Facebook
TwitterBy Inder Sethi [source]
This comprehensive District Information System for Education (DISE) dataset collects district-level educational statistics in India and provides the most up-to-date data on the nation's schools. The project tracks and compiles data on primary and upper primary school students, teachers, institutions, infrastructures and more from all districts in India. It has drastically reduced the time lag between data collection to analysis - from seven to eight years down to only a few months at both district and state levels. DISE is fully supported by the Ministry of Human Resource Development (MHRD) as well as UNICEF so precise regional insights are available regarding Indian education standards. With this institutionalized flow of raw data being collected, verified at Block Education Offices/Coordinators then computerized at a District level before eventually being aggregated into State level analysis – it’s easier than ever before to understand where educational improvements need to be made. From tracking key performance indicators amongst students across all ages right through to measuring access teacher resources - this DISE dataset serves as an invaluable resource towards unlocking potential within the Indian learning system!
For more datasets, click here.
- 🚨 Your notebook can be here! 🚨!
Guide: How to Use the Indian District Level School Data 2015-16
Familiarize yourself with the features of this data set. The dataset consists of five columns which provides an overview at district level educational statistics in India for the year 2015-16. Each row contains individual district-level data with corresponding educational information and statistics like Total Number of Schools, Number of Girls' Schools, Enrolment and more for each district in India during that year.
Understand what kind of analysis can be done using this dataset once imported into a statistical software program or spreadsheet program such as Microsoft Excel or Google Sheets. You can use this dataset to analyze many different aspects related to education in India at a district level; including total number of schools, number and percent girls enrolled, teacher qualifications and more across districts throughout all states in India during the year 2015-16 period covered by this data set.
Pull up a visual representation of your data within a statistical program like SPSS or perhaps one online such as Tableau Public, depending on your preference and needs for analysis purposes - either way it is necessary to have these setup beforehand before attempting to import any given subset into them; click upload file option within them (or any other appropriate action), select all files in your local machine directory where you saved our downloaded csv file “report card” from kaggle above – then just wait until it’s completely uploaded after selecting open/import/apply/etc…and if no errors about encoding appear then begin your desired data mining experience (visualization & analytical techniques).
Once inside your preferred visualization environment, try out different methods for analyzing individual rows which correspond directly onto specific districts located inside this geographic territory that are meant by our target sheet observations mentioned prior – refer back often if lost & take time understanding what any given county contributes when computer processing their respective responses accordingly without overlooking any particular variables taken into account unlike secondary “missing values” under consideration also..
Then define relationships between similar items according figures gathered - notice patterns found among these locations while focusing attention isolation instead – graphic qualities captured midst these demographics we choose visualize key representing intent anyways… therefor aim transform knowledge through effective strategy meant enable more meaningful representation ideas presented starting place develops further details follow courtesy
- Analyzing literacy rate and measure the educational advancement of different districts in India.
- Tracking the progress of various Governmental programs like Sarva Shiksha Abhiyan that focus on improving access to education for children across districts.
- Predicting trends in the quality of school resources, educational infrastructure and student performance to guide district-level decision making processes for improved education outcomes
Facebook
Twitterhttps://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/
The Dataset covers number of Teachers available at the various stages of schooling in the Indian education system, which generally follow a progression from primary to secondary and finally to higher secondary education. Data is captured at country level, State level and at the district level geographies.
Facebook
TwitterAs of 2021, India recorded a higher nationwide share of men with at least 10 years of schooling than that of women. Around half of the male population age between 15 and 49 years stayed in school for at least 10 years, compared to only ** percent of their female counterparts. The gender education gap also remained evident in rural India, with only *** out of three women in this region receiving at least 10 years of schooling.
Facebook
TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
India Educational Attainment: At Least Master's or Equivalent: Population 25+ Years: % Cumulative data was reported at 3.110 % in 2023. This records a decrease from the previous number of 3.160 % for 2022. India Educational Attainment: At Least Master's or Equivalent: Population 25+ Years: % Cumulative data is updated yearly, averaging 3.470 % from Dec 2018 (Median) to 2023, with 4 observations. The data reached an all-time high of 3.470 % in 2020 and a record low of 2.390 % in 2018. India Educational Attainment: At Least Master's or Equivalent: Population 25+ Years: % Cumulative data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s India – Table IN.World Bank.WDI: Social: Education Statistics. The percentage of population ages 25 and over that attained or completed Master's or equivalent.;Data API, UN Educational, Scientific and Cultural Organization (UNESCO), uri: https://databrowser.uis.unesco.org/resources, note: The data are obtained through the UIS API. Detailed documentation is available at: https://api.uis.unesco.org/api/public/documentation/, publisher: UNESCO Institute for Statistics (UIS), type: Bulk file (csv), date accessed: 2025-09-22, date published: 2025-09;;
Facebook
TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Structured JSON datasets for India's education system: enrollment trends, learning outcomes, pupil-teacher ratios, school infrastructure, and education spending. Combines UDISE+ 2023-24, ASER 2024, and World Bank data.
