University Ranking Analysis
Explore, compare and identify bias of popular University ranking systems
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About This Project


Ranking is a key decision-making factor for students in their university selection process. Ranking methodology and criteria can vary significantly across different ranking systems and it can be difficult to understand and compare various ranking systems. Our study focuses on comparing university rankings by 3 reputable ranking systems and identifying potential biases across the different ranking systems. We aim to provide students meaningful insights and help them in their university research process.


Project Concept

We analyzed the results of 3 major university ranking systems across multiple years and created visualizations to represent our findings.

University Rankings Considered

Time University Rankings (UK) - 2011 to 2016
CWUR Rankings (Saudi Arabia) - 2012 to 2015
Shanghai Rankings (China) - 2005 to 2015

Tools Used

Data Gathering: Kaggle
Data Cleansing: Python
Data Visualization: Tableau, d3.js



For a more detailed description of the project, the tools used, and the source code, please visit our Github page.


What We've Learned

A guided tour of interesting findings from our analysis of the three university ranking systems. Analysis Method!

Explore the Data

Try out the interactive visualization below to explore univeristy reliability based on the 3 ranking systems. You can click on the nodes to expand or collapse.

Our Amazing Team



Bingjie Chen


Information Management graduate student majoring in Data Science at University of Washington


Nelson Dsouza


Information Management graduate student majoring in Data Science at University of Washington


Maria George


Information Management graduate student majoring in Data Science at University of Washington


Cory Shyu


Information Management graduate student majoring in Data Science at University of Washington




Project for INFX 575 - Data Science Scaling, Application and Ethics, Summer 2016, University of Washington School of Information



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