Handling missing/incomplete data in R--is there function to mask but not remove NAs?
As you would expect from a DSL aimed at data analysis, R handles missing/incomplete data very well, for instance:
Many R functions have an na.rm flag that when set to TRUE, remove the NAs:
>>> v = mean( c(5, NA, 6, 12, NA, 87, 9, NA, 43, 67), na.rm=T)
>>> v
(5, 6, 12, 87, 9, 43, 67)
But if you want to deal with NAs before the function call, you need to do something like this:
to remove each 'NA' from a vector:
vx = vx[!is.na(a)]
to remove each 'NA' from a vector and replace it w/ a '0':
ifelse(is.na(vx), 0, vx)
to remove entire each row that contains 'NA' from a data frame:
dfx = dfx[complete.cases(dfx),]
All of these functions permanently remove 'NA' or rows with an 'NA' in them.
Sometimes this isn't quite what you want though--making an 'NA'-excised copy of the data frame might be necessary for the next step in the workflow but in subsequent steps you often want those rows back (e.g., to calculate a column-wise statistic for a column that has missing rows caused by a prior call to 'complete cases' yet that column has no 'NA' values in it).
to be as clear as possible about what i'm looking for: python/numpy has a class, masked array, with a mask method, which lets you conceal--but not remove--NAs during a function call. Is there an analogous function in R?
Answer
Exactly what to do with missing data -- which may be flagged as NA if we know it is missing -- may well differ from domain to domain.
To take an example related to time series, where you may want to skip, or fill, or interpolate, or interpolate differently, ... is that just the (very useful and popular) zoo has all these functions related to NA handling:
zoo::na.approx zoo::na.locf
zoo::na.spline zoo::na.trim
allowing to approximate (using different algorithms), carry-forward or backward, use spline interpolation or trim.
Another example would be the numerous missing imputation packages on CRAN -- often providing domain-specific solutions. [ So if you call R a DSL, what is this? "Sub-domain specific solutions for domain specific languages" or SDSSFDSL? Quite a mouthful :) ]
But for your specific question: no, I am not aware of a bit-level flag in base R that allows you to mark observations as 'to be excluded'. I presume most R users would resort to functions like na.omit() et al or use the na.rm=TRUE option you mentioned.