This data contains all the essential data in the form of % with respect to rural and urban Indian states . This dataset is highly accurate as this is taken from the Indian govt. it is updated till 2021 for all states and union territories. source of data is data.gov.in titled - ******All India and State/UT-wise Factsheets of National Family Health Survey******

it is advised to you pls search the data keywords you need by using (Ctrl+f) , as it will help to avoid time wastage. States/UTs

Different columns it contains are Area

Number of Households surveyed Number of Women age 15-49 years interviewed Number of Men age 15-54 years interviewed

Female population age 6 years and above who ever attended school (%)

Population below age 15 years (%)

Sex ratio of the total population (females per 1,000 males)

Sex ratio at birth for children born in the last five years (females per 1,000 males)

Children under age 5 years whose birth was registered with the civil authority (%)

Deaths in the last 3 years registered with the civil authority (%)

Population living in households with electricity (%)

Population living in households with an improved drinking-water source1 (%)

Population living in households that use an improved sanitation facility2 (%)

Households using clean fuel for cooking3 (%) Households using iodized salt (%)

Households with any usual member covered under a health insurance/financing scheme (%)

Children age 5 years who attended pre-primary school during the school year 2019-20 (%)

Women (age 15-49) who are literate4 (%)

Men (age 15-49) who are literate4 (%)

Women (age 15-49) with 10 or more years of schooling (%)

Men (age 15-49) with 10 or more years of schooling (%)

Women (age 15-49) who have ever used the internet (%)

Men (age 15-49) who have ever used the internet (%)

Women age 20-24 years married before age 18 years (%)

Men age 25-29 years married before age 21 years (%)

Total Fertility Rate (number of children per woman) Women age 15-19 years who were already mothers or pregnant at the time of the survey (%)

Adolescent fertility rate for women age 15-19 years5 Neonatal mortality rate (per 1000 live births)

Infant mortality rate (per 1000 live births) Under-five mortality rate (per 1000 live births)

Current Use of Family Planning Methods (Currently Married Women Age 15-49 years) - Any method6 (%)

Current Use of Family Planning Methods (Currently Married Women Age 15-49 years) - Any modern method6 (%)

Current Use of Family Planning Methods (Currently Married Women Age 15-49 years) - Female sterilization (%)

Current Use of Family Planning Methods (Currently Married Women Age 15-49 years) - Male sterilization (%)

Current Use of Family Planning Methods (Currently Married Women Age 15-49 years) - IUD/PPIUD (%)

Current Use of Family Planning Methods (Currently Married Women Age 15-49 years) - Pill (%)  

Current Use of Family Planning Methods (Currently Married Women Age 15-49 years) - Condom (%)

Current Use of Family Planning Methods (Currently Married Women Age 15-49 years) - Injectables (%)

Total Unmet need for Family Planning (Currently Married Women Age 15-49 years)7 (%)

Unmet need for spacing (Currently Married Women Age 15-49 years)7 (%)

Health worker ever talked to female non-users about family planning (%)

Current users ever told about side effects of current method of family planning8 (%)

Mothers who had an antenatal check-up in the first trimester (for last birth in the 5 years before the survey) (%)

Mothers who had at least 4 antenatal care visits (for last birth in the 5 years before the survey) (%)

Mothers whose last birth was protected against neonatal tetanus (for last birth in the 5 years before the survey)9 (%)

Mothers who consumed iron folic acid for 100 days or more when they were pregnant (for last birth in the 5 years before the survey) (%)

Mothers who consumed iron folic acid for 180 days or more when they were pregnant (for last birth in the 5 years before the survey} (%)

Registered pregnancies for which the mother received a Mother and Child Protection (MCP) card (for last birth in the 5 years before the survey) (%)

Mothers who received postnatal care from a doctor/nurse/LHV/ANM/midwife/other health personnel within 2 days of delivery (for last birth in the 5 years before the survey) (%)

Average out-of-pocket expenditure per delivery in a public health facility (for last birth in the 5 years before the survey) (Rs.)

Children born at home who were taken to a health facility for a check-up within 24 hours of birth (for last birth in the 5 years before the survey} (%)

Children who received postnatal care from a doctor/nurse/LHV/ANM/midwife/ other health personnel within 2 days of delivery (for last birth in the 5 years before the survey) (%)

Institutional births (in the 5...

Agriculture was the major source of employment in rural India accounting for almost ** percent of the workforce in 2024. Meanwhile, the construction sector was the major employer within non-agricultural activities during the same period.

Rural population growth (annual %) in India was reported at 0.09713 % in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. India - Rural population growth (annual %) - actual values, historical data, forecasts and projections were sourced from the World Bank on November of 2025.

This package contains Baseline Household and Healthcare Provider data for the study "Telehealth in Rural India" by Erika Deserranno, Andrea Guariso and Amanda Dahlstrand. The study was conducted in 400 villages of the Saran district of Bihar.

