Application of Python Libraries for real-time data processing: The analysis of social isolation data in the State of Santa Catarina

Detalhes bibliográficos
Autor(a) principal: Vicentainer, Denis
Data de Publicação: 2020
Outros Autores: Mattedi, Marcos, Mello, Bruno
Tipo de documento: Artigo
Idioma: por
Título da fonte: Metodologias e Aprendizado
Texto Completo: https://publicacoes.ifc.edu.br/index.php/metapre/article/view/1392
Resumo: The need to watch the spread of Covid-19 (Sars-Cov-2) has raised an unprecedented demand for data storage, processing and analysis. This demand imposes on researchers a faster storage, processing and availability of data for viewing by society and public managers. For that, the common data manipulation tools proved to be inefficient in keeping up with the new demands. Considering these factors, this article aims to explore the solution for processing and mapping data from different bases through Python libraries. The Python language has been noted for its variety of libraries aimed at the field of data science, increasing its efficiency as a tool for processing and analyzing data and statistics. To illustrate this process, the treatment of social isolation data in the State of Santa Catarina will be considered between February and May 2020. The text is divided into three parts, in which: i) operational assumptions and installation of libraries; ii) cleaning and analysis of the social isolation data in Santa Catarina and; iii) elaboration of the mapping, generating a map as a product. This test made it possible, in a practical way, to discover and manipulate inconsistencies in the data, resulting in a faster, more assertive product and ready to be made available.
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spelling Application of Python Libraries for real-time data processing: The analysis of social isolation data in the State of Santa CatarinaAplicación de bibliotecas de Python para el procesamiento de datos en tiempo real: El análisis de datos de aislamiento social en el Estado de Santa CatarinaAplicação das bibliotecas Python para tratamento de dados em tempo real: A análise dos dados de isolamento social em Santa CatarinaPython; ciência de dados; sistemas de informações geográficas (SIG), covid-19Python; data science; geographic information system (GIS); covid-19.Python; Ciencia de los datos; sistemas de información geográfica (SIG), covid-19The need to watch the spread of Covid-19 (Sars-Cov-2) has raised an unprecedented demand for data storage, processing and analysis. This demand imposes on researchers a faster storage, processing and availability of data for viewing by society and public managers. For that, the common data manipulation tools proved to be inefficient in keeping up with the new demands. Considering these factors, this article aims to explore the solution for processing and mapping data from different bases through Python libraries. The Python language has been noted for its variety of libraries aimed at the field of data science, increasing its efficiency as a tool for processing and analyzing data and statistics. To illustrate this process, the treatment of social isolation data in the State of Santa Catarina will be considered between February and May 2020. The text is divided into three parts, in which: i) operational assumptions and installation of libraries; ii) cleaning and analysis of the social isolation data in Santa Catarina and; iii) elaboration of the mapping, generating a map as a product. This test made it possible, in a practical way, to discover and manipulate inconsistencies in the data, resulting in a faster, more assertive product and ready to be made available.La necesidad de observar la propagación de Covid-19 (Sars-Cov-2) ha generado una demanda sin precedentes de almacenamiento, procesamiento y análisis de datos. Esta demanda impone a los investigadores un almacenamiento, procesamiento y disponibilidad más rápidos de los datos para su visualización por parte de la sociedad y los administradores públicos. Por eso, las herramientas comunes de manipulación de datos demostraron ser ineficientes para mantenerse al día con las nuevas demandas. Teniendo en cuenta estos factores, este artículo tiene como objetivo explorar la