The **`separate()` function** from the `tidyr` package can be used to separate a single data frame or table column into multiple columns. We can now separate out that information into multiple other columns, as shown below.
> The tidy data library `tidyr` is required for the `separate()` function.
# 
## Syntax
---
```
separate(
  data,
  col,
  into,
  sep = "[^[:alnum:]]+",
  remove = TRUE,
  convert = FALSE
)
```
---

## Parameters
It takes multiple parameters, as listed below:
* **`data`**: The frame of interest that is involved.
* **`column`**: A column that is to be separated.
* **`into`**: The names of columns that are used for the data to be separated.
* **`sep`**: This is the value to separate the data. default = `_[^[:alnum:]]+_`, regular expression.
* **`remove`**: If set to `TRUE`, remove input column(s) from the output data frame. Default = `TRUE`.
* **`convert`**: This is used for datatype conversions. Default = `FALSE`.


## Example
In the example below, we have a data frame containing customer name, age, and contact number with area code. Our goal is to use the `separate()` function to split the `Contact` column into two sub-columns, `Area Code` and `Phone`.


# Load library
library(tidyr)
#create data frame
df <- data.frame(Customer=c('Allen', 'Tolinton', 'Brusher', 'Dominique'),
                 Age=c(23, 25, 34, 29),
                 Contact=c('209-71953650312', '408-5182774863', '18-9564277497', '11-8946428747'))
# col= Contact a column which we want to separate
# Sinle column will be divided 
# into --> Area Code and Phone  
separate(df, col=Contact, into=c('Area Code', 'Phone'), sep='-')


What is the Separate() function in R?

The separate() function from the tidyr package splits a single data frame column into multiple columns based on specified parameters.