[EAP_2EAP_SEX_AGE_GEO_NB] Labour force by sex, age and rural / urban areas -- ILO modelled estimates, Nov. 2021 (thousands)
Retrieved by DBnomics on September 4, 2023 (6:24 AM).
[AFG] Afghanistan
[AGO] Angola
[ALB] Albania
[ARE] United Arab Emirates
[ARG] Argentina
[ARM] Armenia
[AUS] Australia
[AUT] Austria
[AZE] Azerbaijan
[BDI] Burundi
[BEL] Belgium
[BEN] Benin
[BFA] Burkina Faso
[BGD] Bangladesh
[BGR] Bulgaria
[BHR] Bahrain
[BHS] Bahamas
[BIH] Bosnia and Herzegovina
[BLR] Belarus
[BLZ] Belize
[BOL] Bolivia
[BRA] Brazil
[BRB] Barbados
[BRN] Brunei Darussalam
[BTN] Bhutan
[BWA] Botswana
[CAF] Central African Republic
[CAN] Canada
[CHA] Channel Islands
[CHE] Switzerland
[CHL] Chile
[CHN] China
[CIV] Côte d'Ivoire
[CMR] Cameroon
[COD] Congo, Democratic Republic of the
[COG] Congo
[COL] Colombia
[COM] Comoros
[CPV] Cabo Verde
[CRI] Costa Rica
[CUB] Cuba
[CYP] Cyprus
[CZE] Czechia
[DEU] Germany
[DJI] Djibouti
[DNK] Denmark
[DOM] Dominican Republic
[DZA] Algeria
[ECU] Ecuador
[EGY] Egypt
[ERI] Eritrea
[ESH] Western Sahara
[ESP] Spain
[EST] Estonia
[ETH] Ethiopia
[FIN] Finland
[FJI] Fiji
[FRA] France
[GAB] Gabon
[GBR] United Kingdom
[GEO] Georgia
[GHA] Ghana
[GIN] Guinea
[GMB] Gambia
[GNB] Guinea-Bissau
[GNQ] Equatorial Guinea
[GRC] Greece
[GTM] Guatemala
[GUM] Guam
[GUY] Guyana
[HND] Honduras
[HRV] Croatia
[HTI] Haiti
[HUN] Hungary
[IDN] Indonesia
[IND] India
[IRL] Ireland
[IRN] Iran, Islamic Republic of
[IRQ] Iraq
[ISL] Iceland
[ISR] Israel
[ITA] Italy
[JAM] Jamaica
[JOR] Jordan
[JPN] Japan
[KAZ] Kazakhstan
[KEN] Kenya
[KGZ] Kyrgyzstan
[KHM] Cambodia
[KOR] Korea, Republic of
[KWT] Kuwait
[LAO] Lao People's Democratic Republic
[LBN] Lebanon
[LBR] Liberia
[LBY] Libya
[LCA] Saint Lucia
[LKA] Sri Lanka
[LSO] Lesotho
[LTU] Lithuania
[LUX] Luxembourg
[LVA] Latvia
[MAR] Morocco
[MDA] Moldova, Republic of
[MDG] Madagascar
[MDV] Maldives
[MEX] Mexico
[MKD] North Macedonia
[MLI] Mali
[MLT] Malta
[MMR] Myanmar
[MNE] Montenegro
[MNG] Mongolia
[MOZ] Mozambique
[MRT] Mauritania
[MUS] Mauritius
[MWI] Malawi
[MYS] Malaysia
[NAM] Namibia
[NCL] New Caledonia
[NER] Niger
[NGA] Nigeria
[NIC] Nicaragua
[NLD] Netherlands
[NOR] Norway
[NPL] Nepal
[NZL] New Zealand
[OMN] Oman
[PAK] Pakistan
[PAN] Panama
[PER] Peru
[PHL] Philippines
[PNG] Papua New Guinea
[POL] Poland
[PRI] Puerto Rico
[PRK] Korea, Democratic People's Republic of
[PRT] Portugal
[PRY] Paraguay
[PSE] Occupied Palestinian Territory
[PYF] French Polynesia
[QAT] Qatar
[ROU] Romania
[RUS] Russian Federation
[RWA] Rwanda
[SAU] Saudi Arabia
[SDN] Sudan
[SEN] Senegal
[SLB] Solomon Islands
[SLE] Sierra Leone
[SLV] El Salvador
[SOM] Somalia
[SRB] Serbia
[SSD] South Sudan
[STP] Sao Tome and Principe
[SUR] Suriname
[SVK] Slovakia
[SVN] Slovenia
[SWE] Sweden
[SWZ] Eswatini
[SYR] Syrian Arab Republic
[TCD] Chad
[TGO] Togo
[THA] Thailand
[TJK] Tajikistan
[TKM] Turkmenistan
[TLS] Timor-Leste
[TON] Tonga
[TTO] Trinidad and Tobago
[TUN] Tunisia
[TUR] Türkiye
[TWN] Taiwan, China
[TZA] Tanzania, United Republic of
[UGA] Uganda
[UKR] Ukraine
[URY] Uruguay
[USA] United States
[UZB] Uzbekistan
[VCT] Saint Vincent and the Grenadines
[VEN] Venezuela, Bolivarian Republic of
