Subset distinct/unique rows in ir objects
Arguments
- .data
An object of class
ir.- ...
<
data-masking> Optional variables to use when determining uniqueness. If there are multiple rows for a given combination of inputs, only the first row will be preserved. If omitted, will use all variables.- .keep_all
If
TRUE, keep all variables in.data. If a combination of...is not distinct, this keeps the first row of values.
See also
Other tidyverse:
arrange.ir(),
extract.ir(),
filter-joins,
filter.ir(),
group_by,
mutate-joins,
mutate,
nest,
pivot_longer.ir(),
pivot_wider.ir(),
rename,
rowwise.ir(),
select.ir(),
separate.ir(),
separate_rows.ir(),
slice,
summarize,
unite.ir()
Examples
## distinct
dplyr::distinct(rep(ir_sample_data, 2))
#> # A tibble: 116 × 8
#> id_measurement id_sample sample_type sample_comment klason_lignin
#> * <int> <chr> <chr> <chr> <units>
#> 1 1 GN 11-389 needles Abies Firma Momi fir 0.359944
#> 2 2 GN 11-400 needles Cupressocyparis leylandii… 0.339405
#> 3 3 GN 11-407 needles Juniperus chinensis Chine… 0.267552
#> 4 4 GN 11-411 needles Metasequoia glyptostroboi… 0.350016
#> 5 5 GN 11-416 needles Pinus strobus Torulosa 0.331100
#> 6 6 GN 11-419 needles Pseudolarix amabili Golde… 0.279360
#> 7 7 GN 11-422 needles Sequoia sempervirens Cali… 0.329672
#> 8 8 GN 11-423 needles Taxodium distichum Cascad… 0.356950
#> 9 9 GN 11-428 needles Thuja occidentalis Easter… 0.369360
#> 10 10 GN 11-434 needles Tsuga caroliniana Carolin… 0.289050
#> # … with 106 more rows, and 3 more variables: holocellulose <units>,
#> # spectra <named list>, measurement_id <int>