擅长:python、mysql、java
<p>您可以将<code>df.filter</code>与<code>pd.concat</code>一起使用:</p>
<pre><code>In [589]: start = df.stack().filter(like='start').reset_index()[0]
In [590]: end = df.stack().filter(like='end').reset_index()[0]
In [591]: rate = df.stack().filter(like='Rate').reset_index()[0]
In [594]: x = pd.concat([start.rename('Start'), end.rename('End'), rate.rename('Rate')], 1)
</code></pre>
<p>假设您有<code>2</code>个静态列:<code>ID, PropCode</code>。您可以像这样将这些col附加到<code>x</code>:</p>
<pre><code>In [640]: x[['ID', 'PropCode']] = df[['ID', 'PropCode']].values.tolist() * len(x)
In [641]: x
Out[641]:
Start End Rate ID PropCode
0 1/1/21 1/31/21 80 1 52032
1 2/1/21 2/28/21 85 1 52032
2 3/1/21 3/31/21 90 1 52032
3 4/1/21 4/30/21 95 1 52032
</code></pre>