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.

1.1 Installation

1.1.1 Development Version

You can install the latest development version as follows:

if(!require(remotes)) {


1.1.2 Stable Version

You can install the released version of ezpickr from CRAN with:


1.2 Example

1.2.1 Usage of the pick() Function

This is a basic example which shows you how to import data files:


# 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.

1.2.2 Usage of the viewxl() Function

You can open any data.frame, tibble, matrix, table or vector from an R session into your default-set spreadsheet application window as follows:



# Use `viewxl()` function to open your data object in your spreadsheet:

# 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)
# Then, each list item will appear in your Excel window sheet by sheet.