Description

This Dataset contains details of World Population by country. According to the worldometer, the current population of the world is 8.2 billion people. Highest populated country is India followed by China and USA.

Attribute Information

• Rank : Country Rank by Population.
• Country : Name of the Country.
• Population(2024) : Current Population of each Country.
• Yearly Change : Percentage Yearly Change in Population.
• Net Change : Net change in the Population.
• Density (P/Km²) : Population density (population per square km)
• Land Area(Km²) : Total land area of the Country.
• Migrants (net) : Total number of migrants.
• Fertility Rate : Fertility rate
• Median Age : Median age of the population
• Urban Pop % : Percentage of urban population
• World Share : Share to the word with population.

Acknowledgements

https://www.worldometers.info/world-population/population-by-country/

Image by Gerd Altmann from Pixabay

The total population in India was estimated at 1398.6 million people in 2024, according to the latest census figures and projections from Trading Economics. This dataset provides - India Population - actual values, historical data, forecast, chart, statistics, economic calendar and news.

India is the most populous country in the world with one-sixth of the world's population. According to official estimates in 2022, India's population stood at over 1.42 billion.

This dataset contains the population distribution by state, gender, sex & region.

The file is in .csv format thus it is accessible everywhere.

Historical dataset showing total population for India by year from 1950 to 2025.

About this dataset

Context

The dataset tabulates the population of Indian Village by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of Indian Village across both sexes and to determine which sex constitutes the majority.

Key observations

There is a majority of female population, with 56.64% of total population being female. Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis. No further analysis is done on the data reported from the Census Bureau.

Variables / Data Columns

• Gender: This column displays the Gender (Male / Female)
• Population: The population of the gender in the Indian Village is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of Indian Village total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Indian Village Population by Race & Ethnicity. You can refer the same here

Content

The current population of India is 1,403,717,340 as of Sunday, April 3, 2022, based on Worldometer elaboration of the latest United Nations data. This three datasets contain population data of India (2020 and historical), population forecast and population in major cities.

Attribute Information

• Year - Years from 2020-1955
• Population - Population in the respective year
• Yearly % Change - Percentage Yearly Change in Population
• Yearly Change - Yearly Change in Population
• Migrants (net) - Total number of migrants
• Median Age - Median age of the population
• Fertility Rate - Fertility rate
• Density (P/Km²)- Population density (population per square km)
• Urban Pop %- Percentage of urban population
• Urban Population- Urban population
• Country's Share of World Pop - Population share
• World Population - World Population in the respective year
• India Global Rank - Global Rank in Population

Source

Link : https://www.worldometers.info/world-population/india-population/

Updated Covid 19 and Other Datasets

Link : https://www.kaggle.com/anandhuh/datasets

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Employment Rate in India increased to 52.40 percent in September from 52.20 percent in August of 2025. This dataset provides - India Worker Population Ratio- actual values, historical data, forecast, chart, statistics, economic calendar and news.

Comprehensive socio-economic dataset for India including population demographics, economic indicators, geographic data, and social statistics. This dataset covers key metrics such as GDP, population density, area, capital city, and regional classifications.

The statistic shows the total population of India from 2020 to 2030. In 2024, the estimated total population in India amounted to approximately 1.44 billion people. Total population in India India currently has the second-largest population in the world and is projected to overtake top-ranking China within forty years. Its residents comprise more than one-seventh of the entire world’s population, and despite a slowly decreasing fertility rate (which still exceeds the replacement rate and keeps the median age of the population relatively low), an increasing life expectancy adds to an expanding population. In comparison with other countries whose populations are decreasing, such as Japan, India has a relatively small share of aged population, which indicates the probability of lower death rates and higher retention of the existing population. With a land mass of less than half that of the United States and a population almost four times greater, India has recognized potential problems of its growing population. Government attempts to implement family planning programs have achieved varying degrees of success. Initiatives such as sterilization programs in the 1970s have been blamed for creating general antipathy to family planning, but the combined efforts of various family planning and contraception programs have helped halve fertility rates since the 1960s. The population growth rate has correspondingly shrunk as well, but has not yet reached less than one percent growth per year. As home to thousands of ethnic groups, hundreds of languages, and numerous religions, a cohesive and broadly-supported effort to reduce population growth is difficult to create. Despite that, India is one country to watch in coming years. It is also a growing economic power; among other measures, its GDP per capita was expected to triple between 2003 and 2013 and was listed as the third-ranked country for its share of the global gross domestic product.

Historical dataset of population level and growth rate for the Mumbai, India metro area from 1950 to 2025.

Historical dataset of population level and growth rate for the Gaya, India metro area from 1950 to 2025.

Dataset showing the global tiger population and country-wise distribution in 2025. India leads global tiger conservation with two-thirds of the world's wild tigers.

this is the data of Top 10 populated countries of world as on 30 March 2024 with history of their population from 1955. it also have forecasted population values of these countries from 2025 to 2050.

here are the detail of columns

1: year:1955 to 2050

2: India: (population in millions)

3: china: (population in millions)

4: USA: (population in millions)

5: Indonesia: (population in millions)

6: Pakistan: (population in millions)

7: Nigeria: (population in millions)

8: Brazil: (population in millions)

9: Bangladesh: (population in millions)

10: Russia: (population in millions)

11: Mexico: (population in millions)

Acknowledgement This Dataset is created from https://www.worldometers.info/. If you want to learn more, you can visit the Website.

