英文:
Reverse the order of non-NA values in an r dataframe
问题
I am looking to reverse the order of numeric values in multiple columns of an R dataframe (so that the highest number becomes the lowest, and so forth), whilst leaving the NA values as they are.
An example of my dataframe:
my_data <- data.frame (animal = c("fox", "rabbit", "cow", "sheep", "pig", "mole"),x = c("1", "2", "1", "3", "NA", 'NA'),y = c('NA','NA','1','3','2','NA'),z = c('1','2','3','4','NA','5'),area = c("field","field","farm","farm","farm","farm"))
and then, what I am trying to achieve:
my_ideal_data <- data.frame (animal = c("fox", "rabbit", "cow", "sheep", "pig", "mole"),x = c("3", "2", "3", "1", "NA", 'NA'),y = c('NA','NA','3','1','2','NA'),z = c('5','4','3','2','NA','1'),area = c("field","field","farm","farm","farm","farm"))
The 'animal' and 'area' column remain the same, as do all of the NAs - but I need the values in x, y, and z to be placed in reverse order for each of the columns.
Any help would be greatly appreciated!
Thank you
英文:
I am looking to reverse the order of numeric values in multiple columns of an R dataframe (so that the highest number becomes the lowest, and so forth), whilst leaving the NA values as they are.
An example of my dataframe:
my_data <- data.frame (animal = c("fox", "rabbit", "cow", "sheep", "pig", "mole"),x = c("1", "2", "1", "3", "NA", 'NA'),y = c('NA','NA','1','3','2','NA'),z = c('1','2','3','4','NA','5'),area = c("field","field","farm","farm","farm","farm"))
and then, what I am trying to achieve:
my_ideal_data <- data.frame (animal = c("fox", "rabbit", "cow", "sheep", "pig", "mole"),x = c("3", "2", "3", "1", "NA", 'NA'),y = c('NA','NA','3','1','2','NA'),z = c('5','4','3','2','NA','1'),area = c("field","field","farm","farm","farm","farm"))
The 'animal' and 'area' column remain the same, as do all of the NAs - but I need the values in x, y and z to be placed in reverse order for each of the columns.
Any help would be greatly appreciated!
Thank you
答案1
得分: 1
以下是您要翻译的内容：
在这些数据中，您可以在转换为数值后，简单地从z列中减去6：
my_data$z <- 6 - as.numeric(my_data$z)# > my_data# animal x y z area#1 fox 3 NA 5 field#2 rabbit 2 NA 4 field#3 cow 3 3 3 farm#4 sheep 1 1 2 farm#5 pig NA 2 NA farm#6 mole NA NA 1 farm
如果这些示例数据过于简化，另一种方法是使用grep索引非NA值，然后使用gtools::mixedsort()按降序值排序，然后使用索引替换这些值。这可能会更具可扩展性，而且您不必转换为数值。
idx <- grep("\\d+", my_data$z)vals <- gtools::mixedsort(my_data$z[idx], decreasing = TRUE)my_data$z[idx] <- vals# animal x y z area#1 fox 3 NA 5 field#2 rabbit 2 NA 4 field#3 cow 3 3 3 farm#4 sheep 1 1 2 farm#5 pig NA 2 NA farm#6 mole NA NA 1 farm
如果您想将其应用于多列，您可以使用lapply包装它，形成一个函数：
myfun <- function(x){a <- grep("\\d+", x)x[a] <- gtools::mixedsort(x[a], decreasing = TRUE)x}my_data[c("x", "y", "z")] <- lapply(my_data[c("x", "y", "z")], myfun)
英文:
In these data, you could simply subtract 6 from the z column after converting to numeric:
my_data$z <- 6 - as.numeric(my_data$z)#> my_data# animal x y z area#1 fox 3 NA 5 field#2 rabbit 2 NA 4 field#3 cow 3 3 3 farm#4 sheep 1 1 2 farm#5 pig NA 2 NA farm#6 mole NA NA 1 farm
An alternative if these sample data are too simplified would be to index the non-NA values using grep, then sort by decreasing value using gtools::mixedsort(), then replace those values using [indexing]. This might be a little more scalable, and you dont have to convert to numeric.