The statistic represents the literacy rate in rural areas in India from 2003 through 2011, by gender. In 2007, the literacy rate among females living in rural regions of India was around ** percent.

One of the metrics used by banks to check credit worthiness of an individual is credit score, but for people who have never taken a loan in the past don't have a credit score in first place, and it becomes difficult for banks to lend them.

The "Credit/Loan Dataset - Rural India" is a collection of data points of individuals without a prior credit score and the loan amount sanctioned to them.

The dataset can be used to train models to check the eligible loan amount.

Challenges: 1. The dataset is pretty raw and needs a lot of EDA/FE/FS 2. Some features have > 100 unique values

Abstract

An effective policy response to the economic impacts of the COVID-19 pandemic requires an enormous range of data to inform the design and response of programs. Public health measures require data on the spread of the disease, beliefs in the population, and capacity of the health system. Relief efforts depend on an understanding of hardships being faced by various segments of the population. Food policy requires measurement of agricultural production and hunger. In such a rapidly evolving pandemic, these data must be collected at a high frequency. Given the unexpected nature of the shock and urgency with which a response was required, Indian policymakers needed to formulate policies affecting India's 1.4 billion people, without the detailed evidence required to construct effective programs. To help overcome this evidence gap, researchers from the World Bank, in collaboration with IDinsight, the Development Data Lab, and John Hopkins University sought to produce rigorous and responsive data for policymakers across six states in India: Jharkhand, Rajasthan, Uttar Pradesh, Andhra Pradesh, Bihar, and Madhya Pradesh.

Geographic coverage

Jharkhand, Rajasthan, Uttar Pradesh, Andhra Pradesh, Bihar, and Madhya Pradesh

Analysis unit

Households

Kind of data

Sample survey data [ssd]

Sampling procedure

The samples for these surveys were drawn from surveys and impact evaluations previously conducted by the World Bank, the Ministry of Rural Development, India and IDInsight. A detailed note on the sampling frames is available for download.

Sampling deviation

Details will be made available after all rounds of data collection and analysis is complete.

Mode of data collection

Computer Assisted Telephone Interview [cati]

Response rate

Approximately 55%

According to the results of a survey on WhatsApp usage in rural India in 2018, it was found that about ** percent of respondents never believed information they received via the messaging app. While about ***** percent of respondents always believed the information they received on WhatsApp during the survey period.

India Vital Statistics: Natural Growth Rate: per 1000 Population data was reported at 13.500 NA in 2020. This records a decrease from the previous number of 13.800 NA for 2019. India Vital Statistics: Natural Growth Rate: per 1000 Population data is updated yearly, averaging 18.500 NA from Dec 1970 (Median) to 2020, with 51 observations. The data reached an all-time high of 22.000 NA in 1971 and a record low of 13.500 NA in 2020. India Vital Statistics: Natural Growth Rate: per 1000 Population data remains active status in CEIC and is reported by Office of the Registrar General & Census Commissioner, India. The data is categorized under Global Database’s India – Table IN.GAH001: Vital Statistics.

India Census: Population: Rural: Age: 11 data was reported at 17,851,313.000 Person in 2011. This records an increase from the previous number of 13,013,528.000 Person for 2001. India Census: Population: Rural: Age: 11 data is updated yearly, averaging 13,013,528.000 Person from Mar 1991 (Median) to 2011, with 3 observations. The data reached an all-time high of 17,851,313.000 Person in 2011 and a record low of 9,273,340.000 Person in 1991. India Census: Population: Rural: Age: 11 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.GAD003: Census: Population: by Single Age: Rural.

As per the results of a survey on WhatsApp usage in India in 2017 and 2018, it was found that there was a ten percent increase in the share of active WhatsApp users in rural India to reach around ** percent in 2018. This was about ** percent in urban areas during the survey period.

Dataset Description: Indian School Education Statistics (2021-2022)

This dataset offers a comprehensive overview of Indian School Education Statistics, covering the years 2021-2022. It provides a valuable resource for individuals embarking on their Data Science journey by consolidating various datasets from the Indian Government into a single, easily accessible source. The dataset is available in seven separate .csv files, each with its distinct focus, enabling users to explore diverse aspects of the education landscape in India.

The Seven Key Datasets Included:

1. Percentage of Schools with Drinking Water Facility (2021-22)
2. Gross Enrolment Ratio (2021-22)
3. Drop-out Rate (2021-22)
4. Percentage of Schools with Computers (2021-22)
5. Percentage of Schools with Electricity (2021-22)
6. Schools with Boys' Toilets (2021-22)
7. Schools with Girls' Toilets (2021-22)

This dataset is a treasure trove of information, offering a window into the dynamic landscape of education in India and its evolution over time. By delving into this dataset, you can unlock answers to various pressing questions and tackle pivotal issues, including:

• Identifying states with the highest dropout ratios.
• Assessing the availability of crucial amenities like drinking water and sanitation facilities for boys and girls.
• Exploring the Gross Enrolment Ratio across different educational levels.
• Monitoring shifts in enrollment trends at various stages of education.

