/NumPy 1.17

# 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`.