An Overview of readODS

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Chung-hong Chan ¹

You probably only need to use two functions from this package: read_ods and write_ods.

Write the data PlantGrowth (from the built-in datasets package) as a new file plant.ods in the current working directory of the user’s session.

Update and Append

You can append another sheet into an existing ods file with the sheet name being “mtcars_ods”.

write_ods(mtcars, "plant.ods", sheet = "mtcars_ods", append = TRUE)

Read from a specific sheet. Notice row names are missing.

read_ods("plant.ods", sheet = "mtcars_ods")
#> # A tibble: 32 × 11
#>      mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb
#>    <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#>  1  21       6  160    110  3.9   2.62  16.5     0     1     4     4
#>  2  21       6  160    110  3.9   2.88  17.0     0     1     4     4
#>  3  22.8     4  108     93  3.85  2.32  18.6     1     1     4     1
#>  4  21.4     6  258    110  3.08  3.22  19.4     1     0     3     1
#>  5  18.7     8  360    175  3.15  3.44  17.0     0     0     3     2
#>  6  18.1     6  225    105  2.76  3.46  20.2     1     0     3     1
#>  7  14.3     8  360    245  3.21  3.57  15.8     0     0     3     4
#>  8  24.4     4  147.    62  3.69  3.19  20       1     0     4     2
#>  9  22.8     4  141.    95  3.92  3.15  22.9     1     0     4     2
#> 10  19.2     6  168.   123  3.92  3.44  18.3     1     0     4     4
#> # ℹ 22 more rows

You can also integer for sheet, e.g. 2 for the second sheet.

read_ods("plant.ods", sheet = 2)
#> # A tibble: 32 × 11
#>      mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb
#>    <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#>  1  21       6  160    110  3.9   2.62  16.5     0     1     4     4
#>  2  21       6  160    110  3.9   2.88  17.0     0     1     4     4
#>  3  22.8     4  108     93  3.85  2.32  18.6     1     1     4     1
#>  4  21.4     6  258    110  3.08  3.22  19.4     1     0     3     1
#>  5  18.7     8  360    175  3.15  3.44  17.0     0     0     3     2
#>  6  18.1     6  225    105  2.76  3.46  20.2     1     0     3     1
#>  7  14.3     8  360    245  3.21  3.57  15.8     0     0     3     4
#>  8  24.4     4  147.    62  3.69  3.19  20       1     0     4     2
#>  9  22.8     4  141.    95  3.92  3.15  22.9     1     0     4     2
#> 10  19.2     6  168.   123  3.92  3.44  18.3     1     0     4     4
#> # ℹ 22 more rows

Update an existing sheet and preserve row names

write_ods(mtcars, "plant.ods", sheet = "mtcars_ods", update = TRUE, row_names = TRUE)

Notice the information from the sheet mtcars_ods is updated.

read_ods("plant.ods", sheet = "mtcars_ods")
#> New names:
#> • `` -> `...1`
#> # A tibble: 32 × 12
#>    ...1          mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb
#>    <chr>       <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#>  1 Mazda RX4    21       6  160    110  3.9   2.62  16.5     0     1     4     4
#>  2 Mazda RX4 …  21       6  160    110  3.9   2.88  17.0     0     1     4     4
#>  3 Datsun 710   22.8     4  108     93  3.85  2.32  18.6     1     1     4     1
#>  4 Hornet 4 D…  21.4     6  258    110  3.08  3.22  19.4     1     0     3     1
#>  5 Hornet Spo…  18.7     8  360    175  3.15  3.44  17.0     0     0     3     2
#>  6 Valiant      18.1     6  225    105  2.76  3.46  20.2     1     0     3     1
#>  7 Duster 360   14.3     8  360    245  3.21  3.57  15.8     0     0     3     4
#>  8 Merc 240D    24.4     4  147.    62  3.69  3.19  20       1     0     4     2
#>  9 Merc 230     22.8     4  141.    95  3.92  3.15  22.9     1     0     4     2
#> 10 Merc 280     19.2     6  168.   123  3.92  3.44  18.3     1     0     4     4
#> # ℹ 22 more rows

