taxa_div: Taxonomic Diversity
In zsmith27/mmir: Multi-Metric Index

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
)

`.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.