Context

The World Bank is an international financial institution that provides loans to countries of the world for capital projects. The World Bank's stated goal is the reduction of poverty. Source: https://en.wikipedia.org/wiki/World_Bank

Content

This dataset combines key education statistics from a variety of sources to provide a look at global literacy, spending, and access.

For more information, see the World Bank website.

Fork this kernel to get started with this dataset.

Acknowledgements

https://bigquery.cloud.google.com/dataset/bigquery-public-data:world_bank_health_population

http://data.worldbank.org/data-catalog/ed-stats

https://cloud.google.com/bigquery/public-data/world-bank-education

Citation: The World Bank: Education Statistics

Dataset Source: World Bank. This dataset is publicly available for anyone to use under the following terms provided by the Dataset Source - http://www.data.gov/privacy-policy#data_policy - and is provided "AS IS" without any warranty, express or implied, from Google. Google disclaims all liability for any damages, direct or indirect, resulting from the use of the dataset.

Banner Photo by @till_indeman from Unplash.

Inspiration

Of total government spending, what percentage is spent on education?

This table contains data on the percent of population age 25 and up with a four-year college degree or higher for California, its regions, counties, county subdivisions, cities, towns, and census tracts. Greater educational attainment has been associated with health-promoting behaviors including consumption of fruits and vegetables and other aspects of healthy eating, engaging in regular physical activity, and refraining from excessive consumption of alcohol and from smoking. Completion of formal education (e.g., high school) is a key pathway to employment and access to healthier and higher paying jobs that can provide food, housing, transportation, health insurance, and other basic necessities for a healthy life. Education is linked with social and psychological factors, including sense of control, social standing and social support. These factors can improve health through reducing stress, influencing health-related behaviors and providing practical and emotional support. More information on the data table and a data dictionary can be found in the Data and Resources section. The educational attainment table is part of a series of indicators in the Healthy Communities Data and Indicators Project (HCI) of the Office of Health Equity. The goal of HCI is to enhance public health by providing data, a standardized set of statistical measures, and tools that a broad array of sectors can use for planning healthy communities and evaluating the impact of plans, projects, policy, and environmental changes on community health. The creation of healthy social, economic, and physical environments that promote healthy behaviors and healthy outcomes requires coordination and collaboration across multiple sectors, including transportation, housing, education, agriculture and others. Statistical metrics, or indicators, are needed to help local, regional, and state public health and partner agencies assess community environments and plan for healthy communities that optimize public health. More information on HCI can be found here: https://www.cdph.ca.gov/Programs/OHE/CDPH%20Document%20Library/Accessible%202%20CDPH_Healthy_Community_Indicators1pager5-16-12.pdf The format of the educational attainment table is based on the standardized data format for all HCI indicators. As a result, this data table contains certain variables used in the HCI project (e.g., indicator ID, and indicator definition). Some of these variables may contain the same value for all observations.

To collect feedback on their learning environment from families, students and teachers. Aids in facilitating the understanding of families perceptions, students, and teachers regarding their school. School leaders use feedback from the survey to reflect and make improvements to schools and programs. Each year all parents, teachers and students in grades 6-12 take the NYC School Survey. The survey is aligned to the DOE's Framework for Great Schools. It is designed to collect important information about each school's ability to support student success.

Data includes: board and school information, grade 3 and 6 EQAO student achievements for reading, writing and mathematics, and grade 9 mathematics EQAO and OSSLT. Data excludes private schools, Education and Community Partnership Programs (ECPP), summer, night and continuing education schools.

How Are We Protecting Privacy?

Results for OnSIS and Statistics Canada variables are suppressed based on school population size to better protect student privacy. In order to achieve this additional level of protection, the Ministry has used a methodology that randomly rounds a percentage either up or down depending on school enrolment. In order to protect privacy, the ministry does not publicly report on data when there are fewer than 10 individuals represented.

* Percentages depicted as 0 may not always be 0 values as in certain situations the values have been randomly rounded down or there are no reported results at a school for the respective indicator. * Percentages depicted as 100 are not always 100, in certain situations the values have been randomly rounded up.

The information in the School Information Finder is the most current available to the Ministry of Education at this time, as reported by schools, school boards, EQAO and Statistics Canada. The information is updated as frequently as possible.

This information is also available on the Ministry of Education's School Information Finder website by individual school.