Read from a specific range

read_ods("plant.ods", sheet = "mtcars_ods", range = "A1:C10")
#> New names:
#> • `` -> `...1`
#> # A tibble: 9 × 3
#>   ...1                mpg   cyl
#>   <chr>             <dbl> <dbl>
#> 1 Mazda RX4          21       6
#> 2 Mazda RX4 Wag      21       6
#> 3 Datsun 710         22.8     4
#> 4 Hornet 4 Drive     21.4     6
#> 5 Hornet Sportabout  18.7     8
#> 6 Valiant            18.1     6
#> 7 Duster 360         14.3     8
#> 8 Merc 240D          24.4     4
#> 9 Merc 230           22.8     4

You cannot append to an existing sheet.

write_ods(iris, "plant.ods", sheet = "mtcars_ods", append = TRUE)
#> Error: Sheet mtcars_ods exists. Set update to TRUE is you want to update this sheet.

You cannot update a missing sheet.

write_ods(iris, "plant.ods", sheet = "iris", update = TRUE)
#> Error: Sheet iris does not exist. Cannot update.

Writing multiple sheets simultaneously

It is much faster to write data frames into the same file by putting them in a (named) list.

write_ods(list("iris" = iris, "plant" = PlantGrowth), "plant_multi.ods")
read_ods("plant_multi.ods", sheet = "plant")
#> # A tibble: 30 × 2
#>    weight group
#>     <dbl> <chr>
#>  1   4.17 ctrl 
#>  2   5.58 ctrl 
#>  3   5.18 ctrl 
#>  4   6.11 ctrl 
#>  5   4.5  ctrl 
#>  6   4.61 ctrl 
#>  7   5.17 ctrl 
#>  8   4.53 ctrl 
#>  9   5.33 ctrl 
#> 10   5.14 ctrl 
#> # ℹ 20 more rows

Flat ODS files (`.xml` or `.fods`)

Can be read with read_ods() ² (note that the same function is used to read flat files, no matter the extension). This has the same behaviour and arguments as read_ods()

read_fods("plant.fods")

write_ods() can be used to write Flat ODS files

write_ods(PlantGrowth, "plant.fods")

Misc.

Use the function list_ods_sheets() to list out all sheets in an (F)ODS file.

list_ods_sheets("plant.ods")
#> [1] "Sheet1"     "mtcars_ods"

readODS 2.0.0

Starting from 2.0.0, write_ods writes NA as empty by default.

PlantGrowth2 <- tibble::as_tibble(PlantGrowth)
PlantGrowth2[1,1] <- NA
PlantGrowth2$group <- as.character(PlantGrowth2$group)

## NA is preseved; weight is still <dbl>
read_ods(write_ods(PlantGrowth2))
#> # A tibble: 30 × 2
#>    weight group
#>     <dbl> <chr>
#>  1  NA    ctrl 
#>  2   5.58 ctrl 
#>  3   5.18 ctrl 
#>  4   6.11 ctrl 
#>  5   4.5  ctrl 
#>  6   4.61 ctrl 
#>  7   5.17 ctrl 
#>  8   4.53 ctrl 
#>  9   5.33 ctrl 
#> 10   5.14 ctrl 
#> # ℹ 20 more rows

If you want NA to be written literally as the string “NA”, use na_as_string. You should literally see the string “NA” when the file is opened with LibreOffice, for example.

But the string “NA” messes up the automatic type inference of read_ods.

## NA is preseved; but weight is now <chr>
read_ods(write_ods(PlantGrowth2, na_as_string = TRUE))
#> # A tibble: 30 × 2
#>    weight group
#>    <chr>  <chr>
#>  1 NA     ctrl 
#>  2 5.58   ctrl 
#>  3 5.18   ctrl 
#>  4 6.11   ctrl 
#>  5 4.5    ctrl 
#>  6 4.61   ctrl 
#>  7 5.17   ctrl 
#>  8 4.53   ctrl 
#>  9 5.33   ctrl 
#> 10 5.14   ctrl 
#> # ℹ 20 more rows

Of course you can fix this by specifying col_types.

## NA is preseved; but weight is now <chr>
read_ods(write_ods(PlantGrowth2, na_as_string = TRUE),
         col_types = readr::cols(weight = readr::col_double()))
#> Warning: [0, 1]: expected a double, but got 'NA'
#> # A tibble: 30 × 2
#>    weight group
#>     <dbl> <chr>
#>  1  NA    ctrl 
#>  2   5.58 ctrl 
#>  3   5.18 ctrl 
#>  4   6.11 ctrl 
#>  5   4.5  ctrl 
#>  6   4.61 ctrl 
#>  7   5.17 ctrl 
#>  8   4.53 ctrl 
#>  9   5.33 ctrl 
#> 10   5.14 ctrl 
#> # ℹ 20 more rows

Several functions were removed in readODS 2.0.0. Please consider the API of readODS mature and there should not be any breaking change until readODS 3.0.0.

