How to add month column to a date column in python?

Question

date['Maturity_date'] = data.apply(lambda data: relativedelta(months=int(data['TRM_LNTH_MO'])) + data['POL_EFF_DT'], axis=1)

Tried this also:

date['Maturity_date'] = date['POL_EFF_DT'] + date['TRM_LNTH_MO'].values.astype("timedelta64[M]")

TypeError: 'type' object does not support item assignment

For me working first solution with `date.apply` instead `data.apply` nice. — jezrael, Apr 08 '20 at 07:38

score 0 · Accepted Answer · answered Apr 08 '20 at 07:40

0

import pandas as pd
import datetime

#Convert the date column to date format
date['date_format'] = pd.to_datetime(date['Maturity_date'])

#Add a month column
date['Month'] = date['date_format'].apply(lambda x: x.strftime('%b'))

answered Apr 08 '20 at 07:40

M PAUL

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score 0 · Answer 2 · answered Nov 27 '20 at 19:16

If you are using Pandas, you may use a resource called: "Frequency Aliases". Something very out of the box:

# For "periods": 1 (is the current date you have) and 2 the result, plus 1, by the frequency of 'M' (month).

import pandas as pd

_new_period = pd.date_range(_existing_date, periods=2, freq='M')

Now you can get exactly the period you want as the second element returned:

# The index for your information is 1. Index 0 is the existing date.

_new_period.strftime('%Y-%m-%d')[1]

# You can format in different ways. Only Year, Month or Day. Whatever.

Consult this link for further information

How to add month column to a date column in python?

2 Answers2