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Context
The dataset tabulates the population of Indian Village by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Indian Village. The dataset can be utilized to understand the population distribution of Indian Village by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Indian Village. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Indian Village.
Key observations
Largest age group (population): Male # 75-79 years (10) | Female # 10-14 years (11). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Age groups:
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.
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Indian Village Population by Gender. You can refer the same here
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TwitterThe gender ratio in India was 900 between 2013 and 2015. This meant, for every 1,000 males, 900 females were present. Among its states, Chhattisgarh had the highest gender ratio at 961 in 2015 and 2016, while Haryana recorded the least at 833.
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Context
The dataset tabulates the population of Indian Harbour Beach by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Indian Harbour Beach. The dataset can be utilized to understand the population distribution of Indian Harbour Beach by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Indian Harbour Beach. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Indian Harbour Beach.
Key observations
Largest age group (population): Male # 65-69 years (432) | Female # 60-64 years (578). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Age groups:
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.
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Indian Harbour Beach Population by Gender. You can refer the same here
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Actual value and historical data chart for India Population Female Percent Of Total
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TwitterIndia recorded a gender ratio of approximately *** in 2011. The ratio was expected to improve to *** in 2026. Rural areas are expected to have a lower gender ratio in comparison to urban areas, with around *** women for every 1,000 men.
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TwitterThe growth in India's overall population is driven by its young population. Nearly ** percent of the country's population was between the ages of 15 and 64 years old in 2020. With over *** million people between 18 and 35 years old, India had the largest number of millennials and Gen Zs globally.
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Sex Ratio at Birth: Female per 1000 Male: Uttar Pradesh data was reported at 905.000 NA in 2020. This records an increase from the previous number of 894.000 NA for 2019. Sex Ratio at Birth: Female per 1000 Male: Uttar Pradesh data is updated yearly, averaging 878.000 NA from Dec 2006 (Median) to 2020, with 15 observations. The data reached an all-time high of 905.000 NA in 2020 and a record low of 869.000 NA in 2014. Sex Ratio at Birth: Female per 1000 Male: Uttar Pradesh data remains active status in CEIC and is reported by Office of the Registrar General & Census Commissioner, India. The data is categorized under India Premium Database’s Demographic – Table IN.GAJ001: Memo Items: Sex Ratio at Birth.
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TwitterIn 2011, the sex ratio of the general population in India was *** women to every one thousand men. On the other hand, the sex ratio of the elderly population in India stood at ***** women for every one thousand men, indicating an increase from the previous year. The sex ratio for both population types was forecasted to increase by 2031. After 2011, the sex ratio for the elderly population was estimated to be over ************, which indicates a higher number of elderly women than men.
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TwitterAs of 2021, India recorded a higher nationwide internet usage rate among men than women, at respectively **** percent of male population and **** percent of female population. The gender internet usage gap was also evident in rural India, with only one out of four women aged between 15 and 49 years having ever used the internet before, compared to just under ** percent of their male counterparts in the region.
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TwitterAs per a survey conducted across the country among students, the participation at work for men in India was expected to be ** percent in 2024, a decrease from the participation rate in 2023. A fluctuating trend emerged in the participation rate of this segment of India's workforce since 2016. Meanwhile, the participation at work for women in the organized sector increased from ** percent in 2023 to ** percent in 2024 but still a wide gender gap persists.
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TwitterIn a survey conducted between July 2023 and June 2024, the rate of labor participation for the urban male population was over ** percent compared to the over ** percent rate among females. The rate of labor participation in rural areas was lower across genders.
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TwitterOver ** percent of the Indian population was married in 2020. Of this, women made up a higher share at nearly ** percent, while this stood at about ** percent among men during the same time period. About *** percent overall were categorized as divorced/separated/widowed or widower.
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TwitterAccording to a survey of 2021, ** percent of the male population were mobile internet users in India. On the other hand, ** percent of the female Indian population had used mobile internet across the country. According to the source, female Indian population had used mobile internet less actively compared to male population in that year.
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TwitterIn 2020, the digital literacy rate in India was found to be higher among men as compared to women. The rate of searching and browsing the internet was ** percent among the male population as compared to ** percent among the female population.
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TwitterAccording to a survey conducted between 2019 and 2021 in India, about **** percent of respondents reported having diabetes. The prevalence of diabetes was slightly higher among women aged 15 to 34 years old, compared to men in the same age group.
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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Context
The dataset tabulates the population of Indian Head by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Indian Head. The dataset can be utilized to understand the population distribution of Indian Head by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Indian Head. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Indian Head.
Key observations
Largest age group (population): Male # 15-19 years (222) | Female # 35-39 years (240). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Age groups:
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.
