Wittgenstein Projection: Percentage of the total population by in Democratic Republic of Congo
Democratic Republic of Congo: Wittgenstein Projection: Percentage of the total population by was 0.0% in 2100. ◆ Volatile
Wittgenstein Projection: Percentage of the total population by in Democratic Republic of Congo, 2010–2100
Source: Wittgenstein Centre for Demography and Global Human Capital: http://www.oeaw.ac.at/vid/dataexplorer/.
Analysis
The most recent figure for wittgenstein projection: percentage of the total population by in Democratic Republic of Congo is 0.0%, measured in 2100. That is the lowest value across all 19 years on record.
Over the whole period, wittgenstein projection: percentage of the total population by in Democratic Republic of Congo peaked at 0.0% in 2010 and was at its lowest, 0.0%, in 2065.
That places Democratic Republic of Congo 33rd out of 166 countries with data for 2100, putting it in the top quarter.
The series is highly variable year to year, so single readings are best treated with caution.
Wittgenstein Projection: Percentage of the total population by in Democratic Republic of Congo, year by year
| Year | Value | Change |
|---|---|---|
| 2010 | 0.0% | — |
| 2015 | 0.0% | -25.0% |
| 2020 | 0.0% | +0.0% |
| 2025 | 0.0% | -33.3% |
| 2030 | 0.0% | +0.0% |
| 2035 | 0.0% | +0.0% |
| 2040 | 0.0% | -50.0% |
| 2045 | 0.0% | +0.0% |
| 2050 | 0.0% | +0.0% |
| 2055 | 0.0% | +0.0% |
| 2060 | 0.0% | +0.0% |
| 2065 | 0.0% | -100.0% |
| 2070 | 0.0% | — |
| 2075 | 0.0% | — |
| 2080 | 0.0% | — |
| 2085 | 0.0% | — |
| 2090 | 0.0% | — |
| 2095 | 0.0% | — |
| 2100 | 0.0% | — |
Averages by decade
| Decade | Average | Lowest | Highest | Years |
|---|---|---|---|---|
| 2010s | 0.0% | 0.0% | 0.0% | 2 |
| 2020s | 0.0% | 0.0% | 0.0% | 2 |
| 2030s | 0.0% | 0.0% | 0.0% | 2 |
| 2040s | 0.0% | 0.0% | 0.0% | 2 |
| 2050s | 0.0% | 0.0% | 0.0% | 2 |
| 2060s | 0.0% | 0.0% | 0.0% | 2 |
| 2070s | 0.0% | 0.0% | 0.0% | 2 |
| 2080s | 0.0% | 0.0% | 0.0% | 2 |
| 2090s | 0.0% | 0.0% | 0.0% | 2 |
| 2100s | 0.0% | 0.0% | 0.0% | 1 |
Countries ranked near Democratic Republic of Congo
- 33 Albania 0.0% compare
- 33 Algeria 0.0% compare
- 33 Argentina 0.0% compare
- 33 Armenia 0.0%
- 33 Aruba 0.0% compare
- 33 Australia 0.0%
- 33 Austria 0.0%
- 33 Azerbaijan 0.0% compare
- 33 Bahamas 0.0% compare
- 33 Bahrain 0.0% compare
- 33 Belarus 0.0%
- 33 Belgium 0.0% compare
- 33 Belize 0.0% compare
- 33 Bolivia, Plurinational State of 0.0% compare
- 33 Bosnia and Herzegovina 0.0% compare
- 33 Brazil 0.0% compare
- 33 Bulgaria 0.0% compare
- 33 Cameroon 0.0% compare
- 33 Canada 0.0% compare
- 33 Central African Republic 0.0% compare
- 33 Chile 0.0% compare
- 33 China 0.0% compare
- 33 Colombia 0.0% compare
- 33 Comoros 0.0% compare
- 33 Congo 0.0% compare
- 33 Costa Rica 0.0% compare
- 33 Croatia 0.0% compare
- 33 Cuba 0.0% compare
- 33 Cyprus 0.0%
- 33 Czechia 0.0%
- 33 Denmark 0.0%
- 33 Dominican Republic 0.0% compare
- 33 Ecuador 0.0% compare
- 33 Egypt 0.0% compare
- 33 El Salvador 0.0% compare
- 33 Equatorial Guinea 0.0% compare
- 33 Estonia 0.0%
- 33 Eswatini 0.0% compare
- 33 Finland 0.0%
- 33 France 0.0% compare
- 33 French Polynesia 0.0% compare
- 33 Gabon 0.0% compare
- 33 Georgia 0.0%
- 33 Germany 0.0% compare
- 33 Greece 0.0% compare
- 33 Guyana 0.0% compare
- 33 Haiti 0.0% compare
- 33 Honduras 0.0% compare
- 33 Hong Kong, China 0.0% compare
- 33 Hungary 0.0%
- 33 Iceland 0.0%
- 33 Indonesia 0.0% compare
- 33 Iran, Islamic Republic of 0.0% compare
- 33 Iraq 0.0% compare
- 33 Ireland 0.0%
- 33 Israel 0.0% compare
- 33 Italy 0.0% compare
- 33 Jamaica 0.0% compare
- 33 Japan 0.0%
- 33 Jordan 0.0% compare
- 33 Kazakhstan 0.0%
- 33 Kenya 0.0% compare
- 33 Republic of Korea 0.0% compare
- 33 Kuwait 0.0% compare
- 33 Kyrgyzstan 0.0%
- 33 Latvia 0.0%
- 33 Lebanon 0.0% compare
- 33 Lesotho 0.0% compare
- 33 Lithuania 0.0%
- 33 Luxembourg 0.0% compare
- 33 Macau, China 0.0% compare
- 33 Malaysia 0.0% compare
- 33 Maldives 0.0% compare
- 33 Malta 0.0% compare
- 33 Mauritius 0.0% compare
- 33 Mexico 0.0% compare
- 33 Republic of Moldova 0.0%
- 33 Mongolia 0.0% compare
- 33 Montenegro 0.0% compare
- 33 Myanmar 0.0% compare
- 33 Namibia 0.0% compare
- 33 Netherlands 0.0% compare
- 33 New Caledonia 0.0% compare
