[EMP_2EMP_SEX_GEO_OCU_NB] Employment by sex, rural / urban areas and occupation -- ILO modelled estimates, Nov. 2020 (thousands)
Retrieved by DBnomics on September 4, 2023 (6:24 AM).
[ref_area] Reference area
[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
[HKG] Hong Kong, China
[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
[MAC] Macau, China
[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
[SGP] Singapore
[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
[X22] Americas: Low income
[X23] Americas: Lower-middle income
[X24] Americas: Upper-middle income
[X25] Americas: High income
[X26] Latin America and the Caribbean
[X27] Latin America and the Caribbean: Low income
[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
[X81] Sub-Saharan Africa: High 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
[X93] Africa: High income
[X94] Arab States: Low income
[X95] Europe and Central Asia: Low income
[X96] Central and Western Asia: Low income
[YEM] Yemen
[ZAF] South Africa
[ZMB] Zambia
[ZWE] Zimbabwe
[source] Source
[XA_12987] ILO - Modelled Estimates
[XA_12988] ILO - Modelled Estimates
[XA_12989] ILO - Modelled Estimates
[XA_12990] ILO - Modelled Estimates
[XA_13328] ILO - Modelled Estimates
[XA_13329] ILO - Modelled Estimates
[XA_14065] ILO - Modelled Estimates
[XA_14066] ILO - Modelled Estimates
[XA_15672] ILO - Modelled Estimates
[XA_15716] ILO - Modelled Estimates
[XA_15724] ILO - Modelled Estimates
[XA_15725] ILO - Modelled Estimates
[XA_15726] ILO - Modelled Estimates
[XA_15736] ILO - Modelled Estimates
[XA_15737] ILO - Modelled Estimates
[XA_15738] ILO - Modelled Estimates
[XA_1829] ILO - Modelled Estimates
[XA_1830] ILO - Modelled Estimates
[XA_1832] ILO - Modelled Estimates
[XA_1835] ILO - Modelled Estimates
[XA_1836] ILO - Modelled Estimates
[XA_1837] ILO - Modelled Estimates
[XA_1839] ILO - Modelled Estimates
[XA_1843] ILO - Modelled Estimates
[XA_1848] ILO - Modelled Estimates
[XA_1849] ILO - Modelled Estimates
[XA_1850] ILO - Modelled Estimates
[XA_1852] ILO - Modelled Estimates
[XA_1854] ILO - Modelled Estimates
[XA_1858] ILO - Modelled Estimates
[XA_1862] ILO - Modelled Estimates
[XA_1866] ILO - Modelled Estimates
[XA_1868] ILO - Modelled Estimates
[XA_1869] ILO - Modelled Estimates
[XA_1871] ILO - Modelled Estimates
[XA_1872] ILO - Modelled Estimates
[XA_1874] ILO - Modelled Estimates
[XA_1875] ILO - Modelled Estimates
[XA_1877] ILO - Modelled Estimates
[XA_1881] ILO - Modelled Estimates
[XA_1883] ILO - Modelled Estimates
[XA_1884] ILO - Modelled Estimates
[XA_1885] ILO - Modelled Estimates
[XA_1893] ILO - Modelled Estimates
[XA_1897] ILO - Modelled Estimates
[XA_1901] ILO - Modelled Estimates
[XA_1905] ILO - Modelled Estimates
[XA_1907] ILO - Modelled Estimates
[XA_1909] ILO - Modelled Estimates
[XA_1913] ILO - Modelled Estimates
[XA_1914] ILO - Modelled Estimates
[XA_1916] ILO - Modelled Estimates
[XA_1920] ILO - Modelled Estimates
[XA_1921] ILO - Modelled Estimates
[XA_1922] ILO - Modelled Estimates
