목차

NumPy란

NumPy 특징

ndarray 클래스

# Vector(1차원 행렬)
import numpy as np

a = np.array([1,2,3,4,5,6,7]) 
print(type(a))
Out[-]
<class 'numpy.ndarray'>

NumPy 산술 연산

import numpy as np

data = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
dataTwo = [[1, 1, 1], [2, 2, 2], [3, 3, 3]]

# 행렬과 스칼라의 곱
for i in range(len(data)):
    for j in range(len(data[0])):
        data[i][j] *= 2

print(data)
        
# 행렬끼리 덧셈
for i in range(len(data)):
    for j in range(len(data[0])):
        data[i][j] += dataTwo[i][j]

print(data)
Out[-]
[[2, 4, 6], [8, 10, 12], [14, 16, 18]]
[[3, 5, 7], [10, 12, 14], [17, 19, 21]]