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Interactive data visualization website built with React.js and JSX. Classifying confirmed exoplanets using the k-means clustering algorithm and calculating their ability to eject planets out of their planetary system.

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Exoplanet Classifier and Safronov Number

Which exoplanet type formed from k-means clustering is most likely to scatter bodies found in their planetary system? What is its implication?

the dashboard for the data visualization

We looked at the confirmed exoplanets in the NASA Exoplanet Archive as of June 10, 2023. First and foremost, exoplanets were classified using the k-means clustering algorithm into different types. Next, the exoplanets' Safronov numbers were then calculated to measure their ability to eject bodies like planets out of their planetary system (McDonald & Veras, 2023; Safronov, 1972). We wanted to observe the relationship between the type of exoplanet and its Safronov number and determine the capabilities and implications of certain types of exoplanet scattering bodies found in their planetary system.

Technologies Used

Python, scikit-learn, Pandas, Matplotlib, and NumPy was used to conduct the data analysis. React, Vite, JSX, CSS, and Plotly was used to build the data visualization dashboard.

References

Catriona, H. M., & Veras, D. (2023). Binary asteroid scattering around white dwarfs. Monthly Notices of the Royal Astronomical Society, 520(3), 4009–4022, https://doi.org/10.1093/mnras/stad382

Safronov, V. S. (1972). Evolution of the protoplanetary cloud and formation of the earth and the planets. Keter Publishing House.

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Interactive data visualization website built with React.js and JSX. Classifying confirmed exoplanets using the k-means clustering algorithm and calculating their ability to eject planets out of their planetary system.

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