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This dataset contains counts of live births for California as a whole based on information entered on birth certificates. Final counts are derived from static data and include out of state births to California residents, whereas provisional counts are derived from incomplete and dynamic data. Provisional counts are based on the records available when the data was retrieved and may not represent all births that occurred during the time period.
The final data tables include both births that occurred in California regardless of the place of residence (by occurrence) and births to California residents (by residence), whereas the provisional data table only includes births that occurred in California regardless of the place of residence (by occurrence). The data are reported as totals, as well as stratified by parent giving birth's age, parent giving birth's race-ethnicity, and birth place type. See temporal coverage for more information on which strata are available for which years.
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TwitterThis dataset contains counts of live births for California counties based on information entered on birth certificates. Final counts are derived from static data and include out of state births to California residents, whereas provisional counts are derived from incomplete and dynamic data. Provisional counts are based on the records available when the data was retrieved and may not represent all births that occurred during the time period.
The final data tables include both births that occurred in California regardless of the place of residence (by occurrence) and births to California residents (by residence), whereas the provisional data table only includes births that occurred in California regardless of the place of residence (by occurrence). The data are reported as totals, as well as stratified by parent giving birth's age, parent giving birth's race-ethnicity, and birth place type. See temporal coverage for more information on which strata are available for which years.
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TwitterBy data.world's Admin [source]
The data was obtained from multiple sources. Data from 1985-2002 were downloaded from the National Bureau for Economic Research through the National Center for Health Statistics' National Vital Statistics System. Data from 2003-2015 were sourced using aggregators provided by CDC's WONDER tool, utilizing Year, Month, State, and County filters. It is worth noting that geolocation information for individual babies born after 2005 is not released due to privacy concerns; therefore, all data has been aggregated by month.
The spatial applicability of this dataset is limited to the United States at the county level. It covers a temporal range spanning January 1, 1985 - December 31, 2015. Each row in the dataset represents aggregated birth counts within a specific county for a particular month and year.
Additional notes highlight that this dataset expands on data presented in an essay called The Timing of Baby Making published by The Pudding website in May 2017. While only data ranging from1995-2015 were displayed in the essay itself, this dataset includes an extra ten years of birth data. Furthermore, any non-US residents have been excluded from this dataset.
The provided metadata gives a detailed breakdown of the columns in the dataset, including their descriptions and data types. The included variables allow researchers to analyze births at both individual county and state levels over time. Finally, the dataset is available under the MIT License for public use
Here is a guide on how to effectively use this dataset:
Step 1: Understanding the Columns
The dataset consists of several columns that provide specific information about each birth record. Let's understand what each column represents:
- State: The state (including District of Columbia) where the mother lives.
- County: The county where the mother lives, coded using the FIPS County Code.
- Month: The month in which the birth took place (1 = January, 2 = February, etc.).
- Year: The four-digit year of the birth.
- countyBirths: The calculated sum of births that occurred to mothers living in a county for a given month. If the sum was less than 9, it is listed as NA as per NCHS reporting guidelines.
- stateBirths: The calculated sum of births that occurred to mothers living in a state for a given month. It includes all birth counts, even those from counties with fewer than 9 births.
Step 2: Exploring Birth Trends by State and County
You can analyze birth trends by focusing on specific states or counties within specific time frames. Here's how you can do it:
Filter by State or County:
- Select rows based on your chosen state using the State column. Each number corresponds to a specific state (e.g.,
01= Alabama).- Further narrow down your analysis by selecting specific counties using their respective FIPS codes mentioned in the County column.
Analyze Monthly Variation:
- Calculate monthly total births within your desired location(s) by grouping data based on the Month column.
- Compare the number of births between different months to identify any seasonal trends or patterns.
Visualize Birth Trends:
- Create line charts or bar plots to visualize how the number of births changes over time.
- Plot a line or bar for each month across multiple years to identify any significant changes in birth rates.
Step 3: Comparison and Calculation
You can utilize this dataset to compare birth rates between states, counties, and regions. Here are a few techniques you can try:
- State vs. County Comparison:
- Calculate the total births within each state by aggregating
- Analyzing birth trends: This dataset can be used to analyze and understand the trends in birth rates across different states and counties over the period of 1985 to 2015. Researchers can study factors that may influence these trends, such as socioeconomic factors, healthcare access, or cultural changes.
- Identifying seasonal variations: The dataset includes information on the month of birth for each entry. This data can be utilized to identify any seasonal variations in births across different locations in the US. Understanding these variations can help in planning resources and healthcare services accordingly.
