I wish to replace the blank space w a '.' and then shorten the length of the numerical values (ex 2022) by removing the first 2 characters.

Data

df =

ID  Date        
AA  Q1 2022     
BB  Q4 2024     
CC  Q2 2025     
CC  Q3 2025     
CC  Q1 2021     
DD  Q2 2021 

Desired

ID  Date
AA  Q1.22
BB  Q4.24
CC  Q2.25
CC  Q3.25
CC  Q1.21
DD  Q2.21

Doing

1.replace blank with '.'

df.Date.fillna(value=., inplace=True)

2.Remove first 2 digits from year

df["Date"].str[2:]

3. possibly concat?

Any suggestion is appreciated.

CodePudding user response：

Use Series.replace with a regex pattern (regex=True):

df['Date'] = df['Date'].replace(r'\s\d{2}','.',regex=True)

print(df)

   ID   Date
0  AA  Q1.22
1  BB  Q4.24
2  CC  Q2.25
3  CC  Q3.25
4  CC  Q1.21
5  DD  Q2.21

Explanation regex pattern \s\d{2}:

• \s matches any whitespace character
• \d matches a digit
• {2} matches the previous token (i.e. the digit) exactly 2 times