Using SQL for data consolidation in R
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 av...
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| Autores principales: | , , , , |
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| Formato: | Objeto de conferencia Resumen |
| Lenguaje: | Inglés |
| Publicado: |
2018
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| Materias: | |
| Acceso en línea: | http://sedici.unlp.edu.ar/handle/10915/72795 http://47jaiio.sadio.org.ar/sites/default/files/LatinR_57.pdf |
| Aporte de: |
| Sumario: | 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). |
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