Funny item co-occurrences in 3 million Instacart orders

The other day I was idly wondering what are the strangest combinations of items people buy at grocery stores. The kind of shopping cart that makes the cashier snicker and later tell his friends, "Dude, can you believe this guy came in and only bought condoms and apples?"

So I fired up Claude and started looking for any receipt data I could find.

Grocery stores keep this kind of data very close to the chest. There are consumer apps that collect receipt data (like ReceiptHog and Fetch) but they presumably just sell it to hedge funds or something. Years ago, however, Instacart open-sourced data from 3 million orders as part of a machine learning competition to optimize their recommendation algorithm. The data is still available on Kaggle and it's very rich. What we want is the exact opposite of a recommendation algorithm but this data should work fine.

The Instacart data set includes the following:

• 3,214,874 orders
• ~10 products per order on average
• 49,688 unique products
• 134 unique "aisles" (product categories)

So all we have to do is look at every cart and see which combinations of items are least likely to appear, right? Let's try that. For the sake of testing a few groupings, I included pairs, triples, and quads.

Product co-occurrence count: pairs

count	product 1	product 2
1	Banana	Extra Fancy Unsalted Mixed Nuts
1	Organic Hass Avocado	Baby Cucumbers
1	Organic Hass Avocado	Trail Mix
1	Bag of Organic Bananas	Bananas
1	Limes	Trail Mix
1	Organic Garnet Sweet Potato (Yam)	Clementines
1	Organic Avocado	Zero Calorie Cola
1	Organic Fuji Apple	Baby Cucumbers

Note: maximum pair co-occurrence count is 62,341.

Product co-occurrence count: triples

count	product 1	product 2	product 3
1	Banana	Bag of Organic Bananas	Soda
1	Banana	Bag of Organic Bananas	Clementines
1	Banana	Bag of Organic Bananas	Sparkling Mineral Water
1	Banana	Bag of Organic Bananas	Flat Parsley, Bunch
1	Banana	Bag of Organic Bananas	Sparkling Water
1	Banana	Bag of Organic Bananas	Fresh CA Grown Eggs
1	Banana	Bag of Organic Bananas	Red Seedless Grapes

Note: maximum triple co-occurrence count is 15,066.

Product co-occurrence count: quads

count	product 1	product 2	product 3	product 4
1	Banana	Bag of Organic Bananas	Organic Baby Spinach	Half & Half
1	Banana	Bag of Organic Bananas	Organic Whole Milk	Organic Zucchini
1	Banana	Bag of Organic Bananas	Organic Avocado	Organic Half & Half
1	Banana	Bag of Organic Bananas	Strawberries	Organic Lemon
1	Banana	Bag of Organic Bananas	Organic Hass Avocado	Spring Water
1	Banana	Bag of Organic Bananas	Organic Yellow Onion	Organic Fuji Apple

Note: maximum quad co-occurrence count is 3,828.

Hmm. These aren't very interesting. Maybe that's because there are a ton of combinations that only occur once, and we're only looking at the top 5-10, so we need a better way to sort them.

There are roughly 1.2 billion possible unique pairs of products (unordered pairs from a set of 50,000). About 97% of them never occur in our data, and of the ones that do, around 22 million pairs occur exactly once. When almost every pair is tied at zero or one, "least common" becomes meaningless.

So how should we sort? Claude had a good idea to rank each combination by "lift": how frequently it actually appears divided by how frequently we'd expect it to appear. If you have two very common items like apples and oranges, you'd expect them to co-occur a lot. If they don't, that's notable, and the pair should rank higher. Now let's try that.

