Number of marriages that took place in England and Wales by age, sex, previous partnership status and civil or religious ceremony.

Yearly registered marriages – breakdown by Month

The dataset contains the number of marriages categorized by the age groups of both the bride and the groom. Each record represents a combination of age groups for the bride and groom and the corresponding number of marriages for that combination. A marriage is the act, ceremony or process by which the legal relationship between two persons is formed. The legality of the union may be established by civil, religious or other means as recognised by the laws of the country.

Statistics on marriages which took place in England and Wales which include figures on cohabitation before marriage. The cohort analyses provide statistics on the proportion of men and women who have ever married or remarried by certain ages by year of birth.

Dataset from Singapore Department of Statistics. For more information, visit https://data.gov.sg/datasets/d_a9345e1249b5ac6d5e998217da4ac3d4/view

Number and percentage of marriages, by type of marriage (opposite-sex, same-sex), month of marriage, and place of occurrence, 2000 to 2004.

Sri Lanka Vital Statistics: Number of Marriages: Colombo data was reported at 18,050.000 Person in 2017. This records a decrease from the previous number of 18,163.000 Person for 2016. Sri Lanka Vital Statistics: Number of Marriages: Colombo data is updated yearly, averaging 21,777.500 Person from Dec 1996 (Median) to 2017, with 22 observations. The data reached an all-time high of 24,612.000 Person in 1998 and a record low of 18,050.000 Person in 2017. Sri Lanka Vital Statistics: Number of Marriages: Colombo data remains active status in CEIC and is reported by Department of Census and Statistics. The data is categorized under Global Database’s Sri Lanka – Table LK.G007: Vital Statistics: Number of Marriages.

This dataset is about books. It has 1 row and is filtered where the book is A May bride : a Year of weddings novella. It features 7 columns including author, publication date, language, and book publisher.

Number of marriages by County with rates (per 1000).

Number of divorces and divorce rate per 1,000 marriages, by duration of marriage and place of occurrence, 1970 to most recent year.

In 2023, the average cost of a wedding reception venue in the United States amounted to an estimated 12,800 U.S. dollars. Couples in the U.S. have several costs to keep in mind when planning their special day. Besides the wedding ring, other expensive considerations typically include booking a live reception band and a wedding photographer, which cost an average of 4,300 and 2,900 U.S. dollars respectively in 2023.

This dataset compares birth, death and marriage registrations completed by the Office of the Registrar General, beginning in 1925, to the most current published annual report (2022). Data released for 2024 is preliminary and may not match counts from other sources. The data represents counts in the reference calendar quarters, which are collated approximately 90 days after the end of the quarter. Previously released counts for 2024 are updated to reflect vital event registrations completed after the release of the initial report. Each subsequent quarterly report is the cumulative total of the preceding quarterly reports. ServiceOntario’s ability to provide timely information depends on receiving vital event registration information from a variety of sources. The preliminary data presented may not represent all the events that occurred in the reporting period. This is particularly true for events that occurred near the end of the reporting period as they may not have been received by ServiceOntario by the time the data is collated. Final counts for the reporting year will be released with the publication of the Office of the Registrar General Annual Report. The Vital Statistics Act requires that after the end of each calendar year, the Registrar General publish a report that includes the number of births, marriages, deaths, still-births, adoptions and changes of name registered during the calendar year preceding the one that has ended.

Yearly registered marriages categorised by suburb. Data is limited to cell counts >5.

Number of divorces and various divorce indicators (crude divorce rate, divorce rate for married persons, age-standardized divorce rate, total divorce rate, mean and median duration of marriage, median duration of divorce proceedings, percentage of joint divorce applications), by place of occurrence, 1970 to most recent year.

Abstract

The do-file marital_spouselinks.do combines all data on people's marital statuses and reported spouses to create the following datasets: 1. all_marital_reports - a listing of all the times an individual has reported their current marital status with the id numbers of the reported spouse(s); this listing is as reported so may include discrepancies (i.e. a 'Never married' status following a 'Married' one) 2. all_spouse_pairs_full - a listing of each time each spouse pair has been reported plus summary information on co-residency for each pair 3. all_spouse_pairs_clean_summarised - this summarises the data from all_spouse_pairs_full to give start and end dates of unions 4. marital_status_episodes - this combines data from all the sources to create episodes of marital status, each has a start and end date and a marital status, and if currently married, the spouse ids of the current spouse(s) if reported. There are several variables to indicate where each piece of information is coming from.

The first 2 datasets are made available in case people need the 'raw' data for any reason (i.e. if they only want data from one study) or if they wish to summarise the data in a different way to what is done for the last 2 datasets.