Descriptions for some of the data types can be found in our glossary.

School/school board and school authority contact information are updated and maintained by school boards and may not be the most current version. For the most recent information please visit: https://data.ontario.ca/dataset/ontario-public-school-contact-information.

This feature layer provides the educational attainment levels in the City of Tempe by census tract. The feature layer was created by clipping the ACS Educational Attainment Variables - Boundaries 2014-18, downloaded from Esri's Living Atlas, to the City of Tempe boundary layer.https://tempegov.maps.arcgis.com/home/item.html?id=84e3022a376e41feb4dd8addf25835a3

The American Community Survey Education Tabulation (ACS-ED) is a custom tabulation of the ACS produced for the National Center of Education Statistics (NCES) by the U.S. Census Bureau. The ACS-ED provides a rich collection of social, economic, demographic, and housing characteristics for school systems, school-age children, and the parents of school-age children. In addition to focusing on school-age children, the ACS-ED provides enrollment iterations for children enrolled in public school. The data profiles include percentages (along with associated margins of error) that allow for comparison of school district-level conditions across the U.S. For more information about the NCES ACS-ED collection, visit the NCES Education Demographic and Geographic Estimates (EDGE) program at: https://nces.ed.gov/programs/edge/Demographic/ACS

The Annual Arts Education survey collects information on student participation in and access to arts education at NYCDOE schools.

Please note the following arts-related data are now collected from other sources: The number of certified art teachers and non-certified teachers teaching the arts is collected form the HR and BEDS survey The arts instructional hours provided to elementary students are collected from the Student Transcript and Academic Recording System (STARS) The middle and high school participation in the arts data and the NYSED requirement data are collected form STARS and the HS arts sequence data are also collected form STARS

Success.ai’s Education Industry Data provides access to comprehensive profiles of global professionals in the education sector. Sourced from over 700 million verified LinkedIn profiles, this dataset includes actionable insights and verified contact details for teachers, school administrators, university leaders, and other decision-makers. Whether your goal is to collaborate with educational institutions, market innovative solutions, or recruit top talent, Success.ai ensures your efforts are supported by accurate, enriched, and continuously updated data.

Why Choose Success.ai’s Education Industry Data? 1. Comprehensive Professional Profiles Access verified LinkedIn profiles of teachers, school principals, university administrators, curriculum developers, and education consultants. AI-validated profiles ensure 99% accuracy, reducing bounce rates and enabling effective communication. 2. Global Coverage Across Education Sectors Includes professionals from public schools, private institutions, higher education, and educational NGOs. Covers markets across North America, Europe, APAC, South America, and Africa for a truly global reach. 3. Continuously Updated Dataset Real-time updates reflect changes in roles, organizations, and industry trends, ensuring your outreach remains relevant and effective. 4. Tailored for Educational Insights Enriched profiles include work histories, academic expertise, subject specializations, and leadership roles for a deeper understanding of the education sector.

Data Highlights: 700M+ Verified LinkedIn Profiles: Access a global network of education professionals. 100M+ Work Emails: Direct communication with teachers, administrators, and decision-makers. Enriched Professional Histories: Gain insights into career trajectories, institutional affiliations, and areas of expertise. Industry-Specific Segmentation: Target professionals in K-12 education, higher education, vocational training, and educational technology.

Key Features of the Dataset: 1. Education Sector Profiles Identify and connect with teachers, professors, academic deans, school counselors, and education technologists. Engage with individuals shaping curricula, institutional policies, and student success initiatives. 2. Detailed Institutional Insights Leverage data on school sizes, student demographics, geographic locations, and areas of focus. Tailor outreach to align with institutional goals and challenges. 3. Advanced Filters for Precision Targeting Refine searches by region, subject specialty, institution type, or leadership role. Customize campaigns to address specific needs, such as professional development or technology adoption. 4. AI-Driven Enrichment Enhanced datasets include actionable details for personalized messaging and targeted engagement. Highlight educational milestones, professional certifications, and key achievements.

Strategic Use Cases: 1. Product Marketing and Outreach Promote educational technology, learning platforms, or training resources to teachers and administrators. Engage with decision-makers driving procurement and curriculum development. 2. Collaboration and Partnerships Identify institutions for collaborations on research, workshops, or pilot programs. Build relationships with educators and administrators passionate about innovative teaching methods. 3. Talent Acquisition and Recruitment Target HR professionals and academic leaders seeking faculty, administrative staff, or educational consultants. Support hiring efforts for institutions looking to attract top talent in the education sector. 4. Market Research and Strategy Analyze trends in education systems, curriculum development, and technology integration to inform business decisions. Use insights to adapt products and services to evolving educational needs.