- Studying geographical patterns: By analyzing the county-level data, researchers can explore geographical patterns of childbirth throughout the United States. They can identify regions with high or low birth rates and...
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TwitterPopular Baby Names by Sex and Ethnic Group Data were collected through civil birth registration. Each record represents the ranking of a baby name in the order of frequency. Data can be used to represent the popularity of a name. Caution should be used when assessing the rank of a baby name if the frequency count is close to 10; the ranking may vary year to year.
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TwitterNumber and percentage of live births, by month of birth, 1991 to most recent year.
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Twitterhttps://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/
This dataset contains US baby names from the Social Security Administration dating back to 1879. With over 150 years of data, this is one of the most comprehensive datasets on baby names in the US. The data includes the name, year of birth, sex, and number of babies with that name for each year. This dataset is a great resource for anyone interested in studying baby naming trends over time
This dataset is a compilation of over 140 years of data from the Social Security Administration. It includes data on baby names, year of birth, and sex. There are also columns for the number of babies with that name born in that year.
This dataset can be used to track changes in baby naming trends over time, or to study how popular names have changed in popularity. It can also be used to study how naming trends differ between sexes, or between different years
This dataset could be used for a number of things, including: 1. Determining baby name trends over time 2. Finding out what the most popular baby names are in the US 3. Analyzing how baby name popularity has changed over the years
If you use this dataset in your research, please credit @nickgott, @rflprr and the Social Security Administration via Data.gov
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Twitterhttps://digital.nhs.uk/about-nhs-digital/terms-and-conditionshttps://digital.nhs.uk/about-nhs-digital/terms-and-conditions
This statistical release makes available the most recent monthly data on NHS-funded maternity services in England, using data submitted to the Maternity Services Data Set (MSDS). This is the latest report from the newest version of the data set, MSDS.v.2, which has been in place since April 2019. The new data set was a significant change which added support for key policy initiatives such as continuity of carer, as well as increased flexibility through the introduction of new clinical coding. This was a major change, so data quality and coverage initially reduced from the levels seen in earlier publications. MSDS.v.2 data completeness improved over time, and we are looking at ways of supporting further improvements. This publication also includes the National Maternity Dashboard, which can be accessed via the link below. Data derived from SNOMED codes is used in some measures such as those for birthweight, and others will follow in later publications. SNOMED data is also included in some of the published Clinical Quality Improvement Metrics (CQIMs), where rules have been applied to ensure measure rates are calculated only where data quality is high enough. System suppliers are at different stages of development and delivery to trusts. In some cases, this has limited the aspects of data that can be submitted in the MSDS. To help Trusts understand to what extent they met the Clinical Negligence Scheme for Trusts (CNST) Maternity Incentive Scheme (MIS) Data Quality Criteria for Safety Action 2 Year 6, we have been producing a CNST Scorecard Dashboard showing trust performance against this criteria. The final results for the CNST MIS Y6 SA2 assessment, using July 2024 data, are now available in this dashboard, and can be accessed via the link below. This dashboard also includes data for a few non-CNST MSDS data quality priorities and last month we introduced into the dashboard a new data quality measure on birth site code recording, in accordance with Maternity and Neonatal Programme priorities. This new measure will not be assessed as part of the Maternity Incentive Scheme. This month, a small improvement was made to how the CQIMReadmissions metric uses discharge date information and this has resulted in a small change in the data output. As a result, the published CQIMReadmissions figures from this month's publication onwards are not fully comparable to the figures from earlier months. Last month, MSDS metrics published to support Saving Babies Lives Care Bundle (SBLCB) monitoring were updated to align with the contents of SBLCB version 3. As a result some SBLCB version 2 metrics have been removed from the Measures file and others have been renamed to align with SBLCB version 3 naming conventions. More information about the CQIMReadmissions change and the MSDS metrics published to support SBLCB are available in the accompanying Metadata file. The percentages presented in this report are based on rounded figures and therefore may not total to 100%.
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TwitterThe data (name, year of birth, sex, and number) are from a 100 percent sample of Social Security card applications for 1880 on.
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TwitterThis data set contains the first name statistics for newborns in Münster from 2007 to 2021. Two different lists are made available: A first name hit list with the top 30 most commonly used first names, grouped by year of birth and gender. A list of “first name numbers”. This list shows how many babies have been given multiple first names. First name hitlist The table with the first name hitlist contains the following columns: Year = year of birth Rank = Top 30 rank Gender = girl or boy Name = the chosen name Number = Number of children with this name Please note the following additional information: All given first names are taken into account for the calculation of the first name list, i.e. the second and third names. For example, if “Tom” leads the list in a year, that doesn't mean that Tom was the most popular name, but Tom was the most frequently mentioned first name among the total first, second, third and other given names for babies. First name number The table with the first name number contains the following columns: Year = year of birth Children with.. = How many first names Number = number of children The following is an Excel file, which contains both lists in different spreadsheets, as well as two corresponding CSV files.