[VIR] United States Virgin Islands
[VNM] Viet Nam
[VUT] Vanuatu
[WSM] Samoa
[X01] World
[X02] World: Low income
[X03] World: Lower-middle income
[X04] World: Upper-middle income
[X05] World: High income
[X06] Africa
[X07] Africa: Low income
[X08] Africa: Lower-middle income
[X09] Africa: Upper-middle income
[X10] Northern Africa
[X11] Northern Africa: Lower-middle income
[X12] Northern Africa: Upper-middle income
[X13] Sub-Saharan Africa
[X14] Sub-Saharan Africa: Low income
[X15] Sub-Saharan Africa: Lower-middle income
[X16] Sub-Saharan Africa: Upper-middle income
[X17] Central Africa
[X18] Eastern Africa
[X19] Southern Africa
[X20] Western Africa
[X21] Americas
[X23] Americas: Lower-middle income
[X24] Americas: Upper-middle income
[X25] Americas: High income
[X26] Latin America and the Caribbean
[X28] Latin America and the Caribbean: Lower-middle income
[X29] Latin America and the Caribbean: Upper-middle income
[X30] Latin America and the Caribbean: High income
[X31] Caribbean
[X32] Central America
[X33] South America
[X34] Northern America
[X35] Northern America: High income
[X36] Arab States
[X37] Arab States: Lower-middle income
[X38] Arab States: Upper-middle income
[X39] Arab States: High income
[X40] Asia and the Pacific
[X41] Asia and the Pacific: Low income
[X42] Asia and the Pacific: Lower-middle income
[X43] Asia and the Pacific: Upper-middle income
[X44] Asia and the Pacific: High income
[X45] Eastern Asia
[X46] Eastern Asia: Low income
[X47] Eastern Asia: Upper-middle income
[X48] Eastern Asia: High income
[X49] South-Eastern Asia and the Pacific
[X51] South-Eastern Asia and the Pacific: Lower-middle income
[X52] South-Eastern Asia and the Pacific: Upper-middle income
[X53] South-Eastern Asia and the Pacific: High income
[X54] South-Eastern Asia
[X55] Pacific Islands
[X56] Southern Asia
[X57] Southern Asia: Low income
[X58] Southern Asia: Lower-middle income
[X59] Southern Asia: Upper-middle income
[X60] Europe and Central Asia
[X61] Europe and Central Asia: Lower-middle income
[X62] Europe and Central Asia: Upper-middle income
[X63] Europe and Central Asia: High income
[X64] Northern, Southern and Western Europe
[X65] Northern, Southern and Western Europe: Upper-middle income
[X66] Northern, Southern and Western Europe: High income
[X67] Northern Europe
[X68] Southern Europe
[X69] Western Europe
[X70] Eastern Europe
[X71] Eastern Europe: Lower-middle income
[X72] Eastern Europe: Upper-middle income
[X73] Eastern Europe: High income
[X74] Central Asia
[X75] Central and Western Asia: Lower-middle income
[X76] Central and Western Asia: Upper-middle income
[X77] Central and Western Asia: High income
[X78] Central and Western Asia
[X79] Western Asia
[X80] Northern Africa: Low income
[X82] European Union 28
[X83] G20
[X84] ASEAN
[X85] BRICS
[X86] Eastern Asia: Lower-middle income
[X87] World excluding BRICS
[X88] G7
[X89] MENA
[X90] Arab League
[X91] CARICOM
[X92] European Union 27
[X94] Arab States: Low income
[YEM] Yemen
[ZAF] South Africa
[ZMB] Zambia
[ZWE] Zimbabwe
[XA_12987] ILO - Modelled Estimates
[XA_12988] ILO - Modelled Estimates
