PNC (version 0.1.0)

coverage: Calculate Trait Coverage Statistics

Description

This function calculates comprehensive coverage statistics for trait data, including individual trait coverage rates, complete case coverage, and overall data coverage. It provides both summary statistics and detailed breakdowns of missing and available data.

Usage

coverage(data)

Value

A data frame with the following columns:

Trait

Character. Names of traits plus an "All" row for complete cases

Available_count

Integer. Number of non-missing values for each trait

Missing_count

Integer. Number of missing (NA) values for each trait

Trait_coverage_rate

Character. Percentage of available data for each trait

The "All" row shows statistics for complete cases (rows with no missing values).

Arguments

data

A data frame containing trait data. Each column represents a trait and each row represents an observation (e.g., species, samples).

Details

The function performs the following calculations:

• Individual trait coverage: For each trait, calculates the number and percentage of available (non-NA) values

• Complete case coverage: Counts rows with no missing values across all traits and calculates the percentage

• Overall coverage: Calculates the percentage of all cells in the dataset that contain non-missing values

The function also prints the overall trait coverage rate to the console before returning the detailed summary table.

Examples

# Create sample trait data
trait_data <- data.frame(
  PlantHeight = c(1.2, 1.5, NA, 2.1, 1.8),
  LDMC = c(0.5, NA, 0.8, 1.2, 0.9),
  LA = c(15.2, 18.5, 12.3, NA, 16.7)
)

# Calculate coverage statistics
coverage(trait_data)