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TwitterThe frequency and ranking of first names given to babies born in the province of Alberta, by year of birth and gender of the baby.
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This is a publication on maternity activity in English NHS hospitals. This report examines data relating to delivery and birth episodes in 2023-24, and the booking appointments for these deliveries. This annual publication covers the financial year ending March 2024. Data is included from both the Hospital Episodes Statistics (HES) data warehouse and the Maternity Services Data Set (MSDS). HES contains records of all admissions, appointments and attendances for patients admitted to NHS hospitals in England. The HES data used in this publication are called 'delivery episodes'. The MSDS collects records of each stage of the maternity service care pathway in NHS-funded maternity services, and includes information not recorded in HES. The MSDS is a maturing, national-level dataset. In April 2019, the MSDS transitioned to a new version of the dataset. This version, MSDS v2.0, is an update that introduced a new structure and content - including clinical terminology, in order to meet current clinical practice and incorporate new requirements. It is designed to meet requirements that resulted from the National Maternity Review, which led to the publication of the Better Births report in February 2016. This is the fifth publication of data from MSDS v2.0 and data from 2019-20 onwards is not directly comparable to data from previous years. This publication shows the number of HES delivery episodes during the period, with a number of breakdowns including by method of onset of labour, delivery method and place of delivery. It also shows the number of MSDS deliveries recorded during the period, with a breakdown for the mother's smoking status at the booking appointment by age group. It also provides counts of live born term babies with breakdowns for the general condition of newborns (via Apgar scores), skin-to-skin contact and baby's first feed type - all immediately after birth. There is also data available in a separate file on breastfeeding at 6 to 8 weeks. For the first time information on 'Smoking at Time of Delivery' has been presented using annual data from the MSDS. This includes national data broken down by maternal age, ethnicity and deprivation. From 2025/2026, MSDS will become the official source of 'Smoking at Time of Delivery' information and will replace the historic 'Smoking at Time of Delivery' data which is to become retired. We are currently undergoing dual collection and reporting on a quarterly basis for 2024/25 to help users compare information from the two sources. We are working with data submitters to help reconcile any discrepancies at a local level before any close down activities begin. A link to the dual reporting in the SATOD publication series can be found in the links below. Information on how all measures are constructed can be found in the HES Metadata and MSDS Metadata files provided below. In this publication we have also included an interactive Power BI dashboard to enable users to explore key NHS Maternity Statistics measures. The purpose of this publication is to inform and support strategic and policy-led processes for the benefit of patient care. This report will also be of interest to researchers, journalists and members of the public interested in NHS hospital activity in England. Any feedback on this publication or dashboard can be provided to enquiries@nhsdigital.nhs.uk, under the subject “NHS Maternity Statistics”.
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This dataset contains an aggregation of birth data from the United Statesbetween 1985 and 2015. It consists of information on mothers' locations by state (including District of Columbia) and county, as well as information such as the month they gave birth, and aggregates giving the sum of births during that month. This data has been provided by both the National Bureau for Economic Research and National Center for Health Statistics, whose shared mission is to understand how life works in order to aid individuals in making decisions about their health and wellbeing. This dataset provides valuable insight into population trends across time and location - for example, which states have higher or lower birthrates than others? Which counties experience dramatic fluctuations over time? Given its scope, this dataset could be used in a number of contexts--from epidemiology research to population forecasting. Be sure to check out our other datasets related to births while you're here!
For more datasets, click here.
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This dataset could be used to examine local trends in birth rates over time or analyze births at different geographical locations. In order to maximize your use of this dataset, it is important that you understand what information the various columns contain.
The main columns are: State (including District of Columbia), County (coded using the FIPS county code number), Month (numbering from 1 for January through 12 for December), Year (4-digit year) countyBirths (calculated sum of births that occurred to mothers living in a county for a given month) and stateBirths (calculated sum of births that occurred to mothers living in a state for a given month). These fields should provide enough information for you analyze trends across geographic locations both at monthly and yearly levels. You could also consider combining variables such as
YearwithStateorYearwithMonthor any other grouping combinations depending on your analysis goal.In addition, while all data were downloaded on April 5th 2017, it is worth noting that all sources used followed privacy guidelines as laid out by NCHC so individual births occurring after 2005 are not included due to geolocation concerns.
