SciPy

Sorting, searching, and counting

Sorting

sort(a[, axis, kind, order]) Return a sorted copy of an array.
lexsort(keys[, axis]) Perform an indirect 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]) 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]) 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, either 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) Counts the number of non-zero values in the array a.