<p>使用<a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.groupby.html" rel="nofollow noreferrer">^{<cd1>}</a>两次,然后使用<a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.nlargest.html" rel="nofollow noreferrer">^{<cd2>}</a>,然后使用<a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.reset_index.html" rel="nofollow noreferrer">^{<cd3>}</a>:</p>
<pre><code>(df.groupby(['STATE', 'County'])['POP'].sum()
.groupby(level=0, group_keys=False).nlargest(3).reset_index())
STATE County POP
0 Alabama Baldwin County 182265
1 Alabama Calhoun County 118572
2 Alabama Blount County 57322
3 Wisconsin Waukesha County 389891
4 Wisconsin Winnebago County 166994
5 Wisconsin Washington County 131887
6 Wyoming Natrona County 75450
7 Wyoming Sheridan County 29116
8 Wyoming Park County 28205
</code></pre>
<p>或者,如果愿意,不要重置索引,输出将是:</p>
<pre><code>STATE County
Alabama Baldwin County 182265
Calhoun County 118572
Blount County 57322
Wisconsin Waukesha County 389891
Winnebago County 166994
Washington County 131887
Wyoming Natrona County 75450
Sheridan County 29116
Park County 28205
</code></pre>