将 strptime 函数应用于 pandas 系列
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Applying strptime function to pandas series
提问by thron of three
I have a pandas DataSeries that contains a string formatted date in the form of:
我有一个 Pandas DataSeries，它包含一个字符串格式的日期，格式为：
2016-01-14 11:39:54
2016-01-14 11:39:54
I would like to convert the string to a timestamp.
我想将字符串转换为时间戳。
I am using the applymethod to attemp to pass 'datetime.strptime' to each element of the series
我正在使用该apply方法尝试将“datetime.strptime”传递给系列的每个元素
date_series = date_string.apply(datetime.strptime, args=('%Y-%m-%d %H:%M:%S'))
date_series = date_string.apply(datetime.strptime, args=('%Y-%m-%d %H:%M:%S'))
When I run the code, I get the following error:
当我运行代码时，出现以下错误：
strptime() takes exactly 2 arguments (18 given)
strptime() takes exactly 2 arguments (18 given)
my questions are (1) am I taking the correct approach, (2) why is strptimeconverting my args into 18 arguments?
我的问题是 (1) 我是否采取了正确的方法，(2) 为什么strptime将我的 args 转换为 18 个参数？
回答by root
Use pd.to_datetime:
date_series = pd.to_datetime(date_string)
In general it's best have your dates as Pandas' pd.Timestampinstead of Python's datetime.datetimeif you plan to do your work in Pandas. You may also want to review the Time Series / Date functionality documentation.
一般来说，如果您打算在 Pandas 中工作，最好将日期设为 Pandas，pd.Timestamp而不是 Python datetime.datetime。您可能还想查看时间序列/日期功能文档。
As to why your applyisn't working, argsisn't being read as a tuple, but rather as a string that's being broken up into 17 characters, each being interpreted as a separate argument. To make it be read as a tuple, add a comma: args=('%Y-%m-%d %H:%M:%S',).
至于为什么你apply不工作，args不是作为一个元组读取，而是作为一个被分解为 17 个字符的字符串，每个字符都被解释为一个单独的参数。要使其被视为元组，请添加逗号：args=('%Y-%m-%d %H:%M:%S',)。
This is standard behaviour in Python. Consider the following example:
这是 Python 中的标准行为。考虑以下示例：
x = ('a')
y = ('a',)
print('x info:', x, type(x))
print('y info:', y, type(y))
x info: a <class 'str'>
y info: ('a',) <class 'tuple'>
