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, keepdims])

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

numpy.union1d numpy.sort