[24_446_DF_DCIS_MATRIMONICIT_3] Type of couple and area of citizenship

Name: Type of couple and area of citizenship
Creator: DBnomics

Updated on DBnomics on January 24, 2024 (10:56 AM).

[FREQ] Frequency

[A] annual

[REF_AREA] Territory

[IT] Italy
[IT108] Monza e della Brianza
[IT109] Fermo
[IT110] Barletta-Andria-Trani
[IT111] Sud Sardegna
[ITC] Nord-ovest
[ITC1] Piemonte
[ITC11] Torino
[ITC12] Vercelli
[ITC13] Biella
[ITC14] Verbano-Cusio-Ossola
[ITC15] Novara
[ITC16] Cuneo
[ITC17] Asti
[ITC18] Alessandria
[ITC2] Valle d'Aosta / Vallée d'Aoste
[ITC20] Valle d'Aosta / Vallée d'Aoste
[ITC3] Liguria
[ITC31] Imperia
[ITC32] Savona
[ITC33] Genova
[ITC34] La Spezia
[ITC4] Lombardia
[ITC41] Varese
[ITC42] Como
[ITC43] Lecco
[ITC44] Sondrio
[ITC45] Milano
[ITC46] Bergamo
[ITC47] Brescia
[ITC48] Pavia
[ITC49] Lodi
[ITC4A] Cremona
[ITC4B] Mantova
[ITCD] Nord
[ITCDE] Centro-nord
[ITD] Nord-est
[ITD1] Provincia Autonoma Bolzano / Bozen
[ITD10] Bolzano / Bozen
[ITD2] Provincia Autonoma Trento
[ITD20] Trento
[ITD3] Veneto
[ITD31] Verona
[ITD32] Vicenza
[ITD33] Belluno
[ITD34] Treviso
[ITD35] Venezia
[ITD36] Padova
[ITD37] Rovigo
[ITD4] Friuli-Venezia Giulia
[ITD41] Pordenone
[ITD42] Udine
[ITD43] Gorizia
[ITD44] Trieste
[ITD5] Emilia-Romagna
[ITD51] Piacenza
[ITD52] Parma
[ITD53] Reggio nell'Emilia
[ITD54] Modena
[ITD55] Bologna
[ITD56] Ferrara
[ITD57] Ravenna
[ITD58] Forlì-Cesena
[ITD59] Rimini
[ITDA] Trentino Alto Adige / Südtirol
[ITE] Centro (I)
[ITE1] Toscana
[ITE11] Massa-Carrara
[ITE12] Lucca
[ITE13] Pistoia
[ITE14] Firenze
[ITE15] Prato
[ITE16] Livorno
[ITE17] Pisa
[ITE18] Arezzo
[ITE19] Siena
[ITE1A] Grosseto
[ITE2] Umbria
[ITE21] Perugia
[ITE22] Terni
[ITE3] Marche
[ITE31] Pesaro e Urbino
[ITE32] Ancona
[ITE33] Macerata
[ITE34] Ascoli Piceno
[ITE4] Lazio
[ITE41] Viterbo
[ITE42] Rieti
[ITE43] Roma
[ITE44] Latina
[ITE45] Frosinone
[ITF] Sud
[ITF1] Abruzzo
[ITF11] L'Aquila
[ITF12] Teramo
[ITF13] Pescara
[ITF14] Chieti
[ITF2] Molise
[ITF21] Isernia
[ITF22] Campobasso
[ITF3] Campania
[ITF31] Caserta
[ITF32] Benevento
[ITF33] Napoli
[ITF34] Avellino
[ITF35] Salerno
[ITF4] Puglia
[ITF41] Foggia
[ITF42] Bari
[ITF43] Taranto
[ITF44] Brindisi
[ITF45] Lecce
[ITF5] Basilicata
[ITF51] Potenza
[ITF52] Matera
[ITF6] Calabria
[ITF61] Cosenza
[ITF62] Crotone
[ITF63] Catanzaro
[ITF64] Vibo Valentia
[ITF65] Reggio di Calabria
[ITFG] Mezzogiorno
[ITG] Isole
[ITG1] Sicilia
[ITG11] Trapani
[ITG12] Palermo
[ITG13] Messina
[ITG14] Agrigento
[ITG15] Caltanissetta
[ITG16] Enna
[ITG17] Catania
[ITG18] Ragusa
[ITG19] Siracusa
[ITG2] Sardegna
[ITG25] Sassari
[ITG26] Nuoro
[ITG27] Cagliari
[ITG28] Oristano
[ITG29] Olbia-Tempio
[ITG2A] Ogliastra
[ITG2B] Medio Campidano
[ITG2C] Carbonia-Iglesias

