Bahamas
BHSCaribbean · Americas · UN member
The circle shows each metric's percentile rank (position among countries with data), which is comparable across metrics. Each metric's native score uses its own scale and is not comparable between metrics — see it (and the full formula) in “How is this calculated?”.
69 metrics for this country
Society & culture
100 = tallest mean male height, 0 = shortest — descriptive, not better or worse
Ranks 78th of 200 · native score 56.96 · reference year 1996
61percentileHow is this calculated?
- Metric
- Adult male height
- Scale
- 100 = tallest mean male height, 0 = shortest — descriptive, not better or worse
- Raw value
- 172.747 cm
- Native score
- 56.96 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 61th percentile — ranks 78th of 200. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (172.75 − 159.79) / (182.54 − 159.79) = 56.96Min and max are this dataset's lowest (159.79) and highest (182.54) values, so the score is relative to the current country set.
- Source
- NCD Risk Factor Collaboration (via Our World in Data) · NCD Risk Factor Collaboration (NCD-RisC)
- License
- CC BY 4.0
- Reference year
- 1996
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- Pooled analysis of population-based measured-height studies, retrieved via the Our World in Data mirror. Indexed by year of birth.
100 = highest cocoa supply per person in the dataset, 0 = lowest
Ranks 65th of 191 · native score 9.52 · reference year 2023
66percentileLow reliability (Tier C — Survey / proxy). Survey-based, patchy, or proxy metric. Indicative only — coverage gaps and methodology limits are significant. Not a definitive ranking.
How is this calculated?
- Metric
- Chocolate supply per person (proxy)
- Scale
- 100 = highest cocoa supply per person in the dataset, 0 = lowest
- Raw value
- 1.33996 kg cocoa per person / year
- Native score
- 9.52 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 66th percentile — ranks 65th of 191. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (1.34 − 0) / (14.07 − 0) = 9.52Min and max are this dataset's lowest (0) and highest (14.07) values, so the score is relative to the current country set.
- Source
- FAO (via Our World in Data) · Food and Agriculture Organization of the UN (FAO)
- License
- CC BY 4.0
- Reference year
- 2023
- Retrieved
- 2026-07-12
- Confidence
- Tier C — Survey / proxy
- Source notes
- Cocoa 'food available for consumption' per capita from the FAO Food Balance Sheets, retrieved via the Our World in Data mirror. A supply proxy, not measured consumption — Tier C.
100 = highest female participation in the dataset, 0 = lowest
Ranks 17th of 186 · native score 84.43 · reference year 2025
91percentileHow is this calculated?
- Metric
- Female labour force participation
- Scale
- 100 = highest female participation in the dataset, 0 = lowest
- Raw value
- 70.728 % of women 15+
- Native score
- 84.43 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 91th percentile — ranks 17th of 186. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (70.73 − 4.66) / (82.91 − 4.66) = 84.43Min and max are this dataset's lowest (4.66) and highest (82.91) values, so the score is relative to the current country set.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2025
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = highest fish & seafood supply per person, 0 = lowest — descriptive, not better or worse
Ranks 45th of 191 · native score 32.72 · reference year 2023
77percentileHow is this calculated?
- Metric
- Fish & seafood supply per capita
- Scale
- 100 = highest fish & seafood supply per person, 0 = lowest — descriptive, not better or worse
- Raw value
- 27.6792 kg per person per year
- Native score
- 32.72 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 77th percentile — ranks 45th of 191. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (27.68 − 0.38) / (83.81 − 0.38) = 32.72Min and max are this dataset's lowest (0.38) and highest (83.81) values, so the score is relative to the current country set.
- Source
- FAO Food Balance Sheets (via Our World in Data) · Food and Agriculture Organization of the UN (FAO)
- License
- CC BY 4.0
- Reference year
- 2023
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- Per-capita food available for consumption from the FAO Food Balance Sheets, retrieved via the Our World in Data mirror. This is national food SUPPLY per person, not measured intake.
100 = highest fruit supply per person, 0 = lowest — descriptive, not better or worse
Ranks 4th of 191 · native score 58.23 · reference year 2023
98percentileHow is this calculated?
- Metric
- Fruit supply per capita
- Scale
- 100 = highest fruit supply per person, 0 = lowest — descriptive, not better or worse
- Raw value
- 309.861 kg per person per year
- Native score
- 58.23 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 98th percentile — ranks 4th of 191. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (309.86 − 4.27) / (529.06 − 4.27) = 58.23Min and max are this dataset's lowest (4.27) and highest (529.06) values, so the score is relative to the current country set.
- Source
- FAO Food Balance Sheets (via Our World in Data) · Food and Agriculture Organization of the UN (FAO)
- License
- CC BY 4.0
- Reference year
- 2023
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- Per-capita food available for consumption from the FAO Food Balance Sheets, retrieved via the Our World in Data mirror. This is national food SUPPLY per person, not measured intake.
100 = most gender-equal (GII 0), 0 = most unequal (GII 1)
Ranks 81st of 172 · native score 67.5 · reference year 2023
53percentileHow is this calculated?
- Metric
- Gender equality (inverted GII)
- Scale
- 100 = most gender-equal (GII 0), 0 = most unequal (GII 1)
- Raw value
- 0.325 index (0–1, lower = more equal)
- Native score
- 67.5 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 53th percentile — ranks 81st of 172. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 − [ 100 · (0.33 − 0) / (1 − 0) ] = 67.5The index is kept on its own published scale. Direction is inverted (higher raw value = worse), so the position is subtracted from 100.
- Source
- UNDP Human Development Report (via Our World in Data) · UNDP, Human Development Report Office
- License
- CC BY 3.0 IGO
- Reference year
- 2023
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- Gender Inequality Index from the UNDP Human Development Report, retrieved via the Our World in Data mirror.
- Informal employmentTier A
100 = lowest informal employment (best), 0 = highest
Ranks 36th of 145 · native score 82.38 · reference year 2019
76percentileHow is this calculated?
- Metric
- Informal employment
- Scale
- 100 = lowest informal employment (best), 0 = highest
- Raw value
- 18.252 % of employment
- Native score
- 82.38 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 76th percentile — ranks 36th of 145. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 − [ 100 · (18.25 − 1.09) / (98.49 − 1.09) ] = 82.38Min and max are this dataset's lowest (1.09) and highest (98.49) values, so the score is relative to the current country set. Direction is inverted (higher raw value = worse), so the position is subtracted from 100.
