<p>您可以先<a href="http://pandas.pydata.org/pandas-docs/stable/generated/pandas.read_csv.html" rel="nofollow">^{<cd1>}</a>,然后通过<a href="http://pandas.pydata.org/pandas-docs/stable/generated/pandas.Series.astype.html" rel="nofollow">^{<cd3>}</a>除以<code>10**9</code>将最后两列转换为<code>np.int64</code>。要写入文件,请使用<a href="http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.to_csv.html" rel="nofollow">^{<cd5>}</a>:</p>
<pre><code>import pandas as pd
import numpy as np
import io
temp=u"""1466f7b93975983f6e292a8a4faaa4b2,1619b4d0d283c0dddb17d24a359a3b49,36db348cde68592a31d502366fc52932,2010-03-08 17:09:00.472544,2010-03-12 16:09:58.122987
367c13356a5d22158f0ae56977134e2c,eedb7d0714796b64767a8710ea3844a7,925476200929fd346ea312cbe9a046fe,2010-03-08 17:08:29.174236,2010-03-12 16:09:58.122987
edf6b1e4f67b0e8a5080d299c9f9aeb2,7cb7681b90388a7522d0f06578591567,ffde0649a72ded8e33522c503a4d5cbe,2010-03-08 17:08:22.030524,2010-03-12 16:09:58.122987
6bb2ad8bc78897e99072d4d76cf0f19c,b644947ac4db03bdb518cfa71765f8c8,eb25089d396c06255cbb5f1bad801cc4,2010-03-08 17:07:55.819137,2010-03-12 16:09:58.122987"""
</code></pre>
^{2}$
<pre><code>print df
a b \
0 1466f7b93975983f6e292a8a4faaa4b2 1619b4d0d283c0dddb17d24a359a3b49
1 367c13356a5d22158f0ae56977134e2c eedb7d0714796b64767a8710ea3844a7
2 edf6b1e4f67b0e8a5080d299c9f9aeb2 7cb7681b90388a7522d0f06578591567
3 6bb2ad8bc78897e99072d4d76cf0f19c b644947ac4db03bdb518cfa71765f8c8
c d e
0 36db348cde68592a31d502366fc52932 1268068140 1268410198
1 925476200929fd346ea312cbe9a046fe 1268068109 1268410198
2 ffde0649a72ded8e33522c503a4d5cbe 1268068102 1268410198
3 eb25089d396c06255cbb5f1bad801cc4 1268068075 1268410198
df.to_csv('filename', header=None, index=False)
</code></pre>