Python 熊猫时间戳系列到字符串？
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pandas timestamp series to string?
提问by StatsStudent
I am new to python (coming from R), and I am trying to understand how I can convert a timestamp series in a pandas dataframe (in my case this is called df['timestamp']) into what I would call a string vector in R. is this possible? How would this be done?
我是 python 的新手（来自 R），我试图了解如何将 Pandas 数据帧中的时间戳系列（在我的情况下称为df['timestamp']）转换为我在 R 中称为字符串向量的内容。这可能吗？ ? 这将如何完成？
I tried df['timestamp'].apply('str'), but this seems to simply put the entire column df['timestamp']into one long string. I'm looking to convert each element into a string and preserve the structure, so that it's still a vector (or maybe this a called an array?)
我试过了df['timestamp'].apply('str')，但这似乎只是将整个列df['timestamp']放入一个长字符串中。我希望将每个元素转换为字符串并保留结构，以便它仍然是一个向量（或者这可能是一个称为数组？）
回答by piRSquared
Consider the dataframe df
考虑数据框 df
df = pd.DataFrame(dict(timestamp=pd.to_datetime(['2000-01-01'])))
df
timestamp
0 2000-01-01
Use the datetime accessor dtto access the strftimemethod. You can pass a format string to strftimeand it will return a formatted string. When used with the dtaccessor you will get a series of strings.
使用 datetimedt访问器访问该strftime方法。您可以将格式字符串传递给strftime它，它会返回一个格式化的字符串。与dt访问器一起使用时，您将获得一系列字符串。
df.timestamp.dt.strftime('%Y-%m-%d')
0 2000-01-01
Name: timestamp, dtype: object
Visit strftime.orgfor a handy set of format strings.
访问strftime.org一组方便的格式字符串。
回答by VinceP
Use astype
用 astype
>>> import pandas as pd
>>> df = pd.to_datetime(pd.Series(['Jul 31, 2009', '2010-01-10', None]))
>>> df.astype(str)
0 2009-07-31
1 2010-01-10
2 NaT
dtype: object
returns an array of strings
返回一个字符串数组
回答by MarMat
Following on from VinceP's answer, to convert a datetime Series in-place do the following:
继 VinceP 的回答之后，要就地转换日期时间系列，请执行以下操作：
df['Column_name']=df['Column_name'].astype(str)
df['Column_name']=df['Column_name'].astype(str)
