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dc.rights.licenseAll rights reserveden_US
dc.contributor.advisorDuffany, Jeffrey
dc.contributor.authorAtiles Gil de Lamadrid, Ileana M.
dc.date.accessioned2020-12-15T19:22:57Z
dc.date.available2020-12-15T19:22:57Z
dc.date.issued2019
dc.identifier.citationAtiles 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 Meteorite landing data visualization with Python [Unpublished manuscript].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.urihttp://hdl.handle.net/20.500.12475/1001
dc.descriptionDesign Project Article for the Graduate Programs at Polytechnic University of Puerto Ricoen_US
dc.description.abstractFor 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.isoen_USen_US
dc.publisherPolytechnic University of Puerto Ricoen_US
dc.relation.ispartofComputer Engineering;
dc.relation.ispartofseriesWinter-2019;
dc.relation.haspartSan Juanen_US
dc.subject.lcshMeteoritesen_US
dc.subject.lcshPython (Computer program language)
dc.subject.lcshPolytechnic University of Puerto Rico--Graduate students--Research
dc.subject.lcshPolytechnic University of Puerto Rico--Graduate students--Posters
dc.titleMeteorite Landing Data Visualization with Pythonen_US
dc.typeArticleen_US
dc.rights.holderPolytechnic University of Puerto Rico, Graduate Schoolen_US


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