<p>尝试使用<a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.crosstab.html#pandas-crosstab" rel="nofollow noreferrer">^{<cd1>}</a>:</p>
<pre><code>pd.crosstab(df['Movie'], df['Rate'])
</code></pre>
<pre><code>Rate 1 2 4 5
Movie
2124 0 1 0 0
3029 0 0 0 1
5821 0 0 1 0
7582 1 0 0 0
17479 1 0 0 0
</code></pre>
<hr/>
<p>固定轴名称和列名<a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.rename.html#pandas-dataframe-rename" rel="nofollow noreferrer">^{<cd2>}</a>+<a href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.reset_index.html#pandas-dataframe-reset-index" rel="nofollow noreferrer">^{<cd3>}</a>+<a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.rename_axis.html#pandas-dataframe-rename-axis" rel="nofollow noreferrer">^{<cd4>}</a>:</p>
<pre><code>new_df = (
pd.crosstab(df['Movie'], df['Rate'])
.rename(columns=lambda c: f'Rate_{c}_Count')
.reset_index()
.rename_axis(columns=None)
)
</code></pre>
<pre><code> Movie Rate_1_Count Rate_2_Count Rate_4_Count Rate_5_Count
0 2124 0 1 0 0
1 3029 0 0 0 1
2 5821 0 0 1 0
3 7582 1 0 0 0
4 17479 1 0 0 0
</code></pre>