Facebook
TwitterIn the financial year 2022, the number of female students enrolled in higher education was over ** million across India. This was an increase from the previous year's values but the enrollments were still lower than male students in that year.
Facebook
TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
India Educational Attainment: Doctoral or Equivalent: Population 25+ Years: % Cumulative data was reported at 3.487 % in 2023. This records an increase from the previous number of 3.162 % for 2022. India Educational Attainment: Doctoral or Equivalent: Population 25+ Years: % Cumulative data is updated yearly, averaging 3.162 % from Dec 2010 (Median) to 2023, with 5 observations. The data reached an all-time high of 3.487 % in 2023 and a record low of 2.050 % in 2010. India Educational Attainment: Doctoral or Equivalent: Population 25+ Years: % Cumulative data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s India – Table IN.World Bank.WDI: Social: Education Statistics. The percentage of population ages 25 and over that attained or completed Doctoral or equivalent.;UNESCO Institute for Statistics (UIS). UIS.Stat Bulk Data Download Service. Accessed April 5, 2025. https://apiportal.uis.unesco.org/bdds.;;
Facebook
Twitterhttps://dataful.in/terms-and-conditionshttps://dataful.in/terms-and-conditions
The data shows the year-wise number of institutions and schools for higher education and school education for different levels of education.
Note:
1. Data for Higher Education is till 2021-22 only.
2. No. of Colleges (2000-01 to 2009-10) includes stand alone Institutions like Polytechnics.
3. Total of all schools includes schools from Class I to Class XII for General Education Only (Pre-Primary and other Technical/Vocational Schools not included).
4. Stand Alone Institutions includes: Polytechnics, PGDM, Nursing, Teacher Training and Institutes under Ministries.
5. Data for universities and colleges only till 2020-21.
6. In a few states such as Odisha higher secondary is part of higher education which may not have been covered under U-DISE.
Facebook
TwitterOut of over ** thousand higher education institutions in India, there were ***** universities in 2022 listed on AISHE portal that are empowered to award degrees. Colleges are either affiliated or recognized with universities, while stand-alone institutions provide diploma certification rather than degrees.
Facebook
TwitterComprehensive school education data for India covering 14,71,473 schools, 24.7 Cr students across all 36 states and UTs.
Facebook
TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
India Educational Attainment: At Least Master's or Equivalent: Population 25+ Years: % Cumulative: Male data was reported at 3.390 % in 2023. This records a decrease from the previous number of 3.500 % for 2022. India Educational Attainment: At Least Master's or Equivalent: Population 25+ Years: % Cumulative: Male data is updated yearly, averaging 3.840 % from Dec 2018 (Median) to 2023, with 4 observations. The data reached an all-time high of 3.840 % in 2020 and a record low of 2.810 % in 2018. India Educational Attainment: At Least Master's or Equivalent: Population 25+ Years: % Cumulative: Male data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s India – Table IN.World Bank.WDI: Social: Education Statistics. The percentage of population ages 25 and over that attained or completed Master's or equivalent.;Data API, UN Educational, Scientific and Cultural Organization (UNESCO), uri: https://databrowser.uis.unesco.org/resources, note: The data are obtained through the UIS API. Detailed documentation is available at: https://api.uis.unesco.org/api/public/documentation/, publisher: UNESCO Institute for Statistics (UIS), type: Bulk file (csv), date accessed: 2025-09-22, date published: 2025-09;;
Facebook
TwitterThe Ministry of Human Resource Development (MHRD) initiated an All India Survey on Higher Education (AISHE) to build a robust database and to assess the correct picture of higher Education in the country. The main objectives of the survey was to (1) - identify & capture all the institutions of higher learning in the country, (2) - Collect the data from all the higher education institutions on various aspects of higher education.
Please visit data.gov.in and/or contact Dr N Saravana Kumar.
Methodology
Data is being collected annually since 2011 on the following broad items
%3C!-- --%3E
Data is collected by inviting institutions of higher education to upload information. Around 900 universities, 40.000 colleges and 10.00 stand alone institutions are invited to respond annually (all institutions of higher education in India).
Facebook
TwitterAbout the Dataset This dataset provides information on student enrolment by age and class for schools across India. The data is sourced from UDISE+ (Unified District Information System for Education Plus), a national platform for collecting school-level data.
Key Features:
Covers enrolment from Class I to Class XII
Includes age-wise student distribution
Data from both recognised and unrecognised schools
Useful for educational research, policy-making, and visualization
Source: UDISE+ (United District Information System for Education Plus), Ministry of Education, Government of India
Possible Use Cases:
Age-wise enrolment trend analysis
Dropout rate estimation
Gender and class-wise comparison
Educational planning and policy modelling
Data visualization and machine learning projects
Facebook
TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset provides the latest Education Inflation rate of India, as published by the Ministry of Statistics & Programme Implementation, along with historical trends.
