将日期时间列转换回字符串列？熊猫 - Python
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Converting a datetime column back to a string columns? Pandas - Python
提问by Colin O'Brien
I'm trying to convert a datetime column back to a string in Pandas dataframe.
我正在尝试将日期时间列转换回 Pandas 数据框中的字符串。
the syntax I have so far is:
我到目前为止的语法是：
all_data['Order Day new'] = dt.date.strftime(all_data['Order Day new'], '%d/%m/%Y')
but this returns the error:
但这会返回错误：
descriptor 'strftime' requires a 'datetime.date' object but received a 'Series'.
描述符“strftime”需要“datetime.date”对象，但收到“Series”。
Can anyone tell me where I'm going wrong.
谁能告诉我哪里出错了。
采纳答案by EdChum
If you're using version 0.17.0or higher then you can call this using .dt.strftimewhich is vectorised:
如果您使用的是版本0.17.0或更高版本，那么您可以使用.dt.strftime矢量化的方式调用它：
all_data['Order Day new'] = all_data['Order Day new'].dt.strftime('%Y-%m-%d')
** If your pandas version is older than 0.17.0then you have to call applyand pass the data to strftime:
** 如果您的 Pandas 版本比0.17.0那时旧，您必须调用apply并将数据传递给strftime：
In [111]:
all_data = pd.DataFrame({'Order Day new':[dt.datetime(2014,5,9), dt.datetime(2012,6,19)]})
print(all_data)
all_data.info()
Order Day new
0 2014-05-09
1 2012-06-19
<class 'pandas.core.frame.DataFrame'>
Int64Index: 2 entries, 0 to 1
Data columns (total 1 columns):
Order Day new 2 non-null datetime64[ns]
dtypes: datetime64[ns](1)
memory usage: 32.0 bytes
In [108]:
all_data['Order Day new'] = all_data['Order Day new'].apply(lambda x: dt.datetime.strftime(x, '%Y-%m-%d'))
all_data
Out[108]:
Order Day new
0 2014-05-09
1 2012-06-19
In [109]:
all_data.info()
<class 'pandas.core.frame.DataFrame'>
Int64Index: 2 entries, 0 to 1
Data columns (total 1 columns):
Order Day new 2 non-null object
dtypes: object(1)
memory usage: 32.0+ bytes
You can't call strftimeon the column as it doesn't understand Seriesas a param hence the error
您不能调用strftime该列，因为它不能理解Series为参数，因此错误
回答by Chris
all_data['Order Day new']=all_data['Order Day new'].astype(str)
I think this is more simple, if the date is already in the format you want it in string form.
我认为这更简单，如果日期已经是您想要的字符串形式的格式。