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[XA_1916] ILO - Modelled Estimates
[XA_1920] ILO - Modelled Estimates
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[XA_1946] ILO - Modelled Estimates
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[XA_1950] ILO - Modelled Estimates
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[XA_1960] ILO - Modelled Estimates
[XA_1972] ILO - Modelled Estimates
[XA_1976] ILO - Modelled Estimates
[XA_1978] ILO - Modelled Estimates
[XA_1980] ILO - Modelled Estimates
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[XA_1984] ILO - Modelled Estimates
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[XA_1988] ILO - Modelled Estimates
[XA_1990] ILO - Modelled Estimates
[XA_1992] ILO - Modelled Estimates
[XA_1996] ILO - Modelled Estimates
[XA_2000] ILO - Modelled Estimates
[XA_2002] ILO - Modelled Estimates
[XA_2004] ILO - Modelled Estimates
[XA_2007] ILO - Modelled Estimates
[XA_2008] ILO - Modelled Estimates
[XA_2009] ILO - Modelled Estimates
[XA_2010] ILO - Modelled Estimates
[XA_2012] ILO - Modelled Estimates
[XA_2014] ILO - Modelled Estimates
[XA_2015] ILO - Modelled Estimates
[XA_2016] ILO - Modelled Estimates
[XA_2017] ILO - Modelled Estimates
[XA_2018] ILO - Modelled Estimates
[XA_2024] ILO - Modelled Estimates
[XA_2028] ILO - Modelled Estimates
[XA_2029] ILO - Modelled Estimates
[XA_2030] ILO - Modelled Estimates
[XA_2031] ILO - Modelled Estimates
[XA_2034] ILO - Modelled Estimates
[XA_2036] ILO - Modelled Estimates
[XA_2039] ILO - Modelled Estimates
[XA_2044] ILO - Modelled Estimates
[XA_2048] ILO - Modelled Estimates
[XA_2054] ILO - Modelled Estimates
[XA_2056] ILO - Modelled Estimates
[XA_2060] ILO - Modelled Estimates
[XA_2064] ILO - Modelled Estimates
[XA_2068] ILO - Modelled Estimates
[XA_2070] ILO - Modelled Estimates
[XA_2075] ILO - Modelled Estimates
[XA_2080] ILO - Modelled Estimates
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[XA_2089] ILO - Modelled Estimates
[XA_2090] ILO - Modelled Estimates
[XA_2092] ILO - Modelled Estimates
[XA_2093] ILO - Modelled Estimates
[XA_2096] ILO - Modelled Estimates
[XA_2097] ILO - Modelled Estimates
[XA_2098] ILO - Modelled Estimates
[XA_2100] ILO - Modelled Estimates
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[XA_2102] ILO - Modelled Estimates
[XA_2104] ILO - Modelled Estimates
[XA_2108] ILO - Modelled Estimates
[XA_2109] ILO - Modelled Estimates
[XA_2110] ILO - Modelled Estimates
[XA_2112] ILO - Modelled Estimates
[XA_2113] ILO - Modelled Estimates
[XA_2114] ILO - Modelled Estimates
[XA_2115] ILO - Modelled Estimates
[XA_2116] ILO - Modelled Estimates
[XA_2117] ILO - Modelled Estimates
[XA_2118] ILO - Modelled Estimates
[XA_2121] ILO - Modelled Estimates
[XA_2122] ILO - Modelled Estimates
[XA_2124] ILO - Modelled Estimates
[XA_2125] ILO - Modelled Estimates
[XA_2126] ILO - Modelled Estimates
[XA_2128] ILO - Modelled Estimates
[XA_2129] ILO - Modelled Estimates
[XA_2130] ILO - Modelled Estimates
[XA_2132] ILO - Modelled Estimates
[XA_2133] ILO - Modelled Estimates
[XA_2134] ILO - Modelled Estimates
[XA_2136] ILO - Modelled Estimates
