>>> import pandas as pd

>>> df = pd.DataFrame({'Date':['15/04/2021', '12/05/2021', '4/6/2021']})
>>> df
         Date
0  15/04/2021
1  12/05/2021
2    4/6/2021

>>> df['Date'] = pd.to_datetime(df['Date'])
>>> df
        Date
0 2021-04-15
1 2021-12-05
2 2021-04-06

>>> df['date_formated'] = df['Date'].dt.strftime('%b %d/%y').str.upper()
>>> df
        Date date_formated
0 2021-04-15     APR 15/21
1 2021-12-05     DEC 05/21
2 2021-04-06     APR 06/21

>>> df.info()
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 3 entries, 0 to 2
Data columns (total 2 columns):
 #   Column         Non-Null Count  Dtype         
---  ------         --------------  -----         
 0   Date           3 non-null      datetime64[ns]
 1   date_formated  3 non-null      object        
dtypes: datetime64[ns](1), object(1)
memory usage: 176.0+ bytes

你需要转换你原来的 Date 列到 datetime 格式（默认情况下，Pandas将日期作为字符串读取）。完成此操作后，只需更改显示格式。
试试这个：

# Convert to datetime

df['Date'] = pd.to_datetime(df['Date'], format='%d/%m/%y')

# Solution for title: change display to 'MMM dd/y'

df['Date'] = df['Date'].dt.strftime('%b %d/%y').astype(str).str.upper()

# Solution for comment: change display to 'MMM dd y'

df['Date'] = df['date'].dt.strftime('%b %d %y').astype(str).str.upper()

试试看-

df.loc['Date'] = pd.to_datetime(df.Date).dt.strftime('%b %d/%y').str.upper()