Task 2 – Exploratory Data Analysis (EDA)

Project: Exoplanet Data Analysis

A simulated dataset of 300 exoplanets was created using Python, Pandas, and NumPy.

Analysis Performed

• Explored dataset structure and statistics
• Analyzed discovery methods and orbital periods
• Detected an anomalous planet mass
• Compared median orbital periods for Transit and Radial Velocity methods

Tools

Python | Pandas | NumPy

---

Task 3 – Data Visualization

Project: Exoplanet Data Visualization

Astronomical data was visualized using Python, Pandas, Matplotlib, and Seaborn.

Visualizations

• Exoplanet radius distribution
• Orbital period distribution
• Planet radius vs orbital period
• Stellar temperature vs planet radius
• Host star radius vs planet radius
• Correlation matrix

Tools

Python | Pandas | NumPy | Matplotlib | Seaborn

#Learning Outcome

These projects helped me develop practical skills in data analysis, anomaly detection, statistical analysis, and scientific data visualization while applying data analytics to astronomy and astrophysics.