Order DataFrame rows according to vector with specific order in R
Last Updated :
26 Mar, 2021
In this article, we will see how to sort data frame rows based on the values of a vector with a specific order. There are two functions by which we can sort data frame rows based on the values of a vector.
- match() function
- left_join() function
Example dataset:
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
Vector with specific ordering:
vec <- c("b", "e", "a", "c", "d")
vec
# "b" "e" "a" "c" "d"
Method 1: Using match() function to Sort Data Frame According to Vector.
Match returns a vector of the positions of (first) matches of its first argument in its second.
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.
Code:
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
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Output:
x1 x2 x3
2 2 b 7
5 5 e 10
1 1 a 6
3 3 c 8
4 4 d 9
As we can see from the above output the new data frame is sorted based on the values of the vector.
Method 2: Using left_join() Function of dplyr Package:
First, we have to install and load the dplyr package: now we can use left_join() method to sort the data frame based on the values on the vector.
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.
Code:
R
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)
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Output:
x2 x1 x3
1 b 2 7
2 e 5 10
3 a 1 6
4 c 3 8
5 d 4 9
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