Why Choose Success.ai? 1. Best Price Guarantee Access industry-leading Education Industry Data at unmatched pricing for cost-effective campaigns and strategies. 2. Seamless Integration Easily integrate verified data into CRMs, recruitment platforms, or marketing systems using downloadable formats or APIs. 3. AI-Validated Accuracy Depend on 99% accurate data to reduce wasted outreach and maximize engagement rates. 4. Customizable Solutions Tailor datasets to specific educational fields, geographic regions, or institutional types to meet your objectives.

Strategic APIs for Enhanced Campaigns: 1. Data Enrichment API Enrich existing records with verified education professional profiles to enhance engagement and targeting. 2. Lead Generation API Automate lead generation for a consistent pipeline of qualified professionals in the education sector. Success.ai’s Education Industry Data enables you to connect with educators, administrators, and decision-makers transforming global...

JP: All Education Staff Compensation: Primary: % of Total Expenditure in Primary Public Institutions data was reported at 72.780 % in 2014. This records a decrease from the previous number of 74.701 % for 2013. JP: All Education Staff Compensation: Primary: % of Total Expenditure in Primary Public Institutions data is updated yearly, averaging 78.516 % from Dec 1998 (Median) to 2014, with 16 observations. The data reached an all-time high of 79.354 % in 2008 and a record low of 72.780 % in 2014. JP: All Education Staff Compensation: Primary: % of Total Expenditure in Primary Public Institutions data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Japan – Table JP.World Bank.WDI: Education Statistics. All staff (teacher and non-teachers) compensation is expressed as a percentage of direct expenditure in public educational institutions (instructional and non-instructional) of the specified level of education. Financial aid to students and other transfers are excluded from direct expenditure. Staff compensation includes salaries, contributions by employers for staff retirement programs, and other allowances and benefits.; ; United Nations Educational, Scientific, and Cultural Organization (UNESCO) Institute for Statistics.; Median;

Background, Methodology:

Local Law 102 enacted in 2015 requires the Department of Education of the New York City School District to submit to the Council an annual report concerning physical education for the prior school year.

This report provides information about average frequency and average total minutes per week of physical education as defined in Local Law 102 as reported through the 2015-2016 STARS database. It is important to note that schools self-report their scheduling information in STARS. The report also includes information regarding the number and ratio of certified physical education instructors and designated physical education instructional space.

This report consists of six tabs:

1. PE Instruction Borough-Level
2. PE Instruction District-Level
3. PE Instruction School-Level
4. Certified PE Teachers
5. PE Space

6. Supplemental Programs

7. PE Instruction Borough-Level

This tab includes the average frequency and average total minutes per week of physical education by borough, disaggregated by grade, race and ethnicity, gender, special education status and English language learner status. This report only includes students who were enrolled in the same school across all academic terms in the 2015-16 school year. Data on students with disabilities and English language learners are as of the end of the 2015-16 school year. Data on adaptive PE is based on individualized education programs (IEP) finalized on or before 05/31/2016.

1. PE Instruction District-Level

This tab includes the average frequency and average total minutes per week of physical education by district, disaggregated by grade, race and ethnicity, gender, special education status and English language learner status. This report only includes students who were enrolled in the same school across all academic terms in the 2015-16 school year. Data on students with disabilities and English language learners are as of the end of the 2015-16 school year. Data on adaptive PE is based on individualized education programs (IEP) finalized on or before 05/31/2016.

1. PE Instruction School-Level

This tab includes the average frequency and average total minutes per week of physical education by school, disaggregated by grade, race and ethnicity, gender, special education status and English language learner status. This report only includes students who were enrolled in the same school across all academic terms in the 2015-16 school year. Data on students with disabilities and English language learners are as of the end of the 2015-16 school year. Data on adaptive PE is based on individualized education programs (IEP) finalized on or before 05/31/2016.

1. Certified PE Teachers

This tab provides the number of designated full-time and part-time physical education certified instructors. Does not include elementary, early childhood and K-8 physical education teachers that provide physical education instruction under a common branches license. Also includes ratio of full time instructors teaching in a physical education license to students by school. Data reported is for the 2015-2016 school year as of 10/31/2015.

