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R:循环合并数据帧并cbind这些

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我有一个像[] R: merge unequal dataframes and replace missing rows with 0这样的问题

以下是此问题的数据:

df1 = data.frame(x=c('a', 'b', 'c', 'd', 'e'))
df2 = data.frame(x=c('a', 'b', 'c'),y = c(0,1,0)) 
df3 = data.frame(x=c('a', 'b', 'c', 'd'),y = c(1,1,1,0))
df4 = data.frame(x=c('b', 'a', 'e'),y = c(0,1,0))
zz <- merge(df1, df2, all = TRUE)
zz[is.na(zz)] <- 0

在这个例子中,我将df1与df2合并 . 现在我想创建一个循环来合并df3和df4以及更多数据帧与df1 . 问题是列表中的结果必须是cbind才能生成最终的数据帧 .

谁能帮我?

谢谢!


编辑!这是我创建的循环 . 变量goterms禁止包含10个变量的列表 . 变量是interestGO中列表的名称 . 选择第一个感兴趣的GO,计算结果是变量结果 . 此结果必须与x合并 . 因为它是一个循环,所有10个结果必须是cbind才能创建最终的数据帧 .

for (i in 1:length(goterms)){
  goilmn<-as.data.frame(interestedGO[i])
  resultILMN<-match(goilmn[,1], rownames(xx2),nomatch=0)
  resultILMN[resultILMN] <- 1
  result<-cbind(goilmn,resultILMN)
  colnames(result) <- c('x','result')

  zz<-merge(x, result, all=TRUE)
  resultloop<-zz[is.na(zz)]<-0
  standard[i]<-cbind(resultloop)
}

goterms:
[1] "GO:0009611" "GO:0007596" "GO:0050817" "GO:0061082" "GO:0007599"
[6] "GO:0050776" "GO:0006910" "GO:0034383" "GO:0019932" "GO:0002720"

interestedGO:
$`GO:0009611` 
[1] "ILMN_1651346" "ILMN_1651354" "ILMN_1651599" "ILMN_1651950" "ILMN_1652287"
[6] "ILMN_1652445" "ILMN_1652693" "ILMN_1652825" "ILMN_1653324" "ILMN_1653395"

$`GO:0007596`
[1] "ILMN_1651599" "ILMN_1652693" "ILMN_1652825" "ILMN_1653324" "ILMN_1655595"
[6] "ILMN_1656057" "ILMN_1659077" "ILMN_1659923" "ILMN_1659947" "ILMN_1662619"
[11] "ILMN_1664565" "ILMN_1665132" "ILMN_1665859" "ILMN_1666175" "ILMN_1668052"
[16] "ILMN_1670229" "ILMN_1670305" "ILMN_1670490" "ILMN_1670708"
"ILMN_1671766"                              

$`GO:0050817`
[1] "ILMN_1651599" "ILMN_1652693" "ILMN_1652825" "ILMN_1653324" "ILMN_1655595"
[6] "ILMN_1656057" "ILMN_1659077" "ILMN_1659923" "ILMN_1659947" "ILMN_1662619"
[11] "ILMN_1664565" "ILMN_1665132" "ILMN_1665859" "ILMN_1666175" "ILMN_1668052"
[16] "ILMN_1670229" "ILMN_1670305" "ILMN_1670490" "ILMN_1670708" "ILMN_1671766"
[21] "ILMN_1671928" "ILMN_1675083" "ILMN_1678049" "ILMN_1678728" 
"ILMN_1680805"                            

$`GO:0061082`
[1] "ILMN_1661695" "ILMN_1665132" "ILMN_1716446" "ILMN_1737314" "ILMN_1772387"
[6] "ILMN_1784863" "ILMN_1796094" "ILMN_1800317" "ILMN_1800512" "ILMN_1807074"

x是所有ILMN代码的引用 . 这是x变量的头部 . X [1:100,]

[1] ILMN_1343291 ILMN_1343295 ILMN_1651228 ILMN_1651229 ILMN_1651238
 [6] ILMN_1651254 ILMN_1651259 ILMN_1651260 ILMN_1651262 ILMN_1651278
 [11] ILMN_1651282 ILMN_1651285 ILMN_1651286 ILMN_1651303 ILMN_1651310
 [16] ILMN_1651315 ILMN_1651330 ILMN_1651336 ILMN_1651343 ILMN_1651346
 [21] ILMN_1651347 ILMN_1651354 ILMN_1651358 ILMN_1651370 ILMN_1651373
 [26] ILMN_1651385 ILMN_1651396 ILMN_1651415 ILMN_1651428 ILMN_1651430
 [31] ILMN_1651433 ILMN_1651437 ILMN_1651438 ILMN_1651456 ILMN_1651457

1 回答

  • 3

    我不确定我是否理解你想要的东西,但是这样吗?

    > zz <- Reduce(function(a,b)merge(a,b,all=TRUE, by="x"), list(df1, df2, df3, df4))
    > zz[is.na(zz)] <- 0
    > zz
      x y.x y.y y
    1 a   0   1 1
    2 b   1   1 0
    3 c   0   1 0
    4 d   0   0 0
    5 e   0   0 0
    

    您可以通过使用Reduce避免循环,但请注意,它不一定会导致性能提升 .

    如果你想要单独的数据帧,那么Map(只是mapply的包装器)很有用:

    > zz <- Map(function(b)merge(df1,b,all=TRUE, by="x"), list(df2, df3, df4))
    > zz
    [[1]]
      x  y
    1 a  0
    2 b  1
    3 c  0
    4 d NA
    5 e NA
    
    [[2]]
      x  y
    1 a  1
    2 b  1
    3 c  1
    4 d  0
    5 e NA
    
    [[3]]
      x  y
    1 a  1
    2 b  0
    3 c NA
    4 d NA
    5 e  0
    

    并通过do.call将它们绑定

    > zz <- do.call("cbind", zz)
    > zz[is.na(zz)] <- 0
    > zz
      x y x y x y
    1 a 0 a 1 a 1
    2 b 1 b 1 b 0
    3 c 0 c 1 c 0
    4 d 0 d 0 d 0
    5 e 0 e 0 e 0
    

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