03-Numpy Operations

Arithmetic

You can easily perform array with array arithmetic, or scalar with array arithmetic. Let's see some examples:

import numpy as np
arr = np.arange(0,10)
# array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])

arr + arr
# array([ 0,  2,  4,  6,  8, 10, 12, 14, 16, 18])

arr * arr
# array([ 0,  1,  4,  9, 16, 25, 36, 49, 64, 81])

arr - arr
# array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0])

# Warning on division by zero, but not an error!
# Just replaced with nan
# 잘못된 값으로 나눌때 오류를 발생시키지 않고 nan을 돌려줍니다.
arr/arr
# array([ nan,   1.,   1.,   1.,   1.,   1.,   1.,   1.,   1.,   1.])

# Also warning, but not an error instead infinity
1/arr
# array([inf, ...  ,0.11111111])

arr**3
# array([  0,   1,   8,  27,  64, 125, 216, 343, 512, 729])

 

Universal Array Functions

# 제곱근 
np.sqrt(arr)

# Calcualting exponential (e^)
# 지수 계산 
np.exp(arr)

# 최대값
np.max(arr) # arr.max() 와 같다.

# sin, log 계산
np.sin(arr)
np.log(arr)

 

 

Great Job!