standard deviation on dataframe does not work
r
Solution
`sd` on data.frames has been defunct since R-3.0.0:
> ## Build a db of all R news entries.
> db <- news()
> ## sd
> news(grepl("sd", Text), db=db)
Changes in version 3.0.3:
PACKAGE INSTALLATION
o The new field SysDataCompression in the DESCRIPTION file allows
user control over the compression used for sysdata.rda objects in
the lazy-load database.
Changes in version 3.0.0:
DEPRECATED AND DEFUNCT
o mean() for data frames and sd() for data frames and matrices are
defunct.
Use `sapply(x, sd)` instead.
Problem
I have an unexpected [for me at least] error in calculating a standard deviation. The idea [*] is to convert all missing values to 1 and 0 otherwise. Then extract variables that have some [but not all] missing values, before a correlation is done. That extraction step is attempted with a sd function, but it fails [why?]. ``` library(VIM) data(sleep) # dataset with missing values x = as.data.frame(abs(is.na(sleep))) # converts all NA to 1, otherwise 0 y = x[which(sd(x) > 0)] # attempt to extract variables with missing values Error in is.data.frame(x) : (list) object cannot be coerced to type 'double' # convert to double z = as.data.frame(apply(x, 2, as.numeric)) y = z[which(sd(z) > 0)] Error in is.data.frame(x) : (list) object cannot be coerced to type 'double' ``` [*] R in Action, Robert Kabacoff