[DATA_TYPE] Indicator

[MARRGPOP_FROM2017] marriages (% in respect of total marriages)
[MARRG_FROM2017] marriages

[MARRIAGE_RITE] Rite of marriage celebration

[ALL] all items

[ORDER_MARRIAGE] Order of marriage

[TOT] total

[TYPE_OF_COUPLE] Type of couple

[1] Italian groom and foreign bride
[2] foreign groom and Italian bride
[5] both foreign spouses (at least one of the spouses who resides in Italy)

[CITIZENSHIP] Citizenship

[999] Stateless
[AFR_C_S] Central and South Africa
[AFR_E] Eastern Africa
[AFR_N] Northern Africa
[AFR_W] Western Africa
[AME_C_S] Central and South America
[AME_N] Northern America
[ASI_E] Eastern Asia
[ASI_W] Western Asia
[EU] European Union
[EUR_C_E] Central and Eastern Europe
[EUR_OTH] Other european countries
[OCE] Oceania
[WORLD] All countries of the world
[XASI_C_S] Central and South Asia

[CITIZENSHIP_BRIDEGROOM] Citizenship bridegroom

[WORLD] All countries of the world

[EDU_LEV_BRIDEGROOM] Education level bridegroom

[99] total

[CITIZENSHIP_BRIDE] Citizenship bride

[WORLD] All countries of the world

[EDU_LEV_BRIDE] Education level bride

[99] total

[Y_SAME_CITIZENSHIP] Same citizenship

[9] total

Search filters

Frequency [FREQ] (1)

Territory [REF_AREA] (142)

Indicator [DATA_TYPE] (2)

Rite of marriage celebration [MARRIAGE_RITE] (1)

Order of marriage [ORDER_MARRIAGE] (1)

Type of couple [TYPE_OF_COUPLE] (3)

Citizenship [CITIZENSHIP] (15)

Citizenship bridegroom [CITIZENSHIP_BRIDEGROOM] (1)

Education level bridegroom [EDU_LEV_BRIDEGROOM] (1)

Citizenship bride [CITIZENSHIP_BRIDE] (1)

Education level bride [EDU_LEV_BRIDE] (1)

Same citizenship [Y_SAME_CITIZENSHIP] (1)

This dataset has 6,674 series:

Trim NA Values

Series code	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021	2022
[A.IT.MARRG_FROM2017.ALL.TOT.2.AFR_N.WORLD.99.WORLD.99.9]	1039	1194	1272	2010	2352	1491	403	579	1262	1057	1219	1227	1417	1389	1489	1488	846	977	1186
[A.IT.MARRG_FROM2017.ALL.TOT.2.AFR_W.WORLD.99.WORLD.99.9]	242	314	279	318	453	318	122	179	337	313	343	407	429	408	466	518	326	361	345
[A.IT.MARRG_FROM2017.ALL.TOT.2.AME_C_S.WORLD.99.WORLD.99.9]	574	621	694	805	833	589	420	422	524	508	546	644	704	778	866	917	489	614	682
[A.IT.MARRG_FROM2017.ALL.TOT.2.AME_N.WORLD.99.WORLD.99.9]	252	265	232	223	208	174	158	181	156	172	157	169	175	165	213	195	150	189	200
[A.IT.MARRG_FROM2017.ALL.TOT.2.ASI_E.WORLD.99.WORLD.99.9]	33	27	23	40	48	40	40	50	48	69	79	95	86	84	96	93	53	94	94
[A.IT.MARRG_FROM2017.ALL.TOT.2.ASI_W.WORLD.99.WORLD.99.9]	74	91	77	96	94	81	57	66	78	79	93	109	101	89	109	103	62	83	103
[A.IT.MARRG_FROM2017.ALL.TOT.2.EU.WORLD.99.WORLD.99.9]	913	1075	1017	1195	1159	1193	1170	1102	1178	1138	1143	1221	1299	1227	1466	1507	566	1028	1400
[A.IT.MARRG_FROM2017.ALL.TOT.2.EUR_C_E.WORLD.99.WORLD.99.9]	1061	944	1070	839	807	551	336	394	518	581	621	869	974	905	971	996	611	737	818
[A.IT.MARRG_FROM2017.ALL.TOT.2.EUR_OTH.WORLD.99.WORLD.99.9]	82	91	84	99	77	96	81	68	92	102	105	97	51	55	68	68	131	269	437
[A.IT.MARRG_FROM2017.ALL.TOT.2.OCE.WORLD.99.WORLD.99.9]	48	35	31	53	43	35	47	33	35	40	29	35	29	35	58	50	16	22	26

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