<p>直到<a href="http://pandas.pydata.org/pandas-docs/version/0.16.0/whatsnew.html" rel="nofollow">0.16.0</a>才添加此功能</p>
<blockquote>
<p>Added decimal option in to_csv to provide formatting for non-‘.’ decimal separators (<a href="https://github.com/pydata/pandas/issues/781" rel="nofollow">GH781</a>)</p>
</blockquote>
<p>将pandas升级到更新的版本,就可以了。下面的代码使用<a href="http://pandas.pydata.org/pandas-docs/stable/10min.html" rel="nofollow">10 minute tutorial</a>和pandas版本0.18.1</p>
<pre><code>>>> import pandas as pd
>>> import numpy as np
>>> dates = pd.date_range('20130101', periods=6)
>>> df = pd.DataFrame(np.random.randn(6,4), index=dates, columns=list('ABCD'))
>>> df
A B C D
2013-01-01 -0.157833 1.719554 0.564592 -0.228870
2013-01-02 -0.316600 1.545763 -0.206499 0.793412
2013-01-03 1.905803 1.172803 0.744010 1.563306
2013-01-04 -0.142676 -0.362548 -0.554799 -0.086404
2013-01-05 1.708246 -0.505940 -1.135422 0.810446
2013-01-06 -0.150899 0.794215 -0.628903 0.598574
>>> df.to_csv("test.csv", sep=';', decimal=',')
</code></pre>
<p>这会产生一个“测试.csv“文件如下所示:</p>
^{pr2}$