英文:
Is there an R function to mutate a dataframe and create a new dataframe based on the following conditions?
问题
我有一个类似以下的数据框：
1. 2. 3. 4. 5.
R1 NA 881. NA NA NA
R2 650 NA NA NA NA
R3 743 NA NA NA NA
dput：
structure(list(V1 = c(NA, 650L, 743L), V2 = c(881L, NA, NA), V3 = c(NA, NA, NA), V4 = c(NA, NA, NA), V5 = c(NA, NA, NA)), row.names = c(NA, -3L), class = "data.frame")
英文:
I have a dataframe similar to the following:
1. 2. 3. 4. 5.
R1 NA 881. 950 981. 1000
R2 650 760. 890. NA. NA
R3 743 834. 960. 1001. 1115
I want to mutate the dataframe and create a new dataframe that keeps only the minimum value of each row, all my unwanted values would return as NA, for an output of something like this:
1. 2. 3. 4. 5.
R1 NA 881 NA NA NA
R2 650 NA NA NA NA
R3 743 NA NA NA NA
dput:
structure(list(V1 = c(NA, 650L, 743L), V2 = c(881L, 760L, 834L
), V3 = c(950L, 890L, 960L), V4 = c(981L, NA, 1001L), V5 = c(1000L,
NA, 1115L)), row.names = c(NA, -3L), class = "data.frame")
答案1
得分: 1
在基础R中的解决方案：
t(apply(your_data, 1, \(v) { is.na(v) <- -which.min(v); return(v) }))
这使用了is.na<-赋值，根据索引设置NA值。-which.max(v) 除了第一个最小值之外的所有值。
结果：
V1 V2 V3 V4 V5
[1,] NA 881 NA NA NA
[2,] 650 NA NA NA NA
[3,] 743 NA NA NA NA
英文:
A solution in base R:
t(apply(your_data, 1, \(v) { is.na(v) <- -which.min(v); return(v) }))
This uses the is.na<- assigment, which sets NA values based on index. -which.max(v) everthing except the first minimum value.
Gives:
> V1 V2 V3 V4 V5
> [1,] NA 881 NA NA NA
> [2,] 650 NA NA NA NA
> [3,] 743 NA NA NA NA
答案2
得分: 1
df* NA^(col(df) != max.col(-replace(df, is.na(df), Inf)))
X1 NA 881 NA NA NA
X2 650 NA NA NA NA
X3 743 NA NA NA NA
t(apply(df, 1, (x) ifelse(x == min(x, na.rm = TRUE), x, NA)))
X1 NA 881 NA NA NA
X2 650 NA NA NA NA
X3 743 NA NA NA NA
英文:
df* NA^(col(df) != max.col(-replace(df, is.na(df), Inf)))
X1 X2 X3 X4 X5
R1 NA 881 NA NA NA
R2 650 NA NA NA NA
R3 743 NA NA NA NA
t(apply(df, 1, \(x) ifelse(x == min(x, na.rm = TRUE), x, NA)))
X1 X2 X3 X4 X5
R1 NA 881 NA NA NA
R2 650 NA NA NA NA
R3 743 NA NA NA NA
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