我有一个数据框，我尝试获取字符串，其中的列上包含一些字符串
DF看起来像
member_id,event_path,event_time,event_duration
30595,"2016-03-30 12:27:33",yandex.ru/,1
30595,"2016-03-30 12:31:42",yandex.ru/,0
30595,"2016-03-30 12:31:43",yandex.ru/search/?lr=10738&msid=22901.25826.1459330364.89548&text=%D1%84%D0%B8%D0%BB%D1%8C%D0%BC%D1%8B+%D0%BE%D0%BD%D0%BB%D0%B0%D0%B9%D0%BD&suggest_reqid=168542624144922467267026838391360&csg=3381%2C3938%2C2%2C3%2C1%2C0%2C0,0
30595,"2016-03-30 12:31:44",yandex.ru/search/?lr=10738&msid=22901.25826.1459330364.89548&text=%D1%84%D0%B8%D0%BB%D1%8C%D0%BC%D1%8B+%D0%BE%D0%BD%D0%BB%D0%B0%D0%B9%D0%BD&suggest_reqid=168542624144922467267026838391360&csg=3381%2C3938%2C2%2C3%2C1%2C0%2C0,0
30595,"2016-03-30 12:31:45",yandex.ru/search/?lr=10738&msid=22901.25826.1459330364.89548&text=%D1%84%D0%B8%D0%BB%D1%8C%D0%BC%D1%8B+%D0%BE%D0%BD%D0%BB%D0%B0%D0%B9%D0%BD&suggest_reqid=168542624144922467267026838391360&csg=3381%2C3938%2C2%2C3%2C1%2C0%2C0,0
30595,"2016-03-30 12:31:46",yandex.ru/search/?lr=10738&msid=22901.25826.1459330364.89548&text=%D1%84%D0%B8%D0%BB%D1%8C%D0%BC%D1%8B+%D0%BE%D0%BD%D0%BB%D0%B0%D0%B9%D0%BD&suggest_reqid=168542624144922467267026838391360&csg=3381%2C3938%2C2%2C3%2C1%2C0%2C0,0
30595,"2016-03-30 12:31:49",kinogo.co/,1
30595,"2016-03-30 12:32:11",kinogo.co/melodramy/,0
和另一个带有网址的df
url
003\.ru\/[a-zA-Z0-9-_%$#?.:+=|()]+\/mobilnyj_telefon_bq_phoenix
003\.ru\/[a-zA-Z0-9-_%$#?.:+=|()]+\/mobilnyj_telefon_fly_
003\.ru\/sonyxperia
003\.ru\/[a-zA-Z0-9-_%$#?.:+=|()]+\/mobilnye_telefony_smartfony
003\.ru\/[a-zA-Z0-9-_%$#?.:+=|()]+\/mobilnye_telefony_smartfony\/brands5D5Bbr_23
1click\.ru\/sonyxperia
1click\.ru\/[a-zA-Z0-9-_%$#?.:+=|()]+\/chasy-motorola
我用
urls = pd.read_csv('relevant_url1.csv', error_bad_lines=False)
substr = urls.url.values.tolist()
data = pd.read_csv('data_nts2.csv', error_bad_lines=False, chunksize=50000)
result = pd.DataFrame()
for i, df in enumerate(data):
res = df[df['event_time'].str.contains('|'.join(substr), regex=True)]
但它还给我
UserWarning: This pattern has match groups. To actually get the groups, use str.extract.
我该如何解决？
最佳答案
urls中的至少一个正则表达式模式必须使用捕获组。str.contains仅针对df['event_time']中的每一行返回True或False-
它不使用捕获组。因此，UserWarning提醒您
正则表达式使用捕获组，但不使用匹配项。
如果您希望删除UserWarning，则可以从正则表达式模式中找到并删除捕获组。它们没有显示在您发布的正则表达式模式中，但是它们必须在您的实际文件中。在字符类之外查找括号。
或者，您可以通过以下方式禁止此特定的UserWarning
import warnings
warnings.filterwarnings("ignore", 'This pattern has match groups')
在调用
str.contains之前。这是一个简单的示例，演示了问题(和解决方案):
# import warnings
# warnings.filterwarnings("ignore", 'This pattern has match groups') # uncomment to suppress the UserWarning
import pandas as pd
df = pd.DataFrame({ 'event_time': ['gouda', 'stilton', 'gruyere']})
urls = pd.DataFrame({'url': ['g(.*)']}) # With a capturing group, there is a UserWarning
# urls = pd.DataFrame({'url': ['g.*']}) # Without a capturing group, there is no UserWarning. Uncommenting this line avoids the UserWarning.
substr = urls.url.values.tolist()
df[df['event_time'].str.contains('|'.join(substr), regex=True)]
打印
script.py:10: UserWarning: This pattern has match groups. To actually get the groups, use str.extract.
df[df['event_time'].str.contains('|'.join(substr), regex=True)]
从正则表达式模式中删除捕获组:
urls = pd.DataFrame({'url': ['g.*']})
避免了UserWarning。