High-Value Datasets for Research

The Agricultural Marketing Information Network (AGMARKNET) dataset provides daily price and arrival information for more than 300 different commodities and over 1500 varieties of agricultural produce from wholesale markets across India. This comprehensive dataset is collected from Agricultural Produce Market Committees (APMCs) and covers 4549 markets as of January 16, 2025.

The data is uploaded to the AGMARKNET portal, which provides easy access to commodity-wise, variety-wise daily prices and arrivals information. This information can be used to analyze the dynamics of agricultural markets, identify patterns and trends, and inform policymaking decisions. The dataset is a valuable resource for researchers, policymakers, and market participants who need to understand the challenges facing India’s agricultural sector, which plays a vital role in the country’s economy and food security.

The Banking Outlet section of the Reserve Bank of India’s Database on Indian Economy (DBIE) provides comprehensive data on the distribution and reach of banking services across India. It includes the location (latitude and longitude) of 1280386 banking outlets, along with associated information such as bank name, bank type (Branch, CSP, Office, Business Correspondent, Digital Banking Unit [DBU], NAIO), bank group (e.g., foreign, public, private, payment banks, regional, local), their IFSC codes, date of opening, population group (metropolitan, urban, rural, semi-urban) associated with the outlet, and whether the outlet is a domestic or overseas branch. This dataset supports analyses of financial inclusion, accessibility, and the expansion of banking infrastructure.

Coal Stocks data is taken from thermal power stations across India. The data is collected daily. It contains coal stock data by state, sector, and individual power station. The data field includes mode of transport, capacity, normative stocks, actual stocks, receipt, consumption, plant load factor, the criticalness of the plant, reason for critical etc., for each power station.

The dataset provides information on the daily sales of different types of fertilizers by retail outlets in India. This dataset is valuable for farmers, policymakers, researchers, and other stakeholders in the agriculture sector. Farmers can use the information to plan their fertilizer purchases and ensure that they have access to the fertilizers they need. Policymakers can use the data to monitor the supply and demand of fertilizers in different regions of the country and make informed decisions on fertilizer subsidy policies. Researchers can use the data to study the fertilizer market and identify trends and patterns in fertilizer sales.

Power Generation data is taken from nuclear, thermal and hydro power stations across india. The data is collected on daily basis. It contains generation data by state, sector, power station type, individual power station and unit level. The data field includes installed capacity, day’s power generaiton target, actual generation etc. for each power station.

Dataset Summary

The “Exports and Imports of India” dataset provides a comprehensive view of trade exports and imports of India across the globe. This dataset covers the periodical monthly data of exports in terms of value in both USD and INR and also in terms of quantity, and commodity types, categorized at the 8-digit HS code level. Each record provides the date, target country, type of product (both in terms of HS code and the commodity name), the value of the commodity, and the quantity of the commodity being exported.

The Port Level Import-Export Dataset provides comprehensive monthly data on imports and exports at the principal commodity level, recorded across various ports in India. It includes detailed information on volume, value (in USD and INR), and commodity types, categorized at the 2-digit HS code level. This dataset is a crucial resource for analyzing trade patterns, regional trade performance, and economic activity. It is particularly valuable for economists, policymakers, trade analysts, and researchers studying international trade, economic development, and market trends.

The Groundwater Level dataset, sourced from the Ministry of Jal Shakti, offers a comprehensive view of groundwater levels across India. It includes manually collected data from monitoring wells, high-frequency telemetric readings, and long-term records observation wells dating back to 1969. The datasets enable spatial, temporal, and trend analysis of groundwater fluctuations, supporting research on aquifer health, water availability, and policy decisions for sustainable water management.

The Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA) dataset provides detailed information on the implementation of the MGNREGA program in India. The MGNREGA program is a flagship social welfare program of the Indian government that guarantees 100 days of employment to every rural household in the country, with a special focus on the poorest and most marginalized communities. The dataset includes information on the number of households and individuals who have benefited from the program, the amount of funds disbursed, and the types of work undertaken by program beneficiaries. The dataset is organized according to various dimensions, such as state, district, and financial year, making it easy for users to filter and analyze the data according to their specific needs. The dataset is relevant to a wide range of stakeholders, including government officials, social scientists, policy think tanks, media houses, and newsrooms. The data is collected and maintained by the Ministry of Rural Development, Government of India, and is available for download on the MGNREGA website. The dataset is a valuable resource for researchers, policymakers, and journalists interested in issues related to rural employment, poverty reduction, social inclusion, and sustainable development in India.

