# WRAPCOLS

Formulas / WRAPCOLS
Wrap an array into columns.
`WRAPCOLS(vector, wrap_count, [pad_with])`
• vector - required, array or range to wrap
• wrap_count - required, length of each column

## Examples

• `=WRAPCOLS(C2:J2,4)`

This formula wraps the range C2:J2 into columns that each contain the value 4. This means that the values of each cell in the range C2:J2 will be split into four columns, and each column will contain the same value as the original cells in the range.

• `=WRAPCOLS(B3:B14,4)`

This wraps the range B3:B14 into four columns that each contain values. This means that the values of each cell in the range B3:B14 will be split into four columns, and each column will contain different values from the original cells in the range.

• `=WRAPCOLS(B3:B12,4,"x")`

This formula wraps the range B3:B12 into columns that each contain 4 values, and pads each column with "x". This means that the values of each cell in the range B3:B12 will be split into four columns, and each column will contain four values, with any empty cells in the original range filled with the character "x".

## Summary

The WRAPCOLS function divides a row or column of values into an array and returns the result. It requires three arguments: vector, wrap_count, and pad_with. WRAPCOLS will return an error if the vector is not a one-dimensional array.

• The WRAPCOLS function takes a one-dimensional array and wraps it into a two-dimensional array with a specified number of columns.
• The length of each column is determined by the wrap_count argument.

What is the WRAPCOLS Function?
The WRAPCOLS function is a programming command used to wrap a row or column of values into a new array.
What does the WRAPCOLS Function Return?
The WRAPCOLS function returns the wrapped array.
What are the Benefits of Using the WRAPCOLS Function?
• It allows for easy manipulation of data.
• It can help reduce the amount of code needed for a task.
• It simplifies complex computations.
What are the Limitations of the WRAPCOLS Function?
• It is limited to wrapping data in a single row or column.
• It may not be suitable for large datasets.
• It is not compatible with all programming languages. 