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Collections - Dataful
Collections
Related datasets bundled by topic, one place for a whole line of questioning.
14 of 501 collections
Collection
Trends in Performance Grading Index (PGI) by Ministry of Education
This collection contains details on the key trends and the performance of states in the Performance Grading Index published by the Ministry of Education. This includes the performance of states over the last few years, the cumulative number of states in each level of ranking, and domain-specific changes for states over the last few years. read less
7 datasets
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Collection
Fiscal Health Index
This collection contains the year-wise ranking of states in the Fiscal Health Index compiled by NITI Aayog. It also has the dataset on the average score in different sub-indices for various states for two time-periods: Average from 2014-15 to 2018-19 and Average from 2014-15 to 2021-22.
2 datasets
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Collection
Comprehensive Environmental Pollution Index (CEPI)
This Collection contains Year, State and Industrial Area-wie Comprehensive Environmental Pollution Index (CEPI) along-with status of environment of Industrial Areas/Clusters Comprehensive Environmental Pollution Index (CEPI) which ranges between 0-100 and captures overall quality of the environment covering ambient air, surface water and land by following algorithm of pollution sources, pathways and receptors. CEPI aims to measure the environmental performance of industrial area/clusters. The industrial clusters having aggregated CEPI score of 70 and above are considered as critically polluted areas (CPAs), whereas the areas having CEPI score between 60-70 are considered as severely polluted areas (SPAs) and areas having CEPI score less than 60 are considered as other polluted areas (OPAs).
2 datasets
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Collection
National Multidimensional Poverty Index
The National Multidimensional Poverty Index is key in assessing advancements towards target 1.2 of the Sustainable Development Goals (SDGs) which aims at reducing “at least by half the proportion of men, women and children of all ages living in poverty in all its dimensions” by 2030. NITI Aayog’s Multidimensional Poverty Index (MPI) is based on three dimensions — health, education, and standard of living — with each having a weightage of one-third in the index. These dimensions are further based on 12 segments — nutrition, child and adolescent mortality, maternal health, years of schooling, school attendance, cooking fuel, sanitation, drinking water, electricity, housing, assets, and bank accounts. There are two indices used for arriving at the MPI Value. MPI is the product of the following two indices. Headcount ratio which indicates how many are poor and the intensity of poverty which indicates how poor are the poor. The values are based on the NFHS survey reports.
2 datasets
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Collection
All India and State-wise Consumer Price Index (CPI) Data
This collection contains datasets on year, month, state, sector (rural and urban) and item wise indices and inflation rates for Consumer Price Index (CPI)
37 datasets
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Collection
Train Safety
This collection contains the details about the category wise train accidents, train safety index, and the automatic signalling in route kilometers
3 datasets
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Collection
Inflation Indicators (CPI and WPI)
This Collection contains datasets related to All India level, Month, Commodity and Base Year-wise Consumer Price Index for Industrial Workers, Agricultural Labourers and Rural Labourers, Commodity-wise Consumer Price Index - Rural, Urban, Combined (All India) and Wholesale Price Index (WPI)
4 datasets
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Collection
Statistics of Indian Railways
This Collection contains datasets related to railway personnel, train accidents, revenue, expenditure, punctuality index, compensation paid, traffic etc
19 datasets
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Collection
Economic Survey of India
The collection contains year- and state-wise datasets with historically compiled multiple indicators data related to economy, food security, and others. The specifics of data contained include capital formation, savings and changes in stock of GDP, rate of growth of GVA among sectors such as different types of industries, the production, consumption and availability of food grains and other food items, the index of production and yield of different types of agriculture crops, etc.
17 datasets
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