[XA_2137] ILO - Modelled Estimates
[XA_2138] ILO - Modelled Estimates
[XA_2140] ILO - Modelled Estimates
[XA_2142] ILO - Modelled Estimates
[XA_2144] ILO - Modelled Estimates
[XA_2145] ILO - Modelled Estimates
[XA_2146] ILO - Modelled Estimates
[XA_2148] ILO - Modelled Estimates
[XA_2149] ILO - Modelled Estimates
[XA_2150] ILO - Modelled Estimates
[XA_2152] ILO - Modelled Estimates
[XA_2153] ILO - Modelled Estimates
[XA_2156] ILO - Modelled Estimates
[XA_2158] ILO - Modelled Estimates
[XA_2160] ILO - Modelled Estimates
[XA_2162] ILO - Modelled Estimates
[XA_2164] ILO - Modelled Estimates
[XA_2165] ILO - Modelled Estimates
[XA_2166] ILO - Modelled Estimates
[XA_2168] ILO - Modelled Estimates
[XA_2170] ILO - Modelled Estimates
[XA_2172] ILO - Modelled Estimates
[XA_2173] ILO - Modelled Estimates
[XA_2174] ILO - Modelled Estimates
[XA_2176] ILO - Modelled Estimates
[XA_2178] ILO - Modelled Estimates
[XA_2180] ILO - Modelled Estimates
[XA_2181] ILO - Modelled Estimates
[XA_2182] ILO - Modelled Estimates
[XA_2184] ILO - Modelled Estimates
[XA_2185] ILO - Modelled Estimates
[XA_2186] ILO - Modelled Estimates
[XA_2188] ILO - Modelled Estimates
[XA_2189] ILO - Modelled Estimates
[XA_2190] ILO - Modelled Estimates
[XA_2192] ILO - Modelled Estimates
[XA_2193] ILO - Modelled Estimates
[XA_2198] ILO - Modelled Estimates
[XA_2202] ILO - Modelled Estimates
[XA_2203] ILO - Modelled Estimates
[XA_2206] ILO - Modelled Estimates
[XA_2232] ILO - Modelled Estimates
[XA_2234] ILO - Modelled Estimates
[XA_8368] ILO - Modelled Estimates
[XA_8371] ILO - Modelled Estimates
[XA_8372] ILO - Modelled Estimates
[XA_8373] ILO - Modelled Estimates
[XA_8374] ILO - Modelled Estimates
[XA_8375] ILO - Modelled Estimates
[XA_8376] ILO - Modelled Estimates
[XA_8377] ILO - Modelled Estimates
[XA_8378] ILO - Modelled Estimates
[XA_8379] ILO - Modelled Estimates
[XA_8380] ILO - Modelled Estimates
[XA_8381] ILO - Modelled Estimates
[XA_8382] ILO - Modelled Estimates
[XA_8383] ILO - Modelled Estimates
[XA_8384] ILO - Modelled Estimates
[XA_8385] ILO - Modelled Estimates
[XA_8386] ILO - Modelled Estimates
[XA_8387] ILO - Modelled Estimates
[XA_8388] ILO - Modelled Estimates
[XA_8389] ILO - Modelled Estimates
[XA_8390] ILO - Modelled Estimates
[XA_8391] ILO - Modelled Estimates
[XA_8392] ILO - Modelled Estimates
[XA_8393] ILO - Modelled Estimates
[XA_8394] ILO - Modelled Estimates
[XA_8395] ILO - Modelled Estimates
[XA_8396] ILO - Modelled Estimates
[XA_8397] ILO - Modelled Estimates
[XA_8398] ILO - Modelled Estimates
[XA_8399] ILO - Modelled Estimates
[XA_8400] ILO - Modelled Estimates
[XA_8401] ILO - Modelled Estimates
[XA_8402] ILO - Modelled Estimates
[XA_8403] ILO - Modelled Estimates
[XA_8404] ILO - Modelled Estimates
[XA_8405] ILO - Modelled Estimates
[XA_8406] ILO - Modelled Estimates
[XA_8407] ILO - Modelled Estimates
[XA_8408] ILO - Modelled Estimates
[XA_8409] ILO - Modelled Estimates
[XA_8410] ILO - Modelled Estimates
[XA_8411] ILO - Modelled Estimates
[XA_8412] ILO - Modelled Estimates
[XA_8413] ILO - Modelled Estimates
[XA_8415] ILO - Modelled Estimates
[XA_8416] ILO - Modelled Estimates
[XA_8417] ILO - Modelled Estimates
