Market_Basket_Apriori

!pip install efficient_apriori
import pandas as pd
import numpy as np
from efficient_apriori import apriori

# 數據加載
dataset = pd.read_csv('./Market_Basket_Optimisation.csv', header=None)
print(dataset.shape)

 

print(transcations)

# 將數據存放到transactions中
transcations = []
for i in range(0, dataset.shape[0]):
    temp = []
    for j in range(dataset.shape[1]):
        if str(dataset.values[i,j]) != 'nan':
            temp.append(str(dataset.values[i,j]))
    transcations.append(temp)
print(transcations)

itemsets, rules = apriori(transcations, min_support=0.05, min_confidence=0.2)
print('頻繁項集：', itemsets)
print('關聯規則：', rules)