Finance Expense Categorization Dataset

This dataset contains detailed, structured expense records including transaction dates, amounts, categories, payment methods, merchant details, and location information. It is ideal for personal finance management, business accounting, machine learning classification, and budgeting applications, providing granular insights into spending patterns and expense tracking.

  • opened 49 times
  • last updated 20 Aug 2025
  • by GoMask
The brief that made it

Personal expense tracking and budgeting

Sample rows

preview · 8 of 200 rows · all 20 columns
expense_idstringcurrencystringamountfloatis_business_expensebooleanaddress_statestringuser_idstringtransaction_datedatecategorystringsubcategorystringmerchant_namestringpayment_methodstringreceipt_availablebooleanproject_codestringaddress_streetstringaddress_citystringaddress_postal_codestringaddress_countrystringcreated_atdatetimeupdated_atdatetimedescriptionstring
EXP001USD53.25trueCAUSR-3KJ8Q2ZL2024-04-15FoodRestaurantThe Grove Bistrocredit_cardtrueCODE-2024457 Market StSan Francisco94105US2024-04-15T13:25:08Z2024-04-15T13:30:02ZBusiness lunch at The Grove with client team.
EXP002USD0falseWAUSR-9VD3M5NL2024-02-29OtherRefundPacific Utilitiesbank_transferfalseblank120 Pine AveSeattle98101US2024-02-29T08:15:33ZblankRefund for overcharged utilities bill.
EXP003AUD19.99falseNSWUSR-1ZB7P2XQ2023-12-23EntertainmentStreamingNetflix Australiadebit_cardfalseblank16 George StSydney2000AU2023-12-23T18:05:27ZblankMonthly Netflix subscription for home.
EXP004EUR86.75trueBEUSR-7KH2R9WL2024-04-02TravelTrainDeutsche Bahncredit_cardtruePRJ-2431123 Friedrichstr.Berlin10117DE2024-04-02T09:12:45Z2024-04-02T09:14:00ZBusiness train ticket Berlin to Hamburg.
EXP005CAD45.5falseBCUSR-5CX9N4JB2024-03-29FoodCafeBean & Leafdebit_cardtrueblank555 Burrard StVancouverV6C3A6CA2024-03-29T08:45:16Z2024-03-29T08:46:05ZCoffee and pastries for morning meeting.
EXP006USD1299.99trueILUSR-8DP5S1QK2024-01-18Office SuppliesFurnitureOffice Depotbank_transfertrueMGMT-2024678 Oakwood BlvdChicago60611US2024-01-18T16:02:10Z2024-01-18T16:03:32ZExecutive office chair for new manager.
EXP007CHF10.5falseZHUSR-2FB7L6MC2023-11-04FoodRestaurantZurich Grillcashfalseblank44 BahnhofstrasseZurich8001CH2023-11-04T19:20:12ZblankDinner at Zurich central for personal.
EXP008GBP275.6trueENGUSR-6QJ8T3SC2024-03-13TravelFlightBritish Airwayscredit_cardtrueCONF-202410 PiccadillyLondonW1J9HSGB2024-03-13T12:01:22Z2024-03-13T12:05:05ZFlight to London for conference keynote.

What the 200 rows show

from the 200-row sample

EUR currency stands out: 20 of its 22 rows have is_business_expense = true, against 55 of 178 for the rest.

  • 38%is_business_expense = true
  • 68.3median amount
  • 7payment methods
  • 9categories
  • 11address countries
  • 19subcategories
Is business expense rate by currencyis_business_expense = true
0%50%100%39%USD32 o…63%GBP15 o…9%CAD2 of…91%EUR20 o…6%CHF1 of…0%AUD0 of…22%BRL2 of…38%JPY3 of…
amount200 rows, in bands of 10k
09519018853111001050k90kamount →

Median 68.3, from 0.0 to 85,001.

address_state179 rows with a value · 21 left blank
  1. CA21
  2. ENG21
  3. NY16
  4. ON15
  5. BE10
  6. NSW9
  7. ZH8
  8. GE6
  9. TX6
  10. SP6
20 columns by typefrom the column list below
  • string 14
  • float 1
  • date 1
  • datetime 2
  • boolean 2

Columns

20 columns in four groups
blueprint · 20 columns
columntypedescriptionexample
Text 14 columns
expense_idstringUnique identifier for each expense recorduniqueEXP001
user_idstringUnique identifier for the user or account associated with the expenseUSR-3KJ8Q2ZL
currencystringCurrency code for the transaction (ISO 4217 format, e.g., USD, EUR)8 currenciesUSD
categorystringPrimary category of the expense (e.g., Food, Travel, Utilities, Office Supplies)9 valuesFood
subcategorystringOptional subcategory for more granular classification (e.g., Restaurant, Taxi, Internet)optionalRestaurant
descriptionstringDetailed description or memo for the expenseoptionalBreakfast at Starbucks.
merchant_namestringName of the merchant or vendor where the expense occurredoptionalThe Grove Bistro
payment_methodstringPayment method used for the expense (e.g., credit_card, debit_card, cash, bank_transfer)7 valuescredit_card
project_codestringOptional project or cost center code for business accountingoptionalCODE-2024
address_streetstringStreet address of the merchant or transaction locationoptional457 Market St
address_citystringCity of the merchant or transaction locationoptionalSan Francisco
address_statestringState or province of the merchant or transaction locationoptionalCA
address_postal_codestringPostal or ZIP code of the merchant or transaction locationoptional94105
address_countrystringCountry of the merchant or transaction location (ISO 3166-1 alpha-2 code)11 countries · optionalUS
Numbers 1 column
amountfloatTotal monetary amount of the expense0 or more53.25
Dates and times 3 columns
transaction_datedateDate when the expense transaction occurred2024-04-15
created_atdatetimeTimestamp when the expense record was created2024-04-15T13:25:08Z
updated_atdatetimeTimestamp when the expense record was last updatedoptional2024-04-15T13:30:02Z
True or false 2 columns
is_business_expensebooleanIndicates if the expense is for business purposestrue
receipt_availablebooleanIndicates if a receipt is available for this expenseoptionaltrue

Use it for

  • is business ex…38%75 of 200 rowsmean amount by curren…3.2kUSD167.5GBP56.0CAD4.9kEUR

    A finance dashboard

    The is_business_expense rate, amount by currency and a breakdown of address_state. Excel, Power BI or Tableau.

  • Why do 75 of 200 rows have is_business_expense = true?

    A root-cause class exercise

    Hand out the rows and one question. The answer is in the data, not in the brief.

  • A software demo

    Believable expenses with user_id, transaction_date and amount to fill a screen in front of a buyer.

Not quite right?

Make it yours.

Same 20 columns, your size and your rules. See 20 rows before you pay.

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This dataset200 rows20 columns
Yours10,000 rows20 columnsaddress_street: UK only

blueprint · finance-expense-categorization-dataset

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
  • Categorize expenses by type
  • Segment by transaction date
  • Flag uncategorized entries
  • Include account-level summaries
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
finance-expense-categorization-dataset

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