Create Dataframe Exatracting Words With Period After A Specicfic Word

I’ve the following text:

text_main = "The following leagues were identified: sport: basketball league: N.B.A. style: c.123>d sport: soccer league: E.P.L. sport: football league: N.F.L. style: c.124>d. The other leagues aren't that important."

I need to extract all the sport names (which are coming after sport:) and style (which are coming after style:) and create new columns as sports and style. I’m trying the following code to extract the main sentence (sometimes text are huge):

m = re.split(r'(?<=\.)\s+(?=[A-Z]\w+)', text_main)
text = list(filter(lambda x: re.search(r'leagues were identified', x, flags=re.IGNORECASE), m))[0]
print(text)

The following leagues were identified: sport: basketball league: N.B.A. style: c.123>d sport: soccer league: E.P.L. sport: football league: N.F.L. style: c.124>d.

Then I’m extracting the sport and style names and putting them into a dataframe:

if 'sport:' in text:
    sport_list = re.findall(r'sport:\W*(\w+)', text)

df = pd.DataFrame({'sports': sport_list})
print(df)

    sports
0   basketball
1   soccer
2   football

However, I’m having troubles to extract the styles, as all the styles have period . after the 1st letter (c) and few has sign >. Also, not all the sports have style info.

Desired output:

    sports        style
0   basketball    c.123>d
1   soccer        NA
2   football      c.124>d

What would be the smartest way of doing it? Any suggestions would be appreciated. Thanks!

>Solution :

You can use

\bsport:\s*(\w+)(?:(?:(?!\bsport:).)*?\bstyle:\s*(\S+))?

See the regex demo. Details:

• \b – a word boundary
• sport: – a fixed string
• \s* – zero or more whitespaces
• (\w+) – Group 1: one or more word chars
• (?: – start of an optional non-capturing group:
  • (?:(?!\bsport:).)*? – any char other than line break chars, zero or more occurrences but as few as possible, that does not start a whole word sport: char sequence
  • \bstyle: – a whole word style and then :
  • \s* – zero or more whitespaces
  • (\S+) – Group 1: one or more non-whitespace chars
• )? – end of the optional non-capturing group.

See the Python demo:

import pandas as pd
text_main = "The following leagues were identified: sport: basketball league: N.B.A. style: c.123>d sport: soccer league: E.P.L. sport: football league: N.F.L. style: c.124>d. The other leagues aren't that important."
matches = re.findall(r'\bsport:\s*(\w+)(?:(?:(?!\bsport:).)*?\bstyle:\s*(\S+))?', text_main)
df = pd.DataFrame(matches, columns=['sports', 'style'])

Output:

>>> df
       sports    style
0  basketball   c.123>d
1      soccer          
2    football  c.124>d.