Transactions_dataset

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

transactions = [['Apple','Mango','PineApple'],
['Apple','Orange'],
['Mango' , 'Apple' , 'Orange'],
['PineApple','Orange']]

te = TransactionEncoder()
te_array = te.fit(transactions).transform(transactions)

df = pd.DataFrame(te_array , columns=te.columns_)

freq_item = apriori(df , min_support=0.5 , use_colnames=True)
print(freq_item)

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