这是一道将DataFrame的日期数据转换为python能认识的题目。这里重点讲一下to_datetime的部分使用。 首先说一下: 1/17/07 has the format “%m/%d/%y” 17-1-2007 has the format “%d-%m-%Y” 这是一部分的时间转换格式,通过以上的格式,你可以将DataFrame中的时间格式转 ...
to_datetime() 代码语言:javascript 复制 pandas.to_datetime(arg, errors='raise', dayfirst=False, yearfirst=False, utc=None, format=None, exact=True, unit=None, infer_datetime_format=False, origin='unix', cache=True) 代码语言:javascript 复制 df = pd.DataFrame({"Year":[2022,2021,2022], ...
The pandas.to_datetime() function is used to convert an argument (string, list, dictionary, or a column in a DataFrame) into a datetime object, allowing for easier date manipulation and analysis in Pandas. How do I use to_datetime() to convert a column of date strings to datetime objects?
pandas 来源:https://stackoverflow.com/questions/75633689/converting-multiple-datetime-formats-in-single-column-to-standard-datetime 关注 举报 1条答案按热度按时间 gmol16391# import pandas as pd df = pd.DataFrame({'Date': ['03 Mar 2023 00:00', '03 Mar 2023 00:00', '03 Mar 2023 00:00'...
jrebackaddedDatetimeAPI DesignlabelsMar 17, 2016 Copy link ContributorAuthor sschecommentedMar 17, 2016 I'm trying out a few date formats and want to determine the correct one. If I try'%Y-%m-%d'and'%Y-%m-%d %H:%M:%S', they both match which isn't quite true. ...
You can use dt.strftime if you need to convert datetime to other formats (but note that then dtype of column will be object ( string )): import pandas as pd df = pd.DataFrame({'DOB': {0: '26/1/2016', 1: '26/1/2016'}}) print (df) DOB 0 26/1/2016 1 26/1/2016 df['...
最简单的方法是使用to_datetime：
pandas.to_datetime pandas.to_timedelta pandas.date_range pandas.bdate_range pandas.period_range pandas.timedelta_range pandas.infer_freq pandas.interval_range pandas.eval pandas.tseries.api.guess_datetime_format pandas.util.hash_array pandas.util.hash_pandas_object pandas.api.interchange.from_dataframe...
# try to infer format first, works well for standard formats df['datetime'] = pd.to_datetime(df['fecha'], errors='coerce') # where the conversion resulted in NaT (no value), use the excplicit format m = df['datetime'].isna() ...
File"D:\RuanJianAnZhuang\miniconda\envs\myvn\lib\site-packages\pandas\io\formats\format.py", line1810,in_format_strings values = self.values.astype(object) File"D:\RuanJianAnZhuang\miniconda\envs\myvn\lib\site-packages\pandas\core\arrays\datetimes.py", line666,inastypereturndtl.DatetimeLikeAr...