SpaceX falcon9 has built a spaceship with two stages of which stage one (the main component) has a higher probability of being reusable. This reusable tendency when successful has made the launching of spaceship cheaper than it used to be.
•To bid against SpaceX in the space world, it is important to determine the successful landing of stage one, use the specification to build a Space Y spaceship which will be used to bid against SpaceX falcon9 for a better prize.
•To do these, many analytic process will be done, and they include;
•Data collection using API and webscrapping, wrangling of data to obtain a better comprehensive data, exploration of data using SQL, visualization of data using folium map and plotly dash.
•Prediction of successful landing using machine learning.
•This whole process will help in predicting successful landing keeping in consideration the features of the spaceship and how it affect landing success. This information will help in the building of Space Y spaceship which will be used to bid against Space X.
BACKGROUND
The exploration of space has been ongoing since 1961 with the first cosmonaut in the person of Yuri Gagarin landing in space. Since then, exploration of space has continued with spaceships being destroyed after launching. These destructions has made landing in space very expensive with other spaceships announcing the use of $165 million for manufacturing and launching of spaceship, while Elon Musk is announcing $65million for reusable manufacturing of spaceships since the major component is already available. The reusable spaceship has made landing in space cheap. Bidding against SpaceX will require the manufacturing of reusable spaceships too.
THE PROBLEM STATEMENT
What are the factors that determine the landing success of the reusable component of Space X?
Can a prediction of successful landing be made using SpaceX falcon 9 data?
Is there a relationship between the features of spaceship and the landing success?
PURPOSE OF RESEARCH
To predict the successful landing of SpaceX falcon 9 spaceship to Build Space Y which will bid against Space X.
METHODOLOGY
Data collection methodology:
Data was collected with rest API and beautiful soup
Perform data wrangling
Data was wrangled with python
Perform exploratory data analysis (EDA) using visualization and SQL
Perform interactive visual analytics using Folium and Plotly Dash
Perform predictive analysis using classification models
Classification was used in which the 4 methods of classification was used.