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# numpy.copy

`numpy.``copy`(a, order='K')

  Return an array copy of the given object.

  Parameters : | a : array_like Input data. order : {‘C’, ‘F’, ‘A’, ‘K’}, optional Controls the memory layout of the copy. ‘C’ means C-order, ‘F’ means F-order, ‘A’ means ‘F’ if a is Fortran contiguous, ‘C’ otherwise. ‘K’ means match the layout of a as closely as possible. (Note that this function and :meth:ndarray.copy are very similar, but have different default values for their order= arguments.)
  Returns : | arr : ndarray Array interpretation of a.

  Notes

  This is equivalent to

      >>> np.array(a, copy=True)

  Examples

  Create an array x, with a reference y and a copy z:

      >>> x = np.array([1, 2, 3])
      >>> y = x
      >>> z = np.copy(x)

  Note that, when we modify x, y changes, but not z:

      >>> x[0] = 10
      >>> x[0] == y[0]
      True
      >>> x[0] == z[0]
      False