| dc.rights.license | All rights reserved | en_US |
| dc.contributor.advisor | Duffany, Jeffrey | |
| dc.contributor.author | Atiles Gil de Lamadrid, Ileana M. | |
| dc.date.accessioned | 2020-12-15T19:22:57Z | |
| dc.date.available | 2020-12-15T19:22:57Z | |
| dc.date.issued | 2019 | |
| dc.identifier.citation | Atiles Gil de Lamadrid, I. M. (2019). Meteorite landing data visualization with Python [Unpublished manuscript]. Graduate School, Polytechnic University of Puerto Rico. | en_US |
| dc.identifier.uri | http://hdl.handle.net/20.500.12475/1001 | |
| dc.description | Design Project Article for the Graduate Programs at Polytechnic University of Puerto Rico | en_US |
| dc.description.abstract | For billions of years, the Earth has
witnessed meteorite falls. Meteorites enter the
Earth’s atmosphere and land in more places than
others. Recording on meteorites has been based on
sighting and recovery. Many meteorites recoveries
had been possible to Earth’s conditions (such as
cold temperatures) and human dedication. This
project aims to corroborate data findings using
Python programming language in a JupyterLab web
environment. Data visualization of meteorites
sample data will help to analyze where they land the
most, which is the heaviest in mass and what year
had the most landings. Zipf’s law is considered as an
approach to investigate if meteorites hitting the
Earth follow any distribution pattern.
Key Terms ⎯ Data Visualization, JupyterLab,
Meteorite, Python3. | en_US |
| dc.language.iso | en_US | en_US |
| dc.publisher | Polytechnic University of Puerto Rico | en_US |
| dc.relation.ispartof | Computer Engineering; | |
| dc.relation.ispartofseries | Winter-2019; | |
| dc.relation.haspart | San Juan | en_US |
| dc.subject.lcsh | Meteorites | en_US |
| dc.subject.lcsh | Python (Computer program language) | |
| dc.subject.lcsh | Polytechnic University of Puerto Rico--Graduate students--Research | |
| dc.subject.lcsh | Polytechnic University of Puerto Rico--Graduate students--Posters | |
| dc.title | Meteorite Landing Data Visualization with Python | en_US |
| dc.type | Article | en_US |
| dc.rights.holder | Polytechnic University of Puerto Rico, Graduate School | en_US |