solución para procesar y mapear datos de diferentes bases a través de bibliotecas de Python. El lenguaje Python se ha destacado por su variedad de librerías dirigidas al campo de la ciencia de datos, aumentando su eficiencia como herramienta para procesar y analizar datos y estadísticas. Para ilustrar este proceso, se considerará el tratamiento de los datos de aislamiento social en el Estado de Santa Catarina entre febrero y mayo de 2020. El texto se divide en tres partes, en las que: i) supuestos operativos e instalación de bibliotecas; ii) limpieza y análisis de los datos de aislamiento social en Santa Catarina y; iii) elaboración del mapeo, generando un mapa como producto. Esta prueba permitió, de manera práctica, descubrir y manipular inconsistencias en los datos, dando como resultado un producto más rápido, asertivo y listo para ser puesto a disposición.A necessidade de monitorar a propagação do Covid-19 (Sars-Cov-2) fez emergir uma demanda, sem precedentes, por armazenamento, tratamento e análise de dados. Esta demanda impõe aos pesquisadores maior celeridade e agilidade no armazenamento, tratamento e disponibilização do dado para visualização da sociedade e de gestores públicos. Para tanto, as ferramentas comuns de manipulação de dados se mostraram pouco eficientes em acompanhar as novas demandas. Considerando estes fatores, o presente artigo objetiva explorar a solução de tratamento e mapeamento de dados de diferentes bases através de bibliotecas Python. A linguagem Python tem se notabilizado por sua variedade de bibliotecas direcionadas para a área de ciência de dados, aumentando sua eficiência enquanto ferramenta de tratamento e análise de dados e estatísticas. Para ilustrar este processo será considerado o de tratamento de dados de isolamento social no Estado de Santa Catarina entre fevereiro e maio de 2020. O texto está dividido em três partes, nas quais: i) pressupostos operacionais e instalação das bibliotecas; ii) limpeza e análise do dado de isolamento social em Santa Catarina e; iii) elaboração do mapeamento, gerando um mapa como produto. Este ensaio possibilitou, de forma prática, descobrir e manipular inconsistências no dado, resultando em um produto mais rápido, assertivo e pronto para ser disponibilizado.Instituto Federal Catarinense2020-10-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://publicacoes.ifc.edu.br/index.php/metapre/article/view/139210.21166/metapre.v3i0.1392Methodologies and Learning; Vol. 3 (2020): OVID-19/Coronavirus Mapping; 206 - 217Metodologías y Aprendizaje; Vol. 3 (2020): Mapeando COVID-19/Coronavirus; 206 - 217Metodologias e Aprendizado ; v. 3 (2020): Mapeando COVID-19/Coronavirus; 206 - 2172674-9009reponame:Metodologias e Aprendizadoinstname:Instituto Federal de Educação, Ciência e Tecnologia Catarinense (IFC)instacron:IFCporhttps://publicacoes.ifc.edu.br/index.php/metapre/article/view/1392/1061Copyright (c) 2020 Denis Vicentainer, Marcos Mattedi, Bruno Melloinfo:eu-repo/semantics/openAccessVicentainer, DenisMattedi, MarcosMello, Bruno2020-12-03T18:53:25Zoai:ojs2.publicacoes.ifc.edu.br:article/1392Revistahttps://publicacoes.ifc.edu.br/index.php/metaprePUBhttps://publicacoes.ifc.edu.br/index.php/metapre/oaieduardo.ribeiro@ifc.edu.br2674-90092674-9009opendoar:2020-12-03T18:53:25Metodologias e Aprendizado - Instituto Federal de Educação, Ciência e Tecnologia Catarinense (IFC)false
dc.title.none.fl_str_mv Application of Python Libraries for real-time data processing: The analysis of social isolation data in the State of Santa Catarina
Aplicación de bibliotecas de Python para el procesamiento de datos en tiempo real: El análisis de datos de aislamiento social en el Estado de Santa Catarina
Aplicação das bibliotecas Python para tratamento de dados em tempo real: A análise dos dados de isolamento social em Santa Catarina
title Application of Python Libraries for real-time data processing: The analysis of social isolation data in the State of Santa Catarina
spellingShingle Application of Python Libraries for real-time data processing: The analysis of social isolation data in the State of Santa Catarina
Vicentainer, Denis
Python; ciência de dados; sistemas de informações geográficas (SIG), covid-19
Python; data science; geographic information system (GIS); covid-19.
