Pandas dataframe timedelta is giving exceptions

Question

I am trying to get the next month first date based on billDate in a dataframe.

I did this:

import pandas as pd import datetime from datetime import timedelta dt = pd.to_datetime('15/4/2019', errors='coerce') print(dt) print((dt.replace(day=1) + datetime.timedelta(days=32)).replace(day=1))

It is working perfectly, and the output is :

2019-04-15 00:00:00 2019-05-01 00:00:00

Now, I am applying same logic in my dataframe in the below code

df[comNewColName] = (pd.to_datetime(df['billDate'], errors='coerce').replace(day=1) + datetime.timedelta(days=32)).replace(day=1)

But I am getting error like this:

---> 69 df[comNewColName] = (pd.to_datetime(df['billDate'], errors='coerce').replace(day=1) + datetime.timedelta(days=32)).replace(day=1) 70 '''print(df[['billDate']])''' 71 '''df = df.assign(Product=lambda x: (x['Field_1'] * x['Field_2'] * x['Field_3']))'''

TypeError: replace() got an unexpected keyword argument 'day'

You're calling pandas.Series.replace, not datetime.datetime.replace or pandas.Timestamp.replace. — user2357112
– user2357112, Commented Feb 18, 2022 at 8:33
Does this answer your question? Pandas: convert date in month to the 1st day of next month — FObersteiner
– FObersteiner, Commented Feb 18, 2022 at 12:29

jezrael · Accepted Answer · 2022-02-18 08:33:29Z

You can use Series.to_period for month periods, add 1 for next month and then convert back to datetimes by Series.dt.to_timestamp:

print (df) billDate 0 15/4/2019 1 30/4/2019 2 15/8/2019 df['billDate'] = (pd.to_datetime(df['billDate'], errors='coerce', dayfirst=True) .dt.to_period('m') .add(1) .dt.to_timestamp()) print (df) billDate 0 2019-05-01 1 2019-05-01 2 2019-09-01

Thanks, it perfectly working. but logic is complex. that logic should appear like a pseudo code. Then I have to place that expression in my json. My BA team also able to understand.

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