I have a list with different and repeated IP Addresses. So I want to extract a unique IP Address from the nested list.
import re
pattern='(\d+.{13,15})'
matches =[re.findall(pattern,str(x)) for x in dfs['Task Category']]
print(matches)
import numpy as np
new_list = list(np.concatenate(matches))
print(new_list)
[['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.115.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.115.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.178.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.91.'], [], [], [], [], [], ['192.168.101.115.'], ['192.168.101.178.'], [], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.62.'], ['192.168.101.91.'], ['192.168.101.82.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.79.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.62.'], ['192.168.101.79.'], ['192.168.101.62.'], ['192.168.101.91.'], ['192.168.101.62.'], ['192.168.101.91.'], ['192.168.101.115.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.62.'], ['192.168.101.79.'], ['192.168.101.115.'], ['192.168.101.91.'], ['192.168.101.115.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.62.'], ['192.168.101.43.'], ['192.168.101.62.'], [], ['192.168.101.62.'], [], ['192.168.101.62.'], ['192.168.101.115.'], ['192.168.101.62.'], ['192.168.101.62.'], ['192.168.101.62.'], ['192.168.101.43.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.62.'], ['192.168.101.82.'], ['192.168.101.91.'], [], ['192.168.101.91.'], ['192.168.101.115.'], ['192.168.101.115.'], ['192.168.101.115.'], ['192.168.101.178.'], ['192.168.101.115.'], ['192.168.101.91.'], ['192.168.101.82.'], ['192.168.101.91.'], ['192.168.101.82.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.62.'], ['192.168.101.82.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.62.'], ['192.168.101.62.'], ['192.168.101.62.'], ['192.168.101.82.'], ['192.168.101.62.'], ['192.168.101.91.'], ['192.168.101.62.'], ['192.168.101.115.'], ['192.168.101.91.'], ['192.168.101.115.'], ['192.168.101.62.'], ['192.168.101.115.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.115.'], ['192.168.101.62.'], ['192.168.101.91.'], ['192.168.101.62.'], ['192.168.101.91.'], ['192.168.101.115.'], ['192.168.101.91.'], ['192.168.101.115.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.62.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.62.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.62.'], ['192.168.101.62.'], ['192.168.101.62.'], ['192.168.101.62.'], ['192.168.101.62.'], ['192.168.101.62.'], ['192.168.101.62.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.91.'], ['192.168.101.252.'], ['192.168.101.252.'], ['192.168.101.252.'], ['192.168.101.252.'], ['192.168.101.252.'], ['192.168.101.252.']
>Solution :
Use a set or a Counter:
set(match for x in dfs['Task Category'] for match in re.findall(pattern,str(x))
Or:
from collections import Counter
Counter(match for x in dfs['Task Category'] for match in re.findall(pattern,str(x))
Or, using pandas:
dfs['Task Category'].str.extractall(f'({pattern})')[0].unique()