- 33 New Zealand 0.0%
- 33 Nigeria 0.0% compare
- 33 North Macedonia 0.0% compare
- 33 Norway 0.0%
- 33 Panama 0.0% compare
- 33 Paraguay 0.0% compare
- 33 Peru 0.0% compare
- 33 Philippines 0.0% compare
- 33 Poland 0.0%
- 33 Portugal 0.0% compare
- 33 Puerto Rico 0.0% compare
- 33 Qatar 0.0% compare
- 33 Romania 0.0% compare
- 33 Russian Federation 0.0%
- 33 Samoa 0.0%
- 33 Sao Tome and Principe 0.0% compare
- 33 Saudi Arabia 0.0% compare
- 33 Serbia 0.0%
- 33 Singapore 0.0% compare
- 33 Slovakia 0.0%
- 33 Slovenia 0.0%
- 33 South Africa 0.0% compare
- 33 Spain 0.0% compare
- 33 Saint Lucia 0.0% compare
- 33 Saint Vincent and the Grenadines 0.0% compare
- 33 Suriname 0.0%
- 33 Sweden 0.0%
- 33 Switzerland 0.0%
- 33 Syria 0.0% compare
- 33 Tajikistan 0.0% compare
- 33 Tanzania, United Republic of 0.0% compare
- 33 Thailand 0.0% compare
- 33 Timor-Leste 0.0% compare
- 33 Tonga 0.0% compare
- 33 Trinidad and Tobago 0.0% compare
- 33 Tunisia 0.0% compare
- 33 Türkiye 0.0% compare
- 33 Turkmenistan 0.0%
- 33 Uganda 0.0% compare
- 33 Ukraine 0.0%
- 33 United Arab Emirates 0.0% compare
- 33 United Kingdom of Great Britain and Northern Ireland 0.0% compare
- 33 United States of America 0.0% compare
- 33 Uruguay 0.0% compare
- 33 Vanuatu 0.0% compare
- 33 Venezuela, Bolivarian Republic of 0.0% compare
- 33 Viet Nam 0.0% compare
- 33 Palestine, State of 0.0% compare
- 33 Zambia 0.0% compare
- 33 Zimbabwe 0.0% compare
More reference data data for Democratic Republic of Congo
- Emission Totals - Emissions (N2O) - Agricultural Soils 9.9 (2050)
- Emission Totals - Emissions (CO2eq) from N2O (AR5) - Manure applied 313.43 (2050)
- Emission Totals - Emissions (CO2eq) from N2O (AR5) - IPCC Agriculture 3,062 (2050)
- Emission Totals - Emissions (CO2eq) from CH4 (AR5) - Enteric 3,057 (2050)
- Emission Totals - Emissions (CO2eq) from CH4 (AR5) - Burning - Crop 235.34 (2050)
- Emission Totals - Emissions (CO2eq) (AR5) - Manure left on Pasture 1,764 (2050)
- Emission Totals - Emissions (CO2eq) (AR5) - Manure Management 601.15 (2050)
- Emission Totals - Emissions (N2O) - Crop Residues 1.82 (2050)
- Emission Totals - Emissions (N2O) - Burning - Crop residues 0.2179 (2050)
- Emission Totals - Emissions (CO2eq) from N2O (AR5) - Manure Management 380.5 (2050)
Frequently asked questions
- What is wittgenstein projection: percentage of the total population by in Democratic Republic of Congo?
- Wittgenstein projection: percentage of the total population by in Democratic Republic of Congo was 0.0% in 2100, according to Wittgenstein Centre for Demography and Global Human Capital: http://www.oeaw.ac.at/vid/dataexplorer/.
- What is the highest wittgenstein projection: percentage of the total population by recorded in Democratic Republic of Congo?
- The highest recorded value was 0.0% in 2010.
- What is the lowest wittgenstein projection: percentage of the total population by recorded in Democratic Republic of Congo?
- The lowest recorded value was 0.0% in 2065.
- How does Democratic Republic of Congo rank for wittgenstein projection: percentage of the total population by?
- Democratic Republic of Congo ranks 33rd out of 166 countries with data for 2100.
- Where does this Democratic Republic of Congo data come from?
- The figures come from Wittgenstein Centre for Demography and Global Human Capital: http://www.oeaw.ac.at/vid/dataexplorer/, published as part of Wittgenstein Projection: Percentage of the total population by highest level of educational attainment. No Education. Male. Statizoid updates them automatically from the source API.
Download this data
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About this data
Share of the population of the stated age group that has never attended school. Projections are based on collected census and survey data for the base year (around 2010) and the Medium Shared Socioeconomic Pathways (SSP2) projection model. The SSP2 is a middle-of-the-road scenario that combines medium fertility with medium mortality, medium migration, and the Global Education Trend (GET) education scenario. For more information and other projection models, consult the Wittgenstein Centre for Demography and Global Human Capital's website: http://www.oeaw.ac.at/vid/dataexplorer/