What is the most useful R trick? [closed]

Answer 1

set.seed() sets the random number generator state.

For example:

> set.seed(123)
> rnorm(1)
[1] -0.5604756
> rnorm(1)
[1] -0.2301775
> set.seed(123)
> rnorm(1)
[1] -0.5604756

Answer 2

head() and tail() to get the first and last parts of a dataframe, vector, matrix, function, etc. Especially with large data frames, this is a quick way to check that it has loaded ok.

Answer 3

My new favorite thing is the foreach library. It lets you do all of the nice apply things, but with a somewhat easier syntax:

list_powers <- foreach(i = 1:100) %do% {
  lp <- x[i]^i
  return (lp)
}

The best part is that if you are doing something that actually requires a significant amount of time, you can switch from %do% to %dopar% (with the appropriate backend library) to instantly parallelize, even across a cluster. Very slick.

Answer 4

Another trick. Some packages, like glmnet, only take as inputs the design matrix and the response variable. If one wants to fit a model with all interactions between features, she can't use the formula "y ~ .^2". Using expand.grid() allows us to take advantage of the powerful array indexing and vector operations of R.

interArray=function(X){
    n=ncol(X)
    ind=expand.grid(1:n,1:n)
    return(X[,ind[,1]]*X[,ind[,2]])
}

> X
          X1         X2
1 0.96852363 0.33827107
2 0.08012755 0.69159828
3 0.10167545 0.38119304
4 0.06699458 0.41756415
5 0.08187816 0.09805104

> interArray(X)
           X1          X2        X1.1        X2.1
1 0.938038022 0.327623524 0.327623524 0.114427316
2 0.006420424 0.055416073 0.055416073 0.478308177
3 0.010337897 0.038757974 0.038757974 0.145308137
4 0.004488274 0.027974536 0.027974536 0.174359821
5 0.006704033 0.008028239 0.008028239 0.009614007

Answer 5

CrossTable() from the gmodels package provides easy access to SAS- and SPSS-style crosstabs, along with the usual tests (Chisq, McNemar, etc.). Basically, it's xtabs() with fancy output and some additional tests - but it does make sharing output with the heathens easier.

Answer 6

Data Input trick = RGoogleDocs package

http://www.omegahat.org/RGoogleDocs/

I have found Google spreadsheets to be a fantastic way for all collaborators to be on the same page. Furthermore, Google Forms allows one to capture data from respondents and effortlessly write it to a google spreadsheet. Since data changes frequently and is almost never final it is far preferable for R to read a google spreadsheet directly than to futz with downloading csv files and reading them in.

# Get data from google spreadsheet
library(RGoogleDocs)
ps <-readline(prompt="get the password in ")
auth = getGoogleAuth("me@gmail.com", ps, service="wise")
sheets.con <- getGoogleDocsConnection(auth)
ts2=getWorksheets("Data Collection Repos",sheets.con)
names(ts2)
init.consent <-sheetAsMatrix(ts2$Sheet1,header=TRUE, as.data.frame=TRUE, trim=TRUE)

I cannot rembember which but one or two of the following commands takes several seconds.

1. getGoogleAuth

2. getGoogleDocsConnection

3. getWorksheets