https://github.com/ropensci/writexl

Portable, light-weight data frame to xlsx exporter for R
https://github.com/ropensci/writexl

excel libxlsxwriter r r-package rstats xlsx

Last synced: about 2 months ago
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Portable, light-weight data frame to xlsx exporter for R

• Host: GitHub
• URL: https://github.com/ropensci/writexl
• Owner: ropensci
• License: other
• Created: 2017-08-20T23:10:57.000Z (over 7 years ago)
• Default Branch: master
• Last Pushed: 2024-09-09T17:49:58.000Z (3 months ago)
• Last Synced: 2024-09-09T21:58:06.198Z (3 months ago)
• Topics: excel, libxlsxwriter, r, r-package, rstats, xlsx
• Language: C
• Homepage: https://docs.ropensci.org/writexl
• Size: 731 KB
• Stars: 209
• Watchers: 15
• Forks: 17
• Open Issues: 24
• Metadata Files:
  • Readme: README.md
  • Changelog: NEWS
  • License: LICENSE

Awesome Lists containing this project

• jimsghstars - ropensci/writexl - Portable, light-weight data frame to xlsx exporter for R (C)

README

        
# writexl

[![Project Status: Active – The project has reached a stable, usable state and is being actively developed.](http://www.repostatus.org/badges/latest/active.svg)](http://www.repostatus.org/#active)

[![CRAN_Status_Badge](http://www.r-pkg.org/badges/version/writexl)](http://cran.r-project.org/package=writexl)

[![CRAN RStudio mirror downloads](http://cranlogs.r-pkg.org/badges/writexl)](http://cran.r-project.org/web/packages/writexl/index.html)

[![badge](https://ropensci.r-universe.dev/badges/writexl)](https://ropensci.r-universe.dev)

> Portable, light-weight data frame to xlsx exporter based on libxlsxwriter.  No Java or Excel required.

Wraps the [libxlsxwriter](https://github.com/jmcnamara/libxlsxwriter) library to create files

in Microsoft Excel 'xlsx' format.

## Installation

```r

install.packages("writexl")

```

## Getting started

Currently the package only has `write_xlsx()` to export a data frame to xlsx. 

```r

library(writexl)

library(readxl)

tmp <- writexl::write_xlsx(iris)

readxl::read_xlsx(tmp)

```

```

# A tibble: 150 x 5

   Sepal.Length Sepal.Width Petal.Length Petal.Width Species

                                   

 1          5.1         3.5          1.4         0.2  setosa

 2          4.9         3.0          1.4         0.2  setosa

 3          4.7         3.2          1.3         0.2  setosa

 4          4.6         3.1          1.5         0.2  setosa

 5          5.0         3.6          1.4         0.2  setosa

 6          5.4         3.9          1.7         0.4  setosa

 7          4.6         3.4          1.4         0.3  setosa

 8          5.0         3.4          1.5         0.2  setosa

 9          4.4         2.9          1.4         0.2  setosa

10          4.9         3.1          1.5         0.1  setosa

# ... with 140 more rows

```

Most data types should roundtrip with `readxl`:

```r

library(nycflights13)

out <- readxl::read_xlsx(writexl::write_xlsx(flights))

all.equal(out, flights)

## TRUE

```

Performance is a bit better than `openxlsx` implementation:

```r

library(microbenchmark)

library(nycflights13)

microbenchmark(

  writexl = writexl::write_xlsx(flights, tempfile()),

  openxlsx = openxlsx::write.xlsx(flights, tempfile()),

  times = 5

)

## Unit: seconds

##      expr       min        lq      mean    median        uq       max neval

##   writexl  8.884712  8.904431  9.103419  8.965643  9.041565  9.720743     5

##  openxlsx 17.166818 18.072527 19.171003 18.669805 18.756661 23.189206     5

```

Also the output xlsx files are smaller:

```r

writexl::write_xlsx(flights, tmp1 <- tempfile())

file.info(tmp1)$size

## 29157282

```

```r

openxlsx::write.xlsx(flights, tmp2 <- tempfile())

file.info(tmp2)$size

## 35962067

```