擅长:python、mysql、java
<p>解决方案-<a href="http://pandas.pydata.org/pandas-docs/stable/text.html#indexing-with-str" rel="nofollow">indexing with str</a>并由<a href="http://pandas.pydata.org/pandas-docs/stable/generated/pandas.Series.astype.html" rel="nofollow">^{<cd2>}</a>转换成{<cd1>}:</p>
<pre><code>print (df["TimeCodes"].str[6:])
0 01.001
1 03.201
2 09.231
3 11.301
4 20.601
5 31.231
6 90.441
7 91.301
Name: TimeCodes, dtype: object
df['new'] = df["TimeCodes"].str[6:].astype(float)
print (df)
TimeCodes new
0 00:00:01.001 1.001
1 00:00:03.201 3.201
2 00:00:09.231 9.231
3 00:00:11.301 11.301
4 00:00:20.601 20.601
5 00:00:31.231 31.231
6 00:00:90.441 90.441
7 00:00:91.301 91.301
</code></pre>