- Source
- ILOSTAT (International Labour Organization) · International Labour Organization
- License
- CC BY 4.0
- Reference year
- 2019
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- ILOSTAT via the ILO rplumber API (rplumber.ilo.org). CC BY 4.0 for databases published since 3 May 2023.
100 = highest meat supply per person, 0 = lowest — descriptive, not better or worse
Ranks 9th of 191 · native score 72.61 · reference year 2023
96percentileHow is this calculated?
- Metric
- Meat supply per capita
- Scale
- 100 = highest meat supply per person, 0 = lowest — descriptive, not better or worse
- Raw value
- 114.907 kg per person per year
- Native score
- 72.61 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 96th percentile — ranks 9th of 191. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (114.91 − 3.49) / (156.93 − 3.49) = 72.61Min and max are this dataset's lowest (3.49) and highest (156.93) values, so the score is relative to the current country set.
- Source
- FAO Food Balance Sheets (via Our World in Data) · Food and Agriculture Organization of the UN (FAO)
- License
- CC BY 4.0
- Reference year
- 2023
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- Per-capita food available for consumption from the FAO Food Balance Sheets, retrieved via the Our World in Data mirror. This is national food SUPPLY per person, not measured intake.
100 = universal social protection coverage, 0 = none
Ranks 116th of 214 · native score 49.1 · reference year 2020
46percentileHow is this calculated?
- Metric
- Social protection coverage
- Scale
- 100 = universal social protection coverage, 0 = none
- Raw value
- 49.1 % of population
- Native score
- 49.1 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 46th percentile — ranks 116th of 214. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (49.1 − 0) / (100 − 0) = 49.1The index is kept on its own published scale.
- Source
- ILOSTAT (International Labour Organization) · International Labour Organization
- License
- CC BY 4.0
- Reference year
- 2020
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- ILOSTAT via the ILO rplumber API (rplumber.ilo.org). CC BY 4.0 for databases published since 3 May 2023.
100 = most arrivals (2019), 0 = fewest — descriptive, not better or worse
Ranks 80th of 174 · native score 61.24 · reference year 2019
54percentileHow is this calculated?
- Metric
- International tourist arrivals
- Scale
- 100 = most arrivals (2019), 0 = fewest — descriptive, not better or worse
- Raw value
- 1,807,000 arrivals per year
- Native score
- 61.24 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 54th percentile — ranks 80th of 174. Comparable across metrics.
- Normalization
- Log + min–max (log scale, for skewed data)
score = 100 · (ln 1,807,000 − ln 3,700) / (ln 90,914,000 − ln 3,700) = 61.24Log scale (values are heavily skewed). 0 and 100 are the dataset's min (3,700) and max (90,914,000) — relative, not absolute or year-over-year comparable.
- Source
- UN Tourism (via Our World in Data) · UN Tourism (UNWTO)
- License
- CC BY 4.0
- Reference year
- 2019
- Retrieved
- 2026-07-12
- Confidence
- Tier B — Reputable / modeled
- Source notes
- International tourist arrivals — overnight visitors — from UN Tourism (UNWTO), retrieved via the Our World in Data mirror (OWID's processing layer is CC BY; underlying values are UN Tourism).
100 = highest vegetables supply per person, 0 = lowest — descriptive, not better or worse
Ranks 31st of 191 · native score 41.19 · reference year 2023
84percentileHow is this calculated?
- Metric
- Vegetable supply per capita
- Scale
- 100 = highest vegetables supply per person, 0 = lowest — descriptive, not better or worse
- Raw value
- 173.125 kg per person per year
- Native score
- 41.19 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 84th percentile — ranks 31st of 191. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (173.12 − 5.34) / (412.72 − 5.34) = 41.19Min and max are this dataset's lowest (5.34) and highest (412.72) values, so the score is relative to the current country set.
- Source
- FAO Food Balance Sheets (via Our World in Data) · Food and Agriculture Organization of the UN (FAO)
- License
- CC BY 4.0
- Reference year
- 2023
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- Per-capita food available for consumption from the FAO Food Balance Sheets, retrieved via the Our World in Data mirror. This is national food SUPPLY per person, not measured intake.
Demographics & migration
100 = highest dependency ratio, 0 = lowest — descriptive, not better or worse
Ranks 194th of 215 · native score 26.43 · reference year 2025
10percentileHow is this calculated?
- Metric
- Age dependency ratio
- Scale
- 100 = highest dependency ratio, 0 = lowest — descriptive, not better or worse
- Raw value
- 42.1322 dependents per 100 working-age
- Native score
- 26.43 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 10th percentile — ranks 194th of 215. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (42.13 − 20.05) / (103.59 − 20.05) = 26.43Min and max are this dataset's lowest (20.05) and highest (103.59) values, so the score is relative to the current country set.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2025
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = highest fertility, 0 = lowest — descriptive, not better or worse
Ranks 181st of 215 · native score 14.54 · reference year 2024
16percentileHow is this calculated?
- Metric
- Fertility rate
- Scale
- 100 = highest fertility, 0 = lowest — descriptive, not better or worse
- Raw value
- 1.374 births per woman
- Native score
- 14.54 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 16th percentile — ranks 181st of 215. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (1.37 − 0.58) / (6.03 − 0.58) = 14.54Min and max are this dataset's lowest (0.58) and highest (6.03) values, so the score is relative to the current country set.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = largest female−male gap, 0 = smallest (or male-favouring) — descriptive, not better or worse
Ranks 29th of 215 · native score 67.06 · reference year 2024
87percentileHow is this calculated?
- Metric
- Life expectancy gap (female − male)
- Scale
- 100 = largest female−male gap, 0 = smallest (or male-favouring) — descriptive, not better or worse
- Raw value
- 7.272 years (female − male)
- Native score
- 67.06 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 87th percentile — ranks 29th of 215. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (7.27 − 0.46) / (10.62 − 0.46) = 67.06Min and max are this dataset's lowest (0.46) and highest (10.62) values, so the score is relative to the current country set.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = oldest median age, 0 = youngest — descriptive, not better or worse
Ranks 101st of 237 · native score 44.76 · reference year 2023
58percentileHow is this calculated?
