pandas 从数据框中的字符串中删除字符
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Removing character from string in dataframe
提问by Adrian Y
I have a dataframe, one column of which is filled with entries like this:
我有一个数据框，其中一列充满了这样的条目：
2017-03-01T09:30:00.436
2017-03-01T09:30:00.444
...
Is there a way to convert the entire column into datetime format?
有没有办法将整个列转换为日期时间格式？
So far I have tried using
到目前为止，我已经尝试使用
str.replace('T',' ') over iterrows()
as well as slicing methods but neither seems to work. Any help will be greatly appreciated. Thanks!
以及切片方法，但似乎都不起作用。任何帮助将不胜感激。谢谢！
回答by jezrael
Use regex=Truefor replacesubstrings:
使用regex=True的replace字符串：
df['col'] = df['col'].replace('T', ' ', regex=True)
But maybe need only to_datetime:
但也许只需要to_datetime：
df = pd.DataFrame({'col':['2017-03-01T09:30:00.436','2017-03-01T09:30:00.444']})
df['col'] = pd.to_datetime(df['col'])
print (df['col'])
0 2017-03-01 09:30:00.436
1 2017-03-01 09:30:00.444
Name: col, dtype: datetime64[ns]
回答by jgummersall
to_datetime()should work in converting it to datetime format
to_datetime()应该可以将其转换为日期时间格式
