Tools for Cleaning Up Messy Files

Some tools for cleaning up messy 'Excel' files to be suitable for R. People who have been working with 'Excel' for years built more or less complicated sheets with names, characters, formats that are not homogeneous. To be able to use them in R nowadays, we built a set of functions that will avoid the majority of importation problems and keep all the data at best.


the peep function allow you to "have a look" inside a dplyr workflow

library(thinkr)
library(dplyr)
data(iris)
iris %>% peep(head,summary) %>% plot
iris %>% peep_("head","summary") %>% plot
iris %>% peep(funs(head(.,n=2),summary(.,maxsum=2))) %>% plot
iris %>% peep(funs(summary(.,maxsum=2))) %>% plot

clean_names allow to cean dirty names

library(thinkr)
library(dplyr)
data(iris)
 
iris %>% head
iris %>% clean_names() %>% head
iris %>% clean_names() %>% head

Installation

# install.packages("devtools")
devtools::install_github("ThinkRstat/ThinkR")

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Reference manual

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install.packages("thinkr")

0.13 by Vincent Guyader, 9 months ago


Browse source code at https://github.com/cran/thinkr


Authors: Vincent Guyader [aut, cre]


Documentation:   PDF Manual  


GPL-3 license


Imports assertthat, devtools, dplyr, ggplot2, lazyeval, lubridate, magrittr, officer, stats, stringi, stringr, tidyr, utils, rvg

Suggests knitr, rmarkdown, covr, testthat


See at CRAN