- Metric
- Median age
- Scale
- 100 = oldest median age, 0 = youngest — descriptive, not better or worse
- Raw value
- 34.597 years
- Native score
- 44.76 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 58th percentile — ranks 101st of 237. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (34.6 − 14.32) / (59.63 − 14.32) = 44.76Min and max are this dataset's lowest (14.32) and highest (59.63) values, so the score is relative to the current country set.
- Source
- UN World Population Prospects (via Our World in Data) · UN DESA, Population Division
- License
- CC BY 3.0 IGO
- Reference year
- 2023
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- UN World Population Prospects (median age; medium-variant projections), retrieved via the Our World in Data mirror.
100 = highest foreign-born share, 0 = lowest — descriptive, not better or worse
Ranks 52nd of 214 · native score 16.8 · reference year 2024
76percentileHow is this calculated?
- Metric
- Foreign-born population
- Scale
- 100 = highest foreign-born share, 0 = lowest — descriptive, not better or worse
- Raw value
- 16.8 % foreign-born
- Native score
- 16.8 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 76th percentile — ranks 52nd of 214. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (16.8 − 0) / (100 − 0) = 16.8The index is kept on its own published scale.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = highest net inflow per capita, 0 = highest net outflow — descriptive, not better or worse
Ranks 44th of 215 · native score 54.35 · reference year 2025
80percentileHow is this calculated?
- Metric
- Net migration rate
- Scale
- 100 = highest net inflow per capita, 0 = highest net outflow — descriptive, not better or worse
- Raw value
- 2.32 per 1,000 people
- Native score
- 54.35 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 80th percentile — ranks 44th of 215. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (2.32 − -46.91) / (43.67 − -46.91) = 54.35Min and max are this dataset's lowest (-46.91) and highest (43.67) values, so the score is relative to the current country set.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2025
- Retrieved
- 2026-07-12
- Confidence
- Tier B — Reputable / modeled
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = most populous, 0 = least populous — descriptive, not better or worse
Ranks 174th of 215 · native score 31.38 · reference year 2025
19percentileHow is this calculated?
- Metric
- Total population
- Scale
- 100 = most populous, 0 = least populous — descriptive, not better or worse
- Raw value
- 403,033 people
- Native score
- 31.38 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 19th percentile — ranks 174th of 215. Comparable across metrics.
- Normalization
- Log + min–max (log scale, for skewed data)
score = 100 · (ln 403,033 − ln 9,492) / (ln 1,463,865,525 − ln 9,492) = 31.38Log scale (values are heavily skewed). 0 and 100 are the dataset's min (9,492) and max (1,463,865,525) — relative, not absolute or year-over-year comparable.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2025
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = most dense, 0 = least dense — descriptive, not better or worse
Ranks 161st of 215 · native score 47.56 · reference year 2023
25percentileHow is this calculated?
- Metric
- Population density
- Scale
- 100 = most dense, 0 = least dense — descriptive, not better or worse
- Raw value
- 39.9041 people per km²
- Native score
- 47.56 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 25th percentile — ranks 161st of 215. Comparable across metrics.
- Normalization
- Log + min–max (log scale, for skewed data)
score = 100 · (ln 39.9 − ln 0.14) / (ln 20,569.7 − ln 0.14) = 47.56Log scale (values are heavily skewed). 0 and 100 are the dataset's min (0.14) and max (20,569.7) — relative, not absolute or year-over-year comparable.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2023
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = fastest projected growth, 0 = fastest projected decline — descriptive, not better or worse
Ranks 144th of 237 · native score 29.11 · reference year 2050
39percentileHow is this calculated?
- Metric
- Population change (projection)
- Scale
- 100 = fastest projected growth, 0 = fastest projected decline — descriptive, not better or worse
- Raw value
- 5.7 % change 2024→2050
- Native score
- 29.11 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 39th percentile — ranks 144th of 237. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (5.7 − -32.9) / (99.7 − -32.9) = 29.11Min and max are this dataset's lowest (-32.9) and highest (99.7) values, so the score is relative to the current country set.
- Source
- UN World Population Prospects (via Our World in Data) · UN DESA, Population Division
- License
- CC BY 3.0 IGO
- Reference year
- 2050
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- UN World Population Prospects (median age; medium-variant projections), retrieved via the Our World in Data mirror.
100 = most refugees produced, 0 = fewest — descriptive, not better or worse
Ranks 97th of 211 · native score 54.27 · reference year 2024
54percentileHow is this calculated?
- Metric
- Refugees (by origin)
- Scale
- 100 = most refugees produced, 0 = fewest — descriptive, not better or worse
- Raw value
- 1,449 refugees
- Native score
- 54.27 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 54th percentile — ranks 97th of 211. Comparable across metrics.
- Normalization
- Percentile rank across countries
score = percentile rank of 1,449 among 211 countries = 54.27The score is the country's position in the distribution.
- Source
- UNHCR (via Our World in Data) · UN High Commissioner for Refugees (UNHCR)
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- Refugee population by country of origin, retrieved via the Our World in Data mirror.
100 = highest remittance inflow (% GDP), 0 = lowest — descriptive, not better or worse
Ranks 151st of 193 · native score 0.86 · reference year 2024
22percentileHow is this calculated?
- Metric
- Remittances received
- Scale
- 100 = highest remittance inflow (% GDP), 0 = lowest — descriptive, not better or worse
- Raw value
- 0.416408 % of GDP
- Native score
- 0.86 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 22th percentile — ranks 151st of 193. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (0.42 − 0.01) / (47.15 − 0.01) = 0.86Min and max are this dataset's lowest (0.01) and highest (47.15) values, so the score is relative to the current country set.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = fully rural, 0 = fully urban — descriptive, not better or worse
Ranks 163rd of 215 · native score 18.67 · reference year 2025
24percentileHow is this calculated?
- Metric
- Rural population share
- Scale
- 100 = fully rural, 0 = fully urban — descriptive, not better or worse
- Raw value
- 18.6691 % rural
- Native score
- 18.67 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 24th percentile — ranks 163rd of 215. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (18.67 − 0) / (100 − 0) = 18.67The index is kept on its own published scale.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2025
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = highest male-to-female birth ratio, 0 = lowest — descriptive, not better or worse
Ranks 200th of 215 · native score 11.18 · reference year 2024
7percentileHow is this calculated?
