我想从一个数据帧计算mean和sd,参数为一列,组标识为一列.使用时如何计算tapply?我可以使用sd(v1, group, na.rm=TRUE),但na.rm=TRUE在使用时不适合语句tapply.
omit.na别无选择.我有一大堆参数,在排除所有缺少值的行时,必须逐步完成它们而不会丢失一半的数据帧.
data("weightgain", package = "HSAUR")
tapply(weightgain$weightgain, list(weightgain$source, weightgain$type), mean)
Run Code Online (Sandbox Code Playgroud)
by声明也是如此.
x<-c(1,2,3,4,5,6,7,8,9,NA)
y<-c(2,3,NA,3,4,NA,2,3,NA,2)
group<-rep((factor(LETTERS[1:2])),5)
df<-data.frame(x,y,group)
df
by(df$x,df$group,summary)
by(df$x,df$group,mean)
sd(df$x) #result: NA
sd(df$x, na.rm=TRUE) #result: 2.738613
Run Code Online (Sandbox Code Playgroud)
有任何想法如何完成这项工作?
小智 20
只需设置na.rm=TRUE的tapply功能:
tapply(weightgain$weightgain, list(weightgain$source, weightgain$type), mean, na.rm=TRUE)
Run Code Online (Sandbox Code Playgroud)
我认为这应该做你想要的.
选择所需的列:
v = c("x", "y")#or
v = colnames(df)[1:2]
Run Code Online (Sandbox Code Playgroud)使用sapply遍历v和值传递给tapply:
sapply(v, function(i) tapply(df[[i]], df$group, sd, na.rm=TRUE))
Run Code Online (Sandbox Code Playgroud)