[XA_8419] ILO - Modelled Estimates
[XA_8420] ILO - Modelled Estimates
[XA_8421] ILO - Modelled Estimates
[XA_8422] ILO - Modelled Estimates
[XA_8423] ILO - Modelled Estimates
[XA_8424] ILO - Modelled Estimates
[XA_8425] ILO - Modelled Estimates
[XA_8426] ILO - Modelled Estimates
[XA_8427] ILO - Modelled Estimates
[XA_8428] ILO - Modelled Estimates
[XA_8429] ILO - Modelled Estimates
[XA_8430] ILO - Modelled Estimates
[XA_8431] ILO - Modelled Estimates
[XA_8432] ILO - Modelled Estimates
[XA_8434] ILO - Modelled Estimates
[XA_8435] ILO - Modelled Estimates
[XA_8436] ILO - Modelled Estimates
[XA_8437] ILO - Modelled Estimates
[XA_8438] ILO - Modelled Estimates
[XA_8439] ILO - Modelled Estimates
[XA_8440] ILO - Modelled Estimates
[XA_8441] ILO - Modelled Estimates
[XA_8442] ILO - Modelled Estimates
[XA_8443] ILO - Modelled Estimates
[XA_8444] ILO - Modelled Estimates
[XA_8445] ILO - Modelled Estimates
[XA_8446] ILO - Modelled Estimates
[XA_8447] ILO - Modelled Estimates
[XA_8448] ILO - Modelled Estimates
[XA_8449] ILO - Modelled Estimates
[XA_8450] ILO - Modelled Estimates
[AGE_YTHADULT_Y15-24] Age (Youth, adults): 15-24
[AGE_YTHADULT_YGE15] Age (Youth, adults): 15+
[AGE_YTHADULT_YGE25] Age (Youth, adults): 25+
[GEO_COV_NAT] Area type: National
[GEO_COV_RUR] Area type: Rural
[GEO_COV_URB] Area type: Urban
[SEX_F] Sex: Female
[SEX_M] Sex: Male
[SEX_T] Sex: Total
[A] Annual
Search filters
Reference area [ref_area] (275)
Source [source] (275)
Classification 1 [classif1] (3)
Classification 2 [classif2] (3)
Sex [sex] (3)
Frequency [frequency] (1)
This dataset has 7,425 series:
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_NAT.SEX_F.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Age (Youth, adults): 15-24 – Area type: National – Sex: Female – Annual
- from
- 2005=356.113
- to
- 2020=668.553
- min:
- 351.791
- max:
- 825.078
- avg:
- 520.842
- σ:
- 168.945
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_NAT.SEX_M.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Age (Youth, adults): 15-24 – Area type: National – Sex: Male – Annual
- from
- 2005=1,651.881
- to
- 2020=2,245.871
- min:
- 1,651.881
- max:
- 2,461.993
- avg:
- 2,014.901
- σ:
- 282.033
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_NAT.SEX_T.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Age (Youth, adults): 15-24 – Area type: National – Sex: Total – Annual
- from
- 2005=2,007.994
- to
- 2020=2,914.424
- min:
- 2,007.994
- max:
- 3,287.071
- avg:
- 2,535.743
- σ:
- 448.437
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_RUR.SEX_F.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Age (Youth, adults): 15-24 – Area type: Rural – Sex: Female – Annual
- from
- 2005=279.549
- to
- 2020=546.362
- min:
- 279.549
- max:
- 660.896
- avg:
- 418.343
- σ:
- 132.998
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_RUR.SEX_M.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Age (Youth, adults): 15-24 – Area type: Rural – Sex: Male – Annual
- from
- 2005=1,221.577
- to
- 2020=1,744.538
- min:
- 1,221.577
- max:
- 1,898.206
- avg:
- 1,544.961
- σ:
- 232.702
