sample_df <- canada_load_sample_data() samples_fleet_lst <- canada_get_fleet_samples(sample_df) # Remove JV for this table samples_fleet_lst <- samples_fleet_lst[names(samples_fleet_lst) != "jv"] samples_fleet_lst$ft <- samples_fleet_lst$ft |> mutate(survey_abbrev = "Freezer Trawlers") samples_fleet_lst$ss <- samples_fleet_lst$ss |> mutate(survey_abbrev = "Shoreside") comm_samp <- samples_fleet_lst$ft |> bind_rows(samples_fleet_lst$ss) |> mutate(sex = "U") # Remove the sex colors and legend lengths_raw <- tidy_lengths_raw(comm_samp, survey = c("Freezer Trawlers", "Shoreside"), bin_size = 2, year_range = seq(last_data_yr - 10, last_data_yr), remove_unsexed = FALSE) plot_weights_lengths(lengths_raw, type = "length", include_sex = FALSE, bin_width = 2, x_breaks = seq(30, 80, 10), label_font_size = 4, unit_str = "cm") + geom_vline(xintercept = seq(30, 80, 10), linetype = "dashed", linewidth = 0.1) + coord_cartesian(xlim = c(30, 90))
{width=100% height=50% alt="U.S. at-sea fishery length distribution"} {width=100% height=50% alt="U.S. shoreside fishery length distribution"}
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