[XA_1924] ILO - Modelled Estimates
[XA_1928] ILO - Modelled Estimates
[XA_1931] ILO - Modelled Estimates
[XA_1932] ILO - Modelled Estimates
[XA_1934] ILO - Modelled Estimates
[XA_1935] ILO - Modelled Estimates
[XA_1936] ILO - Modelled Estimates
[XA_1937] ILO - Modelled Estimates
[XA_1938] ILO - Modelled Estimates
[XA_1939] ILO - Modelled Estimates
[XA_1940] ILO - Modelled Estimates
[XA_1942] ILO - Modelled Estimates
[XA_1943] ILO - Modelled Estimates
[XA_1944] ILO - Modelled Estimates
[XA_1946] ILO - Modelled Estimates
[XA_1947] ILO - Modelled Estimates
[XA_1949] ILO - Modelled Estimates
[XA_1950] ILO - Modelled Estimates
[XA_1956] ILO - Modelled Estimates
[XA_1957] ILO - Modelled Estimates
[XA_1960] ILO - Modelled Estimates
[XA_1964] ILO - Modelled Estimates
[XA_1972] ILO - Modelled Estimates
[XA_1976] ILO - Modelled Estimates
[XA_1978] ILO - Modelled Estimates
[XA_1980] ILO - Modelled Estimates
[XA_1982] ILO - Modelled Estimates
[XA_1984] ILO - Modelled Estimates
[XA_1987] ILO - Modelled Estimates
[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
[XA_2081] ILO - Modelled Estimates
[XA_2082] ILO - Modelled Estimates
[XA_2083] ILO - Modelled Estimates
[XA_2084] ILO - Modelled Estimates
[XA_2085] ILO - Modelled Estimates
[XA_2086] ILO - Modelled Estimates
[XA_2088] ILO - Modelled Estimates
[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
[XA_2101] ILO - Modelled Estimates
[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_2120] 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_8414] ILO - Modelled Estimates
[XA_8415] ILO - Modelled Estimates
[XA_8416] ILO - Modelled Estimates
[XA_8417] ILO - Modelled Estimates
[XA_8418] 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
[classif1] Classification 1
[GEO_COV_NAT] Area type: National
[GEO_COV_RUR] Area type: Rural
[GEO_COV_URB] Area type: Urban
[classif2] Classification 2
[OCU_DETAILS_1] Occupation (Detailed): 1. Managers
[OCU_DETAILS_2] Occupation (Detailed): 2. Professionals
[OCU_DETAILS_3] Occupation (Detailed): 3. Technicians and associate professionals
[OCU_DETAILS_4] Occupation (Detailed): 4. Clerical support workers
[OCU_DETAILS_5] Occupation (Detailed): 5. Service and sales workers
[OCU_DETAILS_7] Occupation (Detailed): 7. Craft and related trades workers
[OCU_DETAILS_8] Occupation (Detailed): 8. Plant and machine operators, and assemblers
[OCU_DETAILS_96] Occupation (Detailed): 96. Elementary occupations and skilled agricultural, forestry and fishery workers
[OCU_DETAILS_TOTAL] Occupation (Detailed): Total
[sex] Sex
[SEX_F] Sex: Female
[SEX_M] Sex: Male
[SEX_T] Sex: Total
[frequency] Frequency
[A] Annual
Search filters
Reference area [ref_area] (283)
Source [source] (283)
Classification 1 [classif1] (3)
Classification 2 [classif2] (9)
Sex [sex] (3)
Frequency [frequency] (1)
This dataset has 22,923 series:
[AFG.XA_2198.GEO_COV_NAT.OCU_DETAILS_1.SEX_F.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Area type: National – Occupation (Detailed): 1. Managers – Sex: Female – Annual
