擅长:python、mysql、java
<p>要遍历行,请使用<a href="https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.iterrows.html" rel="nofollow noreferrer">^{<cd1>}</a>:</p>
<pre><code>In [53]: records = df[df['uid'] == query]
In [54]: for index, row in records.iterrows():
...: print(row['uid'], row['iid'], row['rat'])
...:
344.0 1189.0 5.0
344.0 1500.0 5.0
344.0 814.0 5.0
</code></pre>
<hr/>
<p>还有两种方法可以选择数据。您可以使用<a href="https://pandas.pydata.org/pandas-docs/stable/indexing.html#boolean-indexing" rel="nofollow noreferrer">^{<cd2>}</a>:</p>
<pre><code>In [4]: query = 344
In [7]: df[df['uid'] == query]
Out[7]:
uid iid rat
0 344 1189 5.0
1 344 1500 5.0
2 344 814 5.0
</code></pre>
<p>也可以使用<a href="https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.query.html#pandas-dataframe-query" rel="nofollow noreferrer">^{<cd3>}</a>函数:</p>
<pre><code>In [8]: df.query('uid == %d' %query)
Out[8]:
uid iid rat
0 344 1189 5.0
1 344 1500 5.0
2 344 814 5.0
</code></pre>