擅长:python、mysql、java
<p>要获得没有计数的输出,只需尝试<a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.core.groupby.SeriesGroupBy.unique.html" rel="nofollow noreferrer">unique</a></p>
<pre><code>df.groupby("Name")["Likes"].unique()
Name
Amy [Pizza, Sweet Potatoes]
John [Pizza]
Marie [Pizza, Sushi]
Tim [Pizza, Pasta, Sushi]
Name: Likes, dtype: object
</code></pre>
<p>此外,还可以使用<a href="https://pandas.pydata.org/pandas-docs/stable/user_guide/groupby.html#named-aggregation" rel="nofollow noreferrer">named aggregation</a></p>
<pre><code>df.groupby("Name").agg(**{"Likes Food": pd.NamedAgg(column='Likes', aggfunc="size"),
"Food List": pd.NamedAgg(column='Likes', aggfunc="nunique")}).reset_index()
Name Likes Food Food List
0 Amy 2 [Pizza, Sweet Potatoes]
1 John 1 [Pizza]
2 Marie 2 [Pizza, Sushi]
3 Tim 3 [Pizza, Pasta, Sushi]
</code></pre>