- Metric
- Sex ratio at birth
- Scale
- 100 = highest male-to-female birth ratio, 0 = lowest — descriptive, not better or worse
- Raw value
- 1.028 male births per female birth
- Native score
- 11.18 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 7th percentile — ranks 200th of 215. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (1.03 − 1.01) / (1.16 − 1.01) = 11.18Min and max are this dataset's lowest (1.01) and highest (1.16) values, so the score is relative to the current country set.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = fully urban, 0 = fully rural — descriptive, not better or worse
Ranks 53rd of 215 · native score 81.33 · reference year 2025
76percentileHow is this calculated?
- Metric
- Urbanization
- Scale
- 100 = fully urban, 0 = fully rural — descriptive, not better or worse
- Raw value
- 81.3309 % urban
- Native score
- 81.33 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 76th percentile — ranks 53rd of 215. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (81.33 − 0) / (100 − 0) = 81.33The index is kept on its own published scale.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2025
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
Environment & infrastructure
100 = most air passengers, 0 = fewest — descriptive, not better or worse
Ranks 91st of 177 · native score 48.87 · reference year 2023
49percentileHow is this calculated?
- Metric
- Air transport passengers
- Scale
- 100 = most air passengers, 0 = fewest — descriptive, not better or worse
- Raw value
- 1,465,430 passengers per year
- Native score
- 48.87 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 49th percentile — ranks 91st of 177. Comparable across metrics.
- Normalization
- Percentile rank across countries
score = percentile rank of 1,465,432.19 among 177 countries = 48.87The score is the country's position in the distribution.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2023
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
- Climate vulnerabilityTier B
100 = least climate-vulnerable (best), 0 = most vulnerable
Ranks 93rd of 190 · native score 53.01 · reference year 2024
51percentileHow is this calculated?
- Metric
- Climate vulnerability
- Scale
- 100 = least climate-vulnerable (best), 0 = most vulnerable
- Raw value
- 0.447498 index (0–1, higher = more vulnerable)
- Native score
- 53.01 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 51th percentile — ranks 93rd of 190. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 − [ 100 · (0.45 − 0.26) / (0.66 − 0.26) ] = 53.01Min and max are this dataset's lowest (0.26) and highest (0.66) values, so the score is relative to the current country set. Direction is inverted (higher raw value = worse), so the position is subtracted from 100.
- Source
- ND-GAIN Country Index (University of Notre Dame) · University of Notre Dame Global Adaptation Initiative
- License
- CC BY 3.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier B — Reputable / modeled
- Source notes
- ND-GAIN vulnerability score. The source ZIP is version-stamped (no stable 'latest' URL), so the snapshot is pinned to a specific release; refreshes are a manual, documented step.
- CO₂ emissions per capitaTier A
100 = lowest emissions per capita (best), 0 = highest
Ranks 178th of 214 · native score 17.06 · reference year 2024
17percentileHow is this calculated?
- Metric
- CO₂ emissions per capita
- Scale
- 100 = lowest emissions per capita (best), 0 = highest
- Raw value
- 7.64968 tonnes CO₂ per capita
- Native score
- 17.06 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 17th percentile — ranks 178th of 214. Comparable across metrics.
- Normalization
- Percentile rank across countries
score = 100 − [ percentile rank of 7.65 among 214 countries ] = 17.06The score is the country's position in the distribution. Direction is inverted (higher raw value = worse), so the position is subtracted from 100.
- Source
- Global Carbon Project (via Our World in Data) · Global Carbon Project
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- Per-capita CO₂ emissions from the Global Carbon Project's Global Carbon Budget, retrieved via the Our World in Data mirror.
- Access to electricityTier A
100 = universal electricity access, 0 = none
Ranks 1st of 214 · native score 100 · reference year 2023
70percentileHow is this calculated?
- Metric
- Access to electricity
- Scale
- 100 = universal electricity access, 0 = none
- Raw value
- 100 % of population
- Native score
- 100 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 70th percentile — ranks 1st of 214. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (100 − 0) / (100 − 0) = 100The index is kept on its own published scale.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2023
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = highest energy use per capita, 0 = lowest — descriptive, not better or worse
Ranks 59th of 177 · native score 71.76 · reference year 2007
67percentileHow is this calculated?
- Metric
- Energy use per capita
- Scale
- 100 = highest energy use per capita, 0 = lowest — descriptive, not better or worse
- Raw value
- 2,006.6 kg oil-equivalent per capita
- Native score
- 71.76 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 67th percentile — ranks 59th of 177. Comparable across metrics.
- Normalization
- Log + min–max (log scale, for skewed data)
score = 100 · (ln 2,006.6 − ln 9.73) / (ln 16,343.04 − ln 9.73) = 71.76Log scale (values are heavily skewed). 0 and 100 are the dataset's min (9.73) and max (16,343.04) — relative, not absolute or year-over-year comparable.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2007
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = most fixed-broadband subscriptions per capita, 0 = fewest
Ranks 75th of 208 · native score 41.44 · reference year 2024
64percentileHow is this calculated?
- Metric
- Fixed broadband subscriptions
- Scale
- 100 = most fixed-broadband subscriptions per capita, 0 = fewest
- Raw value
- 25.268 per 100 people
- Native score
- 41.44 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 64th percentile — ranks 75th of 208. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (25.27 − 0) / (60.97 − 0) = 41.44Min and max are this dataset's lowest (0) and highest (60.97) values, so the score is relative to the current country set.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = most forested, 0 = least — descriptive, not better or worse
Ranks 51st of 213 · native score 50.94 · reference year 2023
76percentileHow is this calculated?
- Metric
- Forest area
- Scale
- 100 = most forested, 0 = least — descriptive, not better or worse
- Raw value
- 50.9351 % of land area
- Native score
- 50.94 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 76th percentile — ranks 51st of 213. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (50.94 − 0) / (100 − 0) = 50.94The index is kept on its own published scale.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2023
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
- Internet usersTier A
100 = whole population online, 0 = none
Ranks 46th of 209 · native score 92.47 · reference year 2024
78percentileHow is this calculated?
