Dataset Overview 📝

The dataset includes the following key indicators, collected for over 200 countries:

• Government Expenditure on Education (% of GDP): Shows the percentage of a country’s GDP allocated to education.
• Literacy Rate (Adult Total): Represents the percentage of the population aged 15 and above who can read and write.
• Primary Completion Rate: The percentage of children who complete their primary education within the official age group.
• Pupil-Teacher Ratio (Primary and Secondary Education): Indicates the average number of students per teacher at the primary and secondary levels.
• School Enrollment Rates (Primary, Secondary, Tertiary): Reflects the percentage of the relevant age group enrolled in schools across different education levels.

Data Source 🌐

World Bank: This dataset is compiled from the World Bank's educational database, providing reliable, updated statistics on educational progress worldwide.

Potential Use Cases 🔍 This dataset is ideal for anyone interested in:

Educational Research: Understanding how education spending and policies impact literacy, enrollment, and overall educational outcomes. Predictive Modeling: Building models to predict educational success factors, such as completion rates and literacy. Global Education Analysis: Analyzing trends in global education systems and how different countries allocate resources to education. Policy Development: Helping governments and organizations make data-driven decisions regarding educational reforms and funding.

Key Questions You Can Explore 🤔

How does government expenditure on education correlate with literacy rates and school enrollment across different regions? What are the trends in pupil-teacher ratios over time, and how do they affect educational outcomes? How do education indicators differ between low-income and high-income countries? Can we predict which countries will achieve universal primary education based on current trends?

Important Notes ⚠️ - Missing Data: Some values may be missing for certain years or countries. Consider using techniques like forward filling or interpolation when working with time series models. - Data Limitations: This dataset provides global averages and may not capture regional disparities within countries.

Iceland had the highest inequality-adjusted education index score worldwide, amounting to **** out of one on the index. Germany followed with an index score of ****. The inequality-adjusted education index is the education index in the Human Development Index adjusted for inequality.

The average for 2021 based on 165 countries was 72.61 index points. The highest value was in Luxembourg: 422.59 index points and the lowest value was in Turkey: 10.85 index points. The indicator is available from 2017 to 2021. Below is a chart for all countries where data are available.

As of 2024, Angola was the country worldwide where the lowest share of the population had a higher education of a bachelor's degree or higher. A high number of the countries on the list were located in Sub-Saharan Africa. On the other hand, Montenegro was the country where the highest share of the population had completed a bachelor's degree or more.

Context

This ranking was created by aggregating data from 14 websites and counting how many times each country was mentioned in the top 3, top 5, and top 10 places. There is no official measures or rankings for a countries education system.

Content

The 14 web sources are as follows: https://worldpopulationreview.com/country-rankings/education-rankings-by-country https://worldtop20.org/worldbesteducationsystem https://www.currentschoolnews.com/education-news/best-educational-system-in-the-world/ https://www.edsys.in/best-education-system-in-the-world/ https://www.indiaeducation.net/studyabroad/articles/countries-with-the-best-higher-education-system.html http://blog.mpanchang.com/10-best-education-systems-in-the-world/ https://admission.buddy4study.com/study-abroad/best-education-systems-in-world https://www.usnews.com/news/best-countries/best-education https://www.theedadvocate.org/the-edvocates-list-of-the-20-best-education-systems-in-the-world/ https://www.worldatlas.com/articles/10-countries-with-the-best-education-systems.html https://ceoworld.biz/2020/05/10/ranked-worlds-best-countries-for-education-system-2020/ https://www.independent.co.uk/news/education/11-best-school-systems-world-a7425391.html https://naijaquest.com/best-education-system-in-the-world/ https://mintbook.com/blog/best-educational-systems-in-the-world/

Acknowledgements

Created for BAD 52 - Human Relations in Organizations from the Santa Rosa Junior College in Fall 2020.

As of 2022, 70 percent of the South Korean population between 25 and 34 had attained a tertiary education, making it the OECD country with the highest proportion of tertiary education graduates. Canada followed with more than two-thirds, while in Japan, the share was around 66 percent. By comparison, roughly 13 percent of South Africans between 25 and 34 had a tertiary education in 2022.

