Provides information highlights by topic via key indicators for various levels of geography.

Age Range Classification

## Overview

Age Range Classification is a dataset for classification tasks - it contains Face annotations for 9,672 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [BY-NC-SA 4.0 license](https://creativecommons.org/licenses/BY-NC-SA 4.0).

Classification by methods used, age groups and sex. National.

Image Classification Age Range Labels

This repository uses the following labels to categorize age ranges in image classification tasks:

[!Warning] labels_list = ['0-12', '13-20', '21-44', '45-64', '65+']

the values are age range in iamge classification give the README.MD for Repository

0-12: Images depicting individuals aged 0 to 12 years old. 13-20: Images depicting individuals aged 13 to 20 years old. 21-44: Images depicting individuals aged 21 to 44 years old. 45-64: Images… See the full description on the dataset page: https://huggingface.co/datasets/prithivMLmods/Age-Classification-Set.

Curious about age demographics of your clientele in United Kingdom? Wondering about which generation can be most often seen flocking to your store? Dive deep into customer insights using our population by age group data of United Kingdom. Whether your customers are down your street or across the globe, we empower you to pinpoint the ideal demographic for your marketing campaigns or projects. Our dataset offers intricate details on this country's age distribution.

Classification by methods used, age groups and sex. National. Classification by methods used in combination with age groups and sex.

Classification by methods used, age groups and sex. National. Classification by other methods in combination with occupation and sex.

Age and Sex Highlight Tables, Population by broad age groups and sex by Statistical Area Classification, 2011 - Provides information highlights by topic via key indicators for various levels of geography.

Classification by reasons, age groups and sex. National.

This dataset provides a detailed breakdown of the economically active population aged 15 years and above in Qatar, categorized by age group and occupation. The data reflects the distribution of the labor force across various occupational groups and age brackets, offering insights into employment patterns and workforce demographics. The classification of occupations follows the International Standard Classification of Occupations (ISCO-88).

Classification by provinces, age groups and sex. National. Classification by provinces in combination with age groups and sex.

This table is part of a series of tables that present a portrait of Canada based on the various census topics. The tables range in complexity and levels of geography. Content varies from a simple overview of the country to complex cross-tabulations; the tables may also cover several censuses.

Classification by causes, age groups and sex. National. Classification by causes in combination with age groups and sex.

Malawi MW: Primary Completion Rate: Male: % of Relevant Age Group data was reported at 76.225 % in 2014. This records a decrease from the previous number of 76.531 % for 2013. Malawi MW: Primary Completion Rate: Male: % of Relevant Age Group data is updated yearly, averaging 43.999 % from Dec 1974 (Median) to 2014, with 38 observations. The data reached an all-time high of 76.531 % in 2013 and a record low of 26.326 % in 1974. Malawi MW: Primary Completion Rate: Male: % of Relevant Age Group data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Malawi – Table MW.World Bank.WDI: Education Statistics. Primary completion rate, or gross intake ratio to the last grade of primary education, is the number of new entrants (enrollments minus repeaters) in the last grade of primary education, regardless of age, divided by the population at the entrance age for the last grade of primary education. Data limitations preclude adjusting for students who drop out during the final year of primary education.; ; UNESCO Institute for Statistics; Weighted average; Each economy is classified based on the classification of World Bank Group's fiscal year 2018 (July 1, 2017-June 30, 2018).

Dataset contains life-cycle age group census usually resident population counts from the 2013, 2018, and 2023 Censuses, as well as the percentage change in the age group population counts between the 2013 and 2018 Censuses, and between the 2018 and 2023 Censuses. Data is available by regional council.

The life-cycle age groups are:

• under 15 years
• 15 to 29 years
• 30 to 64 years
• 65 years and over.

Map shows the percentage change in the census usually resident population count for life-cycle age groups between the 2018 and 2023 Censuses.

