scrub {psych} | R Documentation |
A tedious part of data analysis is addressing the problem of miscoded data that need to be converted to NA or some other value. For a given data.frame or matrix, scrub will set all values of columns from=from to to=to that are less than a set (vector) of min values or more than a vector of max values to NA. Can also be used to do basic recoding of data for all values=isvalue to newvalue.
The length of the where, isvalue, and newvalues must either match, or be 1.
scrub(x, where, min, max,isvalue,newvalue)
x |
a data frame or matrix |
where |
The variables to examine. (Can be by name or by column number) |
min |
a vector of minimum values that are acceptable |
max |
a vector of maximum values that are acceptable |
isvalue |
a vector of values to be converted to newvalue (one per variable) |
newvalue |
a vector of values to replace those that match isvalue |
Solves a tedious problem that can be done directly but that is sometimes awkward. Will either replace specified values with NA or
The corrected data frame.
Probably could be optimized to avoid one loop
William Revelle
reverse.code
, rescale
for other simple utilities.
data(attitude) x <- scrub(attitude,isvalue=55) #make all occurrences of 55 NA x1 <- scrub(attitude, where=c(4,5,6), isvalue =c(30,40,50), newvalue = c(930,940,950)) #will do this for the 4th, 5th, and 6th variables x2 <- scrub(attitude, where=c(4,4,4), isvalue =c(30,40,50), newvalue = c(930,940,950)) #will just do it for the 4th column #get rid of a complicated set of cases and replace with missing values y <- scrub(attitude,where=2:4,min=c(20,30,40),max= c(120,110,100),isvalue= c(32,43,54)) y1 <- scrub(attitude,where="learning",isvalue=55,newvalue=999) #change a column by name y2 <- scrub(attitude,where="learning",min=45,newvalue=999) #change a column by name y3 <- scrub(attitude,where="learning",isvalue=c(45,48), newvalue=999) #change a column by name look for multiple values in that column y4 <- scrub(attitude,where="learning",isvalue=c(45,48), newvalue= c(999,-999)) #change values in one column to one of two different things