How do I get the average month and day from a list of date times?-CodePudding

I have the following list of date times:

date_list = [Timestamp('2015-05-17 00:00:00'), Timestamp('2016-04-28 00:00:00'), Timestamp('2017-05-17 00:00:00'), Timestamp('2018-05-09 00:00:00'), Timestamp('2019-06-04 00:00:00'), Timestamp('2020-04-28 00:00:00')]

How do I get the average day and month from this list? My current code is as follows:

avg_month_day = datetime.strftime(datetime.fromtimestamp(sum(map(datetime.timestamp,date_list))/len(date_list)),"%m-%d")

However, with the inclusion of the year the result of the above code is "11-10" while I believe it should be "05-12".

CodePudding user response：

You're getting that average because the year is being taken into account. You need to construct new timestamps with an identical year in order to get the result you want.

There may be a more elegant solution but here's one that should work just fine:

import pandas as pd

pd.Series(date_list).apply(lambda d: pd.Timestamp(2020, d.month, d.day)).mean()

Output:

Timestamp('2020-05-12 08:00:00')

From there, you can create your datetime object formatted however you want.