- Metric
- Internet users
- Scale
- 100 = whole population online, 0 = none
- Raw value
- 92.4727 % of population
- Native score
- 92.47 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 78th percentile — ranks 46th of 209. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (92.47 − 0) / (100 − 0) = 92.47The index is kept on its own published scale.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = best logistics performance (index 5), 0 = worst (1)
Ranks 84th of 169 · native score 42.5 · reference year 2022
48percentileHow is this calculated?
- Metric
- Logistics Performance Index
- Scale
- 100 = best logistics performance (index 5), 0 = worst (1)
- Raw value
- 2.7 index (1–5)
- Native score
- 42.5 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 48th percentile — ranks 84th of 169. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (2.7 − 1) / (5 − 1) = 42.5The index is kept on its own published scale.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2022
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
- PM2.5 air pollutionTier A
100 = cleanest air (lowest PM2.5), 0 = most polluted
Ranks 17th of 200 · native score 91.75 · reference year 2023
92percentileHow is this calculated?
- Metric
- PM2.5 air pollution
- Scale
- 100 = cleanest air (lowest PM2.5), 0 = most polluted
- Raw value
- 5.28191 µg/m³
- Native score
- 91.75 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 92th percentile — ranks 17th of 200. Comparable across metrics.
- Normalization
- Percentile rank across countries
score = 100 − [ percentile rank of 5.28 among 200 countries ] = 91.75The score is the country's position in the distribution. Direction is inverted (higher raw value = worse), so the position is subtracted from 100.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2023
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
- Protected land areaTier A
100 = most land protected, 0 = least
Ranks 28th of 212 · native score 34.6 · reference year 2025
87percentileHow is this calculated?
- Metric
- Protected land area
- Scale
- 100 = most land protected, 0 = least
- Raw value
- 34.6 % of land area
- Native score
- 34.6 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 87th percentile — ranks 28th of 212. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (34.6 − 0) / (100 − 0) = 34.6The index is kept on its own published scale.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2025
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
- Renewable energy shareTier A
100 = all energy renewable, 0 = none
Ranks 187th of 212 · native score 1.1 · reference year 2022
11percentileHow is this calculated?
- Metric
- Renewable energy share
- Scale
- 100 = all energy renewable, 0 = none
- Raw value
- 1.1 % of final energy
- Native score
- 1.1 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 11th percentile — ranks 187th of 212. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (1.1 − 0) / (100 − 0) = 1.1The index is kept on its own published scale.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2022
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
Safety & crime
100 = fewest conflict deaths (most at peace), 0 = most
Ranks 1st of 197 · native score 63.71 · reference year 2025
64percentileHow is this calculated?
- Metric
- Deaths in armed conflicts
- Scale
- 100 = fewest conflict deaths (most at peace), 0 = most
- Raw value
- 0 deaths per year
- Native score
- 63.71 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 64th percentile — ranks 1st of 197. Comparable across metrics.
- Normalization
- Percentile rank across countries
score = 100 − [ percentile rank of 0 among 197 countries ] = 63.71The score is the country's position in the distribution. Direction is inverted (higher raw value = worse), so the position is subtracted from 100.
- Source
- Uppsala Conflict Data Program (via Our World in Data) · Uppsala Conflict Data Program (UCDP)
- License
- CC BY 4.0
- Reference year
- 2025
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- Deaths in armed conflicts, best estimate, retrieved via the Our World in Data mirror.
- Homicide rateTier A
100 = safest (fewest homicides), 0 = most homicides
Ranks 182nd of 193 · native score 5.96 · reference year 2022
6percentileHow is this calculated?
- Metric
- Homicide rate
- Scale
- 100 = safest (fewest homicides), 0 = most homicides
- Raw value
- 32.1981 per 100,000 population
- Native score
- 5.96 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 6th percentile — ranks 182nd of 193. Comparable across metrics.
- Normalization
- Percentile rank across countries
score = 100 − [ percentile rank of 32.2 among 193 countries ] = 5.96The score is the country's position in the distribution. Direction is inverted (higher raw value = worse), so the position is subtracted from 100.
- Source
- UNODC (via World Bank) · UN Office on Drugs and Crime / World Bank
- License
- CC BY 4.0
- Reference year
- 2022
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- Intentional homicide victims per 100,000, indicator VC.IHR.PSRC.P5, retrieved via the World Bank API. Primary source is UNODC; the World Bank redistributes the series under CC BY 4.0.
- Road-traffic deathsTier B
100 = lowest road-death rate (best), 0 = highest
Ranks 49th of 190 · native score 88.08 · reference year 2019
74percentileHow is this calculated?
- Metric
- Road-traffic deaths
- Scale
- 100 = lowest road-death rate (best), 0 = highest
- Raw value
- 7.7 deaths per 100,000
- Native score
- 88.08 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 74th percentile — ranks 49th of 190. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 − [ 100 · (7.7 − 0) / (64.6 − 0) ] = 88.08Min and max are this dataset's lowest (0) and highest (64.6) values, so the score is relative to the current country set. Direction is inverted (higher raw value = worse), so the position is subtracted from 100.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2019
- Retrieved
- 2026-07-12
- Confidence
- Tier B — Reputable / modeled
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
Governance & institutions
100 = cleanest (least corrupt), 0 = most corrupt
Ranks 28th of 180 · native score 65 · reference year 2024
84percentileHow is this calculated?
- Metric
- Corruption Perceptions Index
- Scale
- 100 = cleanest (least corrupt), 0 = most corrupt
- Raw value
- 65 CPI score (0–100)
- Native score
- 65 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 84th percentile — ranks 28th of 180. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (65 − 0) / (100 − 0) = 65The index is kept on its own published scale.
- Source
- Transparency International · Transparency International
- License
- CC BY-ND 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- CPI retrieved via the Our World in Data mirror (ourworldindata.org/grapher/ti-corruption-perception-index), which republishes the official TI CPI series verbatim. Snapshot verified against Transparency International's official CPI 2024 figures and matches exactly (spot-checked: DNK 90, FIN 88, SGP 84, DEU 75, USA 65, ESP 56, SSD 8). We were unable to fetch TI's primary file directly (their CDN returns an access-denied stub for the CPI xlsx and no clean CSV is offered), so the OWID mirror is the machine-readable source; primary source and methodology owner is Transparency International.
- Government effectivenessTier A
100 = strongest government effectiveness (index +2.5), 0 = weakest (−2.5)
Ranks 52nd of 204 · native score 64.19 · reference year 2024
75percentileHow is this calculated?
