# Prepare data for example for AZ, 303d Listing
#
# Erik.Leppo@tetratech.com
# 20180611
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# 0. Prep####
wd <- getwd() # assume is package directory
#library(devtools)
# 1. Get data and process#####
# 1.1. Import Data
myFile <- "AZSitesFinal.tab"
df.sites <- read.delim(file.path(wd, "data-raw", "AZ", myFile))
# Create new dataset
df <- unique(df.sites[,c("COMID_NHD2", "WaterbodyName")])
df$ComID <- df$COMID_NHD2
df$WATER.BODY.NAME <- as.character(df$WaterbodyName)
df <- df[,c(3,4)]
df$POLLUTANT <- as.character(NA)
df$FINAL.LISTING.DECISION <- as.character(NA)
# Add elevation category (20180622)
## use Hi/Lo cluster
dim(df)
ec.hi.COMID <- data_Cluster_Hi$COMID
ec.lo.COMID <- data_Cluster_Lo$COMID
boo.hi <- df$ComID %in% ec.hi.COMID
boo.lo <- df$ComID %in% ec.lo.COMID
df$ElevCategory <- as.character(NA)
df[boo.hi, "ElevCategory"] <- "HI"
df[boo.lo, "ElevCategory"] <- "LO"
dim(df)
table(df$ElevCategory, useNA="ifany")
# 1.2. Process Data
View(df)
# QC check
dim(df)
# structure
str(df)
##~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# 2. Save as RDA for use in package####
#
data_303d <- df
devtools::use_data(data_303d, overwrite = TRUE)
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