Rank and count of the top names for baby girls, changes in rank since the previous year and breakdown by country, region, mother's age and month of birth.

Rank and count of the top names for baby boys, changes in rank since the previous year and breakdown by country, region, mother's age and month of birth.

Historic lists of top 100 names for baby boys and girls for 1904 to 2024 at 10-yearly intervals.

The data (name, year of birth, sex, and number) are from a 100 percent sample of Social Security card applications for 1880 on.

Ranks and counts of baby names for boys and girls in England and Wales, 1996 to 2024.

Context

In order to test how gender is linguistically encoded and represented, I have designed a series of studies that involve gender biased and equibiased names. This dataset is designed to help me calculate which names would be most appropriate for stimuli created to display to both US and UK audiences.

Content

These data contain name frequencies and ranks by year (1996-2013, UK) or decade (2000, US) by binary gender (male or female). I have tried to design these data to provide the most useful metrics for determining the most popular names by gender bias (masculine, feminine) and equibias (unisex).

Acknowledgements

• Office for National Statistics (2016a). Baby Names Statistics Boys. Live births (datasets). Retrieved 19 Feb 2017 from: https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/livebirths/datasets/babynamesenglandandwalesbabynamesstatisticsboys
• Office for National Statistics (2016b). Baby Names Statistics Girls. Live births (datasets). Retrieved 19 Feb 2017 from: https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/livebirths/datasets/babynamesenglandandwalesbabynamesstatisticsgirls
• U.S. Census Bureau, Population Division, Population Analysis & Evaluation Staff (2000). via Butler, R. (2016). First name search. Retrieved 13 March 2017 from: http://names.mongabay.com/baby-names/application/

Inspiration

I'm looking to identify popular gender-biased and popular gender neutral (equi-biased) names.

Queensland Top 100 Baby Names

This is a public use data file on Delaware's most popular baby names for 2009 to 2016 obtained from the Delaware certificate of birth. The top 15 names for each gender are represented.

List of male and female baby names in South Australia from 1944 to 2024. The annual data for baby names is published January/February each year.

This file contains the names and codes for Department for Children, Education, Lifelong Learning and Skills as at 31st December 2020 in Wales. (File Size - 16 KB) Field Names - DCELL20CD, DCELL20NM, DCELL20NMW, FIDField Types - Text, Text, TextField Lengths - 9, 20, 28FID = The FID, or Feature ID is created by the publication process when the names and codes / lookup products are published to the Open Geography portal.

Description

INSEE (French national institute of statistics) realeased two datasets reporting the names given to French babies since 1900 : one at the national level and one at the departmental level. This dataset allows to track trends in how French babies are named since 1900, explore the proportion of male/female in population over times, find the more gender neutral names, and more.

What differences between those two datasets and the original ones released by INSEE ?

I've taken the raw files from INSEE and made a little shaping and cleaning work:

• Data are cleaned from missing values in the year column.
• Unusual names (less than 20 babies born in the same year) are dropped.
• Columns names are translated from french to english.
• Department names are added on the department-level dataset (column dpt_name).

Plot example

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The first names from births registered in Ontario from 1917 to 2023. Counts of fewer than 5 names were suppressed for privacy. ## Related Ontario top baby names (female)

The first names file contains data on the first names attributed to children born in France since 1900. These data are available at the level of France and by department. The files available for download list births and not living people in a given year. They are available in two formats (DBASE and CSV). To use these large files, it is recommended to use a database manager or statistical software. The file at the national level can be opened from some spreadsheets. The file at the departmental level is however too large (3.8 million lines) to be consulted with a spreadsheet, so it is proposed in a lighter version with births since 2000 only. The data can be accessed in: - a national data file containing the first names attributed to children born in France between 1900 and 2022 (data before 2012 relate only to France outside Mayotte) and the numbers by sex associated with each first name; - a departmental data file containing the same information at the department of birth level; - a lighter data file that contains information at the department level of birth since the year 2000.

Background:
The Crime Survey for England and Wales (CSEW), previously known as the British Crime Survey (BCS), has been in existence since 1981. The survey traditionally asks a sole randomly selected adult, in a random sample of households, details pertaining to any instances where they, or the household, has been a victim of a crime in the previous 12 months. These are recorded in the victim form data file (VF). A wide range of questions are then asked covering demographics and crime-related subjects such as attitudes to the police and the criminal justice system (CJS). Most of the questionnaire is completed in a face-to-face interview in the respondent's home; these variables are contained within the non-victim form (NVF) data file. Since 2009, the survey has been extended to children aged 10-15 years old; one resident of that age range has also been selected at random from the household and asked about incidents where they have been a victim of crime, and other related topics. The first set of children's data, covering January-December 2009, had experimental status, and is held separately under SN 6601. From 2009-2010, the children's data cover the same period as the adult data and are included with the main dataset. Further information may be found on the ONS Crime Survey for England and Wales web page and for the previous BCS, from the GOV.UK BCS Methodology web page.

