This is documentation for an old release of NumPy (version 1.16). Read this page Search for this page in the documentation of the latest stable release (version 2.2).

Sorting, searching, and counting

Sorting

sort(a[, axis, kind, order])	Return a sorted copy of an array.
lexsort(keys[, axis])	Perform an indirect stable sort using a sequence of keys.
argsort(a[, axis, kind, order])	Returns the indices that would sort an array.
ndarray.sort([axis, kind, order])	Sort an array, in-place.
msort(a)	Return a copy of an array sorted along the first axis.
sort_complex(a)	Sort a complex array using the real part first, then the imaginary part.
partition(a, kth[, axis, kind, order])	Return a partitioned copy of an array.
argpartition(a, kth[, axis, kind, order])	Perform an indirect partition along the given axis using the algorithm specified by the kind keyword.

Searching

argmax(a[, axis, out])	Returns the indices of the maximum values along an axis.
nanargmax(a[, axis])	Return the indices of the maximum values in the specified axis ignoring NaNs.
argmin(a[, axis, out])	Returns the indices of the minimum values along an axis.
nanargmin(a[, axis])	Return the indices of the minimum values in the specified axis ignoring NaNs.
argwhere(a)	Find the indices of array elements that are non-zero, grouped by element.
nonzero(a)	Return the indices of the elements that are non-zero.
flatnonzero(a)	Return indices that are non-zero in the flattened version of a.
where(condition, [x, y])	Return elements chosen from x or y depending on condition.
searchsorted(a, v[, side, sorter])	Find indices where elements should be inserted to maintain order.
extract(condition, arr)	Return the elements of an array that satisfy some condition.

Counting

count_nonzero(a[, axis])

Counts the number of non-zero values in the array a.