The goal of ezpickr is to provide R beginners with a convenient way to pick up their data files and to easily import it as a tidy tibble form into an R environment using GUI file-picker dialogue box (through
ezpickr::pick()), and to provide R users with a convenient way to open and manipulate their data objects using Excel application for a seamless data communication between an Excel window and R session through
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, and .mbox files in an interactive GUI mode A file choose dialog box will be prompted.
Any additional arguments available for each file type and extension:
readr::read_csv() for CSV (Comma-Separated Values) files;
readr::read_csv2() for CSV2 (Semicolon-Separated Values) files;
readr::read_tsv() for ‘TSV’ (Tab-Separated Values) files;
readr::read_file() for ‘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;
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:
This 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)
You 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.