How to make a Structured Array from multiple simple array

Question

import numpy as np

a=np.array([1,2,3,4,5,6,7,8,9])
b=np.array([\"a\",\"b\",\"c\",\"d\",\"e\",\"f\",\"g\",\"h\",\"i\"])
c=np.array([9,8,7,6,5,4,3,2,1])
datatype=np.d         


        

Answer 1

zip does create a list of tuples, which could be memory-intensive if the arrays are big. You could use itertools.izip to be more memory-efficient:

import itertools
d=np.fromiter(itertools.izip(a,b,c),dtype=datatype)

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For small arrays of length ~10:

In [68]: %timeit np.fromiter(itertools.izip(a,b,c),dtype=datatype)
100000 loops, best of 3: 15.8 us per loop

In [69]: %timeit np.array(zip(a,b,c),dtype=datatype)
10000 loops, best of 3: 20.8 us per loop

For arrays of length ~10000:

In [72]: A=np.tile(a,1000)
In [74]: B=np.tile(b,1000)
In [75]: C=np.tile(c,1000)

In [83]: %timeit np.fromiter(itertools.izip(A,B,C),dtype=datatype)
100 loops, best of 3: 10.7 ms per loop

In [84]: %timeit np.array(zip(A,B,C),dtype=datatype)
100 loops, best of 3: 12.7 ms per loop

So np.fromiter appears to be slightly faster than np.array.