Self-completion data:
A series of questions on drinking behaviour, drug use and intimate personal violence (including stalking and sexual victimisation) are administered to adults via a self-completion module which the respondent completes on a laptop computer. Children aged 10-15 years also complete a separate self-completion questionnaire. The questions are contained within the main questionnaire documents, but the data are not available with the main survey; they are available only under Secure Access conditions. Lower-level geographic variables are also available under Secure Access conditions to match to the survey.

History:
Up to 2001, the survey was conducted biennially. From April 2001, interviewing was carried out continually and reported on in financial year cycles and the crime reference period was altered to accommodate this change. The core sample size has increased from around 11,000 in the earlier cycles to over 40,000. Following the National Statistician's Review of Crime Statistics in June 2011 the collation and publication of Crime Statistics moved to the Office for National Statistics (ONS) from 1st April 2012, and the survey changed its name to the Crime Survey for England and Wales (CSEW) accordingly.

Scottish data:
The 1982 and 1988 BCS waves were also conducted in Scotland. The England and Wales data for 1982 and 1988 are held at the UKDA under SNs 1869 and 2706, but the Scottish data for these studies are held separately under SNs 4368 and 4599. Since 1993, separate Scottish Crime and Justice Surveys have been conducted, see the series web page for more details.

New methodology for capping the number of incidents from 2017-18
The CSEW datasets available from 2017-18 onward are based upon a new methodology of capping the number of incidents at the 98th percentile. Incidence variables names have remained consistent with previously supplied data but due to the fact they are based on the new 98th percentile cap, and old data sets are not, comparability has been lost with previous years. More information can be found in the 2017-18 User Guide and the article ‘Improving victimisation estimates derived from the Crime Survey for England and Wales’. ONS intend to publish all micro data back to 1981 with incident data based on the 98th percentile cap later in 2019.

The main CSEW Secure Access dataset (SN 7280) includes:

• the adult and child data also held in the standard End User Licence (EUL) version
• adult self-completion modules on drinking behaviour, drug use, stolen goods, children's self-completion modules and sexual identity and low-level geography variables formerly held under Special Licence access conditions (please note that not all modules occur for each year - see the survey year's documentation for details)
• hate crime variables HATEMT3A-HATEMT3I and HATEPS3A-HATEPS3I from the Victim Form
• the interpersonal violence (IPV) data (comprising the modules on domestic violence, sexual victimisation and stalking)

Users who do not require access to the modules noted above should apply for the EUL version. The Secure Access version has more restrictive access conditions than the standard EUL version - see the 'Access' tab. All studies in the series can be viewed from the Crime Survey for England and Wales series webpage.

This study also includes the following low-level geography variables from 2008 onwards:

• Local Authority District
• Rural and Urban Area Classification
• Police Force Area
• ONS District Level Classification: Supergroup
• ONS District Level Classification: Group
• ONS District Level Classification: Subgroup
• Output Area Classification - Supergroup (7 categories)
• Output Area Classification - Group (21 categories)
• Output Area Classification - Subgroup (52 categories)

A further CSEW low-level geography file including variables down to Super Output Areas (Lower Layer) is available under separate Secure Access study SN 7311.

COVID-19 and the CSEW
The face-to-face CSEW was temporarily suspended on 17 March 2020 as part of the efforts to minimise social contact and stop the spread of COVID-19. A shortened telephone-operated version of the survey (TCSEW) was conducted instead. The TCSEW asked people resident in households in England and Wales about their experiences of a selected range of offences in the 12 months prior to the interview, as well as a short module specific to the pandemic period relating to their perceptions of crime, the police, and anti-social behaviour. Therefore, standard CSEW data are not available for the years 2020/21 and 2021/22; instead, the secure access TCSEW for these years is held under SN 9071.

Latest edition information:
For the 14th edition (November 2025), data and documentation for the 2023/24 CSEW were added to the study.

No data available for 10-15 year-olds for 2022/23

Data for 10-15-year-old respondents is not currently included in the 2022/23 study. The Office for National Statistics is currently assessing these data and deciding whether to include it for this year. The questionnaire for 10-15-year-olds has been included in the documentation and is also available on the ONS Crime and Justice Methodology webpage.

This dataset is imported from the US Department of Commerce, National Telecommunications and Information Administration (NTIA) and its "Data Explorer" site. The underlying data comes from the US Census

1. dataset: Specifies the month and year of the survey as a string, in "Mon YYYY" format. The CPS is a monthly survey, and NTIA periodically sponsors Supplements to that survey.

2. variable: Contains the standardized name of the variable being measured. NTIA identified the availability of similar data across Supplements, and assigned variable names to ease time-series comparisons.

