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.