- Metric
- Government effectiveness
- Scale
- 100 = strongest government effectiveness (index +2.5), 0 = weakest (−2.5)
- Raw value
- 0.709299 index (−2.5 to +2.5)
- Native score
- 64.19 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 75th percentile — ranks 52nd of 204. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (0.71 − -2.5) / (2.5 − -2.5) = 64.19The index is kept on its own published scale.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
- Women in parliamentTier A
100 = all seats held by women, 0 = none (≈50 = parity)
Ranks 134th of 193 · native score 18.42 · reference year 2025
31percentileHow is this calculated?
- Metric
- Women in parliament
- Scale
- 100 = all seats held by women, 0 = none (≈50 = parity)
- Raw value
- 18.4211 % of seats
- Native score
- 18.42 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 31th percentile — ranks 134th of 193. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (18.42 − 0) / (100 − 0) = 18.42The index is kept on its own published scale.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2025
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
Health
- Diabetes prevalenceTier A
100 = lowest diabetes prevalence (best), 0 = highest
Ranks 110th of 208 · native score 75.25 · reference year 2024
47percentileHow is this calculated?
- Metric
- Diabetes prevalence
- Scale
- 100 = lowest diabetes prevalence (best), 0 = highest
- Raw value
- 8.9 % of adults 20–79
- Native score
- 75.25 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 47th percentile — ranks 110th of 208. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 − [ 100 · (8.9 − 1.5) / (31.4 − 1.5) ] = 75.25Min and max are this dataset's lowest (1.5) and highest (31.4) values, so the score is relative to the current country set. Direction is inverted (higher raw value = worse), so the position is subtracted from 100.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = highest health spending per capita, 0 = lowest
Ranks 37th of 193 · native score 73.17 · reference year 2023
81percentileHow is this calculated?
- Metric
- Health expenditure per capita
- Scale
- 100 = highest health spending per capita, 0 = lowest
- Raw value
- 2,262.33 current US$ per capita
- Native score
- 73.17 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 81th percentile — ranks 37th of 193. Comparable across metrics.
- Normalization
- Log + min–max (log scale, for skewed data)
score = 100 · (ln 2,262.33 − ln 17.44) / (ln 13,473.19 − ln 17.44) = 73.17Log scale (values are heavily skewed). 0 and 100 are the dataset's min (17.44) and max (13,473.19) — relative, not absolute or year-over-year comparable.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2023
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
- Hospital beds per 1,000Tier A
100 = most hospital beds per capita in the dataset, 0 = fewest
Ranks 99th of 191 · native score 9.25 · reference year 2023
48percentileHow is this calculated?
- Metric
- Hospital beds per 1,000
- Scale
- 100 = most hospital beds per capita in the dataset, 0 = fewest
- Raw value
- 2.17 per 1,000 people
- Native score
- 9.25 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 48th percentile — ranks 99th of 191. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (2.17 − 0.15) / (21.99 − 0.15) = 9.25Min and max are this dataset's lowest (0.15) and highest (21.99) values, so the score is relative to the current country set.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2023
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = full DTP3 coverage, 0 = none
Ranks 104th of 193 · native score 90 · reference year 2024
45percentileHow is this calculated?
- Metric
- Immunization coverage (DTP3)
- Scale
- 100 = full DTP3 coverage, 0 = none
- Raw value
- 90 % of children aged 12–23 months
- Native score
- 90 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 45th percentile — ranks 104th of 193. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (90 − 0) / (100 − 0) = 90The index is kept on its own published scale.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
- Infant mortality rateTier A
100 = lowest infant mortality in the dataset, 0 = highest
Ranks 89th of 195 · native score 86 · reference year 2024
55percentileHow is this calculated?
- Metric
- Infant mortality rate
- Scale
- 100 = lowest infant mortality in the dataset, 0 = highest
- Raw value
- 11.1 per 1,000 live births
- Native score
- 86 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 55th percentile — ranks 89th of 195. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 − [ 100 · (11.1 − 1.2) / (71.9 − 1.2) ] = 86Min and max are this dataset's lowest (1.2) and highest (71.9) values, so the score is relative to the current country set. Direction is inverted (higher raw value = worse), so the position is subtracted from 100.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
- Life expectancy at birthTier A
100 = longest life expectancy in the dataset, 0 = shortest
Ranks 107th of 215 · native score 63.01 · reference year 2024
50percentileHow is this calculated?
- Metric
- Life expectancy at birth
- Scale
- 100 = longest life expectancy in the dataset, 0 = shortest
- Raw value
- 74.71 years
- Native score
- 63.01 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 50th percentile — ranks 107th of 215. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (74.71 − 54.64) / (86.5 − 54.64) = 63.01Min and max are this dataset's lowest (54.64) and highest (86.5) values, so the score is relative to the current country set.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
- Maternal mortality ratioTier A
100 = lowest maternal mortality (best), 0 = highest
Ranks 120th of 194 · native score 38.4 · reference year 2023
38percentileHow is this calculated?
- Metric
- Maternal mortality ratio
- Scale
- 100 = lowest maternal mortality (best), 0 = highest
- Raw value
- 76 deaths per 100,000 live births
- Native score
- 38.4 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 38th percentile — ranks 120th of 194. Comparable across metrics.
- Normalization
- Percentile rank across countries
score = 100 − [ percentile rank of 76 among 194 countries ] = 38.4The score is the country's position in the distribution. Direction is inverted (higher raw value = worse), so the position is subtracted from 100.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2023
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
- Physicians per 1,000Tier A
100 = most physicians per capita in the dataset, 0 = fewest
Ranks 89th of 195 · native score 19.54 · reference year 2017
55percentileHow is this calculated?
- Metric
- Physicians per 1,000
- Scale
- 100 = most physicians per capita in the dataset, 0 = fewest
- Raw value
- 1.895 per 1,000 people
- Native score
- 19.54 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 55th percentile — ranks 89th of 195. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (1.9 − 0.04) / (9.54 − 0.04) = 19.54Min and max are this dataset's lowest (0.04) and highest (9.54) values, so the score is relative to the current country set.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2017
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
- Tobacco useTier A
100 = lowest tobacco use (best), 0 = highest
Ranks 73rd of 166 · native score 68.93 · reference year 2024
56percentileHow is this calculated?
