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Export creel survey estimates to a file

Source: R/write-estimates.R
write_estimates.Rd

Writes a creel_estimates or creel_summary object to a CSV or xlsx file. For CSV, a three-line comment block is prepended containing the estimation method, variance method, confidence level, and generation timestamp. For xlsx, the data are written directly (Excel does not support comment rows).

Usage

write_estimates(
  x,
  path,
  format = c("auto", "csv", "xlsx"),
  overwrite = FALSE,
  ...
)

Arguments

x

A creel_estimates or creel_summary object.

path

File path for the output. The extension (.csv or .xlsx) determines the format; alternatively, use the format argument to override.

format

One of "csv" (default) or "xlsx". When "csv", a comment header is prepended. When "xlsx", writexl::write_xlsx() is used behind an rlang::check_installed() guard.

overwrite

Logical; if FALSE (default) an error is raised when path already exists.

...

Currently unused; reserved for future arguments.

Value

path, returned invisibly.

Details

CSV format — The output file begins with comment lines starting with # that record survey metadata:

# Survey estimates — tidycreel
# Method: Total Effort | Taylor linearization | 95% CI
# Generated: 2024-06-15 09:32:11 UTC
Estimate,SE,CI Lower,CI Upper,N
372.5,13.18,343.8,401.2,14

These lines can be skipped when reading back with utils::read.csv(path, comment.char = "#").

xlsx format — The data are written without a comment header since Excel does not natively support comment rows. Row 1 will be the column headers.

See also

summary.creel_estimates(), write_schedule()

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_successful_parties(), summarize_trips(), summary.creel_estimates(), validate_creel_data(), validate_design(), validate_incomplete_trips(), validation_report()

Examples

data("example_counts")
data("example_interviews")
cal <- unique(example_counts[, c("date", "day_type")])
design <- suppressWarnings(
  creel_design(cal, date = date, strata = day_type) # nolint
)
design <- suppressWarnings(add_counts(design, example_counts))
design <- suppressWarnings(
  add_interviews(
    design, example_interviews,
    catch = catch_total, effort = hours_fished, trip_status = trip_status
  )
)
#> 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%)
eff <- suppressWarnings(estimate_effort(design))

tmp <- tempfile(fileext = ".csv")
write_estimates(eff, tmp)

# Read back (skipping comment lines)
out <- utils::read.csv(tmp, comment.char = "#")
out
#>   Estimate    SE CI.Lower CI.Upper  N
#> 1    372.5 13.18    343.8    401.2 14