按行，替换指定列中等于值的值 [英] By row, replace values equal to value in specified column

问题描述

希望这是一个简单的.我似乎无法拼凑出一个答案.我有一个数据框.对于每一行，我都有需要更改为 NA 的值.需要为每一行更改的值并不相同.我想根据指定列中的值将每一行的值更改为 NA.

Hopefully this is an easy one. I just can't seem to piece together an answer. I have a data frame. For each row, I have values that I need to change to NA. It is not the same value that needs to be changed for every row. I want to change values to NA for each row based on a value that is in a specified column.

    mydata = as.data.frame(rbind(c("AA","CC","BB","DC","CC"),c("CC","CC","BB","DC","BB"),c("BB","BB","BB","DC","DC")))

    > mydata
      V1 V2 V3 V4 V5
    1 AA CC BB DC CC
    2 CC CC BB DC BB
    3 BB BB BB DC DC

    #for each row, replace values that match the value in column 5 with NA
    apply(mydata[,1:4], 1, function(x){
    x[x %in% x$V5]  = NA
    })

期望的输出

    > mydata
      V1 V2 V3 V4 V5
    1 AA NA BB DC CC
    2 CC CC NA DC BB
    3 BB BB BB NA DC

谢谢！

----更新----

使用下面来自 arvi1000 的代码非常适合将一行中的值与单列值进行比较.有没有办法做这样的事情，但将值与 2 列或更多列进行比较?

Using the code below from arvi1000 works great for comparing values in a row to a single column of values. Is there a way to do something like this but comparing the values to 2 or more columns?

当前代码

    mydata[,1:4][mydata[,1:4]==mydata[,5]] <- NA

假设我还有第 6 列.按行，我想将不等于第 5 列或第 6 列中的值的值更改为 NA.

Let's say I also have a column 6. By row, I want to change values that do not equal values in columns 5 or 6 to NA.

    mydata = as.data.frame(rbind(c("AA","CC","BB","DC","CC","AA"),c("CC","CC","BB","DC","BB","CC"),c("BB","BB","BB","DC","DC","BB")),stringsAsFactors=F)

    > mydata
      V1 V2 V3 V4 V5 V6
    1 AA CC BB DC CC AA
    2 CC CC BB DC BB CC
    3 BB BB BB DC DC BB

期望的输出

    > mydata
      V1 V2 V3 V4 V5 V6
    1 AA CC NA NA CC AA
    2 CC CC BB NA BB CC
    3 BB BB BB DC DC BB

我尝试这样做，但收到错误

I tried to do this, but received an error

 mydata[,1:4][mydata[,1:4]==mydata[,5]|mydata[,6]] <- NA
    Error in mydata[, 1:4] == mydata[, 5] | mydata[, 6] : 
      operations are possible only for numeric, logical or complex types

推荐答案

将 stringsAsFactors=F 添加到 as.data.frame.这是关键，因为 'CC'!='CC' 当它们是不同级别的不同因素时.

Add stringsAsFactors=F to as.data.frame. This is key because 'CC'!='CC' when they are different levels of different factors.

mydata = as.data.frame(rbind(c("AA","CC","BB","DC","CC"),c("CC","CC","BB","DC","BB"),c("BB","BB","BB","DC","DC")),
                       stringsAsFactors=F)

那么:

mydata[,1:4][mydata[,1:4]==mydata[,5]] <- NA

瞧:

  V1   V2   V3   V4 V5
1 AA <NA>   BB   DC CC
2 CC   CC <NA>   DC BB
3 BB   BB   BB <NA> DC

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