<p>可以将参数usecols与列的顺序一起使用:</p>
<pre><code>import pandas as pd
from pandas.compat import StringIO
temp=u"""TIME XGSM
2004 006 01 00 01 37 600 1
2004 006 01 00 02 32 800 5
2004 006 01 00 03 28 000 8
2004 006 01 00 04 23 200 11
2004 006 01 00 05 18 400 17"""
#after testing replace StringIO(temp) to filename
df = pd.read_csv(StringIO(temp),
sep="\s+",
skiprows=1,
usecols=[0,7],
names=['TIME','XGSM'])
print (df)
TIME XGSM
0 2004 1
1 2004 5
2 2004 8
3 2004 11
4 2004 17
</code></pre>
<p>编辑:</p>
<p>您可以使用分隔符<code>regex</code>-2和更多空格,然后添加<code>engine='python'</code>,因为警告:</p>
<blockquote>
<p>ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.</p>
</blockquote>
<pre><code>import pandas as pd
from pandas.compat import StringIO
temp=u"""TIME XGSM
2004 006 01 00 01 37 600 1
2004 006 01 00 02 32 800 5
2004 006 01 00 03 28 000 8
2004 006 01 00 04 23 200 11
2004 006 01 00 05 18 400 17"""
#after testing replace StringIO(temp) to filename
df = pd.read_csv(StringIO(temp), sep=r'\s{2,}', engine='python')
print (df)
TIME XGSM
0 2004 006 01 00 01 37 600 1
1 2004 006 01 00 02 32 800 5
2 2004 006 01 00 03 28 000 8
3 2004 006 01 00 04 23 200 11
4 2004 006 01 00 05 18 400 17
</code></pre>