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Count the number of flags for each record

Source: R/count_flags.R
count_flags.Rd

This function returns the original data frame with an additional column summarizing the total number of flags triggered by each record.

Usage

count_flags(
  occ = NULL,
  flagged_dir = NULL,
  output_format = ".gz",
  flags = "all",
  additional_flags = NULL
)

Arguments

occ

(data.frame or data.table) a dataset containing occurrence records that has been processed by one or more flagging functions. See Details for available flag types.

flagged_dir

(character) optional path to a directory containing files with flagged records saved using the remove_flagged() function. Default is NULL.

output_format

(character) output format used to read the removed records. Options are ".csv" or ".gz". Only used when flagged_dir is not NULL. Default is ".gz".

flags

(character) the flags to be summarized. Use "all" to display all available flags. See Details for all options. Default is "all".

additional_flags

(character) an optional named character vector with the names of additional logical columns to be used as flags. Default is NULL.

Value

The original data frame with an additional column summarizing the total number of flags triggered by each record.

Details

This function expects an occurrence dataset that has already been processed by one or more flagging routines from RuHere or related packages such as CoordinateCleaner. Any logical column in occ can be used as a flag.

The following built-in flag names are recognized:

From RuHere: correct_country, correct_state, cultivated, florabr, faunabr, wcvp, iucn, bien, duplicated, thin_geo, thin_env, consensus

From CoordinateCleaner : .val, .equ, .zer, .cap, .cen, .sea, .urb, .otl, .gbf, .inst, .aohi

Users may also supply additional logical columns using additional_flags.

Examples

# Load example data
data("occ_flagged", package = "RuHere")

# Count flags
sum_flags <- count_flags(occ = occ_flagged)

# Check the distribution of flags per record
table(sum_flags$total_flags)
#> 
#>    0    1    2    3    4 
#> 2426   46  163   14    7 

# Plot histogram
hist(sum_flags$total_flags,
     main = "Distribution of Flags",
     xlab = "Number of Flags",
     col = "steelblue",
     breaks = seq(-0.5, max(sum_flags$total_flags) + 0.5, by = 1))