The dataset contains year-, month-, state- and gender-wise compiled data on population of India from the year 2011 to 2036. The figures of population given for different years are the projected figures, except for the census year of 2011.

In 2022, the union territory of Delhi had the highest urban population density of over 18 thousand persons per square kilometer. While the rural population density was highest in union territory of Puducherry, followed by the state of Bihar.

The share of projected population increase in Uttar Pradesh, India from 2011 until 2036 is expected to grow by nearly ** percent. By contrast, the estimated population increase in Uttarakhand is expected to be less than *** percent during the same time period.

Why project population?
Population projections for a country are becoming increasingly important now than ever before. They are used primarily by government policy makers and planners to better understand and gauge future demand for basic services that predominantly include water, food and energy. In addition, they also support in indicating major movements that may affect economic development and in turn, employment and labour productivity. Consequently, this leads to amending policies in order to better adapt to the needs of society and to various circumstances.

Demographic projections and health interventions Demographic figures serve the foremost purpose of improving health and health related services among the population. Some of the government interventions include antenatal and neonatal care with the aim of reducing maternal and neonatal mortality and morbidity rates. In addition, it also focuses on improving immunization coverage across the country. Further, demographic estimates help in better preempting the needs of growing populations, such as the geriatric population within a country.

Dataset include statics of Indian population of male and female state wise.

what are the other fundamentals indicators would be looked at or added to this data set in the future version ?

Let me know it in comments section.

India's population demographics - total population, growth rate, age-wise and state-wise population, languages spoken, and religion.

About this dataset

Context

The dataset tabulates the Indian Shores population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Indian Shores across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of Indian Shores was 1,192, a 0.50% decrease year-by-year from 2022. Previously, in 2022, Indian Shores population was 1,198, a decline of 0.17% compared to a population of 1,200 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Indian Shores decreased by 511. In this period, the peak population was 1,777 in the year 2004. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the Indian Shores is shown in this column.
• Year on Year Change: This column displays the change in Indian Shores population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. 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 Shores Population by Year. You can refer the same here

The dataset contains Decade and State wise Urban, Rural, Total Population and Decadal Growth Rate

Note: 1. The Population figures exclude population of areas under unlawful occupation of Pakistan and China, where Census could not be taken. 2. In Arunachal Pradesh, the census was conducted for the first time in 1961. 3. Population data of Assam include Union Territory of Mizoram, which was carved out of Assam after the 1971. 4. The 1981 Census could not be held in Assam. Total Population for 1981 has been worked out by Interpolation. 5. The 1991 Census could not be held in Jammu & Kashmir. Total Population for 1991 has been worked out by Interpolation. 6. India and Manipur figures include estimated Population for those of the three sub-divisions viz., Mao Maram,Paomata and Purul of Senapati district of Manipur as census result of 2001 in these three sub-divisions were cancelled due to technical and administrative reasons

The statistic displays the main states and union territories with the highest number of people living in urban areas in India in 2011. In that year, the state of Maharashtra had the highest population with over 50 million people living in urban areas. The population density in India from 2004 to 2014 can be seen here.

The statistic gives the share of aging population in India across selected states and union territories in India in 2011. The regions with the highest share of elderly people were in the state of Kerala, with some 12.6 percent of the population living there were 60 years or older, followed by the state of Goa with 11.2 percent. The share of aging population in the whole country that year was 8.6 percent.

The data shows the year-wise and state or union territory-wise literacy and rural and urban literacy, for male, female, and total literacy, in India according to Census.

Note: 1. Literacy rate is defined as the population of literates in the population aged 7 year and above. 2. The 1991 data (Excluding Jammu & Kashmir)and 2001 data (Excludes figures of Paomata, Mao Maran and Pura sub-divisions of Senapati district of Manipur for 2001) refer to Census of India.

India population growth rate for 2023 was 0.88%, a 0.09% increase from 2022.

