Digital Wallet Transaction Dataset

This dataset provides granular, transaction-level data on digital wallet usage, including top-ups, peer-to-peer transfers, and merchant payments. It features rich contextual information such as user, wallet, merchant, device, and location details, making it ideal for payment analytics, fraud detection, and fintech product development.

  • opened 22 times
  • last updated 20 Aug 2025
  • by GoMask
The brief that made it

Payment behavior analysis and segmentation

Sample rows

preview · 8 of 200 rows · all 18 columns
transaction_idstringtransaction_typestringamountfloatmerchant_categorystringuser_idstringtransaction_datetimedatetimecurrencystringstatusstringsource_wallet_idstringdestination_wallet_idstringmerchant_idstringmerchant_namestringtopup_methodstringfee_amountfloatfailure_reasonstringlocation_citystringlocation_countrystringdevice_typestring
TXN-1A3B8C7Dtop-up150.75blankUSR-9H8G7F6E2023-03-14T09:15:22ZUSDcompletedblankblankblankblankcard2.5blankNew YorkUSmobile
TXN-2B4C9D8Etransfer1200blankUSR-2J5K3L1N2023-05-27T17:42:09ZEURpendingWLT-7A1B2C3DWLT-5E6F7G8Hblankblankblank10blankBerlinDEdesktop
TXN-3C5D1E9Fmerchant-payment32.99retailUSR-5M6N2O7P2023-07-19T12:30:45ZGBPcompletedWLT-8J2K4L6MMCT-3X7Y9Z2AMCT-3X7Y9Z2ATesco Expressblank0blankLondonGBmobile
TXN-4D6E2F1Gtop-up75blankUSR-6P3Q1R8S2023-04-02T08:57:11ZUSDcompletedblankblankblankblankbank-transfer1.5blankChicagoUSdesktop
TXN-5E7F3G2Htransfer300.5blankUSR-7T4U9V5W2023-06-21T15:10:34ZINRcompletedWLT-2F7G1H3JWLT-9K5L8M2Nblankblankblank3blankMumbaiINmobile
TXN-6F8G4H3Imerchant-payment260foodUSR-8W5X2Y1Z2023-08-04T20:22:18ZUSDfailedWLT-3K6L9M8NMCT-5C7B9D2FMCT-5C7B9D2FUber Eatsblank5Insufficient wallet balanceSan FranciscoUSmobile
TXN-7G9H5I4Jtop-up500blankUSR-9Z8A1B2C2023-09-10T16:40:20ZCADcompletedblankblankblankblankcash0blankTorontoCApos
TXN-8H1I6J5Ktransfer99.99blankUSR-1C2D3E4F2023-10-02T13:15:55ZUSDcompletedWLT-1Q2W3E4RWLT-5T6Y7U8Iblankblankblank1blankLos AngelesUSdesktop

What the 200 rows show

from the 200-row sample
  • 100.0median amount
  • 4statuses
  • 4topup methods
  • 4device types
  • 9currencies
  • 16location countries
transaction_type200 rows by value
0357069top-up35%63transfer32%68merchant-pay…34%
amount200 rows, in bands of 1,000
0901801809511403,0006,000amount →

Median 100.0, from 8.6 to 5,250.

merchant_category68 rows with a value · 132 left blank
  1. retail38
  2. food27
  3. transport2
  4. other1
18 columns by typefrom the column list below
  • string 15
  • float 2
  • datetime 1

