r last_data_yr
sample_df <- canada_load_sample_data() |> filter(sex %in% c(1, 2)) 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_summary_tbls_lst <- canada_extract_sampling_by_month( samples_fleet_lst, yr = last_data_yr)
:::::: {.columns} ::: {.column width="45%"} \begin{center}\textbf{Freezer trawlers}\end{center}
table_sampling_by_month( samples_summary_tbls_lst$ft, font_size = 8, header_font_size = 9)
:::
::: {.column width="45%"} \begin{center}\textbf{Shoreside}\end{center}
table_sampling_by_month( samples_summary_tbls_lst$ss, font_size = 8, header_font_size = 9)
::: ::::::
r last_data_yr
load("page.Rdat") load("atsea.ages.Rdat")
# TODO: use this code rather than the pre-made tables below table_sampling_by_month( us_extract_sampling_by_month(c("AGE", "LENGTH", "WEIGHT"), atsea.ages), font_size = 8, header_font_size = 9)
# TODO: use this code rather than the pre-made tables below table_sampling_by_month( us_extract_sampling_by_month(c("AGE", "FISH_LENGTH", "FISH_WEIGHT"), page), font_size = 8, header_font_size = 9)
:::::: {.columns} ::: {.column width="45%"} \begin{center}\textbf{At-Sea}\end{center}
d <- tibble(month = c("May", "Jun", "Aug", "Sep", "Oct", "Nov", "Total"), num_age = c(1015, 69, 0, 265, 376, 0, 1725), num_length = c(1023, 69, 153, 644, 848, 22, 2759), num_weight = c(1023, 69, 153, 644, 848, 22, 2759)) table_sampling_by_month(d, font_size = 8, header_font_size = 9)
:::
::: {.column width="45%"} \begin{center}\textbf{Shore-based}\end{center}
d <- tibble(month = c("Mar", "May", "Jun", "Jul", "Aug", "Sep", "Oct", "Nov", "Total"), num_ages = c(0, 340, 448, 240, 60, 60, 180, 0, 1328), num_lengths = c(20, 720, 540, 500, 500, 370, 560, 20, 3230), num_weights = c(20, 340, 448, 440, 400, 310, 479, 20, 2457)) table_sampling_by_month(d, font_size = 8, header_font_size = 9)
::: ::::::
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