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.