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The only goal of readODS is to enable R to read and write OpenDocument Spreadsheet (ODS) files.
Install the latest stable version from CRAN:
install.packages("readODS")
Or install the development version from Github:
devtools::install_github("chainsawriot/readODS")
In almost all use cases, you only need two functions: read_ods and
write_ods. Simple.
library(readODS)
read_ods("starwars.ods")
#> Name homeworld species
#> 1 Luke Skywalker Tatooine Human
#> 2 C-3PO Tatooine Human
#> 3 R2-D2 Alderaan Human
#> 4 Darth Vader Tatooine Human
#> 5 Leia Organa Tatooine Human
#> 6 Owen Lars Tatooine Human
#> 7 Beru Whitesun lars Stewjon Human
#> 8 R5-D4 Tatooine Human
#> 9 Biggs Darklighter Kashyyyk Wookiee
#> 10 Obi-Wan Kenobi Corellia Human
Reading from the 2nd sheet
read_ods("starwars.ods", sheet = 2)
#> Name height mass hair_color skin_color eye_color birth_year
#> 1 Luke Skywalker 172 77 blond fair blue 19.0
#> 2 C-3PO 202 136 none white yellow 41.9
#> 3 R2-D2 150 49 brown light brown 19.0
#> 4 Darth Vader 178 120 brown, grey light blue 52.0
#> 5 Leia Organa 165 75 brown light blue 47.0
#> 6 Owen Lars 183 84 black light brown 24.0
#> 7 Beru Whitesun lars 182 77 auburn, white fair blue-gray 57.0
#> 8 R5-D4 188 84 blond fair blue 41.9
#> 9 Biggs Darklighter 228 112 brown unknown blue 200.0
#> 10 Obi-Wan Kenobi 180 80 brown fair brown 29.0
#> gender
#> 1 male
#> 2 male
#> 3 female
#> 4 male
#> 5 female
#> 6 male
#> 7 male
#> 8 male
#> 9 male
#> 10 male
Reading from a specific range
read_ods("starwars.ods", sheet = 2, range = "A1:C11")
#> Name height mass
#> 1 Luke Skywalker 172 77
#> 2 C-3PO 202 136
#> 3 R2-D2 150 49
#> 4 Darth Vader 178 120
#> 5 Leia Organa 165 75
#> 6 Owen Lars 183 84
#> 7 Beru Whitesun lars 182 77
#> 8 R5-D4 188 84
#> 9 Biggs Darklighter 228 112
#> 10 Obi-Wan Kenobi 180 80
## preserve the row names
write_ods(mtcars, "mtcars.ods", row_names = TRUE)
Appending a sheet
write_ods(PlantGrowth, "mtcars.ods", append = TRUE, sheet = "plant")
## Default: First sheet
read_ods("mtcars.ods")
#> Warning: Missing column names filled in: 'X1' [1]
#> NA mpg cyl disp hp drat wt qsec vs am gear carb
#> 1 Mazda RX4 21.0 6 160.0 110 3.90 2.620 16.46 0 1 4 4
#> 2 Mazda RX4 Wag 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4 4
#> 3 Datsun 710 22.8 4 108.0 93 3.85 2.320 18.61 1 1 4 1
#> 4 Hornet 4 Drive 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3 1
#> 5 Hornet Sportabout 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2
#> 6 Valiant 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3 1
#> 7 Duster 360 14.3 8 360.0 245 3.21 3.570 15.84 0 0 3 4
#> 8 Merc 240D 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4 2
#> 9 Merc 230 22.8 4 140.8 95 3.92 3.150 22.90 1 0 4 2
#> 10 Merc 280 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4 4
#> 11 Merc 280C 17.8 6 167.6 123 3.92 3.440 18.90 1 0 4 4
#> 12 Merc 450SE 16.4 8 275.8 180 3.07 4.070 17.40 0 0 3 3