Columns

18 columns in three groups
blueprint · 18 columns
columntypedescriptionexample
Text 15 columns
transaction_idstringUnique identifier for each transactionuniqueTXN-1A3B8C7D
user_idstringUnique identifier for the wallet user initiating the transactionUSR-9H8G7F6E
transaction_typestringType of transaction: top-up, transfer, or merchant paymenttop-up · transfer · merchant-paymenttop-up
currencystringCurrency code (ISO 4217) for the transaction amount9 currenciesUSD
statusstringCurrent status of the transactionpending · completed · failed · cancelledcompleted
source_wallet_idstringIdentifier of the wallet from which funds are debited (for transfers and payments)optionalWLT-7A1B2C3D
destination_wallet_idstringIdentifier of the wallet or merchant account receiving fundsoptionalWLT-5E6F7G8H
merchant_idstringUnique identifier for the merchant (for merchant payments)optionalMCT-3X7Y9Z2A
merchant_namestringName of the merchant (for merchant payments)optionalTesco Express
merchant_categorystringCategory of the merchant (e.g., retail, food, transport)4 categories · optionalretail
topup_methodstringMethod used for top-up transactions (e.g., bank transfer, card, cash)bank-transfer · card · cash · other · optionalcard
failure_reasonstringReason for transaction failure, if applicable12 reasons · optionalExceeded transfer limit
location_citystringCity where the transaction occurred (if available)optionalNew York
location_countrystringCountry where the transaction occurred (if available)optionalUS
device_typestringType of device used for the transaction (e.g., mobile, desktop, POS)mobile · desktop · pos · other · optionalmobile
Numbers 2 columns
amountfloatMonetary amount of the transaction in the wallet's currency0.01 or more150.75
fee_amountfloatTransaction fee charged, if any0 or more · optional2.5
Dates and times 1 column
transaction_datetimedatetimeDate and time when the transaction occurred2023-03-14T09:15:22Z

15 SQL practice questions for the Digital Wallet Transaction Dataset

Written for this data and checked against it: 12 SQL and 3 Power BI exercises from beginner to advanced. Try the first three free; the practice kit has all 15, a starter .sql file and an answer key with every expected result.

  1. 01BeginnerFreeSELECT · WHERE · ORDER BY

    Completed transfers over 1000

    List all transactions where transaction_type is 'transfer', status is 'completed' and amount is greater than 1000. Return the columns transaction_id, user_id, amount and currency, ordered by amount from highest to lowest, then by transaction_id ascending.

    Tables: digital_wallet_transaction_dataset · your result: 4 columns, 8 rows
  2. 02BeginnerFreeDISTINCT · ORDER BY

    Distinct currencies used

    Return each distinct currency found in the data as a single column named currency, sorted alphabetically.

    Tables: digital_wallet_transaction_dataset · your result: 1 columns, 9 rows
  3. 03BeginnerFreeGROUP BY · COUNT

    Transactions per type

    Count the transactions for each transaction_type. Return the columns transaction_type and txn_count, ordered by txn_count from highest to lowest, then by transaction_type ascending.

    Tables: digital_wallet_transaction_dataset · your result: 2 columns, 3 rows
  1. 04Average amount by deviceBeginner
  2. 05Fees collected by statusPower BI
  3. 06Merchant categories with many paymentsIntermediate
  4. 07Amount size bucketsIntermediate
  5. 08Monthly transaction volumeIntermediate
  6. 09Countries above average amountIntermediate
  7. 10Failure rate by device typePower BI
  8. 11Rank merchants by spend within categoryAdvanced
  9. 12Running total of completed amountsAdvanced
  10. 13Spikes versus a user's previous amountAdvanced
  11. 14Percent of total amount by type and statusAdvanced
  12. 15Cumulative completed amount by monthPower BI

Get the practice kit: the full dataset, all 15 exercises, a starter .sql and the answer key. One-time $3.99.

Get the practice kit · $3.99

Use it for

  • median amount100.0200 rowsmean amount by transa…397.5top-up651.0transf…139.0mercha…

    A finance dashboard

    Amount by transaction_type and a breakdown of merchant_category. Excel, Power BI or Tableau.

  • What pattern can you find in 200 rows?

    A class exercise

    Hand out the rows and one question. Everyone works from the same 200 rows.

  • A software demo

    Believable transactions with user_id, transaction_type and transaction_datetime to fill a screen in front of a buyer.

Not quite right?

Make it yours.

Same 18 columns, your size and your rules. See 20 rows before you pay.

Preview 20 rows free

1,000 rows: $1.99 · 10,000: $12.99One-time. No subscription. All prices

This dataset200 rows18 columns
Yours1,000 rows18 columnslocation_city: UK only

blueprint · digital-wallet-transaction-dataset

Behind this dataset

Same schema. As many rows as you need.

These 200 rows came out of a blueprint — 18 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
  • Transaction type, amount, and time tracked
  • Customer ID anonymized
  • Merchant category labels available
  • Fraud label for flagged transactions
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
digital-wallet-transaction-dataset

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