如何使用正则表达式设置多个条件来检测熊猫中的模式

Question

我有一个这样的数据框：

text

Is it possible to apply [NUM] times
Is it possible to apply [NUM] time
Called [NUM] hour ago
waited [NUM] hours
waiting [NUM] minute
waiting [NUM] minutes???
Are you kidding me !
Waiting?

我希望能够检测到具有"[NUM] time" or "[NUM] times" or "[NUM] minute" or "[NUM] minutes" or "[NUM] hour" or "[NUM] hours" 的模式。另外，如果它有"!" (or more than one !) 或"??" (at least two ?)。

所以结果应该是这样的：

text.                                  available

Is it possible to apply [NUM] times.   True
Is it possible to apply [NUM] time.    True
Called [NUM] hour ago                  True
waited [NUM] hours                     True
waiting [NUM] minute                   True
waiting [NUM] minutes???               True
Are you kidding me !                   True
Waiting?                               False
I didn't like it                       False

所以我想要这样的东西，但不知道如何将所有这些条件放在一起：

df["available"] = df['text'].apply(lambda x: re.match(r'[\!* | \?+ | [NUM] time | [NUM] hour | [NUM] minute]')

Answer 1

您可以将Series.str.contains 与正则表达式一起使用：

import pandas as pd
df = pd.DataFrame({'text':["Is it possible to apply [NUM] times","Is it possible to apply [NUM] time","Called [NUM] hour ago","waited [NUM] hours","waiting [NUM] minute","waiting [NUM] minutes???","Are you kidding me !","Waiting?", "I didn't like it"]})
df['available'] = df['text'].str.contains(r'\[NUM]\s*(?:hour|minute|time)s?\b|!|\?{2}', regex=True)
## => df['available']
#     0     True
#     1     True
#     2     True
#     3     True
#     4     True
#     5     True
#     6     True
#     7    False
#     8    False

请参阅regex demo。 详情：

• \[NUM] - [NUM] 字符串
• \s* - 零个或多个空格
• (?:hour|minute|time) - 匹配 hour、minute 或 time 的非捕获组
• s? - 一个可选的s
• \b - 单词边界
• | - 或
• ! - 一个 ! 字符
• | - 或
• \?{2} - 两个问号。