The average for 2022 based on 126 countries was 94.03 percent. The highest value was in Finland: 144.85 percent and the lowest value was in Burkina Faso: 33.72 percent. The indicator is available from 1970 to 2023. Below is a chart for all countries where data are available.

Context

Data containing education attainment level, also grouped by age group, sex and geography in Europe. Source is https://ec.europa.eu/eurostat/data/database (official European Data Source). Data is downloaded from the source, documented and uploaded to Kaggle.

Content

Original data

The original data is provided in TSV (tab delimited) format.

Data is grouped by sex, age group and geography. Education attainment is given by International Standard Classification of Education (ISCED11).

ISCED11 education levels are the following: X - No schooling
0 - Early childhood education
1 - Primary education
2 - Lower secondary education
3 - Upper secondary education
4 - Post-secondary non-tertiary education
5 - Short-cycle tertiary education
6 - Bachelor’s or equivalent level
7 - Master’s or equivalent level
8 - Doctoral or equivalent level
9 - Not elsewhere classified

Transformed data

For easiness of use, the original data was transformed using Starter Kernel: Population Education Levels in Europe in a csv format; if you want to replicate this process, you are welcome to fork this Kernel and implement your own data analysis.

How to

The data has the temporal information given as columns (per year). In order to further use this data, it would be more easy to pivot first these columns to get instead date/value pairs. This pivot operation can be done using melt from pandas is done in the starter kernel: * Starter Kernel: Population Education Levels in Europe; we convert the year to an integer. Just run this Kernel to put the data in csv format, with yearly data pivoted.

Acknowledgements

All merit for data collection, curation, and initial publishing goes to Eurostat.

Inspiration

You can use this data for various demographic, economic, public health, social aspects, combining with alternative data from Kaggle and other sources.

Dataset

This dataset was created by Zergham Warraich

Contents

Global General Government Expenditure on Education by Country, 2023 Discover more data with ReportLinker!

The average for 2021 based on 158 countries was 4.48 percent. The highest value was in Kiribati: 14.2 percent and the lowest value was in Nigeria: 0.38 percent. The indicator is available from 1970 to 2023. Below is a chart for all countries where data are available.

The average for 2022 based on 76 countries was 88.21 percent. The highest value was in Andorra: 100 percent and the lowest value was in San Marino: 34.16 percent. The indicator is available from 1998 to 2023. Below is a chart for all countries where data are available.

The average for 2022 based on 124 countries was 92.43 percent. The highest value was in Gibraltar: 130.58 percent and the lowest value was in Niger: 52.99 percent. The indicator is available from 1970 to 2023. Below is a chart for all countries where data are available.

Description:

This dataset presents the tertiary education rates of the top ten most educated countries in the world. These countries have been ranked based on their tertiary education rates, showcasing their commitment to fostering educated populations and their global prominence in various fields. The dataset highlights the percentage of the population with completed tertiary education for each of these leading nations. With South Korea leading the pack at 69.29%, followed by Canada, Japan, Luxembourg, Ireland, Russia, Lithuania, the United Kingdom, the Netherlands, and Norway, this dataset provides valuable insights into global education trends and the impact of education on socioeconomic development.

Columns:

Country: Name of the country Tertiary_Education_Rate: Percentage of the population with completed tertiary education Potential Applications:

• Comparative analysis of tertiary education rates among the top educated countries
• Understanding the correlation between education levels and socioeconomic indicators
• Identifying factors contributing to high educational attainment in leading nations
• Benchmarking educational policies and initiatives against top-performing countries

Among the OECD countries, Canada had the highest proportion of adults with a tertiary education in 2022. About 63 percent of Canadians had achieved a tertiary education in that year. Japan followed with about 56 percent of the population having completed a tertiary education, while in Ireland the share was roughly 54 percent. In India, on the other hand, less than 13 percent of the adult population had completed a tertiary education in 2022.

If this data set benefit your work, don't hesitate to upvote 😀

This data is gathered from United Nations databases, the following links below is been used.

https://rankedex.com/society-rankings/education-index https://en.wikipedia.org/wiki/Education_Index https://www.un.org/development/desa/dpad/wp-content/uploads/sites/45/WESP2022_ANNEX.pdf

This data can be used to measure the influence of education or income or both on any variable or vector, for example, ANOVA models.

