# reshape

reshape(A, dims)

Create an array with the same data as the given array, but with different dimensions. An implementation for a particular type of array may choose whether the data is copied or shared.

## Examples

1. Reshape a 1-dimensional array:

``````julia> arr = [1, 2, 3, 4, 5, 6];
julia> reshape(arr, (2, 3))
2×3 Matrix{Int64}:
1  3  5
2  4  6``````

This example reshapes the 1-dimensional array `arr` into a 2x3 matrix.

2. Reshape a multi-dimensional array:

``````julia> matrix = [1 2 3; 4 5 6; 7 8 9; 10 11 12];
julia> reshape(matrix, (2, 6))
2×6 Matrix{Int64}:
1  3  5  7   9  11
2  4  6  8  10  12``````

It reshapes the 2x3 matrix `matrix` into a 2x6 matrix.

3. Change the shape of a vector:
``````julia> vec = [1, 2, 3, 4, 5, 6];
julia> reshape(vec, (2, 3))
2×3 Matrix{Int64}:
1  3  5
2  4  6``````

This example reshapes the vector `vec` into a 2x3 matrix.

Common mistake example:

``````julia> arr = [1, 2, 3, 4, 5, 6];
julia> reshape(arr, (2, 4))
ERROR: DimensionMismatch("new dimensions (2, 4) must be consistent with array size 6")``````

In this example, the desired dimensions `(2, 4)` are not consistent with the size of the array `arr`. It's important to ensure that the total number of elements remains the same after reshaping.

## See Also

Array, broadcast, cat, combinations, conj!, digits!, fieldnames, fill, fill!, last, length, maximum, minimum, ones, parent, parentindexes, partitions, permutations, pointer, pointer_to_array, promote_shape, rand!, reshape, scale, similar, sum, sum_kbn, takebuf_array, transpose!, vec, zeros,

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