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?

有帮助吗?

解决方案 2

I think this should do what you want.

  1. Select the columns you want:

    v = c("x", "y")#or
    v = colnames(df)[1:2]
    
  2. Use sapply to iterate over v and pass the values to tapply:

    sapply(v, function(i) tapply(df[[i]], df$group, sd, na.rm=TRUE))
    

其他提示

Simply set na.rm=TRUE in the tapply function:

tapply(weightgain$weightgain, list(weightgain$source, weightgain$type), mean, na.rm=TRUE)
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