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World University Rankings

✓ Published0🌍 Public
Ssamozarif@gmail.com
Last edited Sep 12, 2024
Created on Sep 5, 2024

A scatterplot matrix reveals correlations among institutional attributes like quality of education, alumni employment, and world rank, using the Kaggle World University Rankings dataset. The view also maps institutions by country and traces score changes over time. Data is loaded and parsed from a CSV via the `data.csv` import, with numeric coersion applied in `index.js` before rendering. The implementation relies on standard JavaScript and a container-based layout to display the parsed data as text.

AI-generated description

The (https://www.kaggle.com/datasets/mylesoneill/world-university-rankings)

Five specific tasks that can be defined to drive the design of visualizations:

  1. Compare the correlation between institutional attributes such as quality of education, alumni employment, and world rank. Task type: Compare relationship.
  2. Analyze the geographic distribution of institutions by country. Task type: Explore spatial.
  3. Observe how an institution’s rank or score has changed over time. Task type: Discover temporal trend.
  4. Identify institutions with high influence in publications and citations. Task type: Identify extremum (highest/lowest).
  5. Examine the distribution of patents across institutions. Task type: Distribution.
MIT Licensed

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