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frommlxtend.frequent_patterns import apriori, association_rules
importmatplotlib.pyplot as plt
import pandas as pd
import numpy as np
df = pd.read_csv('C:\\Users\\aliet\\Downloads\\retail_dataset.csv')
## Print first 10 rows
df.head(10)
items = set()
for col in df:
items.update(df[col].unique())
    print(items)
itemset = set(items)
encoded_vals = []
for index, row in df.iterrows():
rowset = set(row)
   labels = {}
uncommons = list(itemset - rowset)
commons = list(itemset.intersection(rowset))
   for uc in uncommons:
      labels[uc] = 0
   for com in commons:
      labels[com] = 1
encoded_vals.append(labels)
#encoded_vals[0]
ohe_df = pd.DataFrame(encoded_vals)
freq_items = apriori(ohe_df, min_support=0.2, use_colnames=True, verbose=1)
freq_items.head(7)