convert 6 digit int into to yyyymm in pandas - pandas

Question

I made a file that had three date columns:
pd.DataFrame({'yyyymm':[199501],'yyyy':[1995],'mm':[1],'Address':['AL1'],'Number':[12]})
yyyymm yyyy mm Address Number
0 199501 1995 1 AL1 12
and saved it as a file:
df.to_csv('complete.csv')
I read in the file with:
df=pd.read_csv('complete.csv')
and my 3 date columns are converted to int's, and not dates.
I tried to convert them back to dates with:
df['yyyymm']=df['yyyymm'].astype(str).dt.strftime('%Y%m')
df['yyyy']=df['yyyy'].dt.strftime('%Y')
df['mm']=df['mm'].dt.dtrftime('%m')
with the error:
AttributeError: Can only use .dt accessor with datetimelike values
Very odd, as the command I used to make the datetime column was:
df['yyyymm']=df['col2'].dt.strftime('%Y%m')
Am I missing something? HOw can I convert the 6 digit column back to yyyymm datetime, the 4 digit column to yyyy datetime, and the mm digit column back to datetime?

Answer 1

The columns yyyymm and yyyy and mm are integers. By using .astype(str), you convert these to strings. But a string has no .dt.
You can use pd.to_datetime(..) [pandas-doc] to convert these to a datetime object:
df['yyyymm'] = pd.to_datetime(df['yyyymm'].astype(str), format='%Y%m')
Indeed, this gives us:
>>> pd.to_datetime(df['yyyymm'].astype(str), format='%Y%m')
0 1995-01-01
Name: yyyymm, dtype: datetime64[ns]
The same can be done for the yyyy and mm columns:
>>> pd.to_datetime(df['yyyy'].astype(str), format='%Y')
0 1995-01-01
Name: yyyy, dtype: datetime64[ns]
>>> pd.to_datetime(df['mm'].astype(str), format='%m')
0 1900-01-01
Name: mm, dtype: datetime64[ns]