Python 使用numpy结构化数组初始化时，数据帧速度非常慢

我有一个包含整数和浮点数的

numpy

结构化数组

，我用它来初始化一个

数据帧

：

In [497]: x = np.ones(100000000, dtype=[('f0', '<i8'), ('f1', '<f8'),('f2','<i8'),('f3', '<f8'),('f4', '<f8'),('f5', '<f8'),('f6', '<f8'),('f7', '<f8')])

In [498]: %timeit pd.DataFrame(x)
The slowest run took 4.07 times longer than the fastest. This could mean that an intermediate result is being cached 

In [498]: 1 loops, best of 3: 2min 26s per loop


In [499]: xx=x.view(np.float64).reshape(x.shape + (-1,))

In [500]: %timeit pd.DataFrame(xx)
1 loops, best of 3: 256 ms per loop

[497]中的

：x=np.one（100000000，dtype=[（'f0'，'