EmilyMarkowitz-NOAA
commented
3 months ago Thanks for this!
✔️ I've shown you how to do pull requests (#3 and #2 ) and some issue management (https://github.com/nmfs-fish-tools/DisMAP/issues/4).
⌚ Let me know when the scripts are ready and I'll get on it :) In the meantime, I have written a zero-filling script for our FOSS data that we may be able to apply to your code, which is provided as an example in the AFSC GAP team's production data documentation. It will look something like this:
# Load data
library(dplyr)
library(here)
library(readr)
catch <- readr::read_csv(file = here::here("data/gap_products_foss_catch.csv"))[,-1] # remove "row number" column
haul <- readr::read_csv(file = here::here("data/gap_products_foss_haul.csv"))[,-1] # remove "row number" column
species <- readr::read_csv(file = here::here("data/gap_products_foss_species.csv"))[,-1] # remove "row number" column
# come up with full combination of what species should be listed for what hauls/surveys
# for zero-filled data, all species caught in a survey need to have zero or non-zero row entries for a haul
comb <- dplyr::full_join(
x = dplyr::left_join(catch, haul, by = "HAULJOIN") %>%
dplyr::select(SURVEY_DEFINITION_ID, SPECIES_CODE) %>%
dplyr::distinct(),
y = haul %>%
dplyr::select(SURVEY_DEFINITION_ID, HAULJOIN) %>%
dplyr::distinct(),
by = "SURVEY_DEFINITION_ID",
relationship = "many-to-many"
)
# Join data to make a full zero-filled CPUE dataset
dat <- comb %>%
# add species data to unique species by survey table
dplyr::left_join(species, "SPECIES_CODE") %>%
# add catch data
dplyr::full_join(catch, c("SPECIES_CODE", "HAULJOIN")) %>%
# add haul data
dplyr::full_join(haul) %>% # , c("SURVEY_DEFINITION_ID", "HAULJOIN")
# modify zero-filled rows
dplyr::mutate(
CPUE_KGKM2 = ifelse(is.null(CPUE_KGKM2), 0, CPUE_KGKM2),
CPUE_KGHA = CPUE_KGKM2/100, # Hectares
CPUE_NOKM2 = ifelse(is.null(CPUE_NOKM2), 0, CPUE_NOKM2),
CPUE_NOHA = CPUE_NOKM2/100, # Hectares
COUNT = ifelse(is.null(COUNT), 0, COUNT),
WEIGHT_KG = ifelse(is.null(WEIGHT_KG), 0, WEIGHT_KG) ) Where each table contains the following columns and dimensions. See a preview of these tables here:
Melissa-Karp
When the API is ready and @Melissa-Karp is ready with the Rscript I will need @EmilyMarkowitz-NOAA to modify AK code for downloading (
download_ak.Rfile) and merging the various data files within theCompile_Dismap_Current.Rfile. Please fork this repository and submit a pull request when complete.Task List