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.


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

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

    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)

    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))

    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.

See Also

cummax, eigmax, findmax, hist, hist!, hist2d, hist2d!, histrange, indmax, maxabs, maxabs!, maximum!, mean, mean!, median, median!, minabs, minabs!, minimum!, minmax, quantile!, realmax, std, stdm,

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