The Income classification is for year 2021 and the education index is for 2019 to 2023.

The education index (EI) is one of the parameters that is used to calculate the Human Development Index (HDI). It is calculated by this formula: Education Index = (MYS Index + EYS Index) / 2 where MYS is Mean Years of Schooling and EYS is Expected Years of Schooling.

In this data it is assumed that : 1-Countries EI below 0.4 have Very Low Educated population 2-Countries EI between 0.4 and 0.6 have Low to Moderate Educated population 3-Countries EI between 0.6 and 0.8 have High to Moderate Educated population 4-Countries EI above 0.8 have Very Educated Educated population

This Cost of International Education dataset compiles detailed financial information for students pursuing higher education abroad. It covers multiple countries, cities, and universities around the world, capturing the full tuition and living expenses spectrum alongside key ancillary costs. With standardized fields such as tuition in USD, living-cost indices, rent, visa fees, insurance, and up-to-date exchange rates, it enables comparative analysis across programs, degree levels, and geographies. Whether you’re a prospective international student mapping out budgets, an educational consultant advising on affordability, or a researcher studying global education economics, this dataset offers a comprehensive foundation for data-driven insights.

Description

Potential Uses

• Budget Planning Prospective students can filter by country, program level, or university to forecast total expenses and compare across destinations.
• Policy Analysis Educational policymakers and NGOs can assess the affordability of international education and design support programs.
• Economic Research Economists can correlate living-cost indices and tuition levels with enrollment rates or student demographics.
• University Benchmarking Institutions can benchmark their fees and ancillary costs against peer universities worldwide.

Notes on Data Collection & Quality

• Currency Conversions All monetary values are unified to USD using contemporaneous exchange rates to facilitate direct comparison.
• Living Cost Index Derived from reputable city-index publications (e.g., Numbeo, Mercer) to standardize disparate cost-of-living metrics.
• Data Currency Exchange rates and fee schedules should be periodically updated to reflect market fluctuations and policy changes.

Feel free to explore, visualize, and extend this dataset for deeper insights into the true cost of studying abroad!

Global Public Spending on Tertiary Education by Country, 2023 Discover more data with ReportLinker!

Global Tertiary Education Level Attainment by Country, 2023 Discover more data with ReportLinker!

The folder 'population by educational attainment level (edat1)' presents data on the highest level of education successfully completed by the individuals of a given population.

The folder 'transition from education to work (edatt)' covers data on young people neither in employment nor in education and training – NEET, early leavers from education and training and the labour status of young people by years since completion of highest level of education.

The data shown are calculated as annual averages of quarterly EU Labour Force Survey data (EU-LFS).

Up to the reference year 2008, the data source (EU-LFS) is, where necessary, adjusted and enriched in various ways, in accordance with the specificities of an indicator, including the following:

• correction of the main breaks in the LFS series,
• estimation of the missing values, i.e. in case of missing quarters, annual results and EU aggregates are estimated using adjusted quarterly national labour force survey data or interpolations of the EU-LFS data with reference to the available quarter(s).

Details on the adjustments are available in CIRCABC.

The adjustments are applied in the following online tables:

• Population by educational attainment level (edat1)

- Population by educational attainment level, sex and age (%) - main indicators (edat_lfse_03)
- Population by educational attainment level, sex and NUTS 2 regions (%) (edat_lfse_04)

(Other tables shown in the folder 'population by educational attainment level (edat1)' are not adjusted and therefore the results in these tables might differ).

• Young people by educational and labour status (incl. neither in employment nor in education and training - NEET) (edatt0) – all tables
• Early leavers from education and training (edatt1) – all tables
• Labour status of young people by years since completion of highest level of education (edatt2) – all tables

LFS ad-hoc module data available in the folder 'transition from education to work (edatt)' are not adjusted.

The folder 'young people by educational and labour status (incl. neither in employment nor in education and training - NEET) (edatt0)' also presents one table with quarterly NEET data (lfsi_neet_q). Deviating from the NEET indicator calculation as provided in 3.4, the denominator in this table with quarterly data is the total population of the same age group and sex which explains differences in results. For further information, see the ESMS on 'LFS main indicators'.