Other
20 columns
200 rows
8 formats

Local Food Delivery Order Patterns

This dataset provides detailed, time-stamped records of local food delivery orders, including customer demographics, restaurant information, ordered items, payment methods, and delivery outcomes. It enables granular analysis of demand patterns, peak ordering times, and customer preferences, supporting operational optimization and targeted marketing strategies.

opened 8 times
last updated 5 Sept 2025
by GoMask

The brief that made it

Demand forecasting and peak hour analysis for food delivery services

Sample rows

preview · 8 of 200 rows · all 20 columns

order_idstring	payment_methodstring	customer_ratingfloat	delivery_address_citystring	order_datetimedatetime	customer_idstring	customer_ageinteger	customer_genderstring	delivery_address_streetstring	delivery_address_statestring	delivery_address_postal_codestring	delivery_address_countrystring	restaurant_idstring	restaurant_namestring	restaurant_cuisinestring	order_total_amountfloat	delivery_statusstring	delivery_time_minutesinteger	special_instructionsstring	ordered_itemsstring
ORD0001	credit_card	4.7	San Francisco	2024-03-01T11:32:15	CUST1001	29	female	451 Maple Ave	CA	94121	USA	REST5001	Sushi Zen	Japanese	42.5	delivered	32	No wasabi please	California Roll x2 @12.50; Miso Soup x1 @5.00; Sashimi Platter x1 @12.50
ORD0002	cash	5	Boston	2024-03-01T19:44:58	CUST1002	54	male	612 Oak St	MA	02118	USA	REST5002	Burger House	American	28	delivered	56	Extra napkins	Cheeseburger x2 @9.00; Fries x2 @5.00
ORD0003	debit_card	blank	Seattle	2024-03-02T08:16:42	CUST1003	blank	prefer_not_to_say	832 Pine Lane	WA	98103	USA	REST5003	Cafe Paris	French	18.75	pending	blank	blank	Croissant x2 @3.50; Quiche x1 @7.75; Coffee x1 @4.00
ORD0004	debit_card	4.2	Chicago	2024-03-02T23:59:37	CUST1004	8	male	127 Willow Dr	IL	60640	USA	REST5004	Fiesta Mexicana	Mexican	15.2	delivered	22	Birthday order, add candle	Chicken Taco x2 @4.50; Horchata x1 @3.20; Churro x2 @1.50
ORD0005	credit_card	4.9	Toronto	2024-03-03T13:18:09	CUST1005	62	female	98 Main St	ON	M5V 2T6	Canada	REST5005	Punjab Palace	Indian	54.1	delivered	78	blank	Butter Chicken x1 @18.00; Garlic Naan x2 @5.00; Mango Lassi x2 @6.05; Samosa x2 @7.00
ORD0006	credit_card	blank	New York	2024-03-03T17:55:13	CUST1006	33	female	304 Elm St	NY	10011	USA	REST5006	Little Italy	Italian	38.75	preparing	blank	blank	Margherita Pizza x1 @14.00; Lasagna x1 @18.75; Cannoli x2 @3.00
ORD0007	mobile_wallet	3.8	Austin	2024-03-04T12:25:24	CUST1007	16	female	1902 Spruce Ct	TX	78702	USA	REST5007	Thai Orchid	Thai	21	delivered	28	No peanuts	Pad Thai x1 @11.00; Spring Rolls x2 @5.00
ORD0008	other	blank	London	2024-03-04T18:37:10	CUST1008	blank	other	230 Cedar Rd	ENG	W1D 3LN	UK	REST5008	Dragon House	Chinese	0	pending	blank	Test order, ignore	Water x1 @0.00
ORD0009	mobile_wallet	4.4	Los Angeles	2024-03-05T20:06:59	CUST1009	28	male	72 Birch Ave	CA	90036	USA	REST5009	Pho Palace	Vietnamese	26.9	delivered	34	blank	Pho Beef x1 @12.00; Spring Rolls x2 @7.45
ORD0010	debit_card	4.8	Dublin	2024-03-05T21:40:21	CUST1010	45	female	123 River St	LEIN	D02 X285	Ireland	REST5010	Emerald Eats	Irish	36	delivered	40	Gluten free bread	Irish Stew x1 @16.00; Soda Bread x2 @5.00; Guinness Pie x1 @10.00
ORD0011	cash	blank	Sydney	2024-03-06T07:22:45	CUST1011	blank	prefer_not_to_say	76 South St	NSW	2000	Australia	REST5011	Outback Grill	Australian	17.6	preparing	blank	No sauce	Kangaroo Burger x1 @11.60; Chips x1 @6.00
ORD0012	credit_card	5	Vancouver	2024-03-06T15:15:56	CUST1012	80	male	88 Queen St	ON	V6B 1T7	Canada	REST5012	Maple Diner	Canadian	65.85	delivered	97	Extra cheese	Poutine x2 @12.50; Maple Salmon x2 @18.75; Nanaimo Bar x3 @7.05
ORD0013	credit_card	4.6	Boston	2024-03-07T12:05:28	CUST1013	36	female	234 Market Rd	MA	02116	USA	REST5013	Trattoria Roma	Italian	49.1	delivered	41	No onions	Spaghetti Carbonara x2 @13.00; Tiramisu x2 @7.55; Caprese Salad x1 @8.00
ORD0014	cash	4.9	Cape Town	2024-03-07T18:37:53	CUST1014	59	female	17 Glen Rd	WC	8001	South Africa	REST5014	Braai House	South African	77	delivered	112	Spicy please	Boerewors x2 @24.00; Pap x2 @8.00; Chakalaka x2 @7.50
ORD0015	debit_card	blank	Manchester	2024-03-08T11:09:11	CUST1015	blank	female	16 King St	ENG	M1 4PH	UK	REST5015	Curry Corner	Indian	22	pending	blank	Mild spice	Chicken Tikka x1 @10.00; Rice x1 @4.00; Naan x2 @4.00
ORD0016	mobile_wallet	blank	New York	2024-03-08T16:22:39	CUST1016	25	male	4217 Broadway	NY	10032	USA	REST5016	Green Bowl	Vegetarian	29	out_for_delivery	blank	No onions	Veggie Wrap x2 @9.00; Smoothie x2 @5.50
ORD0017	credit_card	4.3	Los Angeles	2024-03-09T19:02:18	CUST1017	37	female	21 Fifth Ave	CA	90067	USA	REST5017	Wok Express	Chinese	34	delivered	49	blank	Kung Pao Chicken x1 @14.00; Fried Rice x1 @10.00; Egg Roll x2 @5.00
ORD0018	credit_card	4.8	Philadelphia	2024-03-10T15:11:02	CUST1018	60	male	731 Liberty St	PA	19123	USA	REST5018	Pat's Steaks	American	87	delivered	116	Extra cheese	Philly Cheesesteak x3 @16.00; Fries x3 @7.00; Soda x2 @5.00
ORD0019	debit_card	blank	San Jose	2024-03-10T20:40:36	CUST1019	31	male	8 Park Rd	CA	95112	USA	REST5019	Burrito Bros	Mexican	24.5	preparing	blank	blank	Super Burrito x1 @14.50; Chips x1 @4.00; Salsa x2 @3.00
ORD0020	debit_card	3.9	San Francisco	2024-03-11T09:17:50	CUST1020	24	female	611 Market St	CA	94105	USA	REST5020	Bagel Bistro	Bakery	19	delivered	20	Birthday treat	Bagel x2 @4.00; Coffee x2 @3.50; Pastry x1 @4.00

What the 200 rows show

from the 200-row sample

Debit_card (payment method) stands out: mean customer_rating is 4.0, against 4.6 for the rest.

4.5median customer_rating
4customer genders
5delivery statuses
6delivery address countries
19delivery address states
27restaurant cuisines

Mean customer_rating by payment_method115 rows

customer_rating115 rows, in bands of 0.2

Median 4.5, from 3.2 to 5.0.

delivery_address_city200 rows · top 10 of 30 values

Boston24
New York22
San Francisco17
Toronto16
London16
Cape Town11
Seattle10
Los Angeles9
Dublin9
Sydney9

20 columns by typefrom the column list below

string 15
integer 2
float 2
datetime 1

Columns

20 columns in three groups

blueprint · 20 columns
column	type	description	example
Text 15 columns
`order_id`	string	Unique identifier for each food delivery orderunique	ORD0001
`customer_id`	string	Unique identifier for the customer placing the order	CUST1001
`customer_gender`	string	Gender of the customermale · female · other · prefer_not_to_say · optional	female
`delivery_address_street`	string	Street address for delivery	451 Maple Ave
`delivery_address_city`	string	City for delivery address	San Francisco
`delivery_address_state`	string	State for delivery address	CA
`delivery_address_postal_code`	string	Postal code for delivery address	94121
`delivery_address_country`	string	Country for delivery address6 countries	USA
`restaurant_id`	string	Unique identifier for the restaurant fulfilling the order	REST5001
`restaurant_name`	string	Name of the restaurant	Sushi Zen
`restaurant_cuisine`	string	Primary cuisine type of the restaurantoptional	Japanese
`payment_method`	string	Payment method used for the ordercredit_card · debit_card · cash · mobile_wallet · other	credit_card
`delivery_status`	string	Current status of the delivery5 values	delivered
`ordered_items`	string	List of items ordered, each with item name, quantity, and price	Water x1 @0.00
`special_instructions`	string	Any special instructions provided by the customeroptional	No wasabi please
Numbers 4 columns
`customer_age`	integer	Age of the customer at the time of order0 to 120 · optional	29
`order_total_amount`	float	Total amount charged for the order0 or more	42.5
`delivery_time_minutes`	integer	Time taken for delivery in minutes0 or more · optional	32
`customer_rating`	float	Customer rating for the order (1.0 to 5.0)1 to 5 · optional	4.7
Dates and times 1 column
`order_datetime`	datetime	Timestamp when the order was placed	2024-03-01T11:32:15

Use it for

A dashboard
Customer_rating by payment_method and a breakdown of delivery_address_city. Excel, Power BI or Tableau.
Why do the 24 debit_card rows have a mean customer_rating of 4.0?
A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
Orders200
ORD00014.7credit_c…
ORD00025cash
ORD0003debit_ca…
A software demo
Believable orders with order_datetime, customer_id and customer_age to fill a screen in front of a buyer.

This dataset200 rows20 columns

Yours10,000 rows20 columnsdelivery_address_street: UK only

blueprint · local-food-delivery-order-patterns

Behind this dataset

Same schema. As many rows as you need.

These 200 rows came out of a blueprint — 20 columns with generation rules behind each one. Open it in Data Factory to retune a column, add your own, wire in foreign keys, and run it at the size you actually need.

Rules it was built with

Record delivery time and order value
Flag repeat customers
Include cuisine type
Track peak order periods

Rows1,000 rows10,000 rows100,000 rows1,000,000 rows

Open the blueprint in Data Factory

1 credit per row. New accounts start with 25 free credits.

Exports: CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence: yours to use, including commercially
API slug: local-food-delivery-order-patterns

What should your data show?

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Sample rows

What the 200 rows show

Columns

Use it for

A dashboard

A root-cause class exercise

A software demo

Make it yours.

Same schema. As many rows as you need.

More in Other

What should your data show?