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[UNSDG_​IMF_​INPUTS] Sustainable Development Goals, IMF Inputs

Updated by provider on March 21, 2025 (12:00 AM).

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Frequency [FREQ] (1)
REPORTING_TYPE [REPORTING_​TYPE] (1)
SERIES [SERIES] (16)
REF_AREA [REF_​AREA] (196)
SEX [SEX] (1)
AGE [AGE] (2)
URBANISATION [URBANISATION] (1)
INCOME_WEALTH_QUANTILE [INCOME_​WEALTH_​QUANTILE] (1)
EDUCATION_LEV [EDUCATION_​LEV] (1)
OCCUPATION [OCCUPATION] (1)
CUST_BREAKDOWN [CUST_​BREAKDOWN] (1)
COMPOSITE_BREAKDOWN [COMPOSITE_​BREAKDOWN] (1)
DISABILITY_STATUS [DISABILITY_​STATUS] (1)
ACTIVITY [ACTIVITY] (1)
PRODUCT [PRODUCT] (1)

This dataset has 2,515 series:

[A.G.FB_​ATM_​TOTL.148._​T.Y_​GE15._​T._​T._​T._​T._​T._​T._​T._​T._​T] Annual – Global – Number of automated teller machines (ATMs) per 100,000 adults – Chad – 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

from
2004=0
to
2022=1.774
min:
0
max:
1.774
avg:
0.796
σ:
0.59

[A.G.FB_​ATM_​TOTL.152._​T.Y_​GE15._​T._​T._​T._​T._​T._​T._​T._​T._​T] Annual – Global – Number of automated teller machines (ATMs) per 100,000 adults – Chile – 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

from
2004=33.149
to
2023=47.617
min:
33.149
max:
67.236
avg:
51.95
σ:
8.307

[A.G.FB_​ATM_​TOTL.156._​T.Y_​GE15._​T._​T._​T._​T._​T._​T._​T._​T._​T] Annual – Global – Number of automated teller machines (ATMs) per 100,000 adults – China, P.R.: Mainland – 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

from
2006=9.599
to
2023=72.026
min:
9.599
max:
97.031
avg:
55.804
σ:
30.325

[A.G.FB_​ATM_​TOTL.170._​T.Y_​GE15._​T._​T._​T._​T._​T._​T._​T._​T._​T] Annual – Global – Number of automated teller machines (ATMs) per 100,000 adults – Colombia – 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

from
2007=25.487
to
2023=38.963
min:
25.487
max:
42.525
avg:
37.444
σ:
5.42

[A.G.FB_​ATM_​TOTL.174._​T.Y_​GE15._​T._​T._​T._​T._​T._​T._​T._​T._​T] Annual – Global – Number of automated teller machines (ATMs) per 100,000 adults – Comoros – 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

from
2004=0.632
to
2023=7.543
min:
0.593
max:
7.543
avg:
4.244
σ:
2.399

[A.G.FB_​ATM_​TOTL.178._​T.Y_​GE15._​T._​T._​T._​T._​T._​T._​T._​T._​T] Annual – Global – Number of automated teller machines (ATMs) per 100,000 adults – Congo, Republic of – 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

from
2004=0.338
to
2022=13.581
min:
0.338
max:
13.839
avg:
5.803
σ:
5.415

[A.G.FB_​ATM_​TOTL.180._​T.Y_​GE15._​T._​T._​T._​T._​T._​T._​T._​T._​T] Annual – Global – Number of automated teller machines (ATMs) per 100,000 adults – Congo, Democratic Republic of – 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

from
2009=0.098
to
2018=1.401
min:
0.098
max:
1.401
avg:
0.874
σ:
0.436

[A.G.FB_​ATM_​TOTL.188._​T.Y_​GE15._​T._​T._​T._​T._​T._​T._​T._​T._​T] Annual – Global – Number of automated teller machines (ATMs) per 100,000 adults – Costa Rica – 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

from
2004=25.282
to
2023=63.049
min:
25.282
max:
78.475
avg:
54.246
σ:
16.06

[A.G.FB_​ATM_​TOTL.191._​T.Y_​GE15._​T._​T._​T._​T._​T._​T._​T._​T._​T] Annual – Global – Number of automated teller machines (ATMs) per 100,000 adults – Croatia – 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

from
2005=63.725
to
2023=129.056
min:
63.725
max:
156.203
avg:
115.58
σ:
24.743

[A.G.FB_​ATM_​TOTL.196._​T.Y_​GE15._​T._​T._​T._​T._​T._​T._​T._​T._​T] Annual – Global – Number of automated teller machines (ATMs) per 100,000 adults – Cyprus – 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

from
2004=54.926
to
2023=31.589
min:
31.589
max:
69.929
avg:
52.028
σ:
11.965