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Indian Head Population by Gender. You can refer the same here
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the population of Indian Head Park by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Indian Head Park. The dataset can be utilized to understand the population distribution of Indian Head Park by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Indian Head Park. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Indian Head Park.
Key observations
Largest age group (population): Male # 60-64 years (181) | Female # 50-54 years (238). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Age groups:
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.
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Indian Head Park Population by Gender. You can refer the same here
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This dataset provides comprehensive census data at the district level for India. It includes detailed demographic, religious, educational, and workforce-related attributes, making it a rich resource for socio-economic analysis.
District_code: A unique numeric code for each district. State_name: Name of the state to which the district belongs. District_name: Name of the district.
Population: Total population of the district. Male: Total male population in the district. Female: Total female population in the district.
Literate: Total number of literate individuals in the district.
Workers: Total number of workers in the district. Male_Workers: Total number of male workers in the district. Female_Workers: Total number of female workers in the district. Cultivator_Workers: Number of workers engaged as cultivators. Agricultural_Workers: Number of workers engaged in agricultural labor. Household_Workers: Number of workers engaged in household industries.
Hindus: Total number of Hindus in the district. Muslims: Total number of Muslims in the district. Christians: Total number of Christians in the district. Sikhs: Total number of Sikhs in the district. Buddhists: Total number of Buddhists in the district. Jains: Total number of Jains in the district.
Secondary_Education: Number of individuals with secondary education. Higher_Education: Number of individuals with higher education qualifications. Graduate_Education: Number of individuals with graduate-level education.
Age_Group_0_29: Population in the age group 0–29 years. Age_Group_30_49: Population in the age group 30–49 years. Age_Group_50: Population aged 50 years and above.
Number of Districts: 640 Number of Columns: 25 Non-null Values: All columns are complete with no missing data. Detailed breakdown of population by gender, age group, literacy levels, and workforce distribution. Religious composition and education statistics are also included for each district.
Data Analysis and Visualization:
Explore patterns in population distribution, literacy rates, workforce composition, and religious demographics. Machine Learning Applications:
Build predictive models to classify districts or forecast demographic trends. Social Research:
Investigate correlations between education levels, workforce participation, and religion. Policy Planning:
Help policymakers target specific demographics or regions for intervention. Educational Insights:
Analyze the impact of education levels on workforce participation or literacy.
Total Rows: 640 Total Columns: 25 This dataset provides a unique opportunity to understand India's socio-economic and demographic composition at a granular district level.
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TwitterThis statistic depicts the age distribution of India from 2013 to 2023. In 2023, about 25.06 percent of the Indian population fell into the 0-14 year category, 68.02 percent into the 15-64 age group and 6.92 percent were over 65 years of age. Age distribution in India India is one of the largest countries in the world and its population is constantly increasing. India’s society is categorized into a hierarchically organized caste system, encompassing certain rights and values for each caste. Indians are born into a caste, and those belonging to a lower echelon often face discrimination and hardship. The median age (which means that one half of the population is younger and the other one is older) of India’s population has been increasing constantly after a slump in the 1970s, and is expected to increase further over the next few years. However, in international comparison, it is fairly low; in other countries the average inhabitant is about 20 years older. But India seems to be on the rise, not only is it a member of the BRIC states – an association of emerging economies, the other members being Brazil, Russia and China –, life expectancy of Indians has also increased significantly over the past decade, which is an indicator of access to better health care and nutrition. Gender equality is still non-existant in India, even though most Indians believe that the quality of life is about equal for men and women in their country. India is patriarchal and women still often face forced marriages, domestic violence, dowry killings or rape. As of late, India has come to be considered one of the least safe places for women worldwide. Additionally, infanticide and selective abortion of female fetuses attribute to the inequality of women in India. It is believed that this has led to the fact that the vast majority of Indian children aged 0 to 6 years are male.
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Sex Ratio at Birth: Female per 1000 Male: Kerala data was reported at 974.000 NA in 2020. This records an increase from the previous number of 968.000 NA for 2019. Sex Ratio at Birth: Female per 1000 Male: Kerala data is updated yearly, averaging 966.000 NA from Dec 2006 (Median) to 2020, with 15 observations. The data reached an all-time high of 974.000 NA in 2020 and a record low of 922.000 NA in 2006. Sex Ratio at Birth: Female per 1000 Male: Kerala data remains active status in CEIC and is reported by Office of the Registrar General & Census Commissioner, India. The data is categorized under India Premium Database’s Demographic – Table IN.GAJ001: Memo Items: Sex Ratio at Birth.
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the population of Indian Village by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Indian Village. The dataset can be utilized to understand the population distribution of Indian Village by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Indian Village. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Indian Village.
Key observations
Largest age group (population): Male # 75-79 years (10) | Female # 10-14 years (11). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Age groups:
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.
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Indian Village Population by Gender. You can refer the same here