Python; Ciencia de los datos; sistemas de información geográfica (SIG), covid-19
title_short Application of Python Libraries for real-time data processing: The analysis of social isolation data in the State of Santa Catarina
title_full Application of Python Libraries for real-time data processing: The analysis of social isolation data in the State of Santa Catarina
title_fullStr Application of Python Libraries for real-time data processing: The analysis of social isolation data in the State of Santa Catarina
title_full_unstemmed Application of Python Libraries for real-time data processing: The analysis of social isolation data in the State of Santa Catarina
title_sort Application of Python Libraries for real-time data processing: The analysis of social isolation data in the State of Santa Catarina
author Vicentainer, Denis
author_facet Vicentainer, Denis
Mattedi, Marcos
Mello, Bruno
author_role author
author2 Mattedi, Marcos
Mello, Bruno
author2_role author
author
dc.contributor.author.fl_str_mv Vicentainer, Denis
Mattedi, Marcos
Mello, Bruno
dc.subject.por.fl_str_mv Python; ciência de dados; sistemas de informações geográficas (SIG), covid-19
Python; data science; geographic information system (GIS); covid-19.
Python; Ciencia de los datos; sistemas de información geográfica (SIG), covid-19
topic Python; ciência de dados; sistemas de informações geográficas (SIG), covid-19
Python; data science; geographic information system (GIS); covid-19.
Python; Ciencia de los datos; sistemas de información geográfica (SIG), covid-19
description The need to watch the spread of Covid-19 (Sars-Cov-2) has raised an unprecedented demand for data storage, processing and analysis. This demand imposes on researchers a faster storage, processing and availability of data for viewing by society and public managers. For that, the common data manipulation tools proved to be inefficient in keeping up with the new demands. Considering these factors, this article aims to explore the solution for processing and mapping data from different bases through Python libraries. The Python language has been noted for its variety of libraries aimed at the field of data science, increasing its efficiency as a tool for processing and analyzing data and statistics. To illustrate this process, the treatment of social isolation data in the State of Santa Catarina will be considered between February and May 2020. The text is divided into three parts, in which: i) operational assumptions and installation of libraries; ii) cleaning and analysis of the social isolation data in Santa Catarina and; iii) elaboration of the mapping, generating a map as a product. This test made it possible, in a practical way, to discover and manipulate inconsistencies in the data, resulting in a faster, more assertive product and ready to be made available.
publishDate 2020
dc.date.none.fl_str_mv 2020-10-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://publicacoes.ifc.edu.br/index.php/metapre/article/view/1392
10.21166/metapre.v3i0.1392
url https://publicacoes.ifc.edu.br/index.php/metapre/article/view/1392
identifier_str_mv 10.21166/metapre.v3i0.1392
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv https://publicacoes.ifc.edu.br/index.php/metapre/article/view/1392/1061
dc.rights.driver.fl_str_mv Copyright (c) 2020 Denis Vicentainer, Marcos Mattedi, Bruno Mello
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2020 Denis Vicentainer, Marcos Mattedi, Bruno Mello
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Instituto Federal Catarinense
publisher.none.fl_str_mv Instituto Federal Catarinense
dc.source.none.fl_str_mv Methodologies and Learning; Vol. 3 (2020): OVID-19/Coronavirus Mapping; 206 - 217
Metodologías y Aprendizaje; Vol. 3 (2020): Mapeando COVID-19/Coronavirus; 206 - 217
Metodologias e Aprendizado ; v. 3 (2020): Mapeando COVID-19/Coronavirus; 206 - 217
2674-9009
reponame:Metodologias e Aprendizado
instname:Instituto Federal de Educação, Ciência e Tecnologia Catarinense (IFC)
instacron:IFC
instname_str Instituto Federal de Educação, Ciência e Tecnologia Catarinense (IFC)
instacron_str IFC
institution IFC
reponame_str Metodologias e Aprendizado
collection Metodologias e Aprendizado
repository.name.fl_str_mv Metodologias e Aprendizado - Instituto Federal de Educação, Ciência e Tecnologia Catarinense (IFC)
repository.mail.fl_str_mv eduardo.ribeiro@ifc.edu.br
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