Converting a datetime column back to a string columns? Pandas - Python
If you're using version 0.17.0
or higher then you can call this using .dt.strftime
which is vectorised:
all_data['Order Day new'] = all_data['Order Day new'].dt.strftime('%Y-%m-%d')
** If your pandas version is older than 0.17.0
then you have to call apply
and pass the data to 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 strftime
on the column as it doesn't understand Series
as a param hence the error
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.