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_RUR.SEX_T.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Age (Youth, adults): 15-24 – Area type: Rural – Sex: Total – Annual
- from
- 2005=1,501.125
- to
- 2020=2,290.9
- min:
- 1,501.125
- max:
- 2,559.102
- avg:
- 1,963.304
- σ:
- 363.362
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_URB.SEX_F.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Age (Youth, adults): 15-24 – Area type: Urban – Sex: Female – Annual
- from
- 2005=76.565
- to
- 2020=122.191
- min:
- 68.579
- max:
- 170.524
- avg:
- 102.499
- σ:
- 37.388
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_URB.SEX_M.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Age (Youth, adults): 15-24 – Area type: Urban – Sex: Male – Annual
- from
- 2005=430.304
- to
- 2020=501.333
- min:
- 414.724
- max:
- 563.787
- avg:
- 469.94
- σ:
- 52.459
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_URB.SEX_T.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Age (Youth, adults): 15-24 – Area type: Urban – Sex: Total – Annual
- from
- 2005=506.868
- to
- 2020=623.524
- min:
- 483.321
- max:
- 727.969
- avg:
- 572.439
- σ:
- 89.597
[AFG.XA_2198.AGE_YTHADULT_YGE15.GEO_COV_NAT.SEX_F.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Age (Youth, adults): 15+ – Area type: National – Sex: Female – Annual
- from
- 2005=1,007.254
- to
- 2020=1,781.593
- min:
- 1,007.254
- max:
- 2,291.757
- avg:
- 1,480.809
- σ:
- 436.82
Series code | 2005 | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_NAT.SEX_F.A] | 356.113 | 355.682 | 353.275 | 351.791 | 354.743 | 364.58 | 396.196 | 436.282 | 491.761 | 552.436 | 616.715 | 679.894 | 745.197 | 785.17 | 825.078 | 668.553 |
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_NAT.SEX_M.A] | 1651.881 | 1672.484 | 1685.712 | 1700.269 | 1727.084 | 1773.583 | 1864.955 | 1971.028 | 2066.165 | 2157.021 | 2236.425 | 2290.216 | 2334.329 | 2399.403 | 2461.993 | 2245.871 |
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_NAT.SEX_T.A] | 2007.994 | 2028.166 | 2038.986 | 2052.06 | 2081.827 | 2138.163 | 2261.151 | 2407.309 | 2557.926 | 2709.457 | 2853.14 | 2970.11 | 3079.526 | 3184.573 | 3287.071 | 2914.424 |
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_RUR.SEX_F.A] | 279.549 | 281.145 | 281.165 | 281.883 | 286.146 | 296 | 323.682 | 358.625 | 406.567 | 459.339 | 501.062 | 538.869 | 574.673 | 617.521 | 660.896 | 546.362 |
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_RUR.SEX_M.A] | 1221.577 | 1245.317 | 1263.787 | 1283.37 | 1312.36 | 1356.566 | 1435.4 | 1526.466 | 1609.295 | 1689.628 | 1738.096 | 1766.029 | 1786.18 | 1842.567 | 1898.206 | 1744.538 |
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_RUR.SEX_T.A] | 1501.125 | 1526.462 | 1544.952 | 1565.253 | 1598.506 | 1652.566 | 1759.082 | 1885.09 | 2015.863 | 2148.967 | 2239.158 | 2304.898 | 2360.853 | 2460.087 | 2559.102 | 2290.9 |
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_URB.SEX_F.A] | 76.565 | 74.537 | 72.11 | 69.907 | 68.597 | 68.579 | 72.515 | 77.657 | 85.194 | 93.097 | 115.653 | 141.026 | 170.524 | 167.65 | 164.182 | 122.191 |
