Dataset from Singapore Department of Statistics. For more information, visit https://data.gov.sg/datasets/d_3f4bfee2d42f8fb3bea3218c01aa9902/view

Context

This dataset is in context of the real world data science work and how the data analyst and data scientist work.

Content

The dataset consists of four columns Year, Level_1(Ethnic group/gender), Level_2(Age group), and population

Acknowledgements

I would sincerely thank GeoIQ for sharing this dataset with me along with tasks. Just having a basic knowledge of Pandas and Numpy and other python data science libraries is not enough. How can you execute tasks and how can you preprocess the data before making any prediction is very important. Most of the datasets in Kaggle are clean and well arranged but this dataset thought me how real world data science and analysis works. Every data science beginner must work on this dataset and try to execute the tasks. It would only give them a good exposer to the real data science world.

Inspiration

1. Identify the largest Ethnic group in Singapore. Their average population growth over the years and what proportion of the total population do they constitute.
2. Identify the largest age group in Singapore. Their average population growth over the years and what proportion of the total population do they constitute.
3. Identify the group (by age, ethnicity and gender) that: a. Has shown the highest growth rate b. Has shown the lowest growth rate c. Has remained the same
4. Plot a graph for population trends

This statistic illustrates the results of a survey regarding the subscription to mobile data services in Singapore as of ********, by age. During the survey period, approximately **** percent of the respondents in the country with subscription to mobile data services were aged between 40 to 44 years.

This dataset provides information about the number of properties, residents, and average property values for Old Singapore Trail cross streets in Saugatuck, MI.

Age dependency ratio, old (% of working-age population) in Singapore was reported at 17.43 % in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Singapore - Age dependency ratio, old (% of working-age population) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

Singapore SG: Age Dependency Ratio: % of Working-Age Population: Old data was reported at 17.923 % in 2017. This records an increase from the previous number of 16.960 % for 2016. Singapore SG: Age Dependency Ratio: % of Working-Age Population: Old data is updated yearly, averaging 7.597 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 17.923 % in 2017 and a record low of 3.736 % in 1960. Singapore SG: Age Dependency Ratio: % of Working-Age Population: Old data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Singapore – Table SG.World Bank.WDI: Population and Urbanization Statistics. Age dependency ratio, old, is the ratio of older dependents--people older than 64--to the working-age population--those ages 15-64. Data are shown as the proportion of dependents per 100 working-age population.; ; World Bank staff estimates based on age distributions of United Nations Population Division's World Population Prospects: 2017 Revision.; Weighted average;

This dataset is about countries per year in Singapore. It has 1 row and is filtered where the date is 2023. It features 4 columns: country, net migration, and median age.

UIS: Mean years of schooling (ISCED 1 or higher), population 25+ years, male in Singapore was reported at 12.11 Years in 2018, according to the World Bank collection of development indicators, compiled from officially recognized sources. Singapore - Mean years of schooling of the population age 25+. Male - actual values, historical data, forecasts and projections were sourced from the World Bank on June of 2025.

Dataset from Singapore Department of Statistics. For more information, visit https://data.gov.sg/datasets/d_4bd9ffc2595acd61fd1a7f642caf8f36/view

Data for 1970 and from 1980 onwards refer to Singapore residents (citizens and permanent residents).

Data prior to 1980 (except 1970) refer to total population.

Data for 1970 and 1980 refer to all residents present in Singapore on Census day.

Data from 2000 onwards are based on the register-based approach.

Data from 2003 onwards exclude residents who are overseas for a continuous period of 12 months or longer as at the reference period.

Dataset from Singapore Department of Statistics. For more information, visit https://data.gov.sg/datasets/d_f378329d4a46817543287388768477fe/view

This dataset is about countries per year in Singapore. It has 1 row and is filtered where the date is 2021. It features 4 columns: country, ISO 2 country code, and median age.

