举例说明Numpy的数组属性

NumPy数组有一些有用的属性，可以帮助你轻松使用它。本文将向你展示一些如何正确使用它们的例子。

1.常见的NumPy数组属性

1. ndarray.flags。返回ndarray数组的内存信息，如数组的存储方式，是否是其他数组的拷贝。

   >>> import numpy as np
   >>> 
   >>> arr = np.array(['python', 'java', 'javascript'])
   >>> 
   >>> print(arr.flags)
     C_CONTIGUOUS : True
     F_CONTIGUOUS : True
     OWNDATA : True
     WRITEABLE : True
     ALIGNED : True
     WRITEBACKIFCOPY : False
     UPDATEIFCOPY : False
   
   

2. ndarray.itemsize:返回数组中每个元素的大小，单位是字节。

   >>> import numpy as np
   >>> 
   >>> arr = np.array(['python', 'java', 'javascript'])
   >>>
   >>> print(arr.itemsize)
   40
   >>> 
   >>> arr1 = np.array([6, 7, 8, 9, 10], dtype = np.int8)
   >>> 
   >>> print(arr1.itemsize)
   1
   
   

3. ndarray.ndim:返回数组的尺寸。

   >>> import numpy as np
   >>>
   >>> arr1 = np.array([[1, 2, 3],[4, 5, 6],[7, 8, 9]])
   >>> 
   >>> print(arr1.ndim)
   2
   
   

4. ndarray.shape:shape属性的返回值是一个由数组尺寸组成的元组。例如，一个有2行3列的二维数组可以表示为（2,3）。这个属性可以用来调整数组尺寸的大小。

   >>> import numpy as np
   >>>
   # create the Numpy array.
   >>> arr1 = np.array([[1, 2, 3],[4, 5, 6],[7, 8, 9]])
   >>> 
   # print it's dimension.
   >>> print(arr1.ndim)
   2
   # print the NumPy array shape.
   >>> print(arr1.shape)
   (3, 3)
   >>>
   # change the NumPy array shape.
   >>> arr1.shape = (1, 9)
   >>> 
   # print the reshaped array.
   >>> print(arr1)
   [[1 2 3 4 5 6 7 8 9]]
   
   

5. ndarray.reshape():该方法用于调整数组的形状。

   >>> import numpy as np
   >>>
   # create the original 2 dimension array.
   >>> arr1 = np.array([[1, 2, 3],[4, 5, 6]]) 
   >>> 
   # print out the array shape.
   >>> print(arr1.shape)
   (2, 3)
   >>> 
   # reshape the above array to (3,2)
   >>> arr1.reshape(3, 2)
   array([[1, 2],
          [3, 4],
          [5, 6]])
   >>> 
   # you can find that the original array's shape is not changed.
   >>> print(arr1)
   [[1 2 3]
    [4 5 6]]