Butter_bread_Milk

import pandas as pd
from mlxtend.frequent_patterns import apriori , association_rules
from mlxtend.preprocessing import TransactionEncoder

transation = [['butter','bread','milk'],
['butter','flour','milk','sugar'],
['butter','eggs' ,'milk','salt'],
['eggs'],
['butter','flour','milk','salt']]

te = TransactionEncoder()
te_array = te.fit(transation).transform(transation)
df = pd.DataFrame(te_array, columns=te.columns_ )

freq_pattern = apriori(df , min_support=0.8 , use_colnames=True)

print(freq_pattern)

rules = association_rules(freq_pattern , metric='support' , min_threshold=0.05)
print(rules)