ndarray的用法总结

#发现ndarray的一维,二维都可以用[i][j]来访问.对于二维数组来讲,这是[行序号][列序号];但是对于一维来说,j的含义元素(元组)的第j个,因为一维没有列的概念.
import numpy as np
array1 = np.array([[1,2,3], [4,5,6]])  #二维数组, (2,3)
print(array1)

fields = ["a", "b", "c"]
dtype = np.dtype([("a", int),
                 ("b", np.float64),
                 ("c", np.float64)])
ndarray1 = np.empty(shape=(2, ), dtype=dtype) #一维数组, (2, )
for i in range(len(array1)):
    for j, field in enumerate(fields):　　 #绑定下标和数据,下标从0开始
        ndarray1[field][i] = array1[i][j] #dtype和列名关联后可以通过[dtype的列名][行序号]来访问,也可以用[行序号][元组中位置序号]
　　　　 #ndarray1[i][j] = array1[i][j]
print(ndarray1)

print(ndarray1[0][1])
print(ndarray1["b"][0])

ndarray2 = np.empty(shape=(2,3), dtype=np.float64) #二维数组, (2, 3)
for i in range(len(array1)):
    for j in range(len(array1[0])):
        ndarray2[i][j] = array1[i][j]
print(ndarray2)