Facebook
TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
School enrollment, secondary, female (% gross) in India was reported at 78.72 % in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. India - School enrollment, secondary, female (% gross) - actual values, historical data, forecasts and projections were sourced from the World Bank on March of 2026.
Facebook
TwitterIndia's performance in the Sustainable Development Goal indicator for quality of education improved in the ratings for 2024. Although the country improved the SDG targets for net primary enrollment rate in 2023, it lagged in lower secondary completion with a value of over ** percent as of 2022.
Facebook
TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Number of Students: Higher Education: ytd: India: South Australia data was reported at 8,556.000 Person in Oct 2025. This records an increase from the previous number of 8,481.000 Person for Sep 2025. Number of Students: Higher Education: ytd: India: South Australia data is updated monthly, averaging 797.000 Person from Jan 2002 (Median) to Oct 2025, with 286 observations. The data reached an all-time high of 8,556.000 Person in Oct 2025 and a record low of 93.000 Person in Jan 2002. Number of Students: Higher Education: ytd: India: South Australia data remains active status in CEIC and is reported by Department of Education. The data is categorized under Global Database’s Australia – Table AU.G: Education Statistics: Number of Enrolments.
Facebook
TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Enrolment in tertiary education, all programmes, female (number) in India was reported at 17493243 Persons in 2019, according to the World Bank collection of development indicators, compiled from officially recognized sources. India - Enrolment in tertiary education, all programmes, female - actual values, historical data, forecasts and projections were sourced from the World Bank on March of 2026.
Facebook
TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Primary education, teachers in India was reported at 5021474 in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. India - Primary education, teachers - actual values, historical data, forecasts and projections were sourced from the World Bank on March of 2026.
Facebook
TwitterDuring the financial year 2025, India had over ***** million school students enrolled in secondary schools. The highest number of students were enrolled in preparatory schools and the lowest in foundational school.
Facebook
TwitterBy Inder Sethi [source]
This comprehensive District Information System for Education (DISE) dataset collects district-level educational statistics in India and provides the most up-to-date data on the nation's schools. The project tracks and compiles data on primary and upper primary school students, teachers, institutions, infrastructures and more from all districts in India. It has drastically reduced the time lag between data collection to analysis - from seven to eight years down to only a few months at both district and state levels. DISE is fully supported by the Ministry of Human Resource Development (MHRD) as well as UNICEF so precise regional insights are available regarding Indian education standards. With this institutionalized flow of raw data being collected, verified at Block Education Offices/Coordinators then computerized at a District level before eventually being aggregated into State level analysis – it’s easier than ever before to understand where educational improvements need to be made. From tracking key performance indicators amongst students across all ages right through to measuring access teacher resources - this DISE dataset serves as an invaluable resource towards unlocking potential within the Indian learning system!
For more datasets, click here.
- 🚨 Your notebook can be here! 🚨!
Guide: How to Use the Indian District Level School Data 2015-16
Familiarize yourself with the features of this data set. The dataset consists of five columns which provides an overview at district level educational statistics in India for the year 2015-16. Each row contains individual district-level data with corresponding educational information and statistics like Total Number of Schools, Number of Girls' Schools, Enrolment and more for each district in India during that year.
Understand what kind of analysis can be done using this dataset once imported into a statistical software program or spreadsheet program such as Microsoft Excel or Google Sheets. You can use this dataset to analyze many different aspects related to education in India at a district level; including total number of schools, number and percent girls enrolled, teacher qualifications and more across districts throughout all states in India during the year 2015-16 period covered by this data set.
Pull up a visual representation of your data within a statistical program like SPSS or perhaps one online such as Tableau Public, depending on your preference and needs for analysis purposes - either way it is necessary to have these setup beforehand before attempting to import any given subset into them; click upload file option within them (or any other appropriate action), select all files in your local machine directory where you saved our downloaded csv file “report card” from kaggle above – then just wait until it’s completely uploaded after selecting open/import/apply/etc…and if no errors about encoding appear then begin your desired data mining experience (visualization & analytical techniques).
Once inside your preferred visualization environment, try out different methods for analyzing individual rows which correspond directly onto specific districts located inside this geographic territory that are meant by our target sheet observations mentioned prior – refer back often if lost & take time understanding what any given county contributes when computer processing their respective responses accordingly without overlooking any particular variables taken into account unlike secondary “missing values” under consideration also..
Then define relationships between similar items according figures gathered - notice patterns found among these locations while focusing attention isolation instead – graphic qualities captured midst these demographics we choose visualize key representing intent anyways… therefor aim transform knowledge through effective strategy meant enable more meaningful representation ideas presented starting place develops further details follow courtesy
- Analyzing literacy rate and measure the educational advancement of different districts in India.
- Tracking the progress of various Governmental programs like Sarva Shiksha Abhiyan that focus on improving access to education for children across districts.
- Predicting trends in the quality of school resources, educational infrastructure and student performance to guide district-level decision making processes for improved education outcomes