假设我已经对数据框中的句子进行了分词，如下所示：

+-----------------------------------------+-----------+|                sentence                 | sentiment |+-----------------------------------------+-----------+| [i, like, this, app, it, s, awesome]    | positive  || [way, to, many, ads, pop, up, hate, it] | negative  || [ye]                                    | negative  || [p]                                     | positive  || [niceeeee]                              | positive  || [i, do, not, like, the, design]         | negative  || [very, useful, recommended]             | positive  || [ugly]                                  | negative  || [xxx]                                   | negative  || [yes]                                   | positive  |+-----------------------------------------+-----------+

我想通过删除句子列中字符数少于4的行来清理数据框中的不必要数据，最终结果将如下所示：

+-----------------------------------------+-----------+|                sentence                 | sentiment |+-----------------------------------------+-----------+| [i, like, this, app, it, s, awesome]    | positive  || [way, to, many, ads, pop, up, hate, it] | negative  || [niceeeee]                              | positive  || [i, do, not, like, the, design]         | negative  || [very, useful, recommended]             | positive  || [ugly]                                  | negative  |+-----------------------------------------+-----------+

有谁能提供解决这个问题的程序代码吗？我非常感谢您的帮助，这将有助于我的论文工作，谢谢您的关注

回答：

你可以使用apply函数来实现这一点

char_limit=4df[df['sentence'].apply(lambda x : len("".join(x))>=char_limit)]