如何使用python在df中迭代字符串 [英] How to iterating string in df using python

问题描述

我有数据

                     date                    id           request 
0     2016-06-17 09:25:05  [e-mail]  GET HTTP/1.1   
1     2016-06-17 09:25:07  [e-mail]     POST HTTP/1.1   
2     2016-06-17 09:25:47  [e-mail]  CONNECT HTTP/1.1   
3     2016-06-17 09:25:47  [e-mail]     POST HTTP/1.1   
4     2016-06-17 09:25:49  [e-mail]  CONNECT HTTP/1.1 

我需要迭代字符串和'GET'不在df ['request'] 我想从df删除字符串。

I need to iterate string and 'GET' not in df['request'] I want to delete string from df.

欲望输出

               date                    id           request 
0     2016-06-17 09:25:05  [e-mail]  GET HTTP/1.1

我尝试 df = df [df.request中的'GET'] / code>但它返回

I try df = df['GET' in df.request] but it returns

KeyError：False

KeyError: False

推荐答案

您需要布尔索引 与 mask org / pandas-docs / stable / generated / pandas.Series.str.contains.htmlrel =nofollow> str.contains ：

You need boolean indexing with mask created by str.contains:

print (df.request.str.contains('GET'))
0  2016-06-17     True
1  2016-06-17    False
2  2016-06-17    False
3  2016-06-17    False
4  2016-06-17    False

print (df[df.request.str.contains('GET')])
                  date                    id       request
0 2016-06-17  09:25:05  [e-mail]  GET HTTP/1.1

通过评论编辑：

列大小使用 [] ，因为 siz e 是功能：

For comparing column size use [], because size is function:

df_upd = df_upd[df_upd['size'].astype(int) > 3000]

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