Overview

The India Customer Financial Profiles & Transactions Dataset contains 20,000 fully synthetic records that represent the demographic, financial, credit, and transactional behavior of customers across India. This dataset is ideal for machine learning, financial analytics, risk modeling, fintech simulation, and academic research.

All data is algorithmically generated, ensuring:

No real person is represented

No sensitive or identifiable information is included

Full compliance with privacy and research ethics

📂 Dataset File india_customer_financial_profiles_20000_cleaned.csv

A fully cleaned, validated, and standardized dataset containing demographic, financial, and transaction details.

🧾 Data Dictionary 👤 Demographic Information Demographic fields included in the dataset: id — Unique customer ID current_age — Customer age birth_year — Year of birth birth_month — Month of birth gender — Male / Female / Other address — Synthetic Indian address (City, State, PIN)

💰 Financial Attributes Financial attributes included: per_capita_income — Monthly per-person household income yearly_income — Annual income total_debt — Total outstanding debt credit_score — Score between 300–900 num_credit_cards — Number of credit cards]

🧾 Transaction Details Transaction-related fields: transaction_id — Unique transaction ID date — Transaction date (YYYY-MM-DD) client_id — Synthetic ID linked to customer card_id — Card identifier amount — Transaction amount (INR) use_chip — Chip used (Yes/No) merchant_id — Merchant identifier merchant_city — Transaction location (city) merchant_state — State of merchant zip — 6-digit PIN code

🔍 Key Features ✔ 20,000 synthetic customer profiles ✔ Includes demographic + financial + transaction data ✔ Standardized date format (YYYY-MM-DD) ✔ PIN codes extracted and cleaned ✔ No missing values ✔ Consistent and realistic Indian data patterns ✔ High usability for ML and analytics

🧠 Use Cases 🟦 Machine Learning Credit scoring Loan default prediction Fraud detection Customer segmentation Transaction classification

🟩 Data Analytics Financial behavioral trends Income–debt correlation analysis Merchant-level insights Urban vs rural customer profiles

🟧 Fintech Research Synthetic simulation Risk modeling Customer persona creation Spending behavior research

🟪 Education & Learning Data cleaning practice Feature engineering EDA & visualization projects Full ML pipeline demonstrations

🛠️ Data Generation Methodology The dataset was generated using: Synthetic demographic distribution modeling Indian address & PIN pattern simulation Income and credit-score probability distributions Transaction behavior simulation Randomized merchant profiles Rule-based statistical generation No scraping or real-world data sources were used. This dataset is 100% synthetic.

📜 License

This dataset is released under the Creative Commons Attribution 4.0 International (CC BY 4.0) license. You may: Use Modify Redistribute Adapt As long as you provide citation.

✍️ Citation

Use the following format to cite this dataset: Bedmutha, Kundan (2025). India Customer Financial Profiles & Transactions Dataset (20,000 Records).

🙌 Acknowledgements

This dataset was created to support: Students Researchers Machine learning practitioners Fintech analysts Educators Your feedback and suggestions are welcome for future dataset enhancements.

🎉 Thank You!

About this dataset

Context

This list ranks the 244 counties in the Texas by Indian population, as estimated by the United States Census Bureau. It also highlights population changes in each county over the past five years.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates, including:

• 2019-2023 American Community Survey 5-Year Estimates
• 2014-2018 American Community Survey 5-Year Estimates
• 2009-2013 American Community Survey 5-Year Estimates

Variables / Data Columns

• Rank by Indian Population: This column displays the rank of county in the Texas by their Indian population, using the most recent ACS data available.
• County: The County for which the rank is shown in the previous column.
• Indian Population: The Indian population of the county is shown in this column.
• % of Total County Population: This shows what percentage of the total county population identifies as Indian. Please note that the sum of all percentages may not equal one due to rounding of values.
• % of Total Texas Indian Population: This tells us how much of the entire Texas Indian population lives in that county. Please note that the sum of all percentages may not equal one due to rounding of values.
• 5 Year Rank Trend: This column displays the rank trend across the last 5 years.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Actual value and historical data chart for India Urban Population Percent Of Total

Comprehensive demographic dataset for India, Lawrence, KS, US including population statistics, household income, housing units, education levels, employment data, and transportation with year-over-year changes.

Historical dataset of population level and growth rate for the Jaipur, India metro area from 1950 to 2025.

About this dataset

Context

The dataset tabulates the population of Fredericksburg by race. It includes the population of Fredericksburg across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Fredericksburg across relevant racial categories.

Key observations

The percent distribution of Fredericksburg population by race (across all racial categories recognized by the U.S. Census Bureau): 87.96% are white, 0.65% are Black or African American, 1.25% are American Indian and Alaska Native, 0.26% are Asian, 0.68% are Native Hawaiian and other Pacific Islander, 3.07% are some other race and 6.13% are multiracial.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (excluding ethnicity) for the Fredericksburg
• Population: The population of the racial category (excluding ethnicity) in the Fredericksburg is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Fredericksburg total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Fredericksburg Population by Race & Ethnicity. You can refer the same here

The Gross Domestic Product per capita in India was last recorded at 2396.71 US dollars in 2024. The GDP per Capita in India is equivalent to 19 percent of the world's average. This dataset provides - India GDP per capita - actual values, historical data, forecast, chart, statistics, economic calendar and news.