Divide data into groups in R » Data Science Tutorials

Divide data into groups in R, we will learn how to use the split and unsplit functions in R to divide and reassemble vectors into groups.

These functions are useful when you need to separate a large dataset into smaller groups based on specific criteria and then reassemble the data back into a single vector.

Definitions and Basic R Syntaxes

The split function divides data into groups, while the unsplit function reverses the output of the split function. The basic R syntaxes for these functions are:

split(values, groups)
unsplit(split_values, groups)

Creation of Example Data

We will create an example vector and a grouping vector to demonstrate the use of the split and unsplit functions.

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vec <- 1:10
vec
# 1  2  3  4  5  6  7  8  9 10

groups <- c(rep("A", 3), rep("B", 5), rep("C", 2))
groups
# "A" "A" "A" "B" "B" "B" "B" "B" "C" "C"

Example 1: Using split() Function in R

In this example, we will use the split function to divide our example data into three groups based on the grouping vector.

my_split <- split(vec, groups)
my_split
# $A
# [1] 1 2 3
# 
# $B
# [1] 4 5 6 7 8
# 
# $C
# [1] 9 10

As you can see, the split function created a list called my_split, which contains three list elements, each representing a group.

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Example 2: Using unsplit() Function in R

In this example, we will use the unsplit function to reassemble the data back into a single vector.

my_unsplit <- unsplit(my_split, groups)
my_unsplit
# [1] 1 2 3 4 5 6 7 8 9 10

As you can see, the unsplit function successfully reassembled the data back into a single vector.

Conclusion

In this tutorial, we have learned how to use the split and unsplit functions in R to divide and reassemble vectors into groups.

We have demonstrated how to use these functions to separate a large dataset into smaller groups based on specific criteria and then reassemble the data back into a single vector.

With these functions, you can easily manipulate and analyze large datasets in R.