taxa.df <- read.csv("https://www.epa.gov/sites/production/files/2016-06/nrsa_0809_benttaxa.csv",
stringsAsFactors = FALSE)
site.df <- read.csv("https://www.epa.gov/sites/production/files/2015-09/siteinfo_0.csv",
stringsAsFactors = FALSE)
counts.df <- read.csv("https://www.epa.gov/sites/production/files/2016-11/nrsa0809bentcts.csv",
stringsAsFactors = FALSE)
nrsa_nap_0809 <- site.df %>%
dplyr::filter(AGGR_ECO9_2015 %in% "NAP") %>%
dplyr::left_join(counts.df, by = c("UID",
"SITE_ID",
"VISIT_NO",
"DATE_COL")) %>%
dplyr::select(UID, SITE_ID, RT_NRSA_CAT, TARGET_TAXON, TOTAL) %>%
dplyr::left_join(taxa.df, by = "TARGET_TAXON") %>%
dplyr::select(UID:TOTAL, PHYLUM:VOLTINISM) %>%
dplyr::select(-dplyr::contains("_WSA")) %>%
dplyr::filter(!is.na(PHYLUM)) %>%
dplyr::rename_all(base::tolower) %>%
dplyr::mutate_if(is.character, tolower)
usethis::use_data(nrsa_nap_0809, overwrite = TRUE)
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