median

median(v[, region])

Compute the median of whole array `v`, or optionally along the dimensions in `region`. For even number of elements no exact median element exists, so the result is equivalent to calculating mean of two median elements. `NaN` is returned if the data contains any `NaN` values. For applications requiring the handling of missing data, the `DataArrays` package is recommended.

Examples

``````julia> xsum = rand(5)
median(xsum)
0.6850542627340954``````
``````julia> A = rand(3)
3-element Array{Float64,1}:
0.722853
0.606612
0.846898
julia> median(A)
0.6557513931743997``````
1. Calculate the median of a 1D array:

``````julia> arr = [5, 10, 15, 20, 25];
julia> median(arr)
15.0``````

This example calculates the median of the array `arr`.

2. Calculate the median along a specific dimension:

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

It calculates the median along the first dimension (columns) of the matrix.

3. Handling arrays with NaN values:

``````julia> data = [3, 5, NaN, 7, 9];
julia> median(data)
NaN``````

If the array contains NaN values, the result will be NaN.

4. Calculate the median of a range of elements:
``````julia> arr = [10, 20, 30, 40, 50];
julia> median(view(arr, 2:4))
30.0``````

This example calculates the median of a range of elements using a view of the array.

Common mistake example:

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

In this example, an empty array is provided to the `median` function, which results in a `MethodError`. Make sure the array is not empty before calculating the median.