Using SQL for data consolidation in R

Autores
Vinas Forcade, Jennifer; Nacci, Julien; Mels, Cindy; Valcke, Martin; Derluyn, Ilse
Año de publicación
2018
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Working with multiple data sources implies data cleaning and consolidation prior to analysis. R has become popular among social scientists (Kelley, 2007; Clark, 2014), who are advised to screen data in a “favorite spreadsheet program” (Muenchen, 2011:21), before importing it to R. This way, users avoid typing in the R console and are supported by a graphical user interface. Even for experienced R users, querying/ retrieving data from multiple large sources takes a lot of computing power, which is better handled by SQL language (Table 2; KeyCentrix, 2015).
Sociedad Argentina de Informática e Investigación Operativa
Materia
Ciencias Informáticas
SQL
sqldf, R
database consolidation
data cleaning
R.
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-sa/3.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/72795
Acceder
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network_name_str SEDICI (UNLP)
spelling Using SQL for data consolidation in RVinas Forcade, JenniferNacci, JulienMels, CindyValcke, MartinDerluyn, IlseCiencias InformáticasSQLsqldf, Rdatabase consolidationdata cleaningR.Working with multiple data sources implies data cleaning and consolidation prior to analysis. R has become popular among social scientists (Kelley, 2007; Clark, 2014), who are advised to screen data in a “favorite spreadsheet program” (Muenchen, 2011:21), before importing it to R. This way, users avoid typing in the R console and are supported by a graphical user interface. Even for experienced R users, querying/ retrieving data from multiple large sources takes a lot of computing power, which is better handled by SQL language (Table 2; KeyCentrix, 2015).Sociedad Argentina de Informática e Investigación Operativa2018-09info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionResumenhttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdfhttp://sedici.unlp.edu.ar/handle/10915/72795enginfo:eu-repo/semantics/altIdentifier/url/http://47jaiio.sadio.org.ar/sites/default/files/LatinR_57.pdfinfo:eu-repo/semantics/altIdentifier/issn/2618-3196info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-sa/3.0/Creative Commons Attribution-ShareAlike 3.0 Unported (CC BY-SA 3.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T11:12:04Zoai:sedici.unlp.edu.ar:10915/72795Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:12:04.608SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Using SQL for data consolidation in R
title Using SQL for data consolidation in R
spellingShingle Using SQL for data consolidation in R
Vinas Forcade, Jennifer
Ciencias Informáticas
SQL
sqldf, R
database consolidation
data cleaning
R.
title_short Using SQL for data consolidation in R
title_full Using SQL for data consolidation in R
title_fullStr Using SQL for data consolidation in R
title_full_unstemmed Using SQL for data consolidation in R
title_sort Using SQL for data consolidation in R
dc.creator.none.fl_str_mv Vinas Forcade, Jennifer
Nacci, Julien
Mels, Cindy
Valcke, Martin
Derluyn, Ilse
author Vinas Forcade, Jennifer
author_facet Vinas Forcade, Jennifer
Nacci, Julien
Mels, Cindy
Valcke, Martin
Derluyn, Ilse
author_role author
author2 Nacci, Julien
Mels, Cindy
Valcke, Martin
Derluyn, Ilse
author2_role author
author
author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
SQL
sqldf, R
database consolidation
data cleaning
R.
topic Ciencias Informáticas
SQL
sqldf, R
database consolidation
data cleaning
R.
dc.description.none.fl_txt_mv Working with multiple data sources implies data cleaning and consolidation prior to analysis. R has become popular among social scientists (Kelley, 2007; Clark, 2014), who are advised to screen data in a “favorite spreadsheet program” (Muenchen, 2011:21), before importing it to R. This way, users avoid typing in the R console and are supported by a graphical user interface. Even for experienced R users, querying/ retrieving data from multiple large sources takes a lot of computing power, which is better handled by SQL language (Table 2; KeyCentrix, 2015).
Sociedad Argentina de Informática e Investigación Operativa
description Working with multiple data sources implies data cleaning and consolidation prior to analysis. R has become popular among social scientists (Kelley, 2007; Clark, 2014), who are advised to screen data in a “favorite spreadsheet program” (Muenchen, 2011:21), before importing it to R. This way, users avoid typing in the R console and are supported by a graphical user interface. Even for experienced R users, querying/ retrieving data from multiple large sources takes a lot of computing power, which is better handled by SQL language (Table 2; KeyCentrix, 2015).
publishDate 2018
dc.date.none.fl_str_mv 2018-09
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
Resumen
http://purl.org/coar/resource_type/c_5794
info:ar-repo/semantics/documentoDeConferencia
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status_str publishedVersion
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dc.language.none.fl_str_mv eng
language eng
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info:eu-repo/semantics/altIdentifier/issn/2618-3196
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
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Creative Commons Attribution-ShareAlike 3.0 Unported (CC BY-SA 3.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-sa/3.0/
Creative Commons Attribution-ShareAlike 3.0 Unported (CC BY-SA 3.0)
dc.format.none.fl_str_mv application/pdf
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repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
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