Download lookup file from Stats NZ ArcGIS Online or embedded attachment in Stats NZ geographic data service. Download data table (excluding the geometry column for CSV files) using the instructions in the Koordinates help guide.

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Footnotes

Geographical boundaries

Statistical standard for geographic areas 2023 (updated December 2023) has information about geographic boundaries as of 1 January 2023. Address data from 2013 and 2018 Censuses was updated to be consistent with the 2023 areas. Due to the changes in area boundaries and coding methodologies, 2013 and 2018 counts published in 2023 may be slightly different to those published in 2013 or 2018.

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Subnational census usually resident population

The census usually resident population count of an area (subnational count) is a count of all people who usually live in that area and were present in New Zealand on census night. It excludes visitors from overseas, visitors from elsewhere in New Zealand, and residents temporarily overseas on census night. For example, a person who usually lives in Christchurch city and is visiting Wellington city on census night will be included in the census usually resident population count of Christchurch city.

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Caution using time series

Time series data should be interpreted with care due to changes in census methodology and differences in response rates between censuses. The 2023 and 2018 Censuses used a combined census methodology (using census responses and administrative data), while the 2013 Census used a full-field enumeration methodology (with no use of administrative data).

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About the 2023 Census dataset

For information on the 2023 dataset see Using a combined census model for the 2023 Census. We combined data from the census forms with administrative data to create the 2023 Census dataset, which meets Stats NZ's quality criteria for population structure information. We added real data about real people to the dataset where we were confident the people who hadn’t completed a census form (which is known as admin enumeration) will be counted. We also used data from the 2018 and 2013 Censuses, administrative data sources, and statistical imputation methods to fill in some missing characteristics of people and dwellings.

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Data quality

The quality of data in the 2023 Census is assessed using the quality rating scale and the quality assurance framework to determine whether data is fit for purpose and suitable for release. Data quality assurance in the 2023 Census has more information.

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Quality rating of a variable

The quality rating of a variable provides an overall evaluation of data quality for that variable, usually at the highest levels of classification. The quality ratings shown are for the 2023 Census unless stated. There is variability in the quality of data at smaller geographies. Data quality may also vary between censuses, for subpopulations, or when cross tabulated with other variables or at lower levels of the classification. Data quality ratings for 2023 Census variables has more information on quality ratings by variable.

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Age concept quality rating

Age is rated as very high quality.

Age – 2023 Census: Information by concept has more information, for example, definitions and data quality.

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Using data for good

Stats NZ expects that, when working with census data, it is done so with a positive purpose, as outlined in the Māori Data Governance Model (Data Iwi Leaders Group, 2023). This model states that "data should support transformative outcomes and should uplift and strengthen our relationships with each other and with our environments. The avoidance of harm is the minimum expectation for data use. Māori data should also contribute to iwi and hapū tino rangatiratanga”.

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Confidentiality

The 2023 Census confidentiality rules have been applied to 2013, 2018, and 2023 data. These rules protect the confidentiality of individuals, families, households, dwellings, and undertakings in 2023 Census data. Counts are calculated using fixed random rounding to base 3 (FRR3) and suppression of ‘sensitive’ counts less than six, where tables report multiple geographic variables and/or small populations. Individual figures may not always sum to stated totals. Applying confidentiality rules to 2023 Census data and summary of changes since 2018 and 2013 Censuses has more information about 2023 Census confidentiality rules.

The number of postsecondary enrolments, by Classification of Instructional Programs, Primary groupings (CIP_PG), International Standard Classification of Education (ISCED), age group and gender.

This table provides 2021 data on the estimated population aged 16 and over in the Canary Islands by classification of tobacco consumption and age groups.

Number of database distributions according to the age classification model.

This table is part of a series of tables that present a portrait of Canada based on the various census topics. The tables range in complexity and levels of geography. Content varies from a simple overview of the country to complex cross-tabulations; the tables may also cover several censuses.

This table provides statistical information about people in Canada by their demographic, social and economic characteristics as well as provide information about the housing units in which they live.