how to convert the int Date to datetime

i’ve combined many dateframes but the date is not match as it’s look like (datetime & int) as below , it’s contains float number and datetime date.

Date
2022-05-31 00:00:00
2022-05-31 00:00:00
2022-05-31 00:00:00
2022-05-31 00:00:00
44713.0
44713.0
44713.0
44713.0
44713.0
44713.0
44713.0

i’m tried to use the below codes but i found error messages (ValueError: mixed datetimes and integers in passed array) or i found this error elso(‘<‘ not supported between instances of ‘Timestamp’ and ‘int’)

So how can i change the date formatting to be all like dd-mm-yyyy

The full code:-

import pandas as pd
import datetime as dt
import xlrd
from datetime import datetime


    IN_df=pd.concat([IN_df1, IN_df2,IN_df3,IN_df4,IN_df5,IN_df6,IN_df7,IN_df8]).fillna("")
    IN_df=IN_df[(IN_df['Status']=='No Show')&(IN_df['Site']== 'Cairo')]
    IN_df=IN_df.filter(items=['Date','SF ID','Name','Direct Manager','Department','Shift','Status','Reporting Feedback']).reset_index(drop=True).convert_dtypes()
    
    IN_df['Date']=IN_df['Date'].apply(xlrd.xldate_as_datetime, args=(0,))
    IN_df['Date']=pd.to_datetime(IN_df['Date']).dt.date
    
    IN_df.tail()

Answer

Check Below code:

import pandas as pd 


df = pd.DataFrame({'date':['2022-05-31 00:00:00','2022-05-31 00:00:00','44713','2022-05-31 00:00:00','44713']})

df['new_date'] = df.apply(lambda x:  pd.to_datetime(int(x.date), unit='D', origin='1899-12-30') if x.date.isdigit() else pd.to_datetime(x.date) , axis=1)

df

Output:

Updating code as per OP comment below:

df = pd.DataFrame({'date':['2022-05-31 00:00:00','2022-05-31 00:00:00','44743.0','2022-05-31 00:00:00','44713']})

df['new_date'] = df.apply(lambda x:  pd.to_datetime(float(x.date), unit='D', origin='1899-12-30') if x.date[:-2].isdigit() else pd.to_datetime(x.date) , axis=1)

df

Output: