Logistics
23 columns
200 rows
8 formats

Purchase Orders

This dataset provides comprehensive B2B purchase order records, including supplier details, product line items, quantities, pricing, delivery schedules, and fulfillment status. It enables detailed tracking of procurement activities, supplier performance, and order fulfillment, supporting analytics for supply chain optimization and financial planning.

opened 6 times
last updated 29 Oct 2025
by GoMask

The brief that made it

Supply chain and procurement analytics

Sample rows

preview · 8 of 200 rows · all 23 columns

purchase_order_idstring	order_statusstring	unit_pricefloat	fulfilledboolean	supplier_statestring	order_datedate	supplier_idstring	supplier_namestring	supplier_contact_namestring	supplier_emailstring	supplier_phonestring	supplier_street_addressstring	supplier_citystring	supplier_postal_codestring	supplier_countrystring	line_item_idstring	product_idstring	product_namestring	quantityinteger	line_totalfloat	delivery_datedate	fulfillment_datedate	order_totalfloat
PO10001	fulfilled	0.75	true	blank	2023-08-15	SUP101	Alpine Foods Ltd	Maria Svensson	m.svensson@alpinefoods.se	+46 8 45678910	Storgatan 12	Stockholm	11428	Sweden	LI10001	PRD1001	Organic Rye Flour	6000	4500	2023-08-25	2023-08-27	4500
PO10002	fulfilled	31.5	true	blank	2023-07-14	SUP102	GlobalTech Ltd.	blank	blank	blank	5 Shenton Way	Singapore	068806	Singapore	LI10002	PRD1002	Thermal Sensors Type-B	250	7875	2023-07-19	2023-07-21	7875
PO10003	fulfilled	2.9	true	MH	2022-11-23	SUP103	Sunrise Textiles	Ravi Kumar	r.kumar@sunrisetex.in	+91 22 23456789	Plot 44, MIDC	Mumbai	400093	India	LI10003	PRD1003	Cotton Yarn 40s	1200	3480	2022-12-02	2022-12-05	3480
PO10004	pending	299.99	false	BE	2023-01-05	SUP104	TechnoParts GmbH	Klaus Meyer	k.meyer@technoparts.de	+49 30 98765432	Siemensstraße 7	Berlin	10179	Germany	LI10004	PRD1004	Precision Gear Set	65	19499.35	2023-01-13	blank	19499.35
PO10005	fulfilled	33.25	true	blank	2024-03-10	SUP105	Nippon Electronics	blank	sales@nippon.co.jp	blank	1 Chome-1-2 Otemachi	Tokyo	100-0004	Japan	LI10005	PRD1005	LCD Display Panel	300	9975	2024-03-15	2024-03-17	9975
PO10006	pending	1.15	false	blank	2023-09-02	SUP106	PortoSea Exports	Ana Silva	ana.silva@portosea.pt	+351 22 1234567	Rua da Alfândega 45	Porto	4050-030	Portugal	LI10006	PRD1006	Frozen Mackerel	5800	6670	2023-09-11	blank	6670
PO10007	fulfilled	0.55	true	blank	2022-05-18	SUP107	Shanghai Tools Co.	blank	blank	blank	No.33 Nanjing Road	Shanghai	200002	China	LI10007	PRD1007	Industrial Drill Bits	7000	3850	2022-05-30	2022-06-02	3850
PO10008	fulfilled	24.99	true	blank	2023-05-10	SUP108	London Chem Supplies	Olivia Scott	olivia.scott@londonchem.co.uk	+44 20 76543210	Unit 4, Thames Park	London	E16 2DQ	UK	LI10008	PRD1008	Lab Acetone 99%	350	8746.5	2023-05-15	2023-05-17	8746.5
PO10009	pending	11.25	false	BC	2022-10-27	SUP109	Baja Produce MX	Juan Mendez	juan.mendez@bajaproduce.mx	+52 664 5551234	Av. Revolución 89	Tijuana	22000	Mexico	LI10009	PRD1009	Fresh Avocados	60	675	2022-11-02	blank	675
PO10010	pending	1.4	false	NSW	2023-10-03	SUP110	Sydney Mining Ltd	Lucas Taylor	blank	+61 2 12345678	100 Pitt Street	Sydney	2000	Australia	LI10010	PRD1010	Iron Ore Grade A	10000	14000	2023-10-17	blank	14000
PO10011	fulfilled	8.75	true	blank	2024-01-20	SUP111	Cape Fresh SA	blank	info@capefresh.co.za	blank	Long Street 22	Cape Town	8001	South Africa	LI10011	PRD1011	Table Grapes	90	787.5	2024-01-29	2024-01-31	787.5
PO10012	pending	1.29	false	blank	2022-03-03	SUP112	Dublin Dairy Ltd	Sean Murphy	s.murphy@dublindairy.ie	+353 1 2345678	O'Connell St 21	Dublin	D01 F5P2	Ireland	LI10012	PRD1012	Pasteurized Milk 2L	100	129	2022-03-09	blank	129
PO10013	fulfilled	6.8	true	blank	2023-06-22	SUP113	Madrid Fruits	Esteban Garcia	esteban.garcia@madridfruits.es	+34 91 8765432	Calle Mayor 15	Madrid	28013	Spain	LI10013	PRD1013	Mandarins Packed	75	510	2023-06-29	2023-07-02	510
PO10014	pending	24	false	blank	2023-04-05	SUP114	Zagreb Metals	blank	blank	+385 1 9999999	Trg Bana Jelačića 7	Zagreb	10000	Croatia	LI10014	PRD1014	Aluminum Plates	30	720	2023-04-11	blank	720
PO10015	fulfilled	27.99	true	blank	2023-11-12	SUP115	Manchester Steelworks	Eleanor Brown	eleanor.brown@steelworks.co.uk	+44 161 1234567	10 Canal Street	Manchester	M1 2BQ	UK	LI10015	PRD1015	Cold Rolled Steel	80	2239.2	2023-11-17	2023-11-19	2239.2
PO10016	pending	420	false	blank	2022-07-19	SUP116	Pretoria Mining SA	blank	blank	+27 12 3456789	Church St 100	Pretoria	0002	South Africa	LI10016	PRD1016	Gold Nuggets	2	840	2022-07-25	blank	840
PO10017	fulfilled	1.25	true	blank	2024-05-01	SUP117	Lisbon Paper SA	Miguel Costa	miguel.costa@lisbonpaper.pt	+351 21 8765432	Avenida da Liberdade 120	Lisbon	1250-146	Portugal	LI10017	PRD1017	Bleached Kraft Pulp	5000	6250	2024-05-11	2024-05-12	6250
PO10018	pending	13.8	false	blank	2023-03-15	SUP118	Dublin Dairy Ltd	blank	blank	blank	O'Connell St 21	Dublin	D01 F5P2	Ireland	LI10018	PRD1018	Cheddar Cheese 1kg	40	552	2023-03-19	blank	552
PO10019	fulfilled	12.35	true	blank	2022-08-25	SUP119	Tokyo Parts Ltd	Kenji Watanabe	k.watanabe@tokyoparts.co.jp	+81 3 44556677	2-8-1 Marunouchi	Tokyo	100-0005	Japan	LI10019	PRD1019	Piston Rings	180	2223	2022-09-02	2022-09-04	2223
PO10020	pending	9.99	false	MA	2023-12-02	SUP120	Boston Med Equip	Helen White	h.white@bostonmed.com	+1 617 5554321	400 Boylston St	Boston	02116	USA	LI10020	PRD1020	Ultrasound Gel 5L	120	1198.8	2023-12-06	blank	1198.8

What the 200 rows show

from the 200-row sample

51%fulfilled = true
6.3median unit_price
18supplier countries
41supplier cities
120median quantity
1,506median line_total

order_status200 rows by value

unit_price200 rows, in bands of 50

Median 6.3, from 0.0 to 460.5.

supplier_state76 rows with a value · 124 left blank

NSW10
VIC8
Shanghai7
IL7
BE6
MH4
Greater London4
Hyogo4
TX3
CA3

23 columns by typefrom the column list below

string 15
integer 1
float 3
date 3
boolean 1

Columns

23 columns in four groups

blueprint · 23 columns
column	type	description	example
Text 15 columns
`purchase_order_id`	string	Unique identifier for the purchase orderunique	PO10001
`supplier_id`	string	Unique identifier for the supplier	SUP101
`supplier_name`	string	Name of the supplier	Alpine Foods Ltd
`supplier_contact_name`	string	Contact person's name at the supplieroptional	Maria Svensson
`supplier_email`	string	Supplier contact email addressoptional	r.kumar@sunrisetex.in
`supplier_phone`	string	Supplier contact phone numberoptional	+46 8 45678910
`supplier_street_address`	string	Supplier's street addressoptional	Storgatan 12
`supplier_city`	string	Supplier's cityoptional	Stockholm
`supplier_state`	string	Supplier's state or provinceoptional	MH
`supplier_postal_code`	string	Supplier's postal or ZIP codeoptional	11428
`supplier_country`	string	Supplier's countryoptional	Sweden
`line_item_id`	string	Unique identifier for the line item within the purchase orderunique	LI10001
`product_id`	string	Unique identifier for the product being ordered	PRD1001
`product_name`	string	Name or description of the product	Organic Rye Flour
`order_status`	string	Overall status of the purchase orderpending · partially fulfilled · fulfilled · cancelled	fulfilled
Numbers 4 columns
`quantity`	integer	Quantity of the product ordered in this line item1 or more	6000
`unit_price`	float	Price per unit of the product0 or more	0.75
`line_total`	float	Total price for this line item (quantity * unit_price)0 or more	4500
`order_total`	float	Total amount for the purchase order (sum of all line totals)0 or more	4500
Dates and times 3 columns
`order_date`	date	Date when the purchase order was created	2023-08-15
`delivery_date`	date	Expected delivery date for this line item	2023-08-25
`fulfillment_date`	date	Date when the line item was fulfilledoptional	2023-08-27
True or false 1 column
`fulfilled`	boolean	Indicates whether the line item has been fulfilled	true

Use it for

A logistics dashboard
The fulfilled rate, unit_price by order_status and a breakdown of supplier_state. Excel, Power BI or Tableau.
Why do 102 of 200 rows have fulfilled = true?
A class exercise
Hand out the rows and one question. Everyone works from the same 200 rows.
Purchase orders200
PO100010.75fulfilled
PO1000231.5fulfilled
PO10004299.99pending
A software demo
Believable purchase orders with order_date, supplier_id and supplier_name to fill a screen in front of a buyer.

This dataset200 rows23 columns

Yours1,000 rows23 columnssupplier_street_address: UK only

blueprint · purchase-orders

Behind this dataset

Same schema. As many rows as you need.

These 200 rows came out of a blueprint — 23 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

PO number unique per order
Order date before requested delivery date
Status: draft, submitted, approved, fulfilled
Line items reference product catalog
Total matches sum of line items

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

Open the blueprint in Data Factory

1 credit per row. Preview 20 rows free. Buy rows for the full run.

Exports: CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence: yours to use, including commercially
API slug: purchase-orders

What should your data show?

No signup. No card.

Sample rows

What the 200 rows show

Columns

Use it for

A logistics dashboard

A class exercise

A software demo

Make it yours.

Same schema. As many rows as you need.

More in Logistics

What should your data show?