idx <- grep("\\d+", my_data$z)vals <- gtools::mixedsort(my_data$z[idx], decreasing = TRUE)my_data$z[idx] <- vals# animal x y z area#1 fox 3 NA 5 field#2 rabbit 2 NA 4 field#3 cow 3 3 3 farm#4 sheep 1 1 2 farm#5 pig NA 2 NA farm#6 mole NA NA 1 farm
If you wanted to apply it to multiple columns, you could wrap it in a functioning use lapply:
myfun <- function(x){a <- grep("\\d+", x)x[a] <- gtools::mixedsort(x[a], decreasing = TRUE)x}my_data[c("x", "y", "z")] <- lapply(my_data[c("x", "y", "z")], myfun)
答案2
得分: 1
你可以在这里使用一个for循环。
首先将所有的"NA"字符替换为实际的NA。
my_data[my_data == "NA"] <- NA
然后定义一个包含你想要排序的列的向量。
target_col <- c("x", "y", "z")
然后使用for循环遍历目标列，并通过减去max值+ 1来进行替换。
my_data[my_data == "NA"] <- NAtarget_col <- c("x", "y", "z")for (i in target_col) {my_data[!is.na(my_data[,i]),i] <- as.integer(max(my_data[,i], na.rm = T)) + 1 - as.integer(my_data[!is.na(my_data[,i]),i])}
animal x y z area1 fox 3 <NA> 5 field2 rabbit 2 <NA> 4 field3 cow 3 3 3 farm4 sheep 1 1 2 farm5 pig <NA> 2 <NA> farm6 mole <NA> <NA> 1 farm
英文:
You might use a for loop here.
First replace all "NA" characters into real NA.
my_data[my_data == "NA"] <- NA
Then define a vector containing the columns that you want to sort.
target_col <- c("x", "y", "z")
And use a for loop to go over the target columns and perform replacement by deducting the column values by the max values + 1.
my_data[my_data == "NA"] <- NAtarget_col <- c("x", "y", "z")for (i in target_col) {my_data[!is.na(my_data[,i]),i] <- as.integer(max(my_data[,i], na.rm = T)) + 1 - as.integer(my_data[!is.na(my_data[,i]),i])}animal x y z area1 fox 3 <NA> 5 field2 rabbit 2 <NA> 4 field3 cow 3 3 3 farm4 sheep 1 1 2 farm5 pig <NA> 2 <NA> farm6 mole <NA> <NA> 1 farm
答案3
得分: 0
使用dplyr和across函数：
library(dplyr)Cols <- c("x", "y", "z")my_data[,Cols] <- Vectorize(\(x) as.numeric(x))(my_data[,Cols])my_data %>%mutate(across(!!Cols, ~ max(.x[!is.na(.x)]) - .x + 1))
动物 x y z 区域
1 狐狸 3 NA 5 田地
2 兔子 2 NA 4 田地
3 牛 3 3 3 农场
4 羊 1 1 2 农场
5 猪 NA 2 NA 农场
6 鼹鼠 NA NA 1 农场
<details><summary>英文:</summary>With `dplyr` using `across`
library(dplyr)
Cols <- c("x", "y", "z")
my_data[,Cols] <- Vectorize((x) as.numeric(x))(my_data[,Cols])
my_data %>%
mutate(across(!!Cols, ~ max(.x[!is.na(.x)]) - .x + 1))
animal x y z area
1 fox 3 NA 5 field
2 rabbit 2 NA 4 field
3 cow 3 3 3 farm
4 sheep 1 1 2 farm
5 pig NA 2 NA farm
6 mole NA NA 1 farm
</details>
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