In this project, I aim to predict whether the Falcon 9 first stage will land successfully.
SpaceX advertises Falcon 9 rocket launches on its website at a cost of 62 million dollars, significantly less than other providers, which cost upwards of 165 million dollars each. Much of the savings is due to SpaceX's ability to reuse the first stage. By determining the likelihood of the first stage landing successfully, we can estimate the cost of a launch. This information is valuable for companies looking to compete with SpaceX for rocket launch contracts.
To achieve this goal, the following steps were taken:
- Data Collection: Gathering relevant data from various sources.
- Data Wrangling: Cleaning and preprocessing the data for analysis.
- Exploratory Data Analysis (EDA): Understanding the underlying patterns and relationships in the data.
- Interactive Visual Analytics: Creating visual representations to gain insights from the data.
- Predictive Analysis: Building classification models to predict the landing outcome.
The analysis includes the following key results:
- EDA Results: Insights derived from the exploratory data analysis.
- Geospatial Analytics: Analysis of spatial data related to launch sites and trajectories.
- Interactive Dashboard: A dashboard that provides an interactive way to explore the data and results.
- Predictive Analysis: Evaluation of various classification models to predict the success of the Falcon 9 first stage landing.
The complete report, including detailed methodologies, results, and discussions, can be found here.
I welcome feedback and contributions from the community. If you have any suggestions or would like to contribute to the project, please open an issue or submit a pull request on my GitHub repository.