- Metric
- Tobacco use
- Scale
- 100 = lowest tobacco use (best), 0 = highest
- Raw value
- 17.3 % of adults
- Native score
- 68.93 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 56th percentile — ranks 73rd of 166. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 − [ 100 · (17.3 − 3.1) / (48.8 − 3.1) ] = 68.93Min and max are this dataset's lowest (3.1) and highest (48.8) values, so the score is relative to the current country set. Direction is inverted (higher raw value = worse), so the position is subtracted from 100.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
- Under-5 mortality rateTier A
100 = lowest under-5 mortality (best), 0 = highest
Ranks 85th of 195 · native score 56.41 · reference year 2024
56percentileHow is this calculated?
- Metric
- Under-5 mortality rate
- Scale
- 100 = lowest under-5 mortality (best), 0 = highest
- Raw value
- 12.4 deaths per 1,000 live births
- Native score
- 56.41 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 56th percentile — ranks 85th of 195. Comparable across metrics.
- Normalization
- Percentile rank across countries
score = 100 − [ percentile rank of 12.4 among 195 countries ] = 56.41The score is the country's position in the distribution. Direction is inverted (higher raw value = worse), so the position is subtracted from 100.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
Education
100 = highest education spending (% GDP) in the dataset, 0 = lowest
Ranks 164th of 200 · native score 16.73 · reference year 2023
18percentileHow is this calculated?
- Metric
- Government education spending
- Scale
- 100 = highest education spending (% GDP) in the dataset, 0 = lowest
- Raw value
- 2.74192 % of GDP
- Native score
- 16.73 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 18th percentile — ranks 164th of 200. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (2.74 − 0) / (16.39 − 0) = 16.73Min and max are this dataset's lowest (0) and highest (16.39) values, so the score is relative to the current country set.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2023
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = lowest pupil–teacher ratio (best), 0 = highest
Ranks 102nd of 197 · native score 83.63 · reference year 2018
48percentileHow is this calculated?
- Metric
- Pupil–teacher ratio (primary)
- Scale
- 100 = lowest pupil–teacher ratio (best), 0 = highest
- Raw value
- 19.4489 pupils per teacher
- Native score
- 83.63 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 48th percentile — ranks 102nd of 197. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 − [ 100 · (19.45 − 6.93) / (83.41 − 6.93) ] = 83.63Min and max are this dataset's lowest (6.93) and highest (83.41) values, so the score is relative to the current country set. Direction is inverted (higher raw value = worse), so the position is subtracted from 100.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2018
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = highest completion in the dataset, 0 = lowest
Ranks 62nd of 192 · native score 62.05 · reference year 2010
68percentileHow is this calculated?
- Metric
- Lower-secondary completion rate
- Scale
- 100 = highest completion in the dataset, 0 = lowest
- Raw value
- 95.2641 % of relevant age group
- Native score
- 62.05 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 68th percentile — ranks 62nd of 192. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (95.26 − 8.89) / (148.09 − 8.89) = 62.05Min and max are this dataset's lowest (8.89) and highest (148.09) values, so the score is relative to the current country set.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2010
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
Economy
100 = highest employment ratio in the dataset, 0 = lowest
Ranks 27th of 186 · native score 69.68 · reference year 2025
86percentileHow is this calculated?
- Metric
- Employment-to-population ratio
- Scale
- 100 = highest employment ratio in the dataset, 0 = lowest
- Raw value
- 66.983 % of population 15+
- Native score
- 69.68 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 86th percentile — ranks 27th of 186. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (66.98 − 21.21) / (86.9 − 21.21) = 69.68Min and max are this dataset's lowest (21.21) and highest (86.9) values, so the score is relative to the current country set.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2025
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = most export-oriented (% GDP), 0 = lowest — descriptive, not better or worse
Ranks 93rd of 192 · native score 18.46 · reference year 2024
52percentileHow is this calculated?
- Metric
- Exports of goods & services
- Scale
- 100 = most export-oriented (% GDP), 0 = lowest — descriptive, not better or worse
- Raw value
- 37.7836 % of GDP
- Native score
- 18.46 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 52th percentile — ranks 93rd of 192. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (37.78 − 1.1) / (199.76 − 1.1) = 18.46Min and max are this dataset's lowest (1.1) and highest (199.76) values, so the score is relative to the current country set.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = largest net FDI inflow (% GDP), 0 = lowest — descriptive, not better or worse
Ranks 127th of 201 · native score 88.56 · reference year 2024
36percentileHow is this calculated?
- Metric
- Foreign direct investment
- Scale
- 100 = largest net FDI inflow (% GDP), 0 = lowest — descriptive, not better or worse
- Raw value
- 1.51932 % of GDP (net inflows)
- Native score
- 88.56 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 36th percentile — ranks 127th of 201. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (1.52 − -1,303.11) / (170.05 − -1,303.11) = 88.56Min and max are this dataset's lowest (-1,303.11) and highest (170.05) values, so the score is relative to the current country set.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
- GDP growth (projection)Tier B
100 = highest projected growth, 0 = lowest
Ranks 158th of 189 · native score 7.99 · reference year 2031
16percentileHow is this calculated?
- Metric
- GDP growth (projection)
- Scale
- 100 = highest projected growth, 0 = lowest
- Raw value
- 1.72 % per year (avg 2026–2031)
- Native score
- 7.99 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 16th percentile — ranks 158th of 189. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (1.72 − 0.62) / (14.38 − 0.62) = 7.99Min and max are this dataset's lowest (0.62) and highest (14.38) values, so the score is relative to the current country set.
- Source
- IMF (World Economic Outlook) · International Monetary Fund
- License
- IMF terms (reuse with attribution)
- Reference year
- 2031
- Retrieved
- 2026-07-12
- Confidence
- Tier B — Reputable / modeled
- Source notes
- IMF World Economic Outlook via the IMF DataMapper API (imf.org/external/datamapper).
- GDP per capita (PPP)Tier A
100 = highest GDP per capita in the dataset, 0 = lowest (log scale)
Ranks 63rd of 202 · native score 72.87 · reference year 2024
69percentileHow is this calculated?
- Metric
- GDP per capita (PPP)
- Scale
- 100 = highest GDP per capita in the dataset, 0 = lowest (log scale)
- Raw value
- 41,197.9 international $ (PPP, current)
- Native score
- 72.87 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 69th percentile — ranks 63rd of 202. Comparable across metrics.
