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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.

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