<p>使用<code>numpy.savetxt</code>可能会找到一个不错的解决方案,而且可能还有一个比您的更简单的<code>pandas</code>解决方案,但是在本例中,使用标准库<code>csv</code>和{<cd4>}的解决方案非常简洁:</p>
<pre><code>In [45]: import csv
In [46]: from itertools import izip_longest # Use zip_longest in Python 3.
In [47]: rows = izip_longest(array3, array4, array1, array2, fillvalue='')
In [48]: with open("out.csv", "w") as f:
....: csv.writer(f).writerows(rows)
....:
In [49]: !cat out.csv
7.0,6.0,1.0,12.0
10.947368421052632,8.5789473684210531,3.1111111111111112,36.222222222222221
14.894736842105264,11.157894736842106,5.2222222222222223,60.444444444444443
18.842105263157894,13.736842105263158,7.3333333333333339,84.666666666666657
22.789473684210527,16.315789473684212,9.4444444444444446,108.88888888888889
26.736842105263158,18.894736842105264,11.555555555555555,133.11111111111111
30.684210526315788,21.473684210526315,13.666666666666668,157.33333333333331
34.631578947368425,24.05263157894737,15.777777777777779,181.55555555555554
38.578947368421055,26.631578947368421,17.888888888888889,205.77777777777777
42.526315789473685,29.210526315789473,20.0,230.0
46.473684210526315,31.789473684210527,,
50.421052631578945,34.368421052631575,,
54.368421052631575,36.94736842105263,,
58.315789473684205,39.526315789473685,,
62.263157894736842,42.10526315789474,,
66.21052631578948,44.684210526315788,,
70.15789473684211,47.263157894736842,,
74.10526315789474,49.842105263157897,,
78.05263157894737,52.421052631578945,,
82.0,55.0,,
</code></pre>