I have a dataframe with a column like that
COL1
PACK[30% /2 prod.(if fidelity)]
PACK[3.85 € /2 prod.(if fidelity)]
PACK[40% /2nd prod.]
PACK[3.5 € /2 prod.]
I want create other column as following according COL1
fidelity_perc fidelity_euro rem_perc rem_eu
30 3,85 40 3,5
using regex.
For PACK[40% /2nd prod.] I did (?<=PACK\[)\d+(?=%) but it's also walk for PACK[30% /2 prod.(if fidelity)] and I don't want this.
To get the PACK[40% /2nd prod.], you can use
df['COL1'].str.extract(r'PACK\[(\d[\d.]*)%[^][()]*]', expand=False)
See this regex demo.
To get the PACK[30% /2 prod.(if fidelity)], you can use
df['COL1'].str.extract(r'PACK\[(\d[\d.]*)%[^][]*fidelity[^][]*]', expand=False)
See this regex demo
Similarly, if you need to only find a value if there is a + sign, just replace fidelity with \+:
df['COL1'].str.extract(r'PACK\[(\d[\d.]*)%[^][]*\+[^][]*]', expand=False)
Details
PACK\[ - a literal PACK[ string(\d[\d.]*) - Capturing group 1: a digit an then any zero or more digits or dots as many as possible% - a % sign[^][]* - any zero or more chars other than [ and ] as many as possible\+ - a plusfidelity - a fidelity substring[^][]* - any zero or more chars other than [ and ] as many as possible[^][()]* - any zero or more chars other than [, ], ( and ) as many as possible] - a ] char.