用pandas对数据进行处理。
df1<span class="hljs-selector-attr">[<span class="hljs-string">'总分'</span>]</span>=df1<span class="hljs-selector-attr">[[<span class="hljs-string">'思政'</span>,<span class="hljs-string">'微积分'</span>,<span class="hljs-string">'大学英语'</span>]</span>]<span class="hljs-selector-class">.sum</span>(axis=<span class="hljs-number">1</span>)
df1=df1<span class="hljs-selector-class">.sort_values</span>(by=<span class="hljs-string">'总分'</span>,ascending=False,ignore_index=True)
groups=df1<span class="hljs-selector-class">.groupby</span>(<span class="hljs-string">'性别'</span>)<span class="hljs-selector-attr">[<span class="hljs-string">'总分'</span>]</span><span class="hljs-selector-class">.apply</span>(lambda x:sum(x)/len(x))
df1<span class="hljs-selector-attr">[df1[<span class="hljs-string">'性别'</span>]</span>==<span class="hljs-string">'男'</span>]<span class="hljs-selector-attr">[<span class="hljs-string">'总分'</span>]</span><span class="hljs-selector-class">.sort_values</span>()<span class="hljs-selector-class">.to_list</span>()<span class="hljs-selector-attr">[-1]</span>
df1<span class="hljs-selector-attr">[df1[<span class="hljs-string">'性别'</span>]</span> == <span class="hljs-string">'女'</span>]<span class="hljs-selector-attr">[<span class="hljs-string">'总分'</span>]</span><span class="hljs-selector-class">.sort_values</span>()<span class="hljs-selector-class">.to_list</span>()<span class="hljs-selector-attr">[0]</span>