High-Level Project Summary
We developed a number of graphs and did statistical analysis. We hope to provide enough data to predict where most meteorites are found. It is important for future meteor findings for further research of their properties.
Link to Final Project
Link to Project "Demo"
Detailed Project Description
Our first step was to clean the data of meteorites, that we found in NASA's website, by removing NA's and other mistakes. Then we proceeded in data analysis and added graphs and interactional maps.
We used R, PowerPoint and Tableau
Here are our plots:
Space Agency Data
We used the dataset of Meteorite Landings in NASA open data portal (https://data.nasa.gov/Space-Science/Meteorite-Landings/gh4g-9sfh). We used this particular dataset because it is fitted for statistical analysis , meaning that the dataset has few NA values, enough data (48000 rows). Also we were interested to find out where most meteorites are discovered.
Hackathon Journey
It was a very interesting experience to participate in this challenge, because it was a very well organized event, with useful speeches. We gained a lot of experience while constructing our project, but also by observing the presentations of other teams. Our mentors were very helpful too.
References
R
Tableau
https://data.nasa.gov/Space-Science/Meteorite-Landings/gh4g-9sfh
https://stackoverflow.com/
Tags
#stats