[1]

a = [[0,1,2], [3,4,5], [6,7,8]]
print(a[0])
print(a[0][0], a[0][1], a[0][2])
import numpy as np
a = np.arange(12).reshape((3,4))
print(f"ndarray: \n{a}\n")
for data in a:
print(data)

#넘파이의 인덱스 접근
print(a[0,0], a[0,1], a[0,2])
print(a[1,0], a[1,1], a[1,2])
print(a[2,0], a[2,1], a[2,2])
print("a[0,1:] : ", a[0, 1:])
print("a[1, :3] : ", a[1, :3])
print("a[2, 1:3] : ", a[2, 1:3])

a = np.arange(12).reshape((4,3))
print(f"ndarray: \n{a}\n")
print("a[1:,0] : ", a[1:, 0])
print("a[:3, 1] : ", a[:3, 1])
print("a[1:3, 2] : ", a[1:3, 2])


- : 는 그 차원에 대해서 모든 값을 가져오라는 뜻
- ... 은 뒤따르는 모든 차원을 가져오라는 뜻
a = [[0,1,2], [3,4,5], [6,7,8]]
print(a[0])
print(a[0][0], a[0][1], a[0][2])
import numpy as np
a = np.arange(12).reshape((3,4))
print(f"ndarray: \n{a}\n")
for data in a:
print(data)
#넘파이의 인덱스 접근
print(a[0,0], a[0,1], a[0,2])
print(a[1,0], a[1,1], a[1,2])
print(a[2,0], a[2,1], a[2,2])
print("a[0,1:] : ", a[0, 1:])
print("a[1, :3] : ", a[1, :3])
print("a[2, 1:3] : ", a[2, 1:3])
a = np.arange(12).reshape((4,3))
print(f"ndarray: \n{a}\n")
print("a[1:,0] : ", a[1:, 0])
print("a[:3, 1] : ", a[:3, 1])
print("a[1:3, 2] : ", a[1:3, 2])
a = np.arange(16).reshape((4,4))
print(f"ndarray: \n{a}\n")
print("a[1:3, 1:3] : \n", a[1:3, 1:3])
print("a[:2, :3] : \n", a[:2, :3])
print("a[1:, 2:] : \n", a[1:, 2:])
print("a[2:, :-2] : \n", a[2:, :-2])
image = np.arange(9).reshape((3,3))
print(f"ndarray: \n{image}\n")
horizontal_flip = image[:, ::-1]
print(f"horizontal_flip: \n{horizontal_flip}\n")
vertical_flip = image[::-1, :]
print(f"vertical_flip: \n{vertical_flip}\n")
rotation = image[::-1, ::-1]
print(f"rotation: \n{rotation}\n")
#
a = np.arange(16).reshape((4,4))
print(f"ndarray: \n{a}\n")
print("a[0: :] : \n", a[0, :])
print("a[0, ...] : \n", a[0, ...])