Summarize point counts and percent cover

Counts point labels by grouping variables and returns percent cover within each group.

Usage

summarize_points(
  points,
  by = c("site", "transect", "image_id"),
  class_col = "major_category"
)

Arguments

points

A tidy point table.

by

Grouping columns.

class_col

Class/label column to summarize.

Value

A summary tibble with n, n_points, and percent.

Examples

cpc <- system.file("extdata", "HIW_158_W_U-1.cpc", package = "pointcoral")
pts <- read_cpce_file(cpc)
summarize_points(pts, by = "image_id", class_col = "raw_label")
#> # A tibble: 10 × 5
#>    image_id      raw_label     n n_points percent
#>    <chr>         <chr>     <int>    <int>   <dbl>
#>  1 HIW_158_W_U-1 AA            4      100       4
#>  2 HIW_158_W_U-1 CALG         18      100      18
#>  3 HIW_158_W_U-1 LOBO          8      100       8
#>  4 HIW_158_W_U-1 P             2      100       2
#>  5 HIW_158_W_U-1 PEFL          7      100       7
#>  6 HIW_158_W_U-1 PEYS          9      100       9
#>  7 HIW_158_W_U-1 S            21      100      21
#>  8 HIW_158_W_U-1 SPO          27      100      27
#>  9 HIW_158_W_U-1 SS            1      100       1
#> 10 HIW_158_W_U-1 TURF          3      100       3