The goal of ezpickr is to provide R beginners with a convenient way to pick up their data files in a tidy tibble form into an R environment using GUI file-picker dialogue box (ezpickr::pick()
), and to open and manipulate their data objects using Excel application for a seamless data communication between an Excel and R session (ezpickr::viewxl()
).
You can alternatively use ezpickr::pick()
function for choosing .csv, .csv2, .tsv, .txt, .xls, .xlsx, .json, .html, .htm, .php, .pdf, .doc, .docx, .rtf, .RData, .Rda, .RDS, .sav (SPSS), .por, .sas7bdat, .sas7bcat, .dta, .xpt, .mbox, and *.Rmd files in an interactive GUI mode A file choose dialog box will be prompted.
Any additional arguments available for each file type and extension: vroom::vroom()
for ‘CSV’ (Comma-Separated Values); ‘CSV2’ (Semicolon-Separated Values); ‘TSV’ (Tab-Separated Values)‘txt’ (plain text) files; readxl::read_excel()
for ‘Excel’ files; haven::read_spss()
for ‘SPSS’ files; haven::read_stata()
for ‘Stata’ files; haven::read_sas()
for ‘SAS’ files; textreadr::read_document()
for ‘Microsoft Word’, ‘PDF’, ‘RTF’, ‘HTML’, ‘HTM’, and ‘PHP’ files; jsonlite::fromJSON()
for ‘JSON’ files; mboxr::read_mbox()
for ‘mbox’ files; rmarkdown::render()
for ‘Rmd’ files; base::source()
for ‘R’ files; base::readRDS()
for ‘RDS’ files; base::load()
for ‘RDA’ and ‘RDATA’ files.
Each corresponding function depending upon a file extension will be automatically matched and applied once you pick up your file using either the GUI-file-chooser dialog box or explicit path/to/filename.
You can install the latest development version as follows:
if(!require(remotes)) {
install.packages("remotes")
}
remotes::install_github('jooyoungseo/ezpickr')
You can install the released version of ezpickr from CRAN with:
install.packages("ezpickr")
pick()
FunctionThis is a basic example which shows you how to import data files:
library(ezpickr)
# Choosing file and saving it into a variable
## Scenario 1: Picking up a file using interactive GUI dialog box:
data <- pick() ## Please use `picko()` instead if your path/file contains any Korean characters.
## Scenario 2: Picking up a file using an explicit file name ("test.sav" in the example below; however, you can feed other files through this function such as *.SAS, *.DTA, *.csv, *.csv2, *.tsv, *.xlsx, *.txt, *.html, webpage URL, *.json, *.Rda, *.Rdata, and more):
data <- pick("test.sav") ## Please use `picko("test.sav")` instead if your path/file contains any Korean characters.
# Now you can use the imported file as a tibble data frame.
str(data)
viewxl()
FunctionYou can open any data.frame, tibble, matrix, table or vector from an R session into your default-set spreadsheet application window as follows:
library(ezpickr)
data(airquality)
str(airquality)
# Use `viewxl()` function to open your data object in your spreadsheet:
viewxl(airquality)
# Then, when necessary, you can modify the opened data in the spreadsheet and save it as a new data.
# You can pass a list object to the `viewxl()` function like below:
l <- list(iris = iris, mtcars = mtcars, chickwts = chickwts, quakes = quakes)
viewxl(l)
# Then, each list item will appear in your Excel window sheet by sheet.