问题
I´d like to calculate mean and sd from a dataframe with one column for the parameter and one column for a group identifier. How can I calculate them when using tapply
? I could use sd(v1, group, na.rm=TRUE)
, but can´t fit the na.rm=TRUE
into the statement when using tapply
.
omit.na
is no option. I have a whole bunch of parameters and have to go through them step by step without losing half of the dataframe when excluding all lines with one missing value.
data("weightgain", package = "HSAUR")
tapply(weightgain$weightgain, list(weightgain$source, weightgain$type), mean)
The same holds true for the by
statement.
x<-c(1,2,3,4,5,6,7,8,9,NA)
y<-c(2,3,NA,3,4,NA,2,3,NA,2)
group<-rep((factor(LETTERS[1:2])),5)
df<-data.frame(x,y,group)
df
by(df$x,df$group,summary)
by(df$x,df$group,mean)
sd(df$x) #result: NA
sd(df$x, na.rm=TRUE) #result: 2.738613
Any ideas how to get this done?
回答1:
I think this should do what you want.
Select the columns you want:
v = c("x", "y")#or v = colnames(df)[1:2]
Use
sapply
to iterate overv
and pass the values totapply
:sapply(v, function(i) tapply(df[[i]], df$group, sd, na.rm=TRUE))
回答2:
Simply set na.rm=TRUE
in the tapply
function:
tapply(weightgain$weightgain, list(weightgain$source, weightgain$type), mean, na.rm=TRUE)
来源:https://stackoverflow.com/questions/14172556/how-to-pass-na-rm-as-argument-to-tapply