How to assign a value by month for timeseries data?

I have a time series data to which I am trying to assign a value based on which month the sample falls in. Here is an example of what I am looking for:

I think I should be using groupby(), but I was not sure how to do that for a timeseries. Anyone know how use timestamp feature here to derive the value column?

Converting the Timestamp from datetime to period and then grouping them helped me assign the values. Below is the required code for above dataframe:

df["Period"] = df['Timestamp'].dt.to_period('M')
df["Value"] = df.groupby(["Period"]).ngroup() + 1

So, I created a new col Period and then used groupby(), ngroup() methods on it to group and assign a unique value to each period and store in Value column.

P.s I added 1 while creating Value as the groups were being assigned from 0 but I wanted the groups to start from 1.

import datetime
timestamps = [datetime.datetime(1984, 1, 2)]

# format - month: value
valuesdict = {1: 1, 2: 2, 3: 3}

values = [valuesdict[i.month] for i in timestamps]
print(values)

This should work for your use case. The timestamps must be of type datetime.datetime.