Rename columns in ir objects

Rename columns in ir objects

Usage

rename.ir(.data, ...)

rename_with.ir(.data, .fn, .cols = dplyr::everything(), ...)

Source

dplyr::rename()

Arguments

.data

An object of class ir.

...

For rename(): <tidy-select> Use new_name = old_name to rename selected variables.

For rename_with(): additional arguments passed onto .fn.

.fn

A function used to transform the selected .cols. Should return a character vector the same length as the input.

.cols

<tidy-select> Columns to rename; defaults to all columns.

Value

.data with renamed columns. If the spectra column is renamed, and no new valid spectra column is created, the ir class is dropped, else the object is of class ir.

See also

Other tidyverse: arrange.ir(), distinct.ir(), extract.ir(), filter-joins, filter.ir(), group_by, mutate-joins, mutate, nest, pivot_longer.ir(), pivot_wider.ir(), rowwise.ir(), select.ir(), separate.ir(), separate_rows.ir(), slice, summarize, unite.ir()

Examples

## rename
dplyr::rename(ir_sample_data, hol = "holocellulose")
#> # A tibble: 58 × 7
#>    id_measurement id_sample sample_type sample_comment       klason_lignin   hol
#>  *          <int> <chr>     <chr>       <chr>                          [1]   [1]
#>  1              1 GN 11-389 needles     Abies Firma Momi fir         0.360 0.308
#>  2              2 GN 11-400 needles     Cupressocyparis ley…         0.339 0.250
#>  3              3 GN 11-407 needles     Juniperus chinensis…         0.268 0.336
#>  4              4 GN 11-411 needles     Metasequoia glyptos…         0.350 0.184
#>  5              5 GN 11-416 needles     Pinus strobus Torul…         0.331 0.309
#>  6              6 GN 11-419 needles     Pseudolarix amabili…         0.279 0.335
#>  7              7 GN 11-422 needles     Sequoia semperviren…         0.330 0.241
#>  8              8 GN 11-423 needles     Taxodium distichum …         0.357 0.125
#>  9              9 GN 11-428 needles     Thuja occidentalis …         0.369 0.252
#> 10             10 GN 11-434 needles     Tsuga caroliniana C…         0.289 0.349
#> # … with 48 more rows, and 1 more variable: spectra <named list>
dplyr::rename(ir_sample_data, spec = "spectra") # drops ir class
#> # A tibble: 58 × 7
#>    id_measurement id_sample sample_type sample_comment             klason_lignin
#>  *          <int> <chr>     <chr>       <chr>                                [1]
#>  1              1 GN 11-389 needles     Abies Firma Momi fir               0.360
#>  2              2 GN 11-400 needles     Cupressocyparis leylandii…         0.339
#>  3              3 GN 11-407 needles     Juniperus chinensis Chine…         0.268
#>  4              4 GN 11-411 needles     Metasequoia glyptostroboi…         0.350
#>  5              5 GN 11-416 needles     Pinus strobus Torulosa             0.331
#>  6              6 GN 11-419 needles     Pseudolarix amabili Golde…         0.279
#>  7              7 GN 11-422 needles     Sequoia sempervirens Cali…         0.330
#>  8              8 GN 11-423 needles     Taxodium distichum Cascad…         0.357
#>  9              9 GN 11-428 needles     Thuja occidentalis Easter…         0.369
#> 10             10 GN 11-434 needles     Tsuga caroliniana Carolin…         0.289
#> # … with 48 more rows, and 2 more variables: holocellulose [1],
#> #   spec <named list>


## rename_with
dplyr::rename_with(ir_sample_data, .cols = dplyr::starts_with("id_"),
  toupper)
#> # A tibble: 58 × 7
#>    ID_MEASUREMENT ID_SAMPLE sample_type sample_comment             klason_lignin
#>  *          <int> <chr>     <chr>       <chr>                                [1]
#>  1              1 GN 11-389 needles     Abies Firma Momi fir               0.360
#>  2              2 GN 11-400 needles     Cupressocyparis leylandii…         0.339
#>  3              3 GN 11-407 needles     Juniperus chinensis Chine…         0.268
#>  4              4 GN 11-411 needles     Metasequoia glyptostroboi…         0.350
#>  5              5 GN 11-416 needles     Pinus strobus Torulosa             0.331
#>  6              6 GN 11-419 needles     Pseudolarix amabili Golde…         0.279
#>  7              7 GN 11-422 needles     Sequoia sempervirens Cali…         0.330
#>  8              8 GN 11-423 needles     Taxodium distichum Cascad…         0.357
#>  9              9 GN 11-428 needles     Thuja occidentalis Easter…         0.369
#> 10             10 GN 11-434 needles     Tsuga caroliniana Carolin…         0.289
#> # … with 48 more rows, and 2 more variables: holocellulose [1],
#> #   spectra <named list>
dplyr::rename_with(ir_sample_data, toupper) # drops ir class
#> # A tibble: 58 × 7
#>    ID_MEASUREMENT ID_SAMPLE SAMPLE_TYPE SAMPLE_COMMENT             KLASON_LIGNIN
#>  *          <int> <chr>     <chr>       <chr>                                [1]
#>  1              1 GN 11-389 needles     Abies Firma Momi fir               0.360
#>  2              2 GN 11-400 needles     Cupressocyparis leylandii…         0.339
#>  3              3 GN 11-407 needles     Juniperus chinensis Chine…         0.268
#>  4              4 GN 11-411 needles     Metasequoia glyptostroboi…         0.350
#>  5              5 GN 11-416 needles     Pinus strobus Torulosa             0.331
#>  6              6 GN 11-419 needles     Pseudolarix amabili Golde…         0.279
#>  7              7 GN 11-422 needles     Sequoia sempervirens Cali…         0.330
#>  8              8 GN 11-423 needles     Taxodium distichum Cascad…         0.357
#>  9              9 GN 11-428 needles     Thuja occidentalis Easter…         0.369
#> 10             10 GN 11-434 needles     Tsuga caroliniana Carolin…         0.289
#> # … with 48 more rows, and 2 more variables: HOLOCELLULOSE [1],
#> #   SPECTRA <named list>