numpy.argsort

numpy.argsort(a, axis=-1, kind='quicksort', order=None)[source]

Returns the indices that would sort an array.

Perform an indirect sort along the given axis using the algorithm specified by the kind keyword. It returns an array of indices of the same shape asa that index data along the given axis in sorted order.

Parameters:	a : array_like Array to sort. axis : int or None, optional Axis along which to sort. The default is -1 (the last axis). If None, the flattened array is used. kind : {‘quicksort’, ‘mergesort’, ‘heapsort’}, optional Sorting algorithm. order : list, optional When a is an array with fields defined, this argument specifies which fields to compare first, second, etc. Not all fields need be specified.
Returns:	index_array : ndarray, int Array of indices that sort a along the specified axis. In other words, a[index_array] yields a sorted a.

See also

sort

Describes sorting algorithms used.

lexsort

Indirect stable sort with multiple keys.

ndarray.sort

Inplace sort.

argpartition

Indirect partial sort.

Notes

See sort for notes on the different sorting algorithms.

As of NumPy 1.4.0 argsort works with real/complex arrays containing nan values. The enhanced sort order is documented in sort.

Examples

One dimensional array:

>>>

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

>>> np.argsort(x)

array([1, 2, 0])

Two-dimensional array:

>>>

>>> x = np.array([[0, 3], [2, 2]])

>>> x

array([[0, 3],

       [2, 2]])

>>>

>>> np.argsort(x, axis=0)

array([[0, 1],

       [1, 0]])

>>>

>>> np.argsort(x, axis=1)

array([[0, 1],

       [0, 1]])

Sorting with keys:

>>>

>>> x = np.array([(1, 0), (0, 1)], dtype=[('x', '<i4'), ('y', '<i4')])

>>> x

array([(1, 0), (0, 1)],

      dtype=[('x', '<i4'), ('y', '<i4')])

>>>

>>> np.argsort(x, order=('x','y'))

array([1, 0])

>>>

>>> np.argsort(x, order=('y','x'))

array([0, 1])