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Tabulate successful parties by angler type and species sought

Source: R/creel-summaries.R
summarize_successful_parties.Rd

A party is "successful" if any row in the attached catch data has catch_type == "caught" and count > 0 for the species the party was seeking (species_sought). Returns counts of successful and total parties for each angler type x species sought combination.

Usage

summarize_successful_parties(design)

Arguments

design

A creel_design object with interviews attached (including angler_type and species_sought columns) and catch data attached via add_catch.

Value

A data.frame with class c("creel_summary_successful_parties", "data.frame") and columns: angler_type, species_sought, N_successful (integer), N_total (integer), percent (numeric, 1 decimal).

Details

Interview-based summary, not pressure-weighted. This function tabulates raw interview records without applying survey weighting by sampling effort or effort stratum. For pressure-weighted extrapolated estimates, use estimate_catch_rate or estimate_harvest_rate.

See also

Other "Reporting & Diagnostics": adjust_nonresponse(), check_completeness(), compare_variance(), flag_outliers(), season_summary(), standardize_species(), summarize_by_angler_type(), summarize_by_day_type(), summarize_by_method(), summarize_by_species_sought(), summarize_by_trip_length(), summarize_cws_rates(), summarize_hws_rates(), summarize_length_freq(), summarize_refusals(), summarize_trips(), summary.creel_estimates(), validate_creel_data(), validate_design(), validate_incomplete_trips(), validation_report(), write_estimates()

Examples

data(example_calendar)
data(example_interviews)
data(example_catch)
d <- creel_design(example_calendar, date = date, strata = day_type)
d <- add_interviews(d, example_interviews,
  catch = catch_total, effort = hours_fished, harvest = catch_kept,
  trip_status = trip_status, angler_type = angler_type,
  species_sought = species_sought
)
#> ℹ No `n_anglers` provided — assuming 1 angler per interview.
#> ℹ Pass `n_anglers = <column>` to use actual party sizes for angler-hour
#>   normalization.
#> ℹ Added 22 interviews: 17 complete (77%), 5 incomplete (23%)
d <- add_catch(d, example_catch,
  catch_uid = interview_id, interview_uid = interview_id,
  species = species, count = count, catch_type = catch_type
)
summarize_successful_parties(d)
#>   angler_type species_sought N_total N_successful percent
#> 1        bank           bass       5            0     0.0
#> 2        bank        panfish       3            1    33.3
#> 3        bank        walleye       5            3    60.0
#> 4        boat           bass       1            1   100.0
#> 5        boat        panfish       2            0     0.0
#> 6        boat        walleye       6            1    16.7