<p>IIUC</p>
<pre><code>df.groupby('departamento').head(5)
</code></pre>
<p>输出:</p>
<pre><code> produccion
mean std min max
departamento campo
f7fd2c4f 8dd7c41b 4714.695603 1076.940951 3091.015553 6378.546534
82edafb9 1851.291482 841.512944 675.814722 3006.476183
58a0d8ca 1768.151315 347.896113 1033.459536 2242.544338
8ba362f3 257.917212 231.490925 0.000000 497.916659
4f4a249f 192.811711 80.299111 129.190598 356.437730
ec12ad00 44502c89 15.015145 11.467353 0.000000 29.241879
5558f26e 1.107400 0.959445 0.000000 2.762156
85c1a0e5 0.122720 0.425113 0.000000 1.472635
cf33cb8a 2f614c0b 12458.858168 12042.715975 150.635367 25999.977584
5559f8d7 4272.447078 1326.999765 2458.231739 6059.658900
fd6f6562 3378.712031 1194.101786 869.763739 4814.220212
febb6cf6 4149.936221 833.663173 2471.139924 5827.822674
d56beadb 474.831361 810.840341 0.000000 2283.465569
</code></pre>
<p>@接收频率是正确的</p>
<pre><code>df.sort_values(by=('produccion', 'std'), ascending=False)\
.groupby('departamento')\
.head(5)\
.sort_index()
</code></pre>
<p>首先对数据帧进行排序,然后使用<code>head</code>和<code>sort_index</code>对<code>groupby</code>进行排序</p>