In 2023, primary school made up the majority of the school market in India in terms of education levels, at over ** percent. Higher secondary level made up the smallest share of the market during the same time 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.

The gross enrollment ratio (GER) in India for grades 1 to 5, or primary school level, was over *** percent in 2022. However, the ratios decline with successive stages of education. Higher education had the lowest GER of ** percent. The gross enrollment ratio is the number of children enrolled in an education level relative to their population.

Data from www.census.gov.in was downloaded and processed available in this link,

Used the table code :PC11_B07 which contains data regarding working population classified by industrial category, educational level and gender. From these 35 excel tables, data was extracted and transformed into required format using Excel and Power Query detailed here. Transformed it into two datasets of Urban and Rural.

There are two .csv files used here. One is Rural education data district wise and second one is Urban education data district wise.

Forecast: Education Enrolment Rate by Education Level and Education Sector in India 2024 - 2028 Discover more data with ReportLinker!

According to a 2020 survey, ** percent of Indian American respondents in the United States had obtained a postgraduate degree. Only *** percent of survey participants did not have any high school education.

India Vital Statistics: Age Specific Fertility Rate: per 1000 Female Population: Educational Level of Women: Literate: Without Any Formal Education: Age: 35-39 data was reported at 33.400 NA in 2016. This records a decrease from the previous number of 33.600 NA for 2015. India Vital Statistics: Age Specific Fertility Rate: per 1000 Female Population: Educational Level of Women: Literate: Without Any Formal Education: Age: 35-39 data is updated yearly, averaging 33.400 NA from Dec 2010 (Median) to 2016, with 7 observations. The data reached an all-time high of 37.100 NA in 2012 and a record low of 23.700 NA in 2013. India Vital Statistics: Age Specific Fertility Rate: per 1000 Female Population: Educational Level of Women: Literate: Without Any Formal Education: Age: 35-39 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.GAH008: Vital Statistics: Age Specific Fertility Rate: by Education Level of Women.

India Vital Statistics: Age Specific Fertility Rate: per 1000 Female Population: Educational Level of Women: Literate: Graduate and Above: Age: 30-34 data was reported at 96.100 NA in 2016. This records an increase from the previous number of 87.000 NA for 2015. India Vital Statistics: Age Specific Fertility Rate: per 1000 Female Population: Educational Level of Women: Literate: Graduate and Above: Age: 30-34 data is updated yearly, averaging 74.100 NA from Dec 2010 (Median) to 2016, with 7 observations. The data reached an all-time high of 96.100 NA in 2016 and a record low of 72.800 NA in 2012. India Vital Statistics: Age Specific Fertility Rate: per 1000 Female Population: Educational Level of Women: Literate: Graduate and Above: Age: 30-34 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.GAH008: Vital Statistics: Age Specific Fertility Rate: by Education Level of Women.

The dataset contains year-, region-, social-group- and gender-wise All India compiled data on per thousand distribution of scheduled caste, tribe, other backwards classes and other people by their different levels of education such as literate, non-literate, literate upto primary, primary, secondary, middle, higher secondary, graduate and above, post graduate and above levels of education. The dataset has been compiled from table nos. 8, s3.13 and statement nos. 3.13.1 and 3.12.1 of NSS 55th, 61st, 66th and 68th rounds published from the year 2000 to 2012.

India: Ratio of female to male students in tertiary level education: The latest value from 2023 is 0.98 percent, a decline from 1.03 percent in 2022. In comparison, the world average is 1.16 percent, based on data from 62 countries. Historically, the average for India from 1971 to 2023 is 0.65 percent. The minimum value, 0.29 percent, was reached in 1971 while the maximum of 1.09 percent was recorded in 2020.

Literacy in India has been increasing as more and more people receive a better education, but it is still far from all-encompassing. In 2023, the degree of literacy in India was about 77 percent, with the majority of literate Indians being men. It is estimated that the global literacy rate for people aged 15 and above is about 86 percent. How to read a literacy rateIn order to identify potential for intellectual and educational progress, the literacy rate of a country covers the level of education and skills acquired by a country’s inhabitants. Literacy is an important indicator of a country’s economic progress and the standard of living – it shows how many people have access to education. However, the standards to measure literacy cannot be universally applied. Measures to identify and define illiterate and literate inhabitants vary from country to country: In some, illiteracy is equated with no schooling at all, for example. Writings on the wallGlobally speaking, more men are able to read and write than women, and this disparity is also reflected in the literacy rate in India – with scarcity of schools and education in rural areas being one factor, and poverty another. Especially in rural areas, women and girls are often not given proper access to formal education, and even if they are, many drop out. Today, India is already being surpassed in this area by other emerging economies, like Brazil, China, and even by most other countries in the Asia-Pacific region. To catch up, India now has to offer more educational programs to its rural population, not only on how to read and write, but also on traditional gender roles and rights.

As of 2024, employees with doctorate degrees earned an average annual salary of **** million Indian rupees, the highest among other educational qualifications. Employees with high school or below high school level degree earned average salaries of just over ********* rupees in a year.

India Census Dataset

This dataset provides comprehensive census data at the district level for India. It includes detailed demographic, religious, educational, and workforce-related attributes, making it a rich resource for socio-economic analysis.

1. Columns and Descriptions

A. Basic Information

District_code: A unique numeric code for each district. State_name: Name of the state to which the district belongs. District_name: Name of the district.

