Timestamp object has no attribute dt

user_8121824 0
Viewed 52594

I am trying to convert a new column in a dataframe through a function based on the values in the date column, but get an error indicating "Timestamp object has no attribute dt." However, if I run this outside of a function, the dt attribute works fine.

Any guidance would be appreciated.

This code runs with no issues:

sample = {'Date': ['2015-07-02 11:47:00', '2015-08-02 11:30:00']}
dftest = pd.DataFrame.from_dict(sample)
dftest['Date'] = pd.to_datetime(dftest['Date'])
display(dftest.info())
dftest['year'] = dftest['Date'].dt.year
dftest['month'] = dftest['Date'].dt.month

This code gives me the error message:

sample = {'Date': ['2015-07-02 11:47:00', '2015-08-02 11:30:00']}
dftest = pd.DataFrame.from_dict(sample)
dftest['Date'] = pd.to_datetime(dftest['Date'])
def CALLYMD(dftest):
    if dftest['Date'].dt.month>9:
        return str(dftest['Date'].dt.year) + '1231'
    elif dftest['Date'].dt.month>6: 
        return str(dftest['Date'].dt.year) + '0930'
    elif dftest['Date'].dt.month>3: 
        return str(dftest['Date'].dt.year) + '0630'
    else:
        return str(dftest['Date'].dt.year) + '0331'
    

dftest['CALLYMD'] = dftest.apply(CALLYMD, axis=1)

Lastly, I'm open to any suggestions on how to make this code better as I'm still learning.

dataframe timestamp datetime python
3 Answers

I'm guessing you should remove .dt in the second case. When you do apply it's applying to each element, .dt is needed when it's a group of data, if it's only one element you don't need .dt otherwise it will raise {AttributeError: 'Timestamp' object has no attribute 'dt'}

reference: https://stackoverflow.com/a/48967889/13720936

user_137209360

After looking at the timestamp documentation, I found removing the .dt and just doing .year and .month works. However, I'm still confused as to why it works in the first code but does not work in the second code.

user_81218240

here is how to create a yearmonth bucket using the year and month

for key, item in df.iterrows(): 
     year=pd.to_datetime(item['Date']).year
     month=str(pd.to_datetime(item['Date']).month)
     df.loc[key,'YearMonth']="{:.0f}{}".format(year,month.zfill(2))
user_40011770
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