#> 13 Merc 450SL 17.3 8 275.8 180 3.07 3.730 17.60 0 0 3 3
#> 14 Merc 450SLC 15.2 8 275.8 180 3.07 3.780 18.00 0 0 3 3
#> 15 Cadillac Fleetwood 10.4 8 472.0 205 2.93 5.250 17.98 0 0 3 4
#> 16 Lincoln Continental 10.4 8 460.0 215 3.00 5.424 17.82 0 0 3 4
#> 17 Chrysler Imperial 14.7 8 440.0 230 3.23 5.345 17.42 0 0 3 4
#> 18 Fiat 128 32.4 4 78.7 66 4.08 2.200 19.47 1 1 4 1
#> 19 Honda Civic 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2
#> 20 Toyota Corolla 33.9 4 71.1 65 4.22 1.835 19.90 1 1 4 1
#> 21 Toyota Corona 21.5 4 120.1 97 3.70 2.465 20.01 1 0 3 1
#> 22 Dodge Challenger 15.5 8 318.0 150 2.76 3.520 16.87 0 0 3 2
#> 23 AMC Javelin 15.2 8 304.0 150 3.15 3.435 17.30 0 0 3 2
#> 24 Camaro Z28 13.3 8 350.0 245 3.73 3.840 15.41 0 0 3 4
#> 25 Pontiac Firebird 19.2 8 400.0 175 3.08 3.845 17.05 0 0 3 2
#> 26 Fiat X1-9 27.3 4 79.0 66 4.08 1.935 18.90 1 1 4 1
#> 27 Porsche 914-2 26.0 4 120.3 91 4.43 2.140 16.70 0 1 5 2
#> 28 Lotus Europa 30.4 4 95.1 113 3.77 1.513 16.90 1 1 5 2
#> 29 Ford Pantera L 15.8 8 351.0 264 4.22 3.170 14.50 0 1 5 4
#> 30 Ferrari Dino 19.7 6 145.0 175 3.62 2.770 15.50 0 1 5 6
#> 31 Maserati Bora 15.0 8 301.0 335 3.54 3.570 14.60 0 1 5 8
#> 32 Volvo 142E 21.4 4 121.0 109 4.11 2.780 18.60 1 1 4 2
read_ods("mtcars.ods", sheet = "plant", range = "A1:B10")
#> weight group
#> 1 4.17 ctrl
#> 2 5.58 ctrl
#> 3 5.18 ctrl
#> 4 6.11 ctrl
#> 5 4.50 ctrl
#> 6 4.61 ctrl
#> 7 5.17 ctrl
#> 8 4.53 ctrl
#> 9 5.33 ctrl
This package is written entirely in R. Although the efficiency has been improved, please don’t expect the heavily optimized performance of readxl, readr and data.table’s fread.
Also, this package can’t handle ODS files larger than “medium size”. See issue #71.
If you need to read and write large ODS files efficiently, the headless interface of LibreOffice is recommended. See issue #49 for an example.
The logo of readODS is a remix of LibreOffice Calc v6.1 icon created by the Document Foundation. The original LibreOffice logo is licensed under the Creative Commons Attribution Share-Alike 3.0 Unported License. readODS is not a product of the Document Foundation. The logo of readODS is licensed under the Creative Commons Attribution Share-Alike 3.0 Unported License.
The creator of this package is Gerrit-Jan Schutten. The current maintainer is Chung-hong Chan. This package benefits from contributions by Thomas J. Leeper, John Foster, Sergio Oller, Jim Hester, Stephen Watts, Arthur Katossky, Stas Malavin, Duncan Garmonsway, and Mehrad Mahmoudian.
This package emulates the behaviors of readxl::read_xlsx,
writexl::write_xlsx and xlsx::write.xlsx.
This package should be a silent member of rio, so that you don’t need
to care about file format anymore.
GPL3
Contributions in the form of feedback, comments, code, and bug report are welcome.
Please note that the readODS project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.
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