1. PE Space

This tab provides information on all designated indoor, outdoor and off-site spaces used by the school for physical education as reported through the Principal Annual Space Survey and the Outdoor Yard Report. It is important to note that information on each room category is self-reported by principals, and principals determine how each room is classified. Data captures if the PE space is co-located, used by another school or used for another purpose. Includes gyms, athletic fields, auxiliary exercise spaces, dance rooms, field houses, multipurpose spaces, outdoor yards, off-site locations, playrooms, swimming pools and weight rooms as designated PE Space.

1. Supplemental Programs

This tab provides information on the department's supplemental physical education program and a list of schools that use it.I. Includes all Move-to-Improve (MTI) supplemental programs for the 2015-2016 school year.

Link to NY State PE Regulations: http://www.p12.nysed.gov/ciai/pe/documents/title8part135.pdf

Any questions regarding this report should be directed to: Nnennaya Okezie, Executive Director NYC Department of Education, Office of Intergovernmental Affairs Phone: 212-374-4947"

Idiosyncrasies or limitations of the data to be aware of:

This dataset contains statistically weighted estimates of initial education levels, highest education levels, and initial education locations for 43 key health workforce professions actively licensed in California as of July 1st, 2023. These metrics can be compared by workforce category, license type, time since license issue date (in years), race & ethnicity group, assigned sex at birth, and CHIS region.

PLEASE READ THIS DATASET DESCRIPTION IN FULL BEFORE EXPORTING ANY DATA.

This dataset provides transparency about the names and amounts of payments from county school boards to payees. More information about the statute for this dataset is under Maryland Education Article §5-115.

https://mgaleg.maryland.gov/mgawebsite/Laws/StatuteText?article=ged&section=5-115&enactments=false

Each county annually reports payment information about any payee who received an aggregate payment of $25,000 in a fiscal year from a school board.

This started with Fiscal Year 2019 payments. We now have payments data through Fiscal Year 2024 (6/30/24).

Baltimore County is also required to provide the purpose of the payment and whether the payee is a minority business enterprise.

Montgomery County and Howard County data goes back to 2010. Baltimore County and Prince George’s County goes back to 2012. 2019 is the first year where are all counties were required to submit the data with payee names and amounts.

Baltimore City data is missing for 2021 and 2023. Baltimore County data for 2023 needs further review. DBM will work on making these updates.

Separately, Prince George’s County is required to provide additional detail from Education Article §5-101. That info is not part of this dataset.

https://mgaleg.maryland.gov/mgawebsite/Laws/StatuteText?article=ged&section=5-101&enactments=False&archived=False

United States US: Government Expenditure on Education: Total: % of Government Expenditure data was reported at 13.452 % in 2014. This records an increase from the previous number of 13.277 % for 2013. United States US: Government Expenditure on Education: Total: % of Government Expenditure data is updated yearly, averaging 13.277 % from Dec 2010 (Median) to 2014, with 5 observations. The data reached an all-time high of 13.452 % in 2014 and a record low of 12.933 % in 2011. United States US: Government Expenditure on Education: Total: % of Government Expenditure data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Education Statistics. General government expenditure on education (current, capital, and transfers) is expressed as a percentage of total general government expenditure on all sectors (including health, education, social services, etc.). It includes expenditure funded by transfers from international sources to government. General government usually refers to local, regional and central governments.; ; United Nations Educational, Scientific, and Cultural Organization (UNESCO) Institute for Statistics.; Median;

