ATM Cash Refill Forecasts

This dataset provides detailed records of ATM cash withdrawals and refill events, including transaction amounts, timestamps, ATM locations, and operator information. It enables comprehensive analysis of cash usage patterns and supports predictive modeling for optimal ATM cash management, reducing operational costs and minimizing cash-out risks.

  • opened 5 times
  • last updated 12 Jul 2025
  • by GoMask
The brief that made it

Forecasting ATM cash demand to optimize refill schedules

Sample rows

preview · 8 of 200 rows · all 16 columns
atm_idstringtransaction_typestringwithdrawal_amountfloatlocation_countrystringatm_location_namestringlocation_street_addressstringlocation_citystringlocation_statestringlocation_postal_codestringtransaction_datedatetransaction_timestringrefill_amountfloatatm_balance_after_transactionfloatcurrencystringrefill_operator_idstringnotesstring
ATM101withdrawal120USADowntown Branch123 Main StNew YorkNY100012024-03-1508:15:22013040USDblankblank
ATM102withdrawal60USAGrand Plaza Mall456 Market AveLos AngelesCA900172024-03-1512:45:09015420USDblankblank
ATM103withdrawal240USAEastside Grocery789 BroadwayChicagoIL606012024-03-1618:32:41011260USDblankblank
ATM104refill0USAUnion Station1 Metro DrBostonMA021182024-03-1606:01:101800018000USDREF201Routine morning refill
ATM105withdrawal420USACity Center Bank56 Elm StHoustonTX770022024-03-1714:23:1809300USDblankblank
ATM106refill0USALakeside Mall1500 Lake DrMinneapolisMN554022024-03-1705:45:001200012000USDREF204blank
ATM107withdrawal30USA24Hr Pharmacy99 Madison AveDallasTX752012024-03-1809:09:5908000USDblankblank
ATM108withdrawal950USAAirport Concourse1 Airport RdAtlantaGA303202024-03-1821:57:44012500USDblankLarge withdrawal after event

What the 200 rows show

from the 200-row sample
  • 37.5median withdrawal_amount
  • 15currencies
  • 0median refill_amount
  • 9,730median atm_balance_after_transaction
transaction_type200 rows by value
065130126withdrawal63%74refill37%
withdrawal_amount200 rows, in bands of 1,000
09519018266012101105,00010kwithdrawal_amount →

Median 37.5, from 0.0 to 10,000.

location_country200 rows · top 10 of 23 values
  1. USA75
  2. GBR20
  3. AUS17
  4. CAN14
  5. DEU11
  6. ESP10
  7. IND8
  8. ARE8
  9. SGP6
  10. FRA5
16 columns by typefrom the column list below
  • string 12
  • float 3
  • date 1

Columns

16 columns in three groups
blueprint · 16 columns
columntypedescriptionexample
Text 12 columns
atm_idstringUnique identifier for the ATM machineATM101
atm_location_namestringName or description of the ATM's location (e.g., branch name, mall name)Downtown Branch
location_street_addressstringStreet address of the ATM location123 Main St
location_citystringCity where the ATM is locatedNew York
location_statestringState or region where the ATM is locatedNY
location_postal_codestringPostal or ZIP code of the ATM location10001
location_countrystringCountry where the ATM is locatedUSA
transaction_typestringType of transaction: withdrawal or refillwithdrawal · refillwithdrawal
transaction_timestringTime of the transaction in HH:MM:SS format (24-hour clock)optional08:15:22
currencystringCurrency code for the transaction amounts (e.g., USD, EUR)USD
refill_operator_idstringIdentifier for the operator or team performing the refill (if applicable)optionalREF201
notesstringOptional notes or comments about the transaction (e.g., issues, anomalies)optionalRoutine morning refill
Numbers 3 columns
withdrawal_amountfloatAmount of cash withdrawn in this transaction (0 if not a withdrawal)0 or more · optional120
refill_amountfloatAmount of cash refilled in this transaction (0 if not a refill)0 or more · optional0
atm_balance_after_transactionfloatCash balance in the ATM immediately after the transaction0 or more · optional13040
Dates and times 1 column
transaction_datedateDate of the cash withdrawal or refill event2024-03-15

Use it for

  • median withdra…37.5200 rowsmean withdrawal amoun…607.8withdr…0.0refill

    A finance dashboard

    Withdrawal_amount by transaction_type and a breakdown of location_country. 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 atms with atm_location_name, location_street_address and location_city to fill a screen in front of a buyer.

Not quite right?

Make it yours.

Same 16 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 rows16 columns
Yours1,000 rows16 columnsatm_location_name: UK only

blueprint · atm-cash-refill-forecasts

Behind this dataset

Same schema. As many rows as you need.

These 200 rows came out of a blueprint — 16 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
  • ATM ID, withdrawal count, amount, and refill date
  • Simulate patterns by location type
  • Flag emergency vs. scheduled refills
  • No user-level data
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
atm-cash-refill-forecasts

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