擅长:python、mysql、java
<p>将<code>df.groupby('User_ID')['Datetime'].apply(lambda g: len(g)>1)</code>的结果赋给一个变量,以便您可以执行布尔索引,然后使用此索引调用<code>isin</code>,并筛选原始df:</p>
<pre><code>In [366]:
users = df.groupby('User_ID')['Datetime'].apply(lambda g: len(g)>1)
users
Out[366]:
User_ID
189757330 False
222583401 False
287280509 False
329757763 False
414673119 True
624921653 False
Name: Datetime, dtype: bool
In [367]:
users[users]
Out[367]:
User_ID
414673119 True
Name: Datetime, dtype: bool
In [368]:
users[users].index
Out[368]:
Int64Index([414673119], dtype='int64')
In [361]:
df[df['User_ID'].isin(users[users].index)]
Out[361]:
User_ID Latitude Longitude Datetime
5 414673119 41.555014 2.096583 2014-02-24 20:15:30
6 414673119 41.555014 2.097583 2014-02-24 20:16:30
7 414673119 41.555014 2.098583 2014-02-24 20:17:30
</code></pre>
<p>然后可以正常调用上面的<code>to_csv</code></p>