1.6.230. numpy.rank¶

numpy.rank(a)[source]¶

Return the number of dimensions of an array.

If a is not already an array, a conversion is attempted. Scalars are zero dimensional.

Note

This function is deprecated in NumPy 1.9 to avoid confusion with numpy.linalg.matrix_rank. The ndim attribute or function should be used instead.

Parameters:

a : array_like

Array whose number of dimensions is desired. If a is not an array, a conversion is attempted.

Returns:

number_of_dimensions : int

The number of dimensions in the array.

See also

Notes

In the old Numeric package, rank was the term used for the number of dimensions, but in Numpy ndim is used instead.

Examples

>>> np.rank([1,2,3])
1
>>> np.rank(np.array([[1,2,3],[4,5,6]]))
2
>>> np.rank(1)
0