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_URB.SEX_M.A] | 430.304 | 427.168 | 421.924 | 416.899 | 414.724 | 417.017 | 429.554 | 444.562 | 456.87 | 467.393 | 498.329 | 524.187 | 548.149 | 556.836 | 563.787 | 501.333 |
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_URB.SEX_T.A] | 506.868 | 501.705 | 494.034 | 486.806 | 483.321 | 485.597 | 502.069 | 522.219 | 542.064 | 560.489 | 613.982 | 665.213 | 718.674 | 724.486 | 727.969 | 623.524 |
[AFG.XA_2198.AGE_YTHADULT_YGE15.GEO_COV_NAT.SEX_F.A] | 1007.254 | 1025.5 | 1039.803 | 1055.488 | 1079.191 | 1115.333 | 1186.475 | 1273.991 | 1411.328 | 1561.475 | 1722.661 | 1891.848 | 2070.318 | 2178.922 | 2291.757 | 1781.593 |
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Reference area [ref_area] (275)
Source [source] (275)
Classification 1 [classif1] (3)
Classification 2 [classif2] (3)
Sex [sex] (3)
Frequency [frequency] (1)
This dataset has 7,425 series:
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_NAT.SEX_F.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Age (Youth, adults): 15-24 – Area type: National – Sex: Female – Annual
- from
- 2005=356.113
- to
- 2020=668.553
- min:
- 351.791
- max:
- 825.078
- avg:
- 520.842
- σ:
- 168.945
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_NAT.SEX_M.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Age (Youth, adults): 15-24 – Area type: National – Sex: Male – Annual
- from
- 2005=1,651.881
- to
- 2020=2,245.871
- min:
- 1,651.881
- max:
- 2,461.993
- avg:
- 2,014.901
- σ:
- 282.033
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_NAT.SEX_T.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Age (Youth, adults): 15-24 – Area type: National – Sex: Total – Annual
- from
- 2005=2,007.994
- to
- 2020=2,914.424
- min:
- 2,007.994
- max:
- 3,287.071
- avg:
- 2,535.743
- σ:
- 448.437
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_RUR.SEX_F.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Age (Youth, adults): 15-24 – Area type: Rural – Sex: Female – Annual
- from
- 2005=279.549
- to
- 2020=546.362
- min:
- 279.549
- max:
- 660.896
- avg:
- 418.343
- σ:
- 132.998
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_RUR.SEX_M.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Age (Youth, adults): 15-24 – Area type: Rural – Sex: Male – Annual
- from
- 2005=1,221.577
- to
- 2020=1,744.538
- min:
- 1,221.577
- max:
- 1,898.206
- avg:
- 1,544.961
- σ:
- 232.702
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_RUR.SEX_T.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Age (Youth, adults): 15-24 – Area type: Rural – Sex: Total – Annual
- from
- 2005=1,501.125
- to
- 2020=2,290.9
- min:
- 1,501.125
- max:
- 2,559.102
- avg:
- 1,963.304
- σ:
- 363.362
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_URB.SEX_F.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Age (Youth, adults): 15-24 – Area type: Urban – Sex: Female – Annual
- from
- 2005=76.565
- to
- 2020=122.191
- min:
- 68.579
- max:
- 170.524
- avg:
- 102.499
- σ:
- 37.388
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_URB.SEX_M.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Age (Youth, adults): 15-24 – Area type: Urban – Sex: Male – Annual
