[24_446_DF_DCIS_MATRIMONICIT_2] Marriages by type of couple

Name: Marriages by type of couple
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
[3] both foreign spouses
[4] both Italian spouses
[8] at least a foreign spouse
[9] total

[CITIZENSHIP] Citizenship

[WORLD] All countries of the world

[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] (6)

Citizenship [CITIZENSHIP] (1)

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 1,704 series:

Trim NA Values

Series code	1996	1997	1998	1999	2000	2001	2002	2003	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.8.WORLD.WORLD.99.WORLD.99.9]	11993	13490	14236	16548	20001	21513	25590	27730	30662	33017	34396	34559	36918	32059	25082	26617	30724	28173	28278	29425	31116	32323	33933	34185	18832	24380	29574
[A.IT.MARRG_FROM2017.ALL.TOT.9.WORLD.WORLD.99.WORLD.99.9]	278611	277738	280034	280330	284410	264026	270013	264097	248969	247740	245992	250360	246613	230613	217700	204830	207138	194057	189765	194377	203258	191287	195778	184088	96841	180416	189140
[A.IT108.MARRGPOP_FROM2017.ALL.TOT.1.WORLD.WORLD.99.WORLD.99.9]	NA	NA	NA	NA	NA	NA	NA	NA	7.7	8.3	9.4	8.4	9	7.9	7	9.1	9.9	10.1	10.1	11	10.1	12.6	12.6	13.5	14.7	10	10.4
[A.IT108.MARRGPOP_FROM2017.ALL.TOT.2.WORLD.WORLD.99.WORLD.99.9]	NA	NA	NA	NA	NA	NA	NA	NA	2.4	2.6	2.6	2.9	3.3	2.2	1.1	2	2.5	2.4	3.1	3.1	3.7	3	4.6	4.8	4.7	3	4.3
[A.IT108.MARRGPOP_FROM2017.ALL.TOT.3.WORLD.WORLD.99.WORLD.99.9]	NA	NA	NA	NA	NA	NA	NA	NA	2.5	2.8	2.9	3.8	4.4	3.6	2.1	2.6	3.8	4.5	3.2	4.8	3.8	4.1	4.6	5.2	5.8	4.6	4.4
[A.IT108.MARRGPOP_FROM2017.ALL.TOT.4.WORLD.WORLD.99.WORLD.99.9]	NA	NA	NA	NA	NA	NA	NA	NA	87.3	86.3	85.1	85	83.3	86.3	89.8	86.3	83.8	83	83.5	81.1	82.4	80.2	78.1	76.5	74.8	82.4	80.8
[A.IT108.MARRGPOP_FROM2017.ALL.TOT.8.WORLD.WORLD.99.WORLD.99.9]	NA	NA	NA	NA	NA	NA	NA	NA	12.7	13.7	14.9	15	16.7	13.7	10.2	13.7	16.2	17	16.5	18.9	17.6	19.8	21.9	23.5	25.2	17.6	19.2
[A.IT108.MARRGPOP_FROM2017.ALL.TOT.9.WORLD.WORLD.99.WORLD.99.9]	NA	NA	NA	NA	NA	NA	NA	NA	100	100	100	100	100	100	100	100	100	100	100	100	100	100	100	100	100	100	100
[A.IT108.MARRG_FROM2017.ALL.TOT.1.WORLD.WORLD.99.WORLD.99.9]	NA	NA	NA	NA	NA	NA	NA	NA	237	255	289	252	267	231	174	232	252	223	225	251	234	259	278	284	186	215	241
[A.IT108.MARRG_FROM2017.ALL.TOT.2.WORLD.WORLD.99.WORLD.99.9]	NA	NA	NA	NA	NA	NA	NA	NA	75	81	81	86	99	64	27	51	63	52	69	70	86	62	101	100	60	65	100

Showing results 11 - 20 / 1,704