<p>您可以用<a href="http://pandas.pydata.org/pandas-docs/stable/generated/pandas.Series.str.strip.html" rel="nofollow">^{<cd2>}</a>和<a href="http://pandas.pydata.org/pandas-docs/stable/generated/pandas.to_datetime.html" rel="nofollow">^{<cd3>}</a>来尝试<a href="http://pandas.pydata.org/pandas-docs/stable/generated/pandas.read_csv.html" rel="nofollow">^{<cd1>}</a>:</p>
<pre><code>import pandas as pd
import io
temp=u"""[ABCD,color,NORMAL,N,2015-02-20,1]
[XYZA,color,NORMAL,N,2015-05-04,1]
[GFFD,color,NORMAL,N,2015-07-03,1]
[NAAS,color,NORMAL,N,2015-08-26,1]
[LOWW,color,NORMAL,N,2015-09-26,1]
[KARA,color,NORMAL,N,2015-11-08,1]
[ALEQ,color,NORMAL,N,2015-12-04,1]
[VDDE,color,NORMAL,N,2015-12-23,1]
[QWER,color,NORMAL,N,2016-01-18,1]
[KDSS,color,NORMAL,Y,2015-08-29,1]"""
#after testing replace io.StringIO(temp) to filename
df = pd.read_csv(io.StringIO(temp),header=None,names=['a','b','c','d','e','f'])
#remove []
df['a'] = df['a'].str.strip('[')
df['f'] = df['f'].str.strip(']')
#convert column e to datetime
df['e'] = pd.to_datetime(df['e'])
print df
a b c d e f
0 ABCD color NORMAL N 2015-02-20 1
1 XYZA color NORMAL N 2015-05-04 1
2 GFFD color NORMAL N 2015-07-03 1
3 NAAS color NORMAL N 2015-08-26 1
4 LOWW color NORMAL N 2015-09-26 1
5 KARA color NORMAL N 2015-11-08 1
6 ALEQ color NORMAL N 2015-12-04 1
7 VDDE color NORMAL N 2015-12-23 1
8 QWER color NORMAL N 2016-01-18 1
9 KDSS color NORMAL Y 2015-08-29 1
</code></pre>