日期差异：Excel 与 Python 中的不同结果

Question

I have a pandas dataframe with two dates columns with timestamp ( i want to keep time stamp) I want to get the difference in days between those two dates, I used the below. It works just fine.

mergethetwo['diff_days']=(mergethetwo['todaydate']-mergethetwo['LastLogon']).dt.days

The doubt is, when I got the difference between those two dates in Excel, it gave me different number.

In python for example the difference between

5/15/2020 1:48:00 PM (LastLogon) and 6/21/2020 12:00:00 AM(todaydate) is 36.

However, in Excel using

DATEDIF =(LastLogon,todaydate,"d") 5/15/2020 1:48:00 PM and 6/21/2020 12:00:00 AM is 37 days !

Why is the difference? Which one should I trust? As I have 30,000 + rows I can't go through all od them to confirm.

Appreciate your support Thank you

Answer 1

Excel DATEDIF with "D" seems to count "started" days ( dates , as the name of the function says...); whilst the Python timedelta gives the actual delta in time - 36.425 days:

import pandas as pd

td = pd.to_datetime("6/21/2020 12:00:00 AM")-pd.to_datetime("5/15/2020 1:48:00 PM")
# Timedelta('36 days 10:12:00')

td.days
# 36

td.total_seconds() / 86400
# 36.425

You will get the same result if you do todaydate-LastLogon in Excel, without using any function.