# mean

mean(v[, region])

Compute the mean of whole array `v`, or optionally along the dimensions in `region`. Note: Julia does not ignore `NaN` values in the computation. For applications requiring the handling of missing data, the `DataArray` package is recommended.

## Examples

``````julia> xsum = rand(5)
mean(xsum)
0.38190307541901564``````
``````julia> A = rand(3)
3-element Array{Float64,1}:
0.443922
0.79404
0.959896
julia> mean(A)
0.6369315513562785``````
1. Compute the mean of a 1-dimensional array:

``````julia> v = [1, 2, 3, 4, 5];
julia> mean(v)
3.0``````

This example calculates the mean of the array `v`, which is 3.0.

2. Compute the mean along a specific dimension of a multi-dimensional array:

``````julia> A = [1 2 3; 4 5 6; 7 8 9];
julia> mean(A, dims = 1)
1×3 Array{Float64,2}:
4.0  5.0  6.0``````

Here, the `mean` function is used to calculate the mean along the first dimension (columns) of the 2-dimensional array `A`. The result is a 1x3 array with the means of each column.

3. Compute the mean along multiple dimensions:
``````julia> B = [1 2 3; 4 5 6; 7 8 9; 10 11 12];
julia> mean(B, dims = (1, 2))
1-element Array{Float64,1}:
6.5``````

In this example, the `mean` function calculates the mean along both dimensions of the 2-dimensional array `B`. The result is a 1-element array with the overall mean of the array.

Common mistake example:

``````julia> v = []
julia> mean(v)
ERROR: MethodError: no method matching mean(::Array{Any,1})``````

Here, an empty array `v` is provided to the `mean` function, which results in a `MethodError` because Julia cannot determine the appropriate method to use. Make sure to provide a non-empty array to calculate the mean accurately.