从R中的行向量中提取n个值

Question

我一直在寻找/思考如何提取第n个值(例如，第2、第5、第7等)。从我的数据帧中的每一行。

例如，我有以下列：

ID   Q1-2013   Q2-2013   Q3-2013  Q4-2013  Q1-2014   Q2-2014   Q3-2014  Q4-2014

在每一列下都有给定的值。我想要做的是从季度向量(第二-第八列)中提取每一行的第n个值。因此，例如，如果我从每一行中寻找第二个值，我想要的公式/函数将从第2-8列(第1-2013年到第4-2014年)中从每一行中提取/拉出第二个值。此外，公式/函数也将忽略每行中的空白/NA值。

Answer 1

也许这就是你想要的。

我首先在每一列中使用一些NAs修改了虹膜数据集：

iris[] <- lapply(iris, function(x){ x[sample(150, 30, F)] <- NA; x})
head(iris)
#  Sepal.Length Sepal.Width Petal.Length Petal.Width Species
#1          5.1         3.5          1.4          NA  setosa
#2           NA          NA          1.4          NA  setosa
#3           NA          NA          1.3         0.2  setosa
#4          4.6         3.1          1.5          NA  setosa
#5          5.0         3.6          1.4         0.2  setosa
#6          5.4          NA          1.7         0.4  setosa

然后，要提取每个行可以使用的第二个非空项和非NA项，可以使用apply (我知道，不建议在数据帧上使用，但它会执行脏的工作)：

apply(iris, 1, function(x) x[which(!is.na(x) & x != "")[2]])
#  [1] "3.5"       "setosa"    "0.2"       "3.1"       "3.6"       "1.7"       "3.4"       "3.4"       "2.9"       "3.1"       "setosa"   
 #[12] "3.4"       "1.4"       "1.1"       "1.2"       "4.4"       "3.9"       "3.5"       "3.8"       "3.8"       "0.2"       "3.7"      
 #[23] "3.6"       "1.7"       "1.9"       "3.0"       "3.4"       "1.5"       "3.4"       "3.2"       "3.1"       "3.4"       "4.1"      
 #[34] "4.2"       "3.1"       "3.2"       "3.5"       "3.6"       "setosa"    "1.5"       "1.3"       "2.3"       "1.3"       "0.6"      
 #[45] "0.4"       "3.0"       "3.8"       "3.2"       "3.7"       "3.3"       "3.2"       "3.2"       "1.5"       "2.3"       "2.8"      
 #[56] "2.8"       "3.3"       "2.4"       "4.6"       "1.4"       "2.0"       "3.0"       "1.0"       "2.9"       "2.9"       "3.1"      
 #[67] "3.0"       "2.7"       "4.5"       "3.9"       "3.2"       "4.0"       "2.5"       "4.7"       "4.3"       "3.0"       "2.8"      
 #[78] "5.0"       "2.9"       "3.5"       "3.8"       "2.4"       "2.7"       "2.7"       "3.0"       "3.4"       "3.1"       "1.3"      
 #[89] "4.1"       "1.3"       "2.6"       "3.0"       "2.6"       "2.3"       "4.2"       "3.0"       "2.9"       "2.9"       "2.5"      
#[100] "2.8"       "3.3"       "2.7"       "3.0"       "2.9"       "3.0"       "3.0"       "4.5"       "2.9"       "5.8"       "3.6"      
#[111] "3.2"       "1.9"       "5.5"       "2.0"       "5.1"       "3.2"       "5.5"       "3.8"       "virginica" "1.5"       "3.2"      
#[122] "2.8"       "2.8"       "2.7"       "2.1"       "6.0"       "2.8"       "3.0"       "2.8"       "5.8"       "2.8"       "3.8"      
#[133] "5.6"       "1.5"       "2.6"       "3.0"       "5.6"       "5.5"       "4.8"       "3.1"       "5.6"       "5.1"       "2.7"      
#[144] "3.2"       "3.3"       "3.0"       "2.5"       "5.2"       "5.4"       "3.0"      

因为apply将首先将数据帧转换为matrix，所以所有列都被转换为与本例中的character相同的类型。稍后，您可以将其转换为您想要的任何内容(但请注意，在本例中，不能将输出向量直接转换为数字，因为它包含一些字符串，如"setosa“等)。

Answer 2

您还可以使用来自convenient的naLast函数library(SOfun)。

library(SOfun)
dat[dat==''] <- NA #convert all `blank` cells to `NA`
n <- 2 # the row/column index that needs to be extracted
naLast(dat, by='col')[n,] #get the 2nd non-empty/nonNA element for each columns
#V1  V2  V3  V4  V5 
#"G" "B" "B" "B" "C" 

apply的情况也是一样

 apply(dat, 2, function(x) x[which(!is.na(x) & x!='')[2]])
 #V1  V2  V3  V4  V5 
 #"G" "B" "B" "B" "C" 

您还可以指定by='row'

naLast(dat, by='row')[,n] #get the 2nd non-empty/nonNA element for each row
#  1   2   3   4   5   6   7   8   9  10  11  12  13  14  15  16  17  18  19  20 
#"G" "D" "B" "G" "E" "B" "J" "F" "F" "A" "H" "C" "A" "D" "H" "D" "J" "C" "A" "A" 

数据

set.seed(25)
dat <- as.data.frame(matrix(sample(c(NA,'',LETTERS[1:10]), 
        20*5, replace=TRUE), ncol=5), stringsAsFactors=FALSE)

您可以通过以下方式安装该软件包

 library(devtools)
 install_github("mrdwab/SOfun")