我可以访问 apply() 中使用的函数的行索引吗

Can I access the row index for a function used in apply()

我们需要填写一个class化验数据table。我倾向于写太多 for 循环,我正在尝试弄清楚如何使用 apply() 来完成它。我正在扫描最后一列以查找非缺失值,然后在每一列中填写其上方的值,仅在对角线上。因此,如果有 3 列,这将填充最后一列的值。我会为每个 'higher taxonomic level' 或左边的下一列重复它:

# fills in for Family-level taxonomy
for(i in nrows(DataFrame)){  
  if(is.na(DataFrame[[4]][i])) next
    else {
      DataFrame[[3]][i] <- DataFrame[[3]][i-1]
      DataFrame[[2]][i] <- DataFrame[[2]][i-2]
      DataFrame[[1]][i] <- DataFrame[[1]][i-3]
     }
}

# Repeat to fill in Order's higher taxonomy (Phylum and Class)
for(i in nrows(DataFrame)){  # fills in for Family
  if(is.na(DataFrame[[3]][i])) next
    else {
      DataFrame[[2]][i] <- DataFrame[[2]][i-2]
      DataFrame[[1]][i] <- DataFrame[[1]][i-3]
     }
}
# And again for each column to the left.

数据可能如下所示:

Phylum     Class       Order        Family  
Annelida   
           Polychaeta  
                       Eunicida
                                    Oenoidae
                                    Onuphidae     
                       Oweniida
                                    Oweniidae

然后将针对该订单中的每个独特家族、Class 中的每个独特订单以及 Phylum 中的每个独特 Class 重复此操作。本质上,我们需要从其上方的下一个非缺失值开始,将值填充到每个非缺失值的左侧。所以最终结果将是:

Phylum     Class       Order    Family  
Annelida   
Annelida  Polychaeta  
Annelida  Polychaeta  Eunicida
Annelida  Polychaeta  Eunicida Oenoidae
Annelida  Polychaeta  Eunicida Onuphidae     
Annelida  Polychaeta  Oweniida
Annelida  Polychaeta  Oweniida Oweniidae

我们不能只复制列,因为一旦我们到达新的门级别,复制 class 停止有一个缺失值,顺序可能有两个缺失值,等等...
我想挑战在于我需要 Dataframe[[ j ]][ i-n ] 在我将传递给应用的任何函数中的值。当 apply 将 'x' 传递给函数时,它传递的是具有属性(如 index/row 名称)的对象还是仅传递值?

或者这是一个浪费的思路,如果我真的需要速度,请使用 for 循环并使用 rcpp。这是每年完成的数据框,我们将对其进行操作约 8,000 行和 13 列。我认为性能不会成为问题……但我们还没有尝试过。不知道为什么。

这是一种方法:

x <- matrix(rnorm(100), 10,10)
x <- cbind(1:nrow(x), x)

output <- apply(x, 1, function(i) {
  rowID <- as.numeric(i[1])
  x_orig <- unlist(i[-1])
  ## ... do some more stuff
  return(...something...)
})

这是我的方法,只要你的数据看起来像我猜的那样:

library(tidyr)
library(dplyr)
data[data == ""] <- NA
data %>% fill(-Family) %>%
         filter(!is.na(Family)) 

输出:

    Phylum      Class    Order    Family
1 Annelida Polychaeta Eunicida  Oenoidae
2 Annelida Polychaeta Eunicida Onuphidae
3 Annelida Polychaeta Oweniida Oweniidae

如果你想要空行,你可以试试这个,它允许任意嵌套和取消嵌套:

data %>% fill(-Family) %>%
  filter(!is.na(Family)) %>%
  do(plyr::rbind.fill(unlist(lapply(1:nrow(.), function(z) lapply(1:4, function(xx) .[z,][1:xx])), recursive = FALSE))) %>%
  distinct()

     Phylum      Class    Order    Family
1  Annelida       <NA>     <NA>      <NA>
2  Annelida Polychaeta     <NA>      <NA>
3  Annelida Polychaeta Eunicida      <NA>
4  Annelida Polychaeta Eunicida  Oenoidae
5  Annelida Polychaeta Eunicida Onuphidae
6  Annelida Polychaeta Oweniida      <NA>
7  Annelida Polychaeta Oweniida Oweniidae
8  Annelida       blah     <NA>      <NA>
9  Annelida       blah     blah      <NA>
10 Annelida       blah     blah      blah

数据输入:

structure(list(Phylum = c("Annelida", NA, NA, NA, NA, NA, NA, 
NA, NA, NA), Class = c(NA, "Polychaeta", NA, NA, NA, NA, NA, 
"blah", NA, NA), Order = c(NA, NA, "Eunicida", NA, NA, "Oweniida", 
NA, NA, "blah", NA), Family = c(NA, NA, NA, "Oenoidae", "Onuphidae", 
NA, "Oweniidae", NA, NA, "blah")), .Names = c("Phylum", "Class", 
"Order", "Family"), row.names = c(NA, -10L), class = "data.frame")

作为其他解决方案的替代方案,您还可以使用 zoo 包中的 na.locf 函数,它将 NA 值替换为最后一次观察值(locf = 上次观察结转).

# replace empty spaces with NA values
df[df == ""] <- NA

# use na.locf to replace the NA values    
library(zoo)
df <- na.locf(df)

这导致:

> df
    Phylum      Class    Order    Family
1 Annelida       <NA>     <NA>      <NA>
2 Annelida Polychaeta     <NA>      <NA>
3 Annelida Polychaeta Eunicida      <NA>
4 Annelida Polychaeta Eunicida  Oenoidae
5 Annelida Polychaeta Eunicida Onuphidae
6 Annelida Polychaeta Oweniida Onuphidae
7 Annelida Polychaeta Oweniida Oweniidae

已用数据:

df <- structure(list(Phylum = structure(c(2L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("", "Annelida"), class = "factor"), 
                     Class = structure(c(1L, 2L, 1L, 1L, 1L, 1L, 1L), .Label = c("", "Polychaeta"), class = "factor"), 
                     Order = structure(c(1L, 1L, 2L, 1L, 1L, 3L, 1L), .Label = c("", "Eunicida", "Oweniida"), class = "factor"), 
                     Family = structure(c(1L, 1L, 1L, 2L, 3L, 1L, 4L), .Label = c("", "Oenoidae", "Onuphidae", "Oweniidae"), class = "factor")), 
                .Names = c("Phylum", "Class", "Order", "Family"), class = "data.frame", row.names = c(NA, -7L))