5.6.2. Ndarray 对象¶

NumPy的ndarray：一种多维数组对象:

In [3]: import numpy as np
   ...: data = np.random.randn(2, 3)
   ...: print(data)
   ...:
[[ 0.35775698 -1.78119191 -0.80584732]
 [ 2.15299456  0.04187989 -0.18685547]]

#所有元素都乘以10
In [4]: print('data * 10: \n', data * 10)
data * 10:
 [[  3.57756982 -17.81191913  -8.05847316]
 [ 21.52994562   0.41879885  -1.86855466]]

In [5]: print('data shape:', data.shape)
   ...: print('data dtype:', data.dtype)
data shape: (2, 3)
data dtype: float64

In [11]: print(np.zeros(10))
    ...: print(np.zeros((3, 6)))
    ...: print(np.empty((2, 3, 2)))
[0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]
[[0. 0. 0. 0. 0. 0.]
 [0. 0. 0. 0. 0. 0.]
 [0. 0. 0. 0. 0. 0.]]
[[[-2.00000000e+000  1.49457942e-154]
  [ 2.10077583e-312  6.79038654e-313]
  [ 2.22809558e-312  2.14321575e-312]]

 [[ 2.35541533e-312  6.79038654e-313]
  [ 2.22809558e-312  2.14321575e-312]
  [ 2.46151512e-312  2.41907520e-312]]]

In [12]: print(np.arange(15))
[ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14]

ndarray的数据类型:

In [13]: arr1 = np.array([1, 2, 3], dtype=np.float64)
    ...: arr2 = np.array([1, 2, 3], dtype=np.int32)
    ...:
    ...: print(arr1.dtype)
    ...: print(arr2.dtype)
float64
int32

备注

索引和切片与内置list相同