Calculate the percentage of each sample represented by the specified taxon or taxa.

taxa_div(
  .dataframe,
  .key_col,
  .counts_col,
  .group_col,
  .filter = NULL,
  .job,
  .base_log = 2,
  .q,
  .unnest_col = NULL
)

Arguments

.dataframe

A data frame where each row should represent the number of individuals enumerated for a single taxon collected during a single sampling event.

.key_col

One unquoted column name that represents a key (i.e., unique ID) for a sampling event for which to group (i.e., aggregate) the data.

.counts_col

One unquoted column name that represents taxonomic counts.

.group_col

One unquoted column name that represents a taxomic rank or group of interest.

.filter

A logical statement to subset the data frame prior to calculating the metric of interest.

.job

A character string specifying the diversity metric of interest. Below is a list of exceptable inputs:

  • "shannon"Description needed

  • "effective_shannon"Description needed

  • "simpson""Description needed

  • "invsimpson"Description needed

  • "gini_simpson"Description needed

  • "effective_simpson"Description needed

  • "pielou"Description needed

  • "margalef"Description needed

  • "menhinick"Description needed

  • "hill"Description needed

  • "renyi"Description needed

.base_log

The base log value used during the calculation of Shannon Diversity index ("shannon") or Effective Shannon Diversity ("effective_shannon"). The default value is two.

.q

The exponent used during the calculation of Hill Numbers ("hill") and Renyi Entropy ("renyi").

.unnest_col

One unqouted column name that represents nested data. If this column is NULL (default), then the data will not be unnested.

Value

A numeric vector.