Product co-occurrence by lift: pairs

lift	product 1	product 2
0.0007	Banana	Extra Fancy Unsalted Mixed Nuts
0.0010	Organic Hass Avocado	Baby Cucumbers
0.0012	Organic Hass Avocado	Trail Mix
0.0017	Bag of Organic Bananas	Bananas
0.0019	Limes	Trail Mix
0.0020	Organic Garnet Sweet Potato (Yam)	Clementines
0.0021	Organic Avocado	Zero Calorie Cola
0.0025	Organic Fuji Apple	Baby Cucumbers

Product co-occurrence by lift: triples

lift	product 1	product 2	product 3
0.0016	Banana	Bag of Organic Bananas	Soda
0.0019	Banana	Bag of Organic Bananas	Clementines
0.0032	Banana	Bag of Organic Bananas	Sparkling Mineral Water
0.0043	Banana	Bag of Organic Bananas	Flat Parsley, Bunch
0.0047	Banana	Bag of Organic Bananas	Sparkling Water
0.0056	Banana	Bag of Organic Bananas	Fresh CA Grown Eggs

Product co-occurrence by lift: quads

lift	product 1	product 2	product 3	product 4
0.0111	Banana	Bag of Organic Bananas	Organic Baby Spinach	Half & Half
0.0128	Banana	Bag of Organic Bananas	Organic Whole Milk	Organic Zucchini
0.0137	Banana	Bag of Organic Bananas	Organic Avocado	Organic Half & Half
0.0148	Banana	Bag of Organic Bananas	Strawberries	Organic Lemon
0.0155	Banana	Bag of Organic Bananas	Organic Hass Avocado	Spring Water

I think I see a pattern... Of course it's unlikely that someone would buy both organic and non-organic bananas which points to the bigger issue that 50,000 products is too granular. Every product has a dozen+ variants. There are 28 different condom products and 110 different apple products in the produce department alone, so our silly "condoms + apples" example will struggle to rise above the noise.

We have 49,688 products (too narrow) sorted into 134 aisles (too broad). We need something in between. Time to build a classifier! But how?

Enter GPC

It turns out nearly 100% of grocery retailers use a product classification system called GS1 Global Product Classification (GPC). GPC is an ontology of everything you might find at a big-box or a grocer. It divides the universe of products into segments (camping, footwear, lighting, tools, food…), which contain families (bread, beverages, fruits, meat, vegetables…), which contain classes (beans, melons, peppers, fungi…), which contain bricks (chanterelles, enokitake, truffles, morels…).

Some bricks go even deeper into subtypes or attributes, e.g. Morels can have a growing method of CONVENTIONAL or ORGANIC, but for our purposes we can stop at the brick level. There are 5,318 bricks in the full GPC system. Many segments (plumbing, live animals, industrial systems, etc.) aren't sold at grocery stores, so we can drop them. That leaves 9 grocery-relevant segments with 1,697 total bricks, and our products only populate about 1,000 of them. This feels like the right level of granularity and yields a 50x reduction in complexity!

Time to fire up the ol' classifier. Since we're squeezing ~50,000 products into ~1,000 bricks, I used a standard two-stage approach:

1. Shortlist the brick options for each product. First, get embeddings for every product and every brick. I did this locally using qwen3-embedding:8b. Then, for each product, find its 10 nearest bricks by cosine similarity.
2. Choose the best brick. Use an LLM to select the best-fit brick for each product from the 10 options. This cost me ~$5 and took a few minutes, running 60 requests in parallel using gpt-4.1-mini. The full product-to-brick mapping is here in case it's useful to anyone else.

Now let's run our co-occurrence algorithm again and see if using bricks rather than products yields better results.

Brick co-occurrence by lift: pairs

lift	brick 1	brick 2
0.004	Wine – Still	Grains/Cereal – Not Ready to Eat (Frozen)
0.007	Spirits	Grains/Cereal – Not Ready to Eat (Frozen)
0.012	Beer	Baby Leaves
0.013	Spirits	Dates
0.019	Wine – Still	Stem Vegetables (Fresh Cut)
0.020	Spirits	Fish – Unprepared/Unprocessed
0.022	Beer	Fish – Unprepared/Unprocessed (Shelf Stable)

Brick co-occurrence by lift: triples

lift	brick 1	brick 2	brick 3
0.014	Cheese	Wine – Still	Frozen Grains/Cereal
0.019	Milk	Savoury Grain Meals (Shelf Stable)	Spirits
0.019	Cucumbers	Baby/Infant Specialised Foods	Spirits
0.020	Kale	Clementines	Wine – Still
0.021	Broccoli	Baby/Infant Specialised Foods	Spirits

