Big Data Preprocessing Architecture

Provide a tool to easily build customized data flows to pre-process large volumes of information from different sources. To this end, 'bdpar' allows to (i) easily use and create new functionalities and (ii) develop new data source extractors according to the user needs. Additionally, the package provides by default a predefined data flow to extract and pre-process the most relevant information (tokens, dates, ... ) from some textual sources (SMS, Email, tweets, YouTube comments).


Reference manual

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1.0.1 by Miguel Ferreiro-Díaz, a month ago

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Browse source code at

Authors: Miguel Ferreiro-Díaz [aut, cre] , David Ruano-Ordás [aut, ctr] , Tomás R. Cotos-Yañez [aut, ctr] , University of Vigo [cph]

Documentation:   PDF Manual  

GPL-3 license

Imports ini, magrittr, pipeR, purrr, R6, rlist, svMisc, tools, utils

Suggests cld2, knitr, readr, rex, rjson, rmarkdown, rtweet, stringi, stringr, testthat, textutils, tuber

System requirements: Python (>= 2.7)

See at CRAN