擅长:python、mysql、java
<p>您可以使用<a href="http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.ix.html" rel="nofollow">^{<cd1>}</a>选择第二列,并通过<a href="http://pandas.pydata.org/pandas-docs/stable/generated/pandas.Series.astype.html" rel="nofollow">^{<cd4>}</a>将<code>int</code>列转换为{<cd3>}:</p>
<pre><code>print df
c0 0
0 key0:j 1062
1 key0:t 1151
2 key0:u 264
df.ix[:,1] = '"abc"' + df.ix[:,1].astype(str)
print df
c0 0
0 key0:j "abc"1062
1 key0:t "abc"1151
2 key0:u "abc"264
</code></pre>
<p>或者:</p>
^{pr2}$
<p>如果列是<code>a</code>和<code>b</code>:</p>
<pre><code>print df
a b
0 key0:j 1062
1 key0:t 1151
2 key0:u 264
df['b'] = 'abc' + df['b'].astype(str)
print df
a b
0 key0:j abc1062
1 key0:t abc1151
2 key0:u abc264
</code></pre>
<p>编辑:</p>
<p>你可以试试,但我认为它比上面的解决方案慢:</p>
<pre><code>df = df.groupby(['c0'])['c6'].apply(lambda x: 'abc' + str( x.sum())).reset_index()
print df
c0 c6
0 key0:j abc1062
1 key0:t abc1151
2 key0:u abc264
</code></pre>