`ods_sheets`

Please use list_ods_sheets(path = "plant.ods") instead.

## ods_sheets("plant.ods")
list_ods_sheets("plant.ods")
#> [1] "Sheet1"     "mtcars_ods"

`get_num_sheets_in_ods` and `getNrOfSheetsInODS`

Please use list_ods_sheets

##get_num_sheets_in_ods("plant.ods")
length(list_ods_sheets("plant.ods"))
#> [1] 2

`read.ods`

Please use read_ods. In order to emulate the behaviours of read.ods, the followings are recommended

## read.ods from 1.6 to 1.8
read_ods("plant.ods", col_names = FALSE, skip = 0, na = NULL, col_types = NA, as_tibble = FALSE)
#> New names:
#> • `` -> `...1`
#> • `` -> `...2`
#>      ...1  ...2
#> 1  weight group
#> 2    4.17  ctrl
#> 3    5.58  ctrl
#> 4    5.18  ctrl
#> 5    6.11  ctrl
#> 6     4.5  ctrl
#> 7    4.61  ctrl
#> 8    5.17  ctrl
#> 9    4.53  ctrl
#> 10   5.33  ctrl
#> 11   5.14  ctrl
#> 12   4.81  trt1
#> 13   4.17  trt1
#> 14   4.41  trt1
#> 15   3.59  trt1
#> 16   5.87  trt1
#> 17   3.83  trt1
#> 18   6.03  trt1
#> 19   4.89  trt1
#> 20   4.32  trt1
#> 21   4.69  trt1
#> 22   6.31  trt2
#> 23   5.12  trt2
#> 24   5.54  trt2
#> 25    5.5  trt2
#> 26   5.37  trt2
#> 27   5.29  trt2
#> 28   4.92  trt2
#> 29   6.15  trt2
#> 30    5.8  trt2
#> 31   5.26  trt2