B. Population Data

Population: Total population of the district. Male: Total male population in the district. Female: Total female population in the district.

C. Literacy Data

Literate: Total number of literate individuals in the district.

D. Workforce Data

Workers: Total number of workers in the district. Male_Workers: Total number of male workers in the district. Female_Workers: Total number of female workers in the district. Cultivator_Workers: Number of workers engaged as cultivators. Agricultural_Workers: Number of workers engaged in agricultural labor. Household_Workers: Number of workers engaged in household industries.

E. Religion Data

Hindus: Total number of Hindus in the district. Muslims: Total number of Muslims in the district. Christians: Total number of Christians in the district. Sikhs: Total number of Sikhs in the district. Buddhists: Total number of Buddhists in the district. Jains: Total number of Jains in the district.

F. Education Data

Secondary_Education: Number of individuals with secondary education. Higher_Education: Number of individuals with higher education qualifications. Graduate_Education: Number of individuals with graduate-level education.

G. Age Group Data

Age_Group_0_29: Population in the age group 0–29 years. Age_Group_30_49: Population in the age group 30–49 years. Age_Group_50: Population aged 50 years and above.

2. Key Highlights

Number of Districts: 640 Number of Columns: 25 Non-null Values: All columns are complete with no missing data. Detailed breakdown of population by gender, age group, literacy levels, and workforce distribution. Religious composition and education statistics are also included for each district.

3. Potential Use Cases

Data Analysis and Visualization:

Explore patterns in population distribution, literacy rates, workforce composition, and religious demographics. Machine Learning Applications:

Build predictive models to classify districts or forecast demographic trends. Social Research:

Investigate correlations between education levels, workforce participation, and religion. Policy Planning:

Help policymakers target specific demographics or regions for intervention. Educational Insights:

Analyze the impact of education levels on workforce participation or literacy.

4. Dataset Overview

Total Rows: 640 Total Columns: 25 This dataset provides a unique opportunity to understand India's socio-economic and demographic composition at a granular district level.

Actual value and historical data chart for India Labor Force With Basic Education Percent Of Total

India School Drop Out Rate: 6-11 Years Old data was reported at 19.800 % in 2013. This records a decrease from the previous number of 21.300 % for 2012. India School Drop Out Rate: 6-11 Years Old data is updated yearly, averaging 36.945 % from Sep 1960 (Median) to 2013, with 24 observations. The data reached an all-time high of 67.000 % in 1970 and a record low of 19.800 % in 2013. India School Drop Out Rate: 6-11 Years Old data remains active status in CEIC and is reported by Ministry of Education. The data is categorized under India Premium Database’s Education Sector – Table IN.EDA002: School Drop Out Rate: 6-11 Years Old.

During the financial year 2024, India had over *** million school students. The highest number of students were enrolled in elementary schools and the lowest in higher secondary school.

The dataset contains Year-, region- and gender-wise All India compiled data on distribution (per thousand) of persons of age group 15 years and above belonging to scheduled caste (SC), scheduled tribe (ST), other backwards classes (OBC) and other castes by Level of Education such as primary, secondary, higher secondary, middle, diploma/certificate, graduate, post graduate, etc., during the period of 2000 to 2012. The dataset has been compiled from Table Nos. 8, 3.13, Statement Nos. 3.12 and 3.13 of 55th, 61st, 66th and 68th reports of NSS.

Worker Population Ratio: Usual Status: Education: Maharashtra: Rural data was reported at 61.600 % in 2024. This records a decrease from the previous number of 63.200 % for 2023. Worker Population Ratio: Usual Status: Education: Maharashtra: Rural data is updated yearly, averaging 60.900 % from Jun 2018 (Median) to 2024, with 7 observations. The data reached an all-time high of 63.200 % in 2023 and a record low of 54.700 % in 2019. Worker Population Ratio: Usual Status: Education: Maharashtra: Rural data remains active status in CEIC and is reported by Ministry of Statistics and Programme Implementation. The data is categorized under India Premium Database’s Labour Market – Table IN.GBA026: Periodic Labour Force Survey: Annual: Worker Population Ratio: Usual Status: by State: Education Level.

India Vital Statistics: Age Specific Fertility Rate: per 1000 Female Population: Educational Level of Women: Literate: Without Any Formal Education: Age: 30-34 data was reported at 87.400 NA in 2016. This records an increase from the previous number of 83.300 NA for 2015. India Vital Statistics: Age Specific Fertility Rate: per 1000 Female Population: Educational Level of Women: Literate: Without Any Formal Education: Age: 30-34 data is updated yearly, averaging 77.600 NA from Dec 2010 (Median) to 2016, with 7 observations. The data reached an all-time high of 87.400 NA in 2016 and a record low of 75.300 NA in 2011. India Vital Statistics: Age Specific Fertility Rate: per 1000 Female Population: Educational Level of Women: Literate: Without Any Formal Education: Age: 30-34 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.GAH008: Vital Statistics: Age Specific Fertility Rate: by Education Level of Women.

As of 2021, approximately *** percent of the Indian population was multidimensionally poor and deprived in years of schooling. This reflected a lower percentage of population living in multidimensional poverty and deprivation of years of schooling in India. According to the source, a multidimensional poor individual is deprived in one-third or more of ten indicators across three equally weighted dimensions: health, education, and standard of living. Years of schooling and school attendance are the two indicators of the education dimension.