3. description: Provides a concise description of the variable.

4. universe: Specifies the variable representing the universe of persons or households included in the variable's statistics. The specified variable is always included in the file. The only variables lacking universes are isPerson and isHouseholder, as they are themselves the broadest universes measured in the CPS.

5. A large number of *Prop, *PropSE, *Count, and *CountSE columns comprise the remainder of the columns. For each demographic being measured (see below), four statistics are produced, including the estimated proportion of the group for which the variable is true (*Prop), the standard error of that proportion (*PropSE), the estimated number of persons or households in that group for which the variable is true (*Count), and the standard error of that count (*CountSE).

DEMOGRAPHIC CATEGORIES

1. us: The usProp, usPropSE, usCount, and usCountSE columns contain statistics about all persons and households in the universe (which represents the population of the fifty states and the District and Columbia). For example, to see how the prevelance of Internet use by Americans has changed over time, look at the usProp column for each survey's internetUser variable.

2. age: The age category is divided into five ranges: ages 3-14, 15-24, 25-44, 45-64, and 65+. The CPS only includes data on Americans ages 3 and older. Also note that household reference persons must be at least 15 years old, so the age314* columns are blank for household-based variables. Those columns are also blank for person-based variables where the universe is "isAdult" (or a sub-universe of "isAdult"), as the CPS defines adults as persons ages 15 or older. Finally, note that some variables where children are technically in the univese will show zero values for the age314* columns. This occurs in cases where a variable simply cannot be true of a child (e.g. the workInternetUser variable, as the CPS presumes children under 15 are not eligible to work), but the topic of interest is relevant to children (e.g. locations of Internet use).

3. work: Employment status is divided into "Employed," "Unemployed," and "NILF" (Not in the Labor Force). These three categories reflect the official BLS definitions used in official labor force statistics. Note that employment status is only recorded in the CPS for individuals ages 15 and older. As a result, children are excluded from the universe when calculating statistics by work status, even if they are otherwise considered part of the universe for the variable of interest.

4. income: The income category represents annual family income, rather than just an individual person's income. It is divided into five ranges: below $25K, $25K-49,999, $50K-74,999, $75K-99,999, and $100K or more. Statistics by income group are only available in this file for Supplements beginning in 2010; prior to 2010, family income range is available in public use datasets, but is not directly comparable to newer datasets due to the 2010 introduction of the practice of allocating "don't know," "refused," and other responses that result in missing data. Prior to 2010, family income is unkown for approximately 20 percent of persons, while in 2010 the Census Bureau began imputing likely income ranges to replace missing data.

5. education: Educational attainment is divided into "No Diploma," "High School Grad," "Some College," and "College Grad." High school graduates are considered to include GED completers, and those with some college include community college attendees (and graduates) and those who have attended certain postsecondary vocational or technical schools--in other words, it signifies additional education beyond high school, but short of attaining a bachelor's degree or equivilent. Note that educational attainment is only recorded in the CPS for individuals ages 15 and older. As a result, children are excluded from the universe when calculating statistics by education, even if they are otherwise considered part of the universe for the variable of interest.

6. sex: "Male" and "Female" are the two groups in this category. The CPS does not currently provide response options for intersex individuals.

7. race: This category includes "White," "Black," "Hispanic," "Asian," "Am Indian," and "Other" groups. The CPS asks about Hispanic origin separately from racial identification; as a result, all persons identifying as Hispanic are in the Hispanic group, regardless of how else they identify. Furthermore, all non-Hispanic persons identifying with two or more races are tallied in the "Other" group (along with other less-prevelant responses). The Am Indian group includes both American Indians and Alaska Natives.

8. disability: Disability status is divided into "No" and "Yes" groups, indicating whether the person was identified as having a disability. Disabilities screened for in the CPS include hearing impairment, vision impairment (not sufficiently correctable by glasses), cognitive difficulties arising from physical, mental, or emotional conditions, serious difficulty walking or climbing stairs, difficulty dressing or bathing, and difficulties performing errands due to physical, mental, or emotional conditions. The Census Bureau began collecting data on disability status in June 2008; accordingly, this category is unavailable in Supplements prior to that date. Note that disability status is only recorded in the CPS for individuals ages 15 and older. As a result, children are excluded from the universe when calculating statistics by disability status, even if they are otherwise considered part of the universe for the variable of interest.

9. metro: Metropolitan status is divided into "No," "Yes," and "Unkown," reflecting information in the dataset about the household's location. A household located within a metropolitan statistical area is assigned to the Yes group, and those outside such areas are assigned to No. However, due to the risk of de-anonymization, the metropolitan area status of certain households is unidentified in public use datasets. In those cases, the Census Bureau has determined that revealing this geographic information poses a disclosure risk. Such households are tallied in the Unknown group.

10. scChldHome: