Prepare a parameter-long data frame for statistical analysis

nested_data(
  .data,
  qualifiers = NULL,
  key = NULL,
  value,
  fill = NA,
  select_if = ~TRUE,
  filter_all = any_vars(TRUE),
  trans = identity,
  groups = NULL
)

unnested_data(.data, ...)

Arguments

.data: Data in parameter-long form
qualifiers: Columns that add context to observations (e.g., depth, zone, core)
key: The column name that contains the column names of the data matrix
value: The column name that contains the values
fill: If a key/value combination doesn't exist in the input, this value will be assigned in the data matrix. Generally, using NA for geochemical data and 0 for relative abundance data is advised.
select_if: Use ~TRUE to keep all columns; use ~all(is.finite(.)) to keep columns with all finite values. See select_if.
filter_all: Use any_vars(TRUE) to keep all observations; use all_vars(is.finite(.)) to keep only observations with finite (non-missing) values. See filter_all.
trans: A function that will be applied to all columns, column-wise. Use identity to perform no transformation, use scale to scale each column to a mean of zero and variance of 1. See mutate_all.
groups: Use group_by or this argument to group by one or more columns (e.g., core or lake)
...: One or more columns to unnest.

Value

A nested data matrix, which is composed of a tibble::tibble()

with tibble list-columns data, discarded_rows, discarded_columns, and qualifiers.

Examples

nested_data(
  alta_lake_geochem,
  qualifiers = c(age, depth, zone),
  key = param,
  value = value,
  trans = scale
)
#> # A tibble: 1 × 4
#>   discarded_columns discarded_rows   qualifiers        data             
#> * <list>            <list>           <list>            <list>           
#> 1 <tibble [32 × 0]> <tibble [0 × 9]> <tibble [32 × 4]> <tibble [32 × 6]>