| plot_taxa_rank | R Documentation | 
Plot the number of observations that use each taxonomic rank in the dataset.
plot_taxa_rank(
  data,
  id = NA_character_,
  facet_var = NA_character_,
  facet_scales = "free_x",
  alpha = 1
)
| data | (list or tbl_df, tbl, data.frame) The dataset object returned by  | 
| id | (character) Identifier of dataset to be used in plot subtitles. Is automatically assigned when  | 
| facet_var | (character) Name of column to use for faceting. Must be a column of the observation or taxon table. | 
| facet_scales | (character) Should scales be free ("free", default value), fixed ("fixed"), or free in one dimension ("free_x", "free_y")? | 
| alpha | (numeric) Alpha-transparency scale of data points. Useful when many data points overlap. Allowed values are between 0 and 1, where 1 is 100% opaque. Default is 1. | 
The data parameter accepts a range of input types but ultimately requires the 13 columns of the combined observation and taxon tables.
(gg, ggplot) A gg, ggplot object if assigned to a variable, otherwise a plot to your active graphics device
## Not run: 
# Read a dataset of interest
dataset <- read_data(
  id = "neon.ecocomdp.20120.001.001",
  site= c('COMO','LECO'),
  startdate = "2017-06",
  enddate = "2019-09",
  check.size = FALSE)
# Plot the dataset
plot_taxa_rank(dataset)
# Plot with facet by location
plot_taxa_rank(dataset, facet_var = "location_id")
# Flatten the dataset, manipulate, then plot
dataset %>%
  flatten_data() %>%
  dplyr::filter(lubridate::as_date(datetime) > "2003-07-01") %>%
  dplyr::filter(grepl("COMO",location_id)) %>%
  plot_taxa_rank()
## End(Not run)
# Plot the example dataset
plot_taxa_rank(ants_L1)
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