- from
- 2010=1.476
- to
- 2019=2.616
- min:
- 1.476
- max:
- 2.616
- avg:
- 2.162
- σ:
- 0.374
[AFG.XA_2198.GEO_COV_NAT.OCU_DETAILS_1.SEX_M.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Area type: National – Occupation (Detailed): 1. Managers – Sex: Male – Annual
- from
- 2010=42
- to
- 2019=67.903
- min:
- 42
- max:
- 67.903
- avg:
- 55.141
- σ:
- 8.559
[AFG.XA_2198.GEO_COV_NAT.OCU_DETAILS_1.SEX_T.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Area type: National – Occupation (Detailed): 1. Managers – Sex: Total – Annual
- from
- 2010=43.475
- to
- 2019=70.519
- min:
- 43.475
- max:
- 70.519
- avg:
- 57.303
- σ:
- 8.899
[AFG.XA_2198.GEO_COV_NAT.OCU_DETAILS_2.SEX_F.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Area type: National – Occupation (Detailed): 2. Professionals – Sex: Female – Annual
- from
- 2010=31.654
- to
- 2019=92.767
- min:
- 31.654
- max:
- 92.767
- avg:
- 60.292
- σ:
- 22.006
[AFG.XA_2198.GEO_COV_NAT.OCU_DETAILS_2.SEX_M.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Area type: National – Occupation (Detailed): 2. Professionals – Sex: Male – Annual
- from
- 2010=230.098
- to
- 2019=313.673
- min:
- 230.098
- max:
- 313.673
- avg:
- 282.777
- σ:
- 27.355
[AFG.XA_2198.GEO_COV_NAT.OCU_DETAILS_2.SEX_T.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Area type: National – Occupation (Detailed): 2. Professionals – Sex: Total – Annual
- from
- 2010=261.752
- to
- 2019=406.44
- min:
- 261.752
- max:
- 406.44
- avg:
- 343.069
- σ:
- 47.725
[AFG.XA_2198.GEO_COV_NAT.OCU_DETAILS_3.SEX_F.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Area type: National – Occupation (Detailed): 3. Technicians and associate professionals – Sex: Female – Annual
- from
- 2010=6.242
- to
- 2019=2.909
- min:
- 2.46
- max:
- 9.533
- avg:
- 5.604
- σ:
- 2.35
[AFG.XA_2198.GEO_COV_NAT.OCU_DETAILS_3.SEX_M.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Area type: National – Occupation (Detailed): 3. Technicians and associate professionals – Sex: Male – Annual
- from
- 2010=76.102
- to
- 2019=134.075
- min:
- 75.928
- max:
- 134.075
- avg:
- 101.093
- σ:
- 20.801
[AFG.XA_2198.GEO_COV_NAT.OCU_DETAILS_3.SEX_T.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Area type: National – Occupation (Detailed): 3. Technicians and associate professionals – Sex: Total – Annual
- from
- 2010=82.344
- to
- 2019=136.984
- min:
- 82.344
- max:
- 136.984
- avg:
- 106.697
- σ:
- 18.936
[AFG.XA_2198.GEO_COV_NAT.OCU_DETAILS_4.SEX_F.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Area type: National – Occupation (Detailed): 4. Clerical support workers – Sex: Female – Annual
- from
- 2010=6.568
- to
- 2019=14.376
- min:
- 6.568
- max:
- 14.376
- avg:
- 10.641
- σ:
- 2.624
Series code | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 |
---|---|---|---|---|---|---|---|---|---|---|
[AFG.XA_2198.GEO_COV_NAT.OCU_DETAILS_1.SEX_F.A] | 1.476 | 1.595 | 1.836 | 2.136 | 2.429 | 2.437 | 2.343 | 2.266 | 2.485 | 2.616 |