## read.ods older than 1.6
lapply(list_ods_sheets("plant.ods"),
       function(x) read_ods(path = "plant.ods", sheet = x, col_names = FALSE, skip = 0, na = NULL, col_types = NA, as_tibble = FALSE))
#> New names:
#> New names:
#> • `` -> `...1`
#> • `` -> `...2`
#> [[1]]
#>      ...1  ...2
#> 1  weight group
#> 2    4.17  ctrl
#> 3    5.58  ctrl
#> 4    5.18  ctrl
#> 5    6.11  ctrl
#> 6     4.5  ctrl
#> 7    4.61  ctrl
#> 8    5.17  ctrl
#> 9    4.53  ctrl
#> 10   5.33  ctrl
#> 11   5.14  ctrl
#> 12   4.81  trt1
#> 13   4.17  trt1
#> 14   4.41  trt1
#> 15   3.59  trt1
#> 16   5.87  trt1
#> 17   3.83  trt1
#> 18   6.03  trt1
#> 19   4.89  trt1
#> 20   4.32  trt1
#> 21   4.69  trt1
#> 22   6.31  trt2
#> 23   5.12  trt2
#> 24   5.54  trt2
#> 25    5.5  trt2
#> 26   5.37  trt2
#> 27   5.29  trt2
#> 28   4.92  trt2
#> 29   6.15  trt2
#> 30    5.8  trt2
#> 31   5.26  trt2
#> 
#> [[2]]
#>                   ...1 ...2 ...3  ...4 ...5 ...6  ...7  ...8 ...9 ...10 ...11
#> 1                       mpg  cyl  disp   hp drat    wt  qsec   vs    am  gear
#> 2            Mazda RX4   21    6   160  110  3.9  2.62 16.46    0     1     4
#> 3        Mazda RX4 Wag   21    6   160  110  3.9 2.875 17.02    0     1     4
#> 4           Datsun 710 22.8    4   108   93 3.85  2.32 18.61    1     1     4
#> 5       Hornet 4 Drive 21.4    6   258  110 3.08 3.215 19.44    1     0     3
#> 6    Hornet Sportabout 18.7    8   360  175 3.15  3.44 17.02    0     0     3
#> 7              Valiant 18.1    6   225  105 2.76  3.46 20.22    1     0     3
#> 8           Duster 360 14.3    8   360  245 3.21  3.57 15.84    0     0     3
#> 9            Merc 240D 24.4    4 146.7   62 3.69  3.19    20    1     0     4
#> 10            Merc 230 22.8    4 140.8   95 3.92  3.15  22.9    1     0     4
#> 11            Merc 280 19.2    6 167.6  123 3.92  3.44  18.3    1     0     4
#> 12           Merc 280C 17.8    6 167.6  123 3.92  3.44  18.9    1     0     4
#> 13          Merc 450SE 16.4    8 275.8  180 3.07  4.07  17.4    0     0     3
#> 14          Merc 450SL 17.3    8 275.8  180 3.07  3.73  17.6    0     0     3
#> 15         Merc 450SLC 15.2    8 275.8  180 3.07  3.78    18    0     0     3
#> 16  Cadillac Fleetwood 10.4    8   472  205 2.93  5.25 17.98    0     0     3
#> 17 Lincoln Continental 10.4    8   460  215    3 5.424 17.82    0     0     3
#> 18   Chrysler Imperial 14.7    8   440  230 3.23 5.345 17.42    0     0     3
#> 19            Fiat 128 32.4    4  78.7   66 4.08   2.2 19.47    1     1     4
#> 20         Honda Civic 30.4    4  75.7   52 4.93 1.615 18.52    1     1     4
#> 21      Toyota Corolla 33.9    4  71.1   65 4.22 1.835  19.9    1     1     4
#> 22       Toyota Corona 21.5    4 120.1   97  3.7 2.465 20.01    1     0     3
#> 23    Dodge Challenger 15.5    8   318  150 2.76  3.52 16.87    0     0     3
#> 24         AMC Javelin 15.2    8   304  150 3.15 3.435  17.3    0     0     3
#> 25          Camaro Z28 13.3    8   350  245 3.73  3.84 15.41    0     0     3
#> 26    Pontiac Firebird 19.2    8   400  175 3.08 3.845 17.05    0     0     3
#> 27           Fiat X1-9 27.3    4    79   66 4.08 1.935  18.9    1     1     4
#> 28       Porsche 914-2   26    4 120.3   91 4.43  2.14  16.7    0     1     5
#> 29        Lotus Europa 30.4    4  95.1  113 3.77 1.513  16.9    1     1     5
#> 30      Ford Pantera L 15.8    8   351  264 4.22  3.17  14.5    0     1     5
#> 31        Ferrari Dino 19.7    6   145  175 3.62  2.77  15.5    0     1     5
#> 32       Maserati Bora   15    8   301  335 3.54  3.57  14.6    0     1     5
#> 33          Volvo 142E 21.4    4   121  109 4.11  2.78  18.6    1     1     4
#>    ...12
#> 1   carb
#> 2      4
#> 3      4
#> 4      1
#> 5      1
#> 6      2
#> 7      1
#> 8      4
#> 9      2
#> 10     2
#> 11     4
#> 12     4
#> 13     3
#> 14     3
#> 15     3
#> 16     4
#> 17     4
#> 18     4
#> 19     1
#> 20     2
#> 21     1
#> 22     1
#> 23     2
#> 24     2
#> 25     4
#> 26     2
#> 27     1
#> 28     2
#> 29     2
#> 30     4
#> 31     6
#> 32     8
#> 33     2

GESIS Leibniz-Institut für Sozialwissenschaften↩︎
read_fods() and list_fods_sheets() are also available. But since version 2.2.0 read_ods() and list_ods_sheets() can determine whether the file at the path argument is flat or not.↩︎

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.

An Overview of readODS

Chung-hong Chan 1

Update and Append

Writing multiple sheets simultaneously

Flat ODS files (.xml or .fods)

Misc.

readODS 2.0.0

ods_sheets

get_num_sheets_in_ods and getNrOfSheetsInODS

read.ods

Chung-hong Chan ¹

Flat ODS files (`.xml` or `.fods`)

`ods_sheets`

`get_num_sheets_in_ods` and `getNrOfSheetsInODS`

`read.ods`