<p>我认为您可以使用<a href="http://pandas.pydata.org/pandas-docs/stable/generated/pandas.to_datetime.html" rel="nofollow">^{<cd1>}</a>和<code>errors='coerce'</code>来将错误数据替换为<code>NaT</code>和{a2}来删除<code>NaT</code>列中<code>NaT</code>的所有行:</p>
<pre><code>import pandas as pd
from pandas.compat import StringIO
temp=u"""===============================================================================
2016/03/28 12:26:45 - Message
-
2016/03/28 12:26:45 - Message
2016/03/28 12:26:45 - Message
Message
2016/03/28 12:26:45 - Message
2016/03/28 12:26:46 - Message
2016/03/28 12:26:46 - Message
2016/03/28 12:28:30 - Message
2016/03/28 12:28:40 - Message
2016/03/28 12:28:40 - Message
2016/03/28 12:28:40 - Message
-
2016/03/28 12:28:40 - Message
==============================================================================="""
#after testing replace StringIO(temp) to filename
df = pd.read_csv(StringIO(temp), sep="\s+-\s+", names = ["Time", "Text"], engine = "python")
df.Time = pd.to_datetime(df.Time, errors='coerce')
df.dropna(subset=['Time'], inplace=True)
</code></pre>
^{pr2}$