The Mission Antyodaya dataset offers an extensive overview of village-level infrastructure, socio-economic indicators, and resource availability across India. This comprehensive dataset, collected under the Mission Antyodaya initiative, aims to uplift the most underprivileged rural communities by providing detailed insights into various aspects of rural life. This dataset serves as a crucial tool for policymakers, researchers, and development practitioners, providing a holistic view of rural development needs and achievements. By capturing diverse aspects of village life, the dataset facilitates comprehensive monitoring, planning, and implementation of initiatives aimed at improving rural infrastructure and services, thereby contributing to poverty alleviation and sustainable development in India’s rural areas.

The dataset provides an in-depth view of the Pradhan Mantri Awaas Yojana - Gramin (PMAY-G), illustrating the scheme’s progress and impact at the granular level of Gram Panchayats. It includes a multi-year record of houses sanctioned and completed, with detailed breakdowns by social categories to facilitate nuanced policy assessment and socio-economic analyses. The data highlights geographical variances and temporal trends, serving as an invaluable resource for policymakers, social researchers, and the general public interested in the effectiveness and inclusivity of rural housing developments under government schemes.

: The dataset provides comprehensive financial and physical progress information for all road projects that are being implemented under the Pradhan Mantri Gram Sadak Yojana (PMSGY) in India. PMSGY is a government-led initiative aimed at connecting all unconnected habitations in rural areas with all-weather roads, which is critical to the socio-economic development of rural India. The dataset includes information such as the total cost of the project, the amount of funds allocated, the expenditure incurred so far, the length of the road constructed, the percentage of the road completed, and the quality of the construction work. This information can be used to monitor the progress of each project and to identify any areas where improvements are needed.

This dataset provides an extensive and nuanced profile of Self-Help Groups (SHGs) across diverse geographic and socio-economic contexts. It includes detailed information on the SHG’s location, specifying the state, district, block, Gram Panchayat, and village, alongside a unique SHG identifier and its name. Key administrative details such as the date of formation, type of SHG, promoting entity, and banking information—including the bank name, branch, and account opening date—are also recorded. The dataset meticulously documents membership demographics, including total membership counts, gender distribution, and classifications by social categories such as Scheduled Caste, Scheduled Tribe, Other Backward Classes, and Other Social Categories. Additionally, it captures data on members with disabilities, both self-disabled and those with disabled family members, and provides insights into religious affiliations (Hindu, Christian, Muslim, Sikh, Buddhist, Jain, Parsi) and economic status, distinguishing between Above Poverty Line (APL), Below Poverty Line (BPL), and Poorest of the Poor under the PIP category.

The Unified District Information System for Education (UDISE) is a comprehensive database of schools in India, encompassing over 1.5 million schools, 9.6 million teachers, and 264 million children. Developed by the Government of India under the Ministry of Education, UDISE serves as a vital management information system that systematically collects, collates, and disseminates data on various aspects of school education. It captures detailed information on school infrastructure, teacher qualifications, student enrollment, and other key educational parameters. Data is collected bi-annually from pre-primary to higher secondary levels across all states and union territories, ensuring a robust and up-to-date overview of the education sector.

The “VAHAN Vehicle Registrations” dataset provides comprehensive data on vehicle registrations across India, offering insights into various aspects such as vehicle norms, manufacturers, fuel types, categories, and classes. This dataset includes key variables like the date of registration, state names and codes, Regional Transport Office (RTO) names and codes, vehicle manufacturers, fuel types (e.g., petrol, diesel, electric), vehicle categories (e.g., two-wheeler, four-wheeler), and vehicle classes. Additionally, it categorizes data by specific norms, vehicle types, and other criteria, detailing the number of registrations for each category. This resource is invaluable for policymakers, transportation authorities, analysts, and the automotive industry, enabling them to monitor and understand trends in vehicle registrations, compliance with regulations, and the environmental impact of fuel usage across different regions and RTOs in India.

NOTE: Vehicle registration data for Telangana is not available in the VAHAN database, as the state does not subscribe to VAHAN.