Diversity, Equity and Inclusion - Access to Education

This product contains datasets that present data on access to education in the United States and in the world. There are 3 datasets, one for the US and two international: Educational Attainment Levels within the United States from the U.S. Census, Gender Disparity in Education-International, and School Completion Rates-International.

This listing contains the following three datasets that pertain to Access to Education in the United States and the world. More datasets may be added to this product in future.

Education Attainment Levels within the United States - US Census data. Educational attainment refers to the highest level of education that an individual has completed. This is distinct from the level of schooling that an individual is attending. Data covers years 1990-2020. Data for additional years will be added as it becomes available.

Source:

• United States Census Bureau 
• Frequency: Annual
• Formats: CSV
• Code on GitHub 

Gender Disparity in Education - International (%) - Annual | UNICEF This data covers gender disparity in school completion rates and out of school rates for youth at the upper secondary school level for all countries. Data covers years 2015-2020. Data for additional years will be added as it becomes available.

Source:

• UNICEF | Gender and Education 
• Gender Disparities in Education (%) - Annual
• Frequency: Annual
• Formats: CSV
• Code on GitHub 

School Completion Rates - International (%) - Annual | UNICEF This data covers disparity in school completion rates and out of school rates for youth at the upper secondary school level for all countries. Data covers years 2015-2020. Data for additional years will be added as it becomes available.

Source:

• UNICEF | School Completion Rates 
• School Completion Rates (%) - Annual
• Frequency: Annual
• Formats: CSV
• Code on GitHub 

Contact Details

If you find any issues with or have enhancement ideas for any of datasets of this product, open up a GitHub issue in the Github repository of the dataset (listed above) and we will gladly take a look at it. Better yet, submit a pull request. Any contributions you make are greatly appreciated :heart:. If you are looking for specific open datasets currently not available on ADX, please submit a request on our project board here  .

If you have any other questions or feedback, send us an email at data@rearc.io .

Rearc is a cloud, software and services company. We believe that empowering engineers drives innovation. Cloud-native architectures, modern software and data practices, and the ability to safely experiment can enable engineers to realize their full potential. We have partnered with several enterprises and startups to help them achieve agility. Our approach is simple — empower engineers with the best tools possible to make an impact within their industry.