R cor.test : "not enough finite observations"

correlation, dataframe, r

Solution

"Not enough finite obervations" is an error returned by cor.test under certain circumstances. If you take a look a the cor.test.default source code, you'll see :

OK <- complete.cases(x, y)
x <- x[OK]
y <- y[OK]
n <- length(x)

cor.test removes NA values from you vectors [...]

if (method = "pearson") {
    if (n < 3L) 
        stop("not enough finite obervations")

[...]

else {
    if (n<2)
        stop("not enough finite obervations")

If your vectors do not contain enough non-NA values (less than 3), the function will return the error.

Make all of the columns in your dataframe contain enough non-NA values before you use cor.test.

I hope this will be useful.

Problem

I'm currently trying to create an R function computing the corr.test correlation of a specified column with all the numeric columns of a dataframe. Here's my code : ``` #function returning only numeric columns only_num <- function(dataframe) { nums <- sapply(dataframe, is.numeric) dataframe[ , nums] } #function returning a one-variable function computing the cor.test correlation of the variable #with the specified column function_generator <- function(column) { function(x) { cor.test(x, column, na.action = na.omit) } } data_analysis <- function(dataframe, column) { DF <- only_num(dataframe) fonction_corr <- function_generator(column) sapply(DF, fonction_corr) } data_analysis(40, 6, m, DF$Morphine) ``` When I call "data_analysis" at the last line, I get the following error : "Error in cor.test.default(x, column, na.action=na.omit) : not enough finite observations" What could it mean? What should I change? I'm kind of stuck... Thanks. Clément

Original source