results %>% filter(ModelType == "yearly imputed index: Total ~ Year + Month") %>% transmute( area = LocationGroup, species = scientific_name, genus = str_replace(scientific_name, "([[:alpha:]]*) .*", "\\1"), year = as.integer(as.character(Parameter)), p05 = p_population(Estimate, SE, 0.05), p10 = p_population(Estimate, SE, 0.1), p30 = p_population(Estimate, SE, 0.3), p50 = p_population(Estimate, SE, 0.5), p70 = p_population(Estimate, SE, 0.7), p90 = p_population(Estimate, SE, 0.9), p95 = p_population(Estimate, SE, 0.95), Order ) %>% arrange(genus, Order, area) %>% group_by(genus, species) %>% nest() %>% mutate( id = species, Previous = lag(genus), Title = ifelse( is.na(Previous) | Previous != genus, sprintf("## %s\n\n### %s", genus, species), sprintf("### %s", species) ) ) -> monthly_population monthly_population %>% pull(id) %>% sapply( function(id) { knit_expand("_species_area_montly_total.Rmd", id = id) } ) %>% paste(collapse = "\n\n") -> rmd knit(text = rmd, quiet = TRUE) %>% cat()
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