Numpy Array 기본 함수

import numpy as np

arr1 = np.array([[1.0,2,3],[4,5,6]], dtype=np.int32)
print(arr1)
'''
[[1 2 3]
 [4 5 6]]
'''

import numpy as np

print(type(arr1))
'''
<class 'numpy.ndarray'> 
--> 데이터 타입을 출력

''' 

import numpy as np

print(np.ndim(arr1))
'''
2       --> 데이터의 dimension
'''

import numpy as np

print(np.shape(arr1))
'''
(2, 3)     --> 데이터의 형식  (2행 3열)
'''

import numpy as np

print(np.size(arr1))
'''
6       --> 데이터의 크기
'''

import numpy as np

arr = np.arange(0,32,2)
print(arr)

'''
[ 0  2  4  6  8 10 12 14 16 18 20 22 24 26 28 30]  -->2간격으로, 0부터 32사이 
'''

import numpy as np

arr2 = np.arange(32).reshape(4,8)
print(arr2)

'''
[[ 0  1  2  3  4  5  6  7]
 [ 8  9 10 11 12 13 14 15]
 [16 17 18 19 20 21 22 23]
 [24 25 26 27 28 29 30 31]]
'''

import numpy as np

arr1 = np.array([[1.0,2,3],[4,5,6]], dtype=np.int32)

arr1_1 = arr1.astype(np.float64)
print(arr1_1)
print(type(arr1_1))
'''
[[1. 2. 3.]
 [4. 5. 6.]]    -> int32 > float64
<class 'numpy.ndarray'> 
'''