Student demographic and enrollment data by school from 2013-14 through 2017-18

The global education data security market is experiencing robust growth, driven by the increasing digitization of educational institutions and the rising concerns around student data privacy and compliance with regulations like FERPA and GDPR. The market's value in 2025 is estimated at $10 billion, exhibiting a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033, projecting a market value exceeding $30 billion by 2033. Key growth drivers include the expanding adoption of cloud-based learning platforms, the proliferation of connected devices within educational settings, and the increasing sophistication of cyber threats targeting sensitive student and institutional data. Market segmentation reveals a strong demand for cloud-based solutions across both K-12 and higher education sectors, reflecting a broader industry trend towards flexible and scalable IT infrastructure. However, factors like budget constraints within educational institutions, particularly in developing regions, and the complexities associated with integrating data security solutions into existing IT systems present significant restraints to market expansion. Leading vendors such as Cisco, Citrix, McAfee, and others are actively developing and marketing advanced security solutions tailored to the specific needs of the education sector, further fueling market competition and innovation. The North American market currently dominates the education data security landscape, fueled by high technology adoption rates and stringent data privacy regulations. However, significant growth opportunities exist in the Asia-Pacific region, driven by rapid digital transformation in education systems and increasing internet penetration across developing economies like India and China. The European market is also expected to witness substantial growth, influenced by the implementation of GDPR and a focus on digital learning initiatives. Further growth will be fueled by the development of AI-powered security solutions that can proactively identify and mitigate threats in real-time, combined with robust data loss prevention (DLP) mechanisms to protect sensitive information. The increasing adoption of multi-factor authentication (MFA) and zero-trust security models are also expected to significantly impact market growth in the coming years.

This data presents statistics for students fully, partially, not receiving special education services, related services and transportation services. Data is categorized by district, superintendent, citywide counts and percentages.

Various data tables on student demographics, school enrollment trends, characteristics of traditional public school students and charter school students, student achievement, budget and school resources, principal and teacher information, building and school utilization and the availability of specialized facilities.

In this project, we aim to analyze and gain insights into the performance of students based on various factors that influence their academic achievements. We have collected data related to students' demographic information, family background, and their exam scores in different subjects.

**********Key Objectives:*********

1. Performance Evaluation: Evaluate and understand the academic performance of students by analyzing their scores in various subjects.

2. Identifying Underlying Factors: Investigate factors that might contribute to variations in student performance, such as parental education, family size, and student attendance.

3. Visualizing Insights: Create data visualizations to present the findings effectively and intuitively.

Dataset Details:

• The dataset used in this analysis contains information about students, including their age, gender, parental education, lunch type, and test scores in subjects like mathematics, reading, and writing.

Analysis Highlights:

• We will perform a comprehensive analysis of the dataset, including data cleaning, exploration, and visualization to gain insights into various aspects of student performance.

• By employing statistical methods and machine learning techniques, we will determine the significant factors that affect student performance.

Why This Matters:

Understanding the factors that influence student performance is crucial for educators, policymakers, and parents. This analysis can help in making informed decisions to improve educational outcomes and provide support where it is most needed.

Acknowledgments:

We would like to express our gratitude to [mention any data sources or collaborators] for making this dataset available.

Please Note:

This project is meant for educational and analytical purposes. The dataset used is fictitious and does not represent any specific educational institution or individuals.

The global market for Education Data Security Tools is experiencing robust growth, driven by increasing concerns about data breaches and the rising adoption of digital learning platforms. The expanding use of cloud-based services and the proliferation of sensitive student data, including personal information, academic records, and financial details, necessitate robust security measures. This has led educational institutions of all levels—from K-12 schools to universities—to invest heavily in sophisticated security solutions. The market is segmented by various tool types, including endpoint protection, data loss prevention (DLP), identity and access management (IAM), and security information and event management (SIEM) solutions. Major players like Cisco, Citrix, McAfee, and others are actively developing and marketing tailored solutions to meet the unique security needs of the education sector. The market’s growth is further fueled by government regulations aimed at protecting student data privacy, such as FERPA in the United States and GDPR in Europe. However, budget constraints in some educational institutions and the complexity of implementing and managing these solutions pose challenges to widespread adoption. The forecast period (2025-2033) anticipates continued expansion, driven by technological advancements in artificial intelligence (AI) and machine learning (ML) that enhance threat detection and response capabilities within education data security tools. The competitive landscape is characterized by both established cybersecurity vendors and niche players focusing on the education sector. Strategic partnerships and mergers and acquisitions are expected to shape the market dynamics. The increasing adoption of Bring Your Own Device (BYOD) policies in educational settings is also influencing the market, creating the need for solutions that can effectively secure devices from diverse vendors and operating systems. The market is geographically diverse, with North America and Europe currently holding significant market shares, but the Asia-Pacific region is projected to witness faster growth due to increasing digital literacy and government initiatives promoting digital education. Overall, the Education Data Security Tools market presents a substantial opportunity for vendors who can offer comprehensive, user-friendly, and cost-effective solutions that address the specific challenges faced by educational institutions.