[AFG.XA_2198.GEO_COV_NAT.OCU_DETAILS_1.SEX_M.A] | 42 | 44.085 | 47.586 | 50.715 | 53.532 | 57.465 | 59.854 | 62.375 | 65.894 | 67.903 |
[AFG.XA_2198.GEO_COV_NAT.OCU_DETAILS_1.SEX_T.A] | 43.475 | 45.68 | 49.422 | 52.851 | 55.96 | 59.903 | 62.197 | 64.641 | 68.379 | 70.519 |
[AFG.XA_2198.GEO_COV_NAT.OCU_DETAILS_2.SEX_F.A] | 31.654 | 34.316 | 39.351 | 45.85 | 51.273 | 61.492 | 72.645 | 84.937 | 88.632 | 92.767 |
[AFG.XA_2198.GEO_COV_NAT.OCU_DETAILS_2.SEX_M.A] | 230.098 | 238.822 | 263.948 | 283.495 | 294.016 | 298.01 | 300.91 | 300.297 | 304.499 | 313.673 |
[AFG.XA_2198.GEO_COV_NAT.OCU_DETAILS_2.SEX_T.A] | 261.752 | 273.138 | 303.299 | 329.346 | 345.289 | 359.502 | 373.555 | 385.233 | 393.131 | 406.44 |
[AFG.XA_2198.GEO_COV_NAT.OCU_DETAILS_3.SEX_F.A] | 6.242 | 6.519 | 7.254 | 8.268 | 9.533 | 6.223 | 3.917 | 2.46 | 2.717 | 2.909 |
[AFG.XA_2198.GEO_COV_NAT.OCU_DETAILS_3.SEX_M.A] | 76.102 | 75.928 | 82.129 | 86.281 | 91.463 | 102.62 | 111.916 | 121.539 | 128.878 | 134.075 |
[AFG.XA_2198.GEO_COV_NAT.OCU_DETAILS_3.SEX_T.A] | 82.344 | 82.447 | 89.383 | 94.549 | 100.996 | 108.844 | 115.833 | 123.999 | 131.595 | 136.984 |
[AFG.XA_2198.GEO_COV_NAT.OCU_DETAILS_4.SEX_F.A] | 6.568 | 7.493 | 7.876 | 9.131 | 10.451 | 11.791 | 12.21 | 12.568 | 13.947 | 14.376 |
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Reference area [ref_area] (283)
Source [source] (283)
Classification 1 [classif1] (3)
Classification 2 [classif2] (9)
Sex [sex] (3)
Frequency [frequency] (1)
This dataset has 22,923 series:
[AFG.XA_2198.GEO_COV_NAT.OCU_DETAILS_1.SEX_F.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Area type: National – Occupation (Detailed): 1. Managers – Sex: Female – Annual
- from
- 2010=1.476
- to
- 2019=2.616
- min:
- 1.476
- max:
- 2.616
- avg:
- 2.162
- σ:
- 0.374
[AFG.XA_2198.GEO_COV_NAT.OCU_DETAILS_1.SEX_M.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Area type: National – Occupation (Detailed): 1. Managers – Sex: Male – Annual
- from
- 2010=42
- to
- 2019=67.903
- min:
- 42
- max:
- 67.903
- avg:
- 55.141
- σ:
- 8.559
[AFG.XA_2198.GEO_COV_NAT.OCU_DETAILS_1.SEX_T.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Area type: National – Occupation (Detailed): 1. Managers – Sex: Total – Annual
- from
- 2010=43.475
- to
- 2019=70.519
- min:
- 43.475
- max:
- 70.519
- avg:
- 57.303
- σ:
- 8.899
[AFG.XA_2198.GEO_COV_NAT.OCU_DETAILS_2.SEX_F.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Area type: National – Occupation (Detailed): 2. Professionals – Sex: Female – Annual
- from
- 2010=31.654
- to
- 2019=92.767
- min:
- 31.654
- max:
- 92.767
- avg:
- 60.292
- σ:
- 22.006
[AFG.XA_2198.GEO_COV_NAT.OCU_DETAILS_2.SEX_M.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Area type: National – Occupation (Detailed): 2. Professionals – Sex: Male – Annual
- from
- 2010=230.098
- to
- 2019=313.673
- min:
- 230.098
- max:
- 313.673
- avg:
- 282.777
- σ:
- 27.355
