[A.G.FB_ATM_TOTL.104._T.Y_GE15._T._T._T._T._T._T._T._T._T] Annual – Global – Number of automated teller machines (ATMs) per 100,000 adults – Myanmar – 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
Updated on DBnomics on March 22, 2025 (3:18 AM)
- from
- 2012=0.091
- to
- 2019=6.863
- min:
- 0.091
- max:
- 6.863
- avg:
- 2.984
- σ:
- 2.261
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Period | Value | [NATURE] | [OBS_STATUS] | [SOURCE_DETAIL] | [UNIT_MULT] |
---|---|---|---|---|---|
2012 | 0.0906517821934353 | C | A | IMF | 0 |
2013 | 0.606442011486932 | C | A | IMF | 0 |
2014 | 1.68348793942303 | C | A | IMF | 0 |
2015 | 1.95390966410294 | C | A | IMF | 0 |
2016 | 2.66161288812107 | C | A | IMF | 0 |
2017 | 4.37887535270112 | C | A | IMF | 0 |
2018 | 5.6340980061969 | C | A | IMF | 0 |
2019 | 6.86315863189676 | C | A | IMF | 0 |
Dimension | Dimension value |
---|---|
[FREQ] Frequency | [A] Annual |
[REPORTING_TYPE] REPORTING_TYPE | [G] Global |
[SERIES] SERIES | [FB_ATM_TOTL] Number of automated teller machines (ATMs) per 100,000 adults |
[REF_AREA] REF_AREA | [104] Myanmar |
[SEX] SEX | [_T] Both sexes or no breakdown by sex |
[AGE] AGE | [Y_GE15] 15 years old and over |
[URBANISATION] URBANISATION | [_T] Total |
[INCOME_WEALTH_QUANTILE] INCOME_WEALTH_QUANTILE | [_T] Total (national average) or no breakdown |
[EDUCATION_LEV] EDUCATION_LEV | [_T] Total or no breakdown by education level |
[OCCUPATION] OCCUPATION | [_T] Total or no breakdown by Occupation |
[CUST_BREAKDOWN] CUST_BREAKDOWN | [_T] No breakdown |
[COMPOSITE_BREAKDOWN] COMPOSITE_BREAKDOWN | [_T] No breakdown |
[DISABILITY_STATUS] DISABILITY_STATUS | [_T] No breakdown by disability |
[ACTIVITY] ACTIVITY | [_T] No breakdown |
[PRODUCT] PRODUCT | [_T] No breakdown |