The do-file is quite complicated with many sources of data going through multiple processes to create variables in the datasets so it is not always straightforward to explain where each variable come from on the documentation. The 4 datasets build on each other and the do-file is documented throughout so anyone wanting to understand in great detail may be better off examining that. However, below is a brief description of how the datasets are created:

Marital status data are stored in the tables of the study they were collected in: AHS Adult Health Study [ahs_ahs1] CEN Census (initial CRS census) [cen_individ] CENM In-migration (CRS migration form) [crs_cenm] GP General form (filled for various reasons) [gp_gpform] SEI Socio-economic individual (annual survey from 2007 onwards) [css_sei] TBH TB household (study of household contacts of TB patients) [tb_tbh] TBO TB controls (matched controls for TB patients) [tb_tbo & tb_tboto2007] TBX TB cases (TB patients) [tb_tbx & tb_tbxto2007] In many of the above surveys as well as their current marital status, people were asked to report their current and past spouses along with (sometimes) some information about the marriage (start/end year etc.). These data are stored all together on the table gen_spouse, with variables indicating which study the data came from. Further evidence of spousal relationships is taken from gen_identity (if a couple appear as co-parents to a CRS member) and from crs_residency_episodes_clean_poly, a combined dataset (if they are living in the same household at the same time). Note that co-parent couples who are not reported in gen_spouse are only retained in the datasets if they have co-resident episodes.

The marital status data are appended together and the spouse id data merged in. Minimal data editing/cleaning is carried out. As the spouse data are in long format, this dataset is reshaped wide to have one line per marital status report (polygamy in the area allows for men to have multiple spouses at one time): this dataset is saved as all_marital_reports.

The list of reported spouses on gen_spouse is appended to a list of co-parents (from gen_identity) and this list is cleaned to try to identify and remove obvious id errors (incestuous links, same sex [these are not reported in this culture] and large age difference). Data reported by men and women are compared and variables created to show whether one or both of the couple report the union. Many records have information on start and end year of marriage, and all have the date the union was reported. This listing is compared to data from residency episodes to add dates that couples were living together (not all have start/end dates so this is to try to supplement this), in addition the dates that each member of the couple was last known to be alive or first known to be dead are added (from the residency data as well). This dataset with all the records available for each spouse pair is saved as all_spouse_pairs_full.

The date data from all_spouse_pairs_full are then summarised to get one line per couple with earliest and latest known married date for all, and, if available, marriage and separation date. For each date there are also variables created to indicate the source of the data.
As culture only allows for women having one spouse at a time, records for women with 'overlapping' husbands are cleaned. This dataset is then saved as all_spouse_pairs_clean_summarised.

Both the cleaned spouse pairs and the cleaned marital status datasets are converted into episodes: the spouse listing using the marriage or first known married date as the beginning and the last known married plus a year or separation date as the end, the marital status data records collapsed into periods of the same status being reported (following some cleaning to remove impossible reports) and the start date being the first of these reports, the end date being the last of the reports plus a year. These episodes are appended together and a series of processes run several times to remove overalapping episodes. To be able to assign specific spouse ids to each married episode, some episodes need to be 'split' into more than one (i.e. if a man is married to one woman from 2005 to 2017 and then marries another woman in 2008 and remains married to her till 2017 his intial married episode would be from 2005 to 2017, but this would need to be split into one from 2005 to 2008 which would just have 1 idspouse attached and another from 2008 to 2017, which would have 2 idspouse attached). After this splitting process the spouse ids are merged in.
The final episode dataset is saved as marital_status_episodes.

Analysis unit

Individual

Mode of data collection

Face-to-face [f2f]

Number of marriages and various nuptiality indicators (crude marriage rate, number of marriages of different-gender or same-gender couples [when available], total first-marriage rate and probability of ever marrying according to the first-marriage table), by place of occurrence, 1991 to most recent year.

Total first marriage rates and age-specific first marriage rates per 1,000 males, all marriages, by place of occurrence, 2000 to 2004.

Registered marriage officiants in Ontario.

The dataset includes:

• first name, last name and location of the marriage officiant
• affiliation
• a date stamp at the end indicating the date when the changes were made by the operations team

To search: Use the Control+F buttons to find a specific city or person.

Note: Registrations and cancellations of marriage officiants are generally updated within 4 weeks of notification.

This data is related to:

• Getting married: How to get the government documents you need if you plan to marry in Ontario.
• How to get a copy of an Ontario marriage certificate online
• Law: Marriage Act

This dataset shows all marriages in Basel-Stadt by date of marriage. All marriages in which the husband was resident in Basel-Stadt at the time of the wedding shall be taken into account. For methodological reasons, the values published here may differ from those in public statistics: In the latter, subsequently reported marriages are counted in the last year not yet concluded. In this record, they are subsequently counted in the year of the wedding date.

Mean age and median age at divorce and at marriage, for persons who divorced in a given year, by sex or gender and place of occurrence, 1970 to most recent year.