擅长:python、mysql、java
<p>您可以按以下步骤进行:</p>
<pre><code>df_sum= df.copy()
df_sum['elevation']*= df_sum['counts']
df_sum['width']*= df_sum['counts']
df_sum= df_sum.groupby(['building', 'day']).agg(dict(elevation=sum, width=sum, counts=sum))
df_sum['elevation']/= df_sum['counts']
df_sum['width']/= df_sum['counts']
df_sum.reset_index(inplace=True)
df_sum.drop('counts', axis='columns', inplace=True)
</code></pre>
<p>结果是:</p>
<pre><code> building day elevation width
0 A1 2019-07-02 7.10 2.00
1 A1 2019-07-03 7.44 2.91
</code></pre>