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

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Step 1: Read the data\n",

"transactions = [['eggs', 'milk','bread'],\n", "['eggs', 'apple'],\n", "['milk', 'bread'],\n", "['apple', 'milk'],\n", "['milk', 'apple', 'bread']]

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step 2: Encode the data\n", "te=TransactionEncoder()\n", "te_array=te.fit(transactions).transform(transactions)

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

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Step 3: Find the frequent itemsets \n", "

freq_items = apriori(df, min_support = 0.5, use_colnames = True)

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print(freq_items)

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Step 4: Generate the association rules \n", "

rules = association_rules(freq_items, metric ='support', min_threshold=0.05)

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rules = rules.sort_values(['support', 'confidence'], ascending =[False,False])

print(rules)