Brick co-occurrence by lift: quads

lift	brick 1	brick 2	brick 3	brick 4
0.027	Banana	Strawberries	Garlic	Spirits
0.028	Milk Substitutes	Strawberries	Carrots	Spirits
0.032	Banana	Milk Substitutes	Baby Food	Spirits
0.035	Banana	Milk	Wine – Still	Savoury Grain Meals

Far less repetition! But there's still something missing. Just because these are the rarest combinations doesn't make them interesting. For some reason people don't buy wine and frozen rice together, or beer and fish. So what? How do we make these combos spicier? Funnier?

We need a humor index for products.

What's funny?

Claude dutifully scored all ~1,000 grocery bricks with a 0–1 humor score, based roughly on how taboo they are or how likely they'd be to come up in a stand-up comedy routine. The general ranges:

score	# of bricks	examples
0.0 – 0.1	726	Milk, Armenian Cucumber, Herbs, Prepared Fish
0.1 – 0.3	271	Confectionery, Cooking Wines, Breath Fresheners, Ear Care
0.3 – 0.5	50	Energy Drinks, Toilet Paper, Denture Care, Diet Aids
0.5 – 0.7	12	Wart/Corn Treatments, Foot Care, Medical Lubricants, Appetite Control
0.7 – 1.0	15	Condoms, Intimate Lubricants, Contraception, Enemas/Douches

(Humor scores for all bricks are here)

Now we can multiply each combo's aggregate humor into the ranking alongside its rarity, and we should get much better results. Let's try that.

Funniest rare combos: pairs

brick 1	brick 2
Garlic	Diarrhoea Remedies
Kale	Enemas/Douches
Garlic	Enemas/Douches
Flat Parsley	Condoms
Baby Food	Enemas/Douches
Coriander	Enemas/Douches
Baby Food	Condoms
Baby Food	Adult Diapers

Funniest rare combos: triples

brick 1	brick 2	brick 3
Cheese	Almond Milk	Intimate Lubricants
Milk	Almond Milk	Intimate Lubricants
Apples	Avocados	Intimate Lubricants
Onions	Raspberries	Antacids/Flatulence Remedies
Apples	Tinned Vegetables	Condoms
Milk	Almond Milk	Enemas/Douches

Funniest rare combos: quads

brick 1	brick 2	brick 3	brick 4
Milk	Almond Milk	Tomatoes	Antacids/Flatulence Remedies
Apples	Avocados	Ice Cream	Antacids/Flatulence Remedies
Cheese	Milk	Apples	Condoms
Bananas	Apples	Kale	Antacids/Flatulence Remedies
Bananas	Yogurt	Milk	Enemas/Douches

Much better! Some of these even made me laugh out loud. Kale and an enema? Parsley and condoms? Adult diapers and baby food? There's gotta be a joke in there somewhere.

That said, in a large enough shopping cart, funny combos become more likely just by chance. If you're ordering all your groceries for the week you're going to pick up everything, from the boring to the spicier. So what happens if we look only at small carts, where the entire order is just 2 or 3 items?

Funniest small carts: 2 items

item 1	item 2
Vitamin D Milk	Ultra Thin Condoms
Cola	Ultra Thin Condoms
Bag of Organic Bananas	Anti-Diarrheal
Italian Bread	Ultra Thin Condoms
Oreo Chocolate Sandwich Cookies	Personal Lubricant
Bag of Organic Bananas	Incontinence Underwear

Funniest small carts: 3 items

item 1	item 2	item 3
String Cheese	Potato Chips	Omeprazole Acid Reducer
Black Cherry Yogurt	Hass Avocado	Omeprazole Acid Reducer
String Cheese	Black Cherry Yogurt	Personal Lubricant
String Cheese	Italian Bread	Personal Lubricant
Vitamin D Milk	Italian Bread	Anti-Diarrheal
Bag of Organic Bananas	Cola	Personal Lubricant

Small orders are less common but we still got some fun ones. Oreos and lube? Sounds like a good time!