根据 R 中具有特定顺序的向量对 DataFrame 行进行排序

在本文中，我们将看到如何根据具有特定顺序的向量的值对数据框行进行排序。有两个函数可以根据向量的值对数据框行进行排序。

• 匹配（）函数
• left_join()函数

示例数据集：

data <- data.frame(x1 = 1:5,               
                  x2 = letters[1:5],
                  x3 = 6:10)
                                                     
data
  x1 x2 x3
1  1  a  6
2  2  b  7
3  3  c  8
4  4  d  9
5  5  e 10

具有特定顺序的向量：

vec <- c("b", "e", "a", "c", "d")               
vec                                           
# "b" "e" "a" "c" "d"

方法一：使用match()函数根据向量对数据帧进行排序。

Match 在其第二个参数中返回其第一个参数的（第一个）匹配项的位置向量。

Syntax: match(x, table, nomatch = NA_integer_, incomparables = NULL)

Parameters:

• X: Vector or NULL: the values to be matched. Long vectors are supported.
• table: vector or NULL: the values to be matched against. Long vectors are not supported.
• nomatch: the value to be returned in the case when no match is found. Note that it is coerced to integer.
• incomparables: A vector of values that cannot be matched. Any value in x matching a value in this vector is assigned the nomatch value. For historical reasons, FALSE is equivalent to NULL.

代码：

R

data <- data.frame(x1 = 1:5,               
                   x2 = letters[1:5],
                   x3 = 6:10)
vec <- c("b", "e", "a", "c", "d") 
  
new_dataset <- data[match(vec, data$x2), ]       
new_dataset

输出：

x1 x2 x3
2  2  b  7
5  5  e 10
1  1  a  6
3  3  c  8
4  4  d  9

正如我们从上面的输出中看到的，新的数据框是根据向量的值排序的。

方法二：使用dplyr包的left_join()函数：

首先，我们必须安装并加载 dplyr 包：现在我们可以使用 left_join() 方法根据向量上的值对数据框进行排序。

Syntax: left_join(x, y, by = NULL, copy = FALSE, suffix = c(“.x”, “.y”), …)

Parameters:

• x, y: tbls to join
• by: a character vector of variables to join by. If NULL, the default, *_join() will do a natural join, using all variables with common names across the two tables. A message lists the variables so that you can check they’re right (to suppress the message, simply explicitly list the variables that you want to join).
• copy: If x and y are not from the same data source, and copy is TRUE, then y will be copied into the same src as x. This allows you to join tables across srcs, but it is a potentially expensive operation so you must opt into it.
• suffix: If there are non-joined duplicate variables in x and y, these suffixes will be added to the output to disambiguate them. Should be a character vector of length 2.

代码：

电阻

install.packages("dplyr")                  
library("dplyr")
data <- data.frame(x1 = 1:5,               
                   x2 = letters[ 1 : 5] ,
                   x3 = 6:10)
  
vec <- c("b", "e", "a", "c", "d")  
  
new_dataset <- left_join(data.frame(x2 = vec),  
                     data,
                     by = "x2")
print(new_dataset)                                      

输出：

x2 x1 x3
1  b  2  7
2  e  5 10
3  a  1  6
4  c  3  8
5  d  4  9