我希望将dataframe的第三列除以5。
[[44]]
Ethnicity Variant Sum
1: ASW ACCEPTOR 1
2: ASW CDS 68
3: ASW CGA_CNVWIN 1000
4: ASW CGA_MIRB 0
5: ASW DELETE 0
6: ASW DISRUPT 0
7: ASW DONOR 0
8: ASW FRAMESHIFT 0
9: ASW INSERT 1
10: ASW INTRON 54我使用了三个命令,每个命令都是成功的,但有非目标效果。
lapply(ASWldtSUM,function(x)(x/5))返回
[[44]]
Ethnicity Variant Sum
1: NA NA 0.2
2: NA NA 13.6
3: NA NA 200.0
4: NA NA 0.0
5: NA NA 0.0它的不幸效果是将所有行除以5,导致类不是$Sum列中的整数时出现问题。
lapply(ASWldtSUM,function(x[,3])(x/5))具有只返回一个向量的效果,如果这不是一个嵌套的数据数组,而是语句,那么这个向量就能很好地工作。
ASWdtSUM$NEWCOL<-lapply(ASWldtSUM,function(x[,3])(x/5))不能简单地编写,因为它是嵌套的。
如以下语句所示,快速使用:
rapply(ASWldtSUM,function(x) if (is.integer(x)) {(x/5)})导致结果混乱。
那么,是否有一种简单的方法可以将第4列附加到每个嵌套的DataFrame中,或者将每个DF (Sum)的第三列替换为除以5的值?
发布于 2014-06-03 08:29:04
非常简单,如果ASWldtSUM是包含数据帧的列表的名称,那么您可以这样做:
lapply(ASWldtSUM,FUN=function(x) { x[,3]=x[,3]/5; return(x) })基本上,您将(整个)第三列替换为(整个)第三colum的除法5。
在实践中:
> ASWldtSUM1=data.frame(Ethnicity=rep('ASW',10),Variant=c("ACCEPTOR","CDS","CGA_CNVWIN","CGA_MIRB","DELETE","DISRUPT","DONOR","FRAMESHIFT","INSERT","INTRON"), Sum=c(1,68,1000,0,0,0,0,0,1,54))
> #created a first data.frame (equal to your example)
> ASWldtSUM2=data.frame(Ethnicity=rep('ASW',10),Variant=c("ACCEPTOR","CDS","CGA_CNVWIN","CGA_MIRB","DELETE","DISRUPT","DONOR","FRAMESHIFT","INSERT","INTRON"), Sum=c(1,2,3,4,5,6,7,8,9,10))
> #created a second data.frame (with different values for the third column)
> ASWldtSUM=list(ASWldtSUM1,ASWldtSUM2)
> #created a list of data frames
> lapply(ASWldtSUM,FUN=function(x) { x[,3]=x[,3]/5; return(x) })
> #apply the function to divide third column to each nested data.frame
[[1]]
Ethnicity Variant Sum
1 ASW ACCEPTOR 0.2
2 ASW CDS 13.6
3 ASW CGA_CNVWIN 200.0
4 ASW CGA_MIRB 0.0
5 ASW DELETE 0.0
6 ASW DISRUPT 0.0
7 ASW DONOR 0.0
8 ASW FRAMESHIFT 0.0
9 ASW INSERT 0.2
10 ASW INTRON 10.8
[[2]]
Ethnicity Variant Sum
1 ASW ACCEPTOR 0.2
2 ASW CDS 0.4
3 ASW CGA_CNVWIN 0.6
4 ASW CGA_MIRB 0.8
5 ASW DELETE 1.0
6 ASW DISRUPT 1.2
7 ASW DONOR 1.4
8 ASW FRAMESHIFT 1.6
9 ASW INSERT 1.8
10 ASW INTRON 2.0
> #desired result发布于 2014-06-03 08:36:15
有很多种方法可以做到这一点。这里有一个:
创建一些示例数据:
dat <- lapply(1:3, function(x)data.frame(a=sample(letters, 4), b=sample(LETTERS, 4), z=rnorm(4)))
dat
[[1]]
a b z
1 r M 0.3054329
2 v I -0.8051859
3 t Q -1.6082701
4 u D -0.2315290
[[2]]
a b z
1 j W -0.4692469
2 f S 0.3112689
3 a D 0.4208704
4 w Z 0.6903139
[[3]]
....接下来,在lapply()中使用一个小的匿名函数。为了更好地说明,我乘100,而不是除以5:
lapply(dat, function(x){x[3] <- x[3]*100; x})
[[1]]
a b z
1 r M 30.54329
2 v I -80.51859
3 t Q -160.82701
4 u D -23.15290
[[2]]
a b z
1 j W -46.92469
2 f S 31.12689
3 a D 42.08704
4 w Z 69.03139
[[3]]
....https://stackoverflow.com/questions/24010366
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