- Normalization
- Log + min–max (log scale, for skewed data)
score = 100 · (ln 41,197.93 − ln 1,154.89) / (ln 155,941.29 − ln 1,154.89) = 72.87Log scale (values are heavily skewed). 0 and 100 are the dataset's min (1,154.89) and max (155,941.29) — relative, not absolute or year-over-year comparable.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = largest government revenue (% GDP), 0 = lowest — descriptive, not better or worse
Ranks 107th of 155 · native score 14.53 · reference year 2024
31percentileHow is this calculated?
- Metric
- Government revenue
- Scale
- 100 = largest government revenue (% GDP), 0 = lowest — descriptive, not better or worse
- Raw value
- 19.3844 % of GDP
- Native score
- 14.53 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 31th percentile — ranks 107th of 155. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (19.38 − 3.03) / (115.55 − 3.03) = 14.53Min and max are this dataset's lowest (3.03) and highest (115.55) values, so the score is relative to the current country set.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = highest gross savings (% GDP), 0 = lowest — descriptive, not better or worse
Ranks 105th of 177 · native score 51.36 · reference year 2024
41percentileHow is this calculated?
- Metric
- Gross savings
- Scale
- 100 = highest gross savings (% GDP), 0 = lowest — descriptive, not better or worse
- Raw value
- 19.2134 % of GDP
- Native score
- 51.36 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 41th percentile — ranks 105th of 177. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (19.21 − -21.13) / (57.42 − -21.13) = 51.36Min and max are this dataset's lowest (-21.13) and highest (57.42) values, so the score is relative to the current country set.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = highest inflation in the dataset, 0 = lowest/most negative — descriptive, not better or worse
Ranks 168th of 192 · native score 12.76 · reference year 2024
13percentileHow is this calculated?
- Metric
- Inflation rate
- Scale
- 100 = highest inflation in the dataset, 0 = lowest/most negative — descriptive, not better or worse
- Raw value
- 0.409162 % annual change (CPI)
- Native score
- 12.76 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 13th percentile — ranks 168th of 192. Comparable across metrics.
- Normalization
- Percentile rank across countries
score = percentile rank of 0.41 among 192 countries = 12.76The score is the country's position in the distribution.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
- Labour productivityTier A
100 = highest output per worker, 0 = lowest
Ranks 62nd of 177 · native score 70.27 · reference year 2024
65percentileHow is this calculated?
- Metric
- Labour productivity
- Scale
- 100 = highest output per worker, 0 = lowest
- Raw value
- 65,603.6 constant PPP$ per worker
- Native score
- 70.27 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 65th percentile — ranks 62nd of 177. Comparable across metrics.
- Normalization
- Log + min–max (log scale, for skewed data)
score = 100 · (ln 65,603.6 − ln 2,444.23) / (ln 263,863.91 − ln 2,444.23) = 70.27Log scale (values are heavily skewed). 0 and 100 are the dataset's min (2,444.23) and max (263,863.91) — relative, not absolute or year-over-year comparable.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = highest debt (% GDP) in the dataset, 0 = lowest — descriptive, not better or worse
Ranks 52nd of 193 · native score 23.91 · reference year 2025
73percentileHow is this calculated?
- Metric
- Government debt
- Scale
- 100 = highest debt (% GDP) in the dataset, 0 = lowest — descriptive, not better or worse
- Raw value
- 73.8 % of GDP
- Native score
- 23.91 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 73th percentile — ranks 52nd of 193. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (73.8 − 0) / (308.7 − 0) = 23.91Min and max are this dataset's lowest (0) and highest (308.7) values, so the score is relative to the current country set.
- Source
- IMF (World Economic Outlook) · International Monetary Fund
- License
- IMF terms (reuse with attribution)
- Reference year
- 2025
- Retrieved
- 2026-07-12
- Confidence
- Tier B — Reputable / modeled
- Source notes
- IMF World Economic Outlook via the IMF DataMapper API (imf.org/external/datamapper).
- Unemployment rateTier A
100 = lowest unemployment in the dataset, 0 = highest
Ranks 144th of 186 · native score 73.36 · reference year 2025
23percentileHow is this calculated?
- Metric
- Unemployment rate
- Scale
- 100 = lowest unemployment in the dataset, 0 = highest
- Raw value
- 9.207 % of labour force
- Native score
- 73.36 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 23th percentile — ranks 144th of 186. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 − [ 100 · (9.21 − 0.13) / (34.2 − 0.13) ] = 73.36Min and max are this dataset's lowest (0.13) and highest (34.2) values, so the score is relative to the current country set. Direction is inverted (higher raw value = worse), so the position is subtracted from 100.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2025
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
- Youth unemployment rateTier A
100 = lowest youth unemployment (best), 0 = highest
Ranks 133rd of 186 · native score 75.38 · reference year 2025
29percentileHow is this calculated?
- Metric
- Youth unemployment rate
- Scale
- 100 = lowest youth unemployment (best), 0 = highest
- Raw value
- 19.248 % of labour force 15–24
- Native score
- 75.38 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 29th percentile — ranks 133rd of 186. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 − [ 100 · (19.25 − 0.46) / (76.77 − 0.46) ] = 75.38Min and max are this dataset's lowest (0.46) and highest (76.77) values, so the score is relative to the current country set. Direction is inverted (higher raw value = worse), so the position is subtracted from 100.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2025
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
Quality of life & wellbeing
- Human Development IndexTier A
100 = highest human development (HDI 1.0), 0 = lowest (HDI 0)
Ranks 66th of 193 · native score 82 · reference year 2023
66percentileHow is this calculated?
- Metric
- Human Development Index
- Scale
- 100 = highest human development (HDI 1.0), 0 = lowest (HDI 0)
- Raw value
- 0.82 HDI (0–1)
- Native score
- 82 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 66th percentile — ranks 66th of 193. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (0.82 − 0) / (1 − 0) = 82The index is kept on its own published scale.
- Source
- UNDP — Human Development Report · United Nations Development Programme
- License
- CC BY 3.0 IGO
- Reference year
- 2023
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- Human Development Index, retrieved via the Our World in Data mirror (ourworldindata.org/grapher/human-development-index), which republishes the UNDP HDR series. Primary source and methodology owner is UNDP.