How to give space before and after on a pandas dataframe object?

Question

I have a dataframe_

df  
date    
13MAY2022
13MAY2022
13MAY2022
13MAY2022

How can we give space between these objects?

My expectations like this_

df  
date        modified_date
13MAY2022   13 MAY 2022
13MAY2022   13 MAY 2022
13MAY2022   13 MAY 2022
13MAY2022   13 MAY 2022

Answer 1

Here is another str.replace approach using lookarounds:

regex = r'(?<=[A-Z])(?![A-Z])|(?<![A-Z])(?=[A-Z])'
df["modified_date"] = df["date"].str.replace(regex, r' ', regex=True)

Here is a regex demo showing that the replacement logic is working.

Answer 2

Use Series.str.replace by non digits with add space before and after same values:

df['modified_date'] = df['date'].str.replace(r'(\D+)', r' \1 ', regex=True)
#if need append and prepend space only for uppercase letters
df['modified_date'] = df['date'].str.replace(r'([A-Z]+)', r' \1 ', regex=True)
print (df)
        date modified_date
0  13MAY2022   13 MAY 2022
1  13MAY2022   13 MAY 2022
2  13MAY2022   13 MAY 2022
3  13MAY2022   13 MAY 2022

With converting to datetimes:

df['modified_date'] = pd.to_datetime(df['date']).dt.strftime('%d %B %Y')
print (df)
        date modified_date
0  13MAY2022   13 May 2022
1  13MAY2022   13 May 2022
2  13MAY2022   13 May 2022
3  13MAY2022   13 May 2022

---

df['modified_date'] = pd.to_datetime(df['date']).dt.strftime('%d %B %Y').str.upper()
print (df)
        date modified_date
0  13MAY2022   13 MAY 2022
1  13MAY2022   13 MAY 2022
2  13MAY2022   13 MAY 2022
3  13MAY2022   13 MAY 2022

Answer 3

One way to do it:

import dateutil.parser

df['modified_date'] = df['date'].apply(
    lambda x: dateutil.parser.parse(x).strftime("%d %b %Y").upper())

dateutil.parser.parse(x) infers a datetime object from the string, strftime("%d %b %Y") turns the datetime object back into a string in the form "day month year", and then I put upper() at the end to match the original case. If you have dates not in this format, though, this won't give a result in the original format.