Welcome to the dawn of the commercial space age, where companies like Virgin Galactic, Rocket Lab, Blue Origin, and SpaceX are pioneering affordable space travel. Among these, SpaceX stands out with its impressive accomplishments, including regular International Space Station missions, the Starlink project, and manned space missions. A significant factor in SpaceX's success is its cost-effective approach, notably the reuse of the Falcon 9 rocket's first stage, dramatically reducing launch costs.
This project focuses on Space Y, a new competitor aspiring to challenge SpaceX's dominance. As a data scientist at Space Y, my mission is to determine the cost of each launch by analyzing SpaceX's data and predicting whether the first stage of their Falcon 9 rocket will be reused.
- Gather SpaceX Launch Data: Collect public information about SpaceX launches, focusing on the Falcon 9 rocket.
- Dashboard Creation: Develop dashboards for the Space Y team to visualize SpaceX's launch data and insights.
- Predict First Stage Reuse: Train a machine learning model to predict the likelihood of SpaceX reusing Falcon 9's first stage based on available data.
- Cost Analysis: Estimate the cost of each launch based on the reuse prediction and other factors.
SpaceX's cutting-edge approach to space travel served as inspiration for the project. The data will be gathered from public sources, and the project also draws inspiration from the work of Forest Katsch at zlsadesign.com. His detailed diagrams and infographics on spaceflight provide valuable context for understanding the scale and complexity of the Falcon 9 rocket.
notebooks/: Jupyter notebooks detailing the exploratory data analysis and model development process.dashboards/: Interactive dashboards showcasing insights about SpaceX launches and model predictions.
- Webscraping
- Data Wrangling
- Data Analysis and Visualization & Folium Map
- SQL & Db2 database
- Supervised Machine Learning Predictive Models
- Dashboard with Plotly Dash