<ul style='margin-top:20px;'>

<li>India population growth rate for 2022 was <strong>0.79%</strong>, a <strong>0.03% decline</strong> from 2021.</li>
<li>India population growth rate for 2021 was <strong>0.82%</strong>, a <strong>0.15% decline</strong> from 2020.</li>
<li>India population growth rate for 2020 was <strong>0.97%</strong>, a <strong>0.07% decline</strong> from 2019.</li>
</ul>Annual population growth rate for year t is the exponential rate of growth of midyear population from year t-1 to t, expressed as a percentage . Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.

The projected median age of population in India, at national level, was expected to go up to more than 34 years by 2036 versus almost 25 years in 2011. At state level, Tamil Nadu reflected the highest projected median age with over 40 years in 2036 versus nearly 30 years in 2011.

The projected median age of population of a country is contingent upon several health metrics such as the fertility rate, birth rate, and mortality rate. For instance, if a country or state sees a lower fertility and mortality rate, the geriatric population is expected to increase proportionally.

According to the latest census data, Lakshadweep, the island union territory had the highest share of Muslim population in the country, where 97 percent of its population identified as followers of the Islamic faith. Jammu & Kashmir ranked second at 68 percent during the same time period. With almost all major religions being practiced throughout the country, India is known for its religious diversity. Islam makes up the highest share among minority faiths in the country.

The dataset contains the State and Year-wise Telephones per 100 population.

Note: 1)Including Public DELs, Pvt. DELs, CMPs and WLL ( Fixed & Limited) 2)Chhattisgarh, Jharkhand, NE-II, Uttarakhand, Kolkata and Chennai are included in MP, Bihar, NE- I,UP[E&W],WB and TN respectively.

India Census: Population: by Religion: Muslim: Urban data was reported at 68,740,419.000 Person in 2011. This records an increase from the previous number of 49,393,496.000 Person for 2001. India Census: Population: by Religion: Muslim: Urban data is updated yearly, averaging 59,066,957.500 Person from Mar 2001 (Median) to 2011, with 2 observations. The data reached an all-time high of 68,740,419.000 Person in 2011 and a record low of 49,393,496.000 Person in 2001. India Census: Population: by Religion: Muslim: Urban data remains active status in CEIC and is reported by Census of India. The data is categorized under India Premium Database’s Demographic – Table IN.GAE001: Census: Population: by Religion.

The statistic illustrates the leading states and union territories in India with the highest old-age dependency ratio in 2011. In that year, the state of Punjab had an old-age dependency ratio of just over 16 percent.

The Multidimensional Poverty Index (MPI) is a comprehensive measure that assesses poverty beyond income, capturing individuals’ various deprivations in areas critical to human well-being. Unlike traditional poverty metrics, which primarily focus on monetary aspects, the MPI incorporates multiple dimensions, including health, education, and living standards. Each dimension is further broken down into indicators, such as child mortality, years of schooling, access to clean water, sanitation, and adequate housing.

Population, female (% of total population) in India was reported at 48.42 % in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. India - Population, female (% of total) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

The data shows the year-wise gender ratio of population for states and union territories of India over the time period of 110 years starting from 1901 to 2011 according to the census reports.

Note: 1. For working out the gender ratio of India and Assam for 1981, interpolated figures for Assam have been used. 2. For working out the gender ratio of India and Jammu & Kashmir for 1991, interpolated figures for Jammu & Kashmir have been used. 3. The gender ratio for Arunachal Pradesh is not available for the years 1901-1951 and for Pondicherry it is not available for the years 1901, 1931 and 1941.

Per Capita Net State Domestic Product (Per Capita NSDP) measures the average economic output generated per person within a specific state or region after accounting for the depreciation of capital assets. It is calculated by dividing the Net State Domestic Product (NSDP), which represents the total value of goods and services produced within a state, by its population. Unlike Gross State Domestic Product (GSDP), which reflects the overall production without considering depreciation, NSDP provides a more accurate representation of the state's sustainable economic output. The per capita element offers insight into the average living standards and productivity of individuals within the state, making it a valuable indicator for comparing economic performance across regions and assessing the financial well-being of residents. Higher Per Capita NSDP typically indicates better economic conditions and higher living standards, though it doesn't account for income inequality or distribution within the population.