问将所有列与一列匹配的条件
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Stack Overflow用户

提问于 2019-07-03 12:10:08

回答 2查看 48关注 0票数 2

我有一个数据帧(df)，其中我希望将每一列与最后一列进行匹配，以便为每一列提供新值。

以下是我的示例数据帧(df)：

> df
              S1  S2  S3  S4  S5  main
Gene1         1   1   1   1   2   1
Gene2         1   2   1   1   1   1
Gene3         1   1   1   1   2   2
Gene4         2   1   1   1   1   1
Gene5         1   2   1   2   1   1
Gene6         1   1   1   1   1   2
Gene7        NA  NA   2   1   1   1
Gene8         1   2   1   1   1   2
Gene9         2   1   1   2   1   1

我希望将我的1到5列中的每一列与满足以下条件的最后一列进行匹配。下面的“%s”表示从1到5的每一列。

If S = 2 and main = 2, then value is True Positive (TP)
If S = 2 and main = 1, then value is False Positive (FP)
If S = 1 and main = 2, then value is False Negative (FN)
If S = 1 and main = 1, then value is True Negative (TN)
And NAs to remain as NAs.

因此，我的新数据框(df_updated)应该如下所示。

> df_updated
              S1  S2  S3  S4  S5
Gene1         TN  TN  TN  TN  FP
Gene2         TN  FP  TN  TN  TN
Gene3         FN  FN  FN  FN  TP
Gene4         FP  TN  TN  TN  TN
Gene5         TN  FP  TN  FP  TN
Gene6         FN  FN  FN  FN  FN
Gene7         NA  NA  FP  TN  TN
Gene8         FN  TP  FN  FN  FN
Gene9         FP  TN  TN  FP  TN

我知道match函数，但我不确定如何循环它们，并对每一列使用上述特定的匹配。

感谢您的帮助，谢谢。

dataframe

match

col

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回答 2

Stack Overflow用户

回答已采纳

发布于 2019-07-03 12:18:10

你可以使用dplyr的case_when

library(dplyr)

mutate_all(df, ~case_when(
           .x < main ~ "FN",
           .x > main ~ "FP",
           near(.x, 1) & near(.x, main) ~ "TN",
           near(.x, 2) & near(.x, main) ~ "TP"
           )) %>%
select(-main)
#>     S1   S2 S3 S4 S5
#> 1   TN   TN TN TN FP
#> 2   TN   FP TN TN TN
#> 3   FN   FN FN FN TP
#> 4   FP   TN TN TN TN
#> 5   TN   FP TN FP TN
#> 6   FN   FN FN FN FN
#> 7 <NA> <NA> FP TN TN
#> 8   FN   TP FN FN FN
#> 9   FP   TN TN FP TN

票数 3

Stack Overflow用户

发布于 2019-07-03 12:28:00

使用base R，您还可以创建一个嵌套了ifelse的函数，并将该函数应用于每一列并获取值。

get_value <- function(x,main) {
 ifelse(main == 2 & x == 2, "TP", 
      ifelse(main == 1 & x == 2, "FP", 
            ifelse(main == 2 & x == 1, "FN", 
                 ifelse(main == 1 & x == 1 ,"TN", NA))))
}

df1 <- df[-ncol(df)]
df1[] <- lapply(df1, get_value, df$main)   

df1
#        S1   S2 S3 S4 S5
#Gene1   TN   TN TN TN FP
#Gene2   TN   FP TN TN TN
#Gene3   FN   FN FN FN TP
#Gene4   FP   TN TN TN TN
#Gene5   TN   FP TN FP TN
#Gene6   FN   FN FN FN FN
#Gene7 <NA> <NA> FP TN TN
#Gene8   FN   TP FN FN FN
#Gene9   FP   TN TN FP TN