Apriori og

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

transactions=[
['Bread','Milk'],
['Bread','Diaper','Beer','Eggs'],
['Milk','Diaper','Beer','Coke'],
['Bread','Milk','Diaper','Beer'],
['Bread','Milk','Diaper','Coke']
]

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

freq_patterns=apriori(df,min_support=0.6,use_colnames=True)
print(freq_patterns)

rules=association_rules(freq_patterns,metric='support',min_threshold=0.5)
print(rules)