Apriori Implementation.py

import pandas as pd
import numpy as np
from apyori import apriori

st_df=pd.read_csv("Market_Basket_Optimisation.csv",header=None)

#converting dataframe into list of lists
l=[]
for i in range(1,7501):
    l.append([str(st_df.values[i,j]) for j in range(0,20)])

#applying apriori algorithm
association_rules = apriori(l, min_support=0.0045, min_confidence=0.2, min_lift=3, min_length=2)
association_results = list(association_rules)

for i in range(0, len(association_results)):
    print(association_results[i][0])


for item in association_results:
    # first index of the inner list
    # Contains base item and add item
    pair = item[0]
    items = [x for x in pair]
    print("Rule: " + items[0] + " -> " + items[1])
    # second index of the inner list
    print("Support: " + str(item[1]))
    # third index of the list located at 0th position
    # of the third index of the inner list
    print("Confidence: " + str(item[2][0][2]))
    print("Lift: " + str(item[2][0][3]))
    print("-----------------------------------------------------")