Sourced from the Open Government Data (OGD) Platform India, this dataset not only serves as a valuable resource for beginners in their Data Science journey but also presents an array of opportunities for in-depth analysis and research within the realm of Indian education.

India Census: Population: Rural: Age: 2 data was reported at 17,065,758.000 Person in 2011. This records a decrease from the previous number of 18,734,931.000 Person for 2001. India Census: Population: Rural: Age: 2 data is updated yearly, averaging 17,728,730.000 Person from Mar 1991 (Median) to 2011, with 3 observations. The data reached an all-time high of 18,734,931.000 Person in 2001 and a record low of 17,065,758.000 Person in 2011. India Census: Population: Rural: Age: 2 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.GAD003: Census: Population: by Single Age: Rural.

With Canada’s support, SOPAR-Bala Vikasa worked to keep children in rural India in school by enhancing COVID-19 safety measures.

According to a survey conducted in 2023 among rural households in India, nearly 85 percent of parents with some level of education allocated specific study time for their children. In contrast, only about 69 percent of illiterate parents did the same for their children at home.

The dataset has Industry-wise IEM part-A consolidated data on Investment and Employment in India from August 1991 to till last month.

The dataset helps in identifying the investment and employment patterns in India, at macro level.

Kagglers using this dataset can also explore another similar dataset, which has state-wise data with the same timeline as in the current dataset. Link to the dataset is here.

By exploring both the datasets, one can understand the most latest state-wise as well as industry-wise investment and employment scenario in India.

Source: data.gov.in

India Census: Population: Rural: Male: Age: 4 data was reported at 9,092,251.000 Person in 2011. This records a decrease from the previous number of 9,830,219.000 Person for 2001. India Census: Population: Rural: Male: Age: 4 data is updated yearly, averaging 9,181,290.000 Person from Mar 1991 (Median) to 2011, with 3 observations. The data reached an all-time high of 9,830,219.000 Person in 2001 and a record low of 9,092,251.000 Person in 2011. India Census: Population: Rural: Male: Age: 4 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.GAD003: Census: Population: by Single Age: Rural.

Context

Consumer Price Indices (CPI) measure changes over time in general level of prices of goods and services that households acquire for the purpose of consumption. CPI numbers are widely used as a macroeconomic indicator of inflation, as a tool by governments and central banks for inflation targeting and for monitoring price stability, and as deflators in the national accounts. CPI is also used for indexing dearness allowance to employees for increase in prices. CPI is therefore considered as one of the most important economic indicators. For construction of CPI numbers, two requisite components are weighting diagrams (consumption patterns) and price data collected at regular intervals.

Content

The data refers to group wise all India Consumer Price Index for Rural & Urban with base year 2010.

Acknowledgements

• The dataset is published by Central Statistical Office.
• This data is sourced from India's Goverment's Open Data website: data.gov.in
• Released Under: National Data Sharing and Accessibility Policy (NDSAP)

Inspiration

This can be used for various purposes including tasks such as exploring growth/inflation in India over the time.

The dataset contains year-wise historically compiled data on the area and production of spices in India. The different types of spices covered in the dataset include vanilla, ajwan, black pepper, cardamom, cinnamon/tejpata, clove, coriander, cumin, dill/poppy/celery, fennel, fenugreek, garlic, ginger, mint (mentha), nutmeg, red chillies (dried), saffron/vanilla, tamarind, turmeric, red chillies, chillies, pepper, saffron, chilies, etc.

In 2023, 43.51 percent of the workforce in India were employed in agriculture, while the other half was almost evenly distributed among the two other sectors, industry and services. While the share of Indians working in agriculture is declining, it is still the main sector of employment. A BRIC powerhouseTogether with Brazil, Russia, and China, India makes up the four so-called BRIC countries. They are the four fastest-growing emerging countries dubbed BRIC, an acronym, by Jim O’Neill at Goldman Sachs. Being major economies themselves already, these four countries are said to be at a similar economic developmental stage -- on the verge of becoming industrialized countries -- and maybe even dominating the global economy. Together, they are already larger than the rest of the world when it comes to GDP and simple population figures. Among these four, India is ranked second across almost all key indicators, right behind China. Services on the riseWhile most of the Indian workforce is still employed in the agricultural sector, it is the services sector that generates most of the country’s GDP. In fact, when looking at GDP distribution across economic sectors, agriculture lags behind with a mere 15 percent contribution. Some of the leading services industries are telecommunications, software, textiles, and chemicals, and production only seems to increase – currently, the GDP in India is growing, as is employment.