## code to prepare `stations` dataset goes here
library(dplyr)
library(tidyr)
library(tibble)
library(readr)
library(readxl)
require(stringr)
require(lubridate)
Zoopxl<-read_excel(file.path("data-raw", "data", "zoop_stations.xlsx"))%>%
rename(Source=Project)%>%
filter(Source!="FMWT")%>% # Remove FMWT stations since we have good ones now
mutate(Source=recode(Source, TNS="STN"),
StationID=paste(Source, Station))%>%
drop_na()
WQ<-read_csv(file.path("data-raw", "data", "EMP", "wq_stations.csv"),
col_types=cols_only(site="c", lat="d", long="d"))%>%
select(Station=site, Latitude=lat, Longitude=long)%>%
mutate(Source="EMP",
StationID=paste(Source, Station))%>%
drop_na()
#EZ stations
EZ<-read_csv(file.path("data-raw", "data", "EMP", "SACSJ_delta_water_quality_1975_2019.csv"), na=c("NA", "ND"),
col_types = cols_only(Station="c", Date="c", NorthLat="d", WestLong="d"))%>%
rename(Latitude=NorthLat, Longitude=WestLong)%>%
mutate(Date=parse_date_time(Date, "%m/%d/%Y", tz="America/Los_Angeles"),
Station=paste(Station, Date),
Source="EMP")%>%
select(Station, Latitude, Longitude, Source)%>%
mutate(StationID=paste(Source, Station))%>%
drop_na()
ZoopEZ<-zooper::stationsEMPEZ%>%
mutate(Station=paste(Station, Date),
Source="EMP")%>%
select(Station, Latitude, Longitude, Source)%>%
mutate(StationID=paste(Source, Station))%>%
drop_na()
#EMP Bivalve stations
EMPBIV <-read_excel(file.path("data-raw", "data", "EMP", "1975-18 CPUE bivalves only, 2019Sept9.xlsx"),
sheet = "75-17 station locations", skip=1)%>%
select(Station=Site_Code, Latitude, Longitude)%>%
mutate(Source="EMP")%>%
mutate(StationID=paste(Source, Station))%>%
drop_na()
stations<-bind_rows(
Zoopxl,
WQ%>%
filter(!(StationID%in%unique(Zoopxl$StationID))),
EZ,
EMPBIV,
ZoopEZ)%>%
drop_na()
usethis::use_data(stations, overwrite = TRUE)
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