Annual – Global – Number of automated teller machines (ATMs) per 100,000 adults – Belarus – Both sexes or no breakdown by sex – 15 years old and over – Total – Total (national average) or no breakdown – Total or no breakdown by education level – Total or no breakdown by Occupation – No breakdown – No breakdown – No breakdown by disability – No breakdown – No breakdown [A.G.FB_ATM_TOTL.112._T.Y_GE15._T._T._T._T._T._T._T._T._T]

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Source

Provider
International Monetary Fund
Dataset
Sustainable Development Goals, IMF Inputs
Series ID
[IMF/UNSDG_IMF_INPUTS/A.G.FB_ATM_TOTL.112._T.Y_GE15._T._T._T._T._T._T._T._T._T]
Updated by DBnomics on
April 5, 2022

Dimensions

Frequency [FREQ]
Annual [A]
REPORTING_TYPE [REPORTING_TYPE]
Global [G]
SERIES [SERIES]
Number of automated teller machines (ATMs) per 100,000 adults [FB_ATM_TOTL]
REF_AREA [REF_AREA]
Belarus [112]
SEX [SEX]
Both sexes or no breakdown by sex [_T]
AGE [AGE]
15 years old and over [Y_GE15]
URBANISATION [URBANISATION]
Total [_T]
INCOME_WEALTH_QUANTILE [INCOME_WEALTH_QUANTILE]
Total (national average) or no breakdown [_T]
EDUCATION_LEV [EDUCATION_LEV]
Total or no breakdown by education level [_T]
OCCUPATION [OCCUPATION]
Total or no breakdown by Occupation [_T]
CUST_BREAKDOWN [CUST_BREAKDOWN]
No breakdown [_T]
COMPOSITE_BREAKDOWN [COMPOSITE_BREAKDOWN]
No breakdown [_T]
DISABILITY_STATUS [DISABILITY_STATUS]
No breakdown by disability [_T]
ACTIVITY [ACTIVITY]
No breakdown [_T]
PRODUCT [PRODUCT]
No breakdown [_T]
Period Value OBS_STATUSUNIT_MULT
200410.857921465768A0
200515.3987050865993A0
200618.9524902121819A0
200725.6743266461461A0
200830.2475002945184A0
200933.3721171451507A0
201037.9229983608796A0
201141.226053125555A0
201246.1740305574519A0
201351.1769829766426A0
201454.7693122094382A0
201555.5480957284723A0
201655.29196134807A0
201755.6671750109495A0
201853.8938462461458A0
201954.9569111707409A0
202055.8593573229882A0