Singapore Old-Age Support Ratio: Citizen: Per >65 Years: 20-64 Years data was reported at 4.000 Per Person in 2019. This records a decrease from the previous number of 4.200 Per Person for 2018. Singapore Old-Age Support Ratio: Citizen: Per >65 Years: 20-64 Years data is updated yearly, averaging 7.800 Per Person from Jun 1970 (Median) to 2019, with 32 observations. The data reached an all-time high of 13.500 Per Person in 1970 and a record low of 4.000 Per Person in 2019. Singapore Old-Age Support Ratio: Citizen: Per >65 Years: 20-64 Years data remains active status in CEIC and is reported by Department of Statistics. The data is categorized under Global Database’s Singapore – Table SG.G001: Population: Statistics.

Dataset from Singapore Department of Statistics. For more information, visit https://data.gov.sg/datasets/d_87d4a928fbaf172af7cdd8d4254218aa/view

The daily aggregated time-series data used in this study, "Predicting public mental health needs in a crisis using social media indicators: A Singapore big data study" (including actual values and normalised values), are available in the figshare repository. The count of daily emergency room visits data (“IMH Visits”) is available from the corresponding author upon reasonable request.The study can be cited as:Othman, N.A., Panchapakesan, C., Loh, S.B., Zhang, M., Gupta, R.K., Martanto, W., Phang, Y.S., Morris, R.J.T., Loke, W.C., Tan, K.B., Subramaniam, M., Yang, Y. Predicting public mental health needs in a crisis using social media indicators: a Singapore big data study. Sci Rep 14, 23222 (2024). https://doi.org/10.1038/s41598-024-73978-5

The Singapore Nanopore Expression (SG-NEx) project is an international collaboration to generate reference transcriptomes and a comprehensive benchmark data set for long read Nanopore RNA-Seq. Transcriptome profiling is done using PCR-cDNA sequencing (PCR-cDNA), amplification-free cDNA sequencing (direct cDNA), direct sequencing of native RNA (direct RNA), and short read RNA-Seq. The SG-NEx core data includes 5 of the most commonly used cell lines and it is extended with additional cell lines and samples that cover a broad range of human tissues. All core samples are sequenced with at least 3 high quality replicates. For a subset of samples spike-in RNAs are used and matched m6A profiling data is available.

This record contains the underlying research data for the publication "Singaporean mothers' perception of their three-year-old child's weight status: A cross-sectional study" and the full-text is available from: https://ink.library.smu.edu.sg/soss_research/2459Objective: Inaccurate parental perception of their child's weight status is commonly reported in Western countries. It is unclear whether similar misperception exists in Asian populations. This study aimed to evaluate the ability of Singaporean mothers to accurately describe their three-year-old child's weight status verbally and visually.

Retirement Age Women in Singapore remained unchanged at 63 Years in 2025 from 63 Years in 2024. This dataset provides - Singapore Retirement Age Women - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Singapore Old-Age Dependency Ratio: Resident: Per 100(15-64 Years): >65 Years data was reported at 20.400 Per 100 Person in 2019. This records an increase from the previous number of 19.200 Per 100 Person for 2018. Singapore Old-Age Dependency Ratio: Resident: Per 100(15-64 Years): >65 Years data is updated yearly, averaging 8.300 Per 100 Person from Jun 1957 (Median) to 2019, with 63 observations. The data reached an all-time high of 20.400 Per 100 Person in 2019 and a record low of 3.900 Per 100 Person in 1957. Singapore Old-Age Dependency Ratio: Resident: Per 100(15-64 Years): >65 Years data remains active status in CEIC and is reported by Department of Statistics. The data is categorized under Global Database’s Singapore – Table SG.G001: Population: Statistics.

UIS: Mean years of schooling (ISCED 1 or higher), population 25+ years, both sexes in Singapore was reported at 11.62 Years in 2018, according to the World Bank collection of development indicators, compiled from officially recognized sources. Singapore - Mean years of schooling of the population age 25+. Total - actual values, historical data, forecasts and projections were sourced from the World Bank on August of 2025.