Pandas extract information which starts with [\s\d_/] and ends in [\s\d_/]

Your regex is not correct for what you're looking to match, which is easy to see with visualization tools like https://regexper.com/ (no affiliation; just grabbed the top Google result).

You have: [^\s\d_/]lemon|apple|coconut[\s\d_/$]

but likely want something like: [\s\d_/](lemon|apple|coconut)[\s\d_/]

You can use

df['Paths'].str.findall(r'(?<![^\W_])(?:lemon|apple|coconut)(?![^\W_])').str.join(", ")
df['Paths'].str.findall(r'(?<![^\W\d_])(?:lemon|apple|coconut)(?![^\W\d_])').str.join(", ")

See the regex demo (and regex demo #2), the regex matches

• (?<![^\W_]) - a location that is not immediately preceded with a char other than a non-word char and an underscore (it is a left-hand word boundary with the _ subtracted from it)
• (?:lemon|apple|coconut) - a non-capturing group matching any of the words inside the group
• (?![^\W_]) - a location that is not immediately followed with a char other than a non-word char and an underscore (it is a right-hand word boundary with the _ subtracted from it).

If you use (?<![^\W\d_]) and (?![^\W\d_]) your word boundaries will be letter boundaries, i.e. it will be \b with digits and underscore subtracted from it. See the Python demo:

import pandas as pd
df = pd.DataFrame({"Paths":["/var/prj/lemon_123/xyz", "/var/prj/123_apple/coconut", "/var/prj/lemonade/coconutapple", "/var/prj/apple/lemon"]})
df['Paths'].str.findall(r'(?<![^\W_])(?:lemon|apple|coconut)(?![^\W_])').str.join(", ")
#  0             lemon
#  1    apple, coconut
#  2                  
#  3      apple, lemon
#  Name: Paths, dtype: object