Three functions in R that people often get confused are **sort**, **order**, and **rank**.

Here’s the difference between these functions:

**sort()**will sort a vector in ascending order**order()**will return the index of each element in a vector in sorted order**rank()**will assign a rank to each element in a vector (smallest = 1)

The following example shows how to use each of these functions in practice.

**Example: Use sort(), order(), & rank() with Vectors**

The following code shows how to use **sort()**, **order()**, and** rank()** functions with a vector with four values:

#create vector x <- c(0, 20, 10, 15) #sort vector sort(x) [1] 0 10 15 20 #order vector order(x) [1] 1 3 4 2 #rank vector rank(x) [1] 1 4 2 3

Here’s what each function did:

**1.** The **sort()** function simply sorted the values in the vector in ascending order.

**2.** The **order()** function returned the index of each element in sorted order.

- If you put the values from the original vector in order based on these index values, you’ll end up with a sorted vector.
- For example, order() tells us to put the value in index position
**1**first – this is 0 in the original vector. - Then order() tells us to put the value in index position
**3**next – this is 10 in the original vector. - Then order() tells us to put the value in index position
**4**next – this is 15 in the original vector. - Then order() tells us to put the value in index position
**2**next – this is 20 in the original vector. - The end result is a sorted vector – 0, 10, 15, 20.

**3.** The **rank()** function assigned a rank to each element in the vector, using 1 for the smallest value.

- For example, rank() tells us that the first value in the original vector is the smallest (rank = 1) and the second value in the original vector is the largest (rank = 4)

Note that we can use the following syntax to use **sort()**, **order()**, and r**ank()** in reverse order:

#create vector x <- c(0, 20, 10, 15) #sort vector in decreasing order sort(x, decreasing=TRUE) [1] 20 15 10 0 #order vector in decreasing order order(x, decreasing=TRUE) [1] 2 4 3 1 #rank vector in reverse order (largest value = 1) rank(-x) [1] 4 1 3 2

Notice that these results are the exact opposite of the ones produced in the previous examples.

**Note: How to Handle Ties with rank() Function**

We can use the **ties.method** argument to specify how we should handle ties when using the** rank()** function:

rank(x, ties.method='average')

You can use one of the following options to specify how to handle ties:

**average**: (Default) Assigns each tied element to the average rank (elements ranked in the 3rd and 4th position would both receive a rank of 3.5)**first**: Assigns the first tied element to the lowest rank (elements ranked in the 3rd and 4th positions would receive ranks 3 and 4 respectively)**min**: Assigns every tied element to the lowest rank (elements ranked in the 3rd and 4th position would both receive a rank of 3)**max**: Assigns every tied element to the highest rank (elements ranked in the 3rd and 4th position would both receive a rank of 4)**random**: Assigns every tied element to a random rank (either element tied for the 3rd and 4th position could receive either rank)

Depending on your scenario, one of these methods might make more sense to use than the others.

**Additional Resources**

The following tutorials explain how to perform other common operations in R:

How to Sort by Multiple Columns in R

How to Sort a Data Frame by Date in R

How to Calculate Percentile Rank in R