Lithuania vs Sub-Saharan Africa (SSA): Access to electricity, rural, Percent of rural population
Lithuania
100
in 2022
Sub-Saharan Africa (SSA)
30.66
in 2022
Lithuania rank
1st
Sub-Saharan Africa (SSA) rank
1st
Access to electricity, rural, Percent of rural population over time
- Lithuania
- Sub-Saharan Africa (SSA)
How they compare
Lithuania currently reports 100 against 30.66 in Sub-Saharan Africa (SSA), a difference of 69.34.
That makes Lithuania's figure about 3.3 times Sub-Saharan Africa (SSA)'s.
Across all 23 years both countries report, Lithuania has been ahead every year.
Lithuania ranks 1st and Sub-Saharan Africa (SSA) ranks 1st of 211 countries.
Lithuania has averaged higher in every one of the 3 decades both report.
Head to head by decade
| Decade | Lithuania | Sub-Saharan Africa (SSA) | Difference | Ahead |
|---|---|---|---|---|
| 2000s | 99.89 | 14.41 | 85.48 | Lithuania |
| 2010s | 99.97 | 21.92 | 78.05 | Lithuania |
| 2020s | 100 | 29.93 | 70.07 | Lithuania |
Averages of every year both report within each decade.
Frequently asked questions
- Which has higher access to electricity, rural, percent of rural population, Lithuania or Sub-Saharan Africa (SSA)?
- Lithuania, at 100 against 30.66 in Sub-Saharan Africa (SSA) as of 2022.
- What is the difference in access to electricity, rural, percent of rural population between Lithuania and Sub-Saharan Africa (SSA)?
- 69.34, with Lithuania ahead.
- How many years of comparable data are there for Lithuania and Sub-Saharan Africa (SSA)?
- 23 years are reported by both, from 2000 to 2022.
- How do Lithuania and Sub-Saharan Africa (SSA) rank globally for access to electricity, rural, percent of rural population?
- Lithuania ranks 1st and Sub-Saharan Africa (SSA) ranks 1st of 211 countries.
- Where does this data come from?
- International Monetary Fund, published as Access to electricity, rural, Percent of rural population (Not Applicable). Statizoid refreshes it automatically from the source and publishes the full history for both places.
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About this data
This dataset provides information on global climate and weather patterns, providing insights into temperature variations, land cover accounts, and shifts in mean sea levels.