>>> import mlxtend
>>> from mlxtend.frequent_patterns import apriori
>>> frequent_itemsets = apriori(df, min_support = 0.6, use_colnames = True)
>>> frequent_itemsets
     support                itemsets
0        0.6                 (Apple)
1        0.8                 (Beans)
2        0.6                (Cookie)
3        0.8                  (Eggs)
4        0.6                  (Milk)
5        0.6                (Yogurt)
6        0.6           (Eggs, Apple)
7        0.6         (Cookie, Beans)
8        0.6           (Eggs, Beans)
9        0.6         (Yogurt, Beans)
10       0.6          (Cookie, Eggs)
11       0.6   (Eggs, Cookie, Beans)