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.
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.