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A Python-based analysis of Kepler’s Third Law using planetary data. The project calculates T^2/r^3 ratios and visualizes the linear relationship between orbital period and distance on a log-log plot to verify the physical laws governing the Solar System.

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Kepler's Third Law Verification

Project Description This project demonstrates the verification of Kepler's Third Law of Planetary Motion (T^2∝r^3) using observational data from the Solar System. By calculating the ratio of the square of the orbital period to the cube of the semi-major axis, we can confirm the constant nature of this ratio for planets orbiting the same central body.

Technologies Used Python 3.x Pandas: For astronomical data processing and vectorised calculations. Matplotlib: For visualization of the physical correlation.

Key Features Physical Modeling: Implementation of the formula Stosunek=T^2/r^3.

Data Transformation: Creation of custom columns for T^2 and r^3 to linearize the relationship.

Visualization: Log-log scatter plot to verify the linear dependence, providing a clear visual proof of Kepler's law.

How to Run Ensure you have planets.csv in the same directory (or create the DataFrame directly in the script). Install dependencies: pip install pandas matplotlib Run the script: python main.py

Results The script generates a plot where the correlation between the square of the orbital period and the cube of the distance is clearly visible as a linear trend. This confirms the theoretical prediction of Kepler's Third Law.

About

A Python-based analysis of Kepler’s Third Law using planetary data. The project calculates T^2/r^3 ratios and visualizes the linear relationship between orbital period and distance on a log-log plot to verify the physical laws governing the Solar System.

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