear) %>% summarise(n = n()) #Source: local data frame [8 x 3] #Groups: cyl [?] # # cyl gear n # (dbl) (dbl) (int) #1 4 3 1 #2 4 4 8 #3 4 5 2 #4 6 … Read more

What does the dot mean in R – personal preference, naming convention or more?

A dot in function name can mean any of the following: nothing at all a separator between method and class in S3 methods to hide the function name Possible meanings 1. Nothing at all The dot in data.frame doesn’t separate data from frame, other than visually. 2. Separation of methods and classes in S3 methods … Read more

Aggregate a data frame based on unordered pairs of columns

One way is to create extra columns with pmax and pmin of id1 and id2as follows. I’ll use data.table solution here. require(data.table) DT <- data.table(DF) # Following mnel’s suggestion, g1, g2 could be used directly in by # and it could be even shortened by using `id1` and id2` as their names DT.OUT <- DT[, … Read more

Aggregate a dataframe on a given column and display another column

A base R solution is to combine the output of aggregate() with a merge() step. I find the formula interface to aggregate() a little more useful than the standard interface, partly because the names on the output are nicer, so I’ll use that: The aggregate() step is maxs <- aggregate(Score ~ Group, data = dat, … Read more

dplyr: “Error in n(): function should not be called directly”

I presume you have dplyr and plyr loaded in the same session. dplyr is not plyr. ddply is not a function in the dplyr package. Both dplyr and plyr have the functions summarise/summarize. Look at the results of conflicts() to see masked objects.

dplyr summarise: Equivalent of “.drop=FALSE” to keep groups with zero length in output

The issue is still open, but in the meantime, especially since your data are already factored, you can use complete from “tidyr” to get what you might be looking for: library(tidyr) df %>% group_by(b) %>% summarise(count_a=length(a)) %>% complete(b) # Source: local data frame [3 x 2] # # b count_a # (fctr) (int) # 1 … Read more

Idiomatic R code for partitioning a vector by an index and performing an operation on that partition

Yet another option is ave. For good measure, I’ve collected the answers above, tried my best to make their output equivalent (a vector), and provided timings over 1000 runs using your example data as an input. First, my answer using ave: ave(df$x, df$index, FUN = function(z) z/sum(z)). I also show an example using data.table package … Read more

Remove group from data.frame if at least one group member meets condition

Try library(dplyr) df2 %>% group_by(group) %>% filter(!any(world == “AF”)) Or as per metionned by @akrun: setDT(df2)[, if(!any(world == “AF”)) .SD, group] Or setDT(df2)[, if(all(world != “AF”)) .SD, group] Which gives: #Source: local data frame [7 x 3] #Groups: group # # world place group #1 AB 1 1 #2 AC 1 1 #3 AD 2 … Read more