Numpy

numpy_sort_search2.py

## Searching

import numpy as np

## 1. argmax()
a = np.arange(6).reshape(2,3)
print(a)

#[Output]:
#[[0 1 2]
# [3 4 5]]

## argsort() for flattened array
np.argmax(a)

#[Output]:
#5

## agrsort() along first axis
np.argmax(a, axis=0)

#[Output]:
#array([1, 1, 1], dtype=int64)


## 2. argwhere()
## It is returning the indices of elements which are satisfying the condition.
np.argwhere(a>=2)

#[Output]:
#array([[0, 2],
#       [1, 0],
#       [1, 1],
#       [1, 2]], dtype=int64)

## Counting
## count_nonzero()
np.count_nonzero(np.array([[0,1],[1,1],[2,0]]))

#[Output]:
#[[0 1]
# [1 1]
# [2 0]]
#4

np.count_nonzero(np.array([[0,1],[1,1],[2,0]]), axis=0)

#[Output]:
#array([2, 2], dtype=int64)

np.count_nonzero(np.array([[0,1],[1,1],[2,0]]), axis=1)

#[Output]:
#array([1, 2, 1], dtype=int64)