[AFG.XA_2198.GEO_COV_NAT.OCU_DETAILS_2.SEX_T.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Area type: National – Occupation (Detailed): 2. Professionals – Sex: Total – Annual
- from
- 2010=261.752
- to
- 2019=406.44
- min:
- 261.752
- max:
- 406.44
- avg:
- 343.069
- σ:
- 47.725
[AFG.XA_2198.GEO_COV_NAT.OCU_DETAILS_3.SEX_F.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Area type: National – Occupation (Detailed): 3. Technicians and associate professionals – Sex: Female – Annual
- from
- 2010=6.242
- to
- 2019=2.909
- min:
- 2.46
- max:
- 9.533
- avg:
- 5.604
- σ:
- 2.35
[AFG.XA_2198.GEO_COV_NAT.OCU_DETAILS_3.SEX_M.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Area type: National – Occupation (Detailed): 3. Technicians and associate professionals – Sex: Male – Annual
- from
- 2010=76.102
- to
- 2019=134.075
- min:
- 75.928
- max:
- 134.075
- avg:
- 101.093
- σ:
- 20.801
[AFG.XA_2198.GEO_COV_NAT.OCU_DETAILS_3.SEX_T.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Area type: National – Occupation (Detailed): 3. Technicians and associate professionals – Sex: Total – Annual
- from
- 2010=82.344
- to
- 2019=136.984
- min:
- 82.344
- max:
- 136.984
- avg:
- 106.697
- σ:
- 18.936
[AFG.XA_2198.GEO_COV_NAT.OCU_DETAILS_4.SEX_F.A] Afghanistan – ILO - Modelled Estimates (XA_2198) – Area type: National – Occupation (Detailed): 4. Clerical support workers – Sex: Female – Annual
- from
- 2010=6.568
- to
- 2019=14.376
- min:
- 6.568
- max:
- 14.376
- avg:
- 10.641
- σ:
- 2.624
Series code | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 |
---|---|---|---|---|---|---|---|---|---|---|
[AFG.XA_2198.GEO_COV_NAT.OCU_DETAILS_1.SEX_F.A] | 1.476 | 1.595 | 1.836 | 2.136 | 2.429 | 2.437 | 2.343 | 2.266 | 2.485 | 2.616 |
[AFG.XA_2198.GEO_COV_NAT.OCU_DETAILS_1.SEX_M.A] | 42 | 44.085 | 47.586 | 50.715 | 53.532 | 57.465 | 59.854 | 62.375 | 65.894 | 67.903 |
[AFG.XA_2198.GEO_COV_NAT.OCU_DETAILS_1.SEX_T.A] | 43.475 | 45.68 | 49.422 | 52.851 | 55.96 | 59.903 | 62.197 | 64.641 | 68.379 | 70.519 |
[AFG.XA_2198.GEO_COV_NAT.OCU_DETAILS_2.SEX_F.A] | 31.654 | 34.316 | 39.351 | 45.85 | 51.273 | 61.492 | 72.645 | 84.937 | 88.632 | 92.767 |
[AFG.XA_2198.GEO_COV_NAT.OCU_DETAILS_2.SEX_M.A] | 230.098 | 238.822 | 263.948 | 283.495 | 294.016 | 298.01 | 300.91 | 300.297 | 304.499 | 313.673 |
[AFG.XA_2198.GEO_COV_NAT.OCU_DETAILS_2.SEX_T.A] | 261.752 | 273.138 | 303.299 | 329.346 | 345.289 | 359.502 | 373.555 | 385.233 | 393.131 | 406.44 |
[AFG.XA_2198.GEO_COV_NAT.OCU_DETAILS_3.SEX_F.A] | 6.242 | 6.519 | 7.254 | 8.268 | 9.533 | 6.223 | 3.917 | 2.46 | 2.717 | 2.909 |
[AFG.XA_2198.GEO_COV_NAT.OCU_DETAILS_3.SEX_M.A] | 76.102 | 75.928 | 82.129 | 86.281 | 91.463 | 102.62 | 111.916 | 121.539 | 128.878 | 134.075 |
[AFG.XA_2198.GEO_COV_NAT.OCU_DETAILS_3.SEX_T.A] | 82.344 | 82.447 | 89.383 | 94.549 | 100.996 | 108.844 | 115.833 | 123.999 | 131.595 | 136.984 |
[AFG.XA_2198.GEO_COV_NAT.OCU_DETAILS_4.SEX_F.A] | 6.568 | 7.493 | 7.876 | 9.131 | 10.451 | 11.791 | 12.21 | 12.568 | 13.947 | 14.376 |
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