We hope you find this dataset useful and can benefit from its content! With proper understanding of what each field contains, we are confident you will gain valuable insights on birth rates across counties within the United States during this period
- Establishing county-level trends in birth rates for the US over time.
- Analyzing the relationship between month of birth and health outcomes for US babies after they are born (e.g., infant mortality, neurological development, etc.).
- Comparing state/county-level differences in average numbers of twins born each year
If you use this dataset in your research, please credit the original authors. Data Source
See the dataset description for more information.
File: allBirthData.csv | Column name | Description | |:-----------------|:-----------------------------------------------------------------------------------------------------------------| | State | The numerical order of the state where the mother lives. (Integer) | | Month | The month in which the birth took place. (Integer) | | Year | The year of the birth. (Integer) | | countyBirths | The calculated sum of births that occurred to mothers living in that county for that particular month. (Integer) | | stateBirths | The aggregate number at the level of entire states for any given month-year combination. (Integer) | | County | The county where the mother lives, coded using FIPS County Code. (Integer) |
If you use this dataset in your research, please credit the original authors. If you use this dataset in your research, please credit data.world's Admin.
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Twitterhttps://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/
US Social Security applications are a great way to track trends in how babies born in the US are named.
Data.gov releases two datasets that are helplful for this: one at the national level and another at the state level. Note that only names with at least 5 babies born in the same year (/ state) are included in this dataset for privacy.
I've taken the raw files here and combined/normalized them into two CSV files (one for each dataset) as well as a SQLite database with two equivalently-defined tables. The code that did these transformations is available here.
New to data exploration in R? Take the free, interactive DataCamp course, "Data Exploration With Kaggle Scripts," to learn the basics of visualizing data with ggplot. You'll also create your first Kaggle Scripts along the way.
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Dataset from Singapore Department of Statistics. For more information, visit https://data.gov.sg/datasets/d_6150f21b0892b3fdde546d2a1af2af82/view
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TwitterOpen Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
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A live birth is a baby showing signs of life at birth. This dataset shows the latest live births by Ward.
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TwitterBirth Statistics (i) Number of Known Births for Different Sexes and Crude Birth Rate for the Period from 1981 to 2024 (ii) Percentage Distribution of Live Births by Birth Weight for the Period from 2012 to 2023
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TwitterThis dataset contains counts of live births to California residents by ZIP Code based on information entered on birth certificates. Final counts are derived from static data and include out-of-state births to California residents. The data tables include births to residents of California by ZIP Code of residence (by residence).
Note that ZIP Codes are intended for mail delivery routing and do not represent geographic regions. ZIP Codes are subject to change over time and may not represent the same locations between different time periods. All ZIP Codes in the list of California ZIP Codes used for validation are included for all years, but this does not mean that the ZIP Code was in use at that time.
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Twitterhttps://www.usa.gov/government-works/https://www.usa.gov/government-works/
The world population has grown rapidly, particularly over the past century: in 1900, there were fewer than 2 billion people on the planet. The world population is around 8045311488 in 2023.
Two metrics determine the change in the world population: the number of babies born and the number of people dying. How many babies are born each year?
There were 133.99 million births in 2022, compared to 92.08 million births in 1950
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TwitterOpen Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
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Annual live births in England and Wales by age of mother and father, type of registration, median interval between births, number of previous live-born children and National Statistics Socio-economic Classification (NS-SEC).
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TwitterApache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
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Popular Baby Names by Sex and Ethnic Group Data were collected through civil birth registration. Each record represents the ranking of a baby name in the order of frequency. Data can be used to represent the popularity of a name. Caution should be used when assessing the rank of a baby name if the frequency count is close to 10; the ranking may vary year to year.
Potential Use Cases - Demographic Studies – Analyze cultural shifts in naming trends. - Social Research – Understand how societal events influence name popularity. - Parenting & Baby Naming Tools – Develop apps that suggest trending or unique names. - Marketing & Branding – Identify popular names for personalized products or campaigns.
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset contains counts of live births for California as a whole based on information entered on birth certificates. Final counts are derived from static data and include out of state births to California residents, whereas provisional counts are derived from incomplete and dynamic data. Provisional counts are based on the records available when the data was retrieved and may not represent all births that occurred during the time period.
The final data tables include both births that occurred in California regardless of the place of residence (by occurrence) and births to California residents (by residence), whereas the provisional data table only includes births that occurred in California regardless of the place of residence (by occurrence). The data are reported as totals, as well as stratified by parent giving birth's age, parent giving birth's race-ethnicity, and birth place type. See temporal coverage for more information on which strata are available for which years.