- from
- 2005=430.304
- to
- 2020=501.333
- min:
- 414.724
- max:
- 563.787
- avg:
- 469.94
- σ:
- 52.459
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_URB.SEX_T.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Age (Youth, adults): 15-24 – Area type: Urban – Sex: Total – Annual
- from
- 2005=506.868
- to
- 2020=623.524
- min:
- 483.321
- max:
- 727.969
- avg:
- 572.439
- σ:
- 89.597
[AFG.XA_2198.AGE_YTHADULT_YGE15.GEO_COV_NAT.SEX_F.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Age (Youth, adults): 15+ – Area type: National – Sex: Female – Annual
- from
- 2005=1,007.254
- to
- 2020=1,781.593
- min:
- 1,007.254
- max:
- 2,291.757
- avg:
- 1,480.809
- σ:
- 436.82
Series code | 2005 | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_NAT.SEX_F.A] | 356.113 | 355.682 | 353.275 | 351.791 | 354.743 | 364.58 | 396.196 | 436.282 | 491.761 | 552.436 | 616.715 | 679.894 | 745.197 | 785.17 | 825.078 | 668.553 |
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_NAT.SEX_M.A] | 1651.881 | 1672.484 | 1685.712 | 1700.269 | 1727.084 | 1773.583 | 1864.955 | 1971.028 | 2066.165 | 2157.021 | 2236.425 | 2290.216 | 2334.329 | 2399.403 | 2461.993 | 2245.871 |
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_NAT.SEX_T.A] | 2007.994 | 2028.166 | 2038.986 | 2052.06 | 2081.827 | 2138.163 | 2261.151 | 2407.309 | 2557.926 | 2709.457 | 2853.14 | 2970.11 | 3079.526 | 3184.573 | 3287.071 | 2914.424 |
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_RUR.SEX_F.A] | 279.549 | 281.145 | 281.165 | 281.883 | 286.146 | 296 | 323.682 | 358.625 | 406.567 | 459.339 | 501.062 | 538.869 | 574.673 | 617.521 | 660.896 | 546.362 |
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_RUR.SEX_M.A] | 1221.577 | 1245.317 | 1263.787 | 1283.37 | 1312.36 | 1356.566 | 1435.4 | 1526.466 | 1609.295 | 1689.628 | 1738.096 | 1766.029 | 1786.18 | 1842.567 | 1898.206 | 1744.538 |
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_RUR.SEX_T.A] | 1501.125 | 1526.462 | 1544.952 | 1565.253 | 1598.506 | 1652.566 | 1759.082 | 1885.09 | 2015.863 | 2148.967 | 2239.158 | 2304.898 | 2360.853 | 2460.087 | 2559.102 | 2290.9 |
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_URB.SEX_F.A] | 76.565 | 74.537 | 72.11 | 69.907 | 68.597 | 68.579 | 72.515 | 77.657 | 85.194 | 93.097 | 115.653 | 141.026 | 170.524 | 167.65 | 164.182 | 122.191 |
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_URB.SEX_M.A] | 430.304 | 427.168 | 421.924 | 416.899 | 414.724 | 417.017 | 429.554 | 444.562 | 456.87 | 467.393 | 498.329 | 524.187 | 548.149 | 556.836 | 563.787 | 501.333 |
[AFG.XA_2198.AGE_YTHADULT_Y15-24.GEO_COV_URB.SEX_T.A] | 506.868 | 501.705 | 494.034 | 486.806 | 483.321 | 485.597 | 502.069 | 522.219 | 542.064 | 560.489 | 613.982 | 665.213 | 718.674 | 724.486 | 727.969 | 623.524 |
[AFG.XA_2198.AGE_YTHADULT_YGE15.GEO_COV_NAT.SEX_F.A] | 1007.254 | 1025.5 | 1039.803 | 1055.488 | 1079.191 | 1115.333 | 1186.475 | 1273.991 | 1411.328 | 1561.475 | 1722.661 | 1891.848 | 2070.318 | 2178.922 | 2291.757 | 1781.593 |
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