data-raw/twentymm.R

In sbashevkin/discretewq: Integrated Dataset of Discrete Water Quality in the San Francisco Estuary

## code to prepare `twentymm` dataset goes here

require(readr)
require(dplyr)
require(lubridate)
require(tidyr)

twentymm_stations<-read_csv(file.path("data-raw", "20mm", "20mmStations.csv"),
                            col_types=cols_only(Station="c", LatD="d", LatM="d", LatS="d",
                                                LonD="d", LonM="d", LonS="d"))%>%
  mutate(Latitude=LatD+LatM/60+LatS/3600,
         Longitude=(LonD+LonM/60+LonS/3600)*-1)%>%
  select(Station, Latitude, Longitude)%>%
  drop_na()

twentymm <- read_csv(file.path("data-raw", "20mm", "Station.csv"),
                     col_types = cols_only(StationID="c", SurveyID="c", Station="c",
                                           LatDeg="d", LatMin="d", LatSec="d", LonDeg="d",
                                           LonMin="d", LonSec="d", Temp="d", TopEC="d",
                                           BottomEC = "d", Secchi="d", Comments="c"))%>%
  mutate(Latitude=LatDeg+LatMin/60+LatSec/3600,
         Longitude=(LonDeg+LonMin/60+LonSec/3600)*-1)%>%
  left_join(read_csv(file.path("data-raw", "20mm", "Survey.csv"),
                     col_types = cols_only(SurveyID="c", SampleDate = "c"))%>%
              rename(Date=SampleDate)%>%
              mutate(Date = parse_date_time(Date, "%m/%d/%Y %H:%M:%S", tz="America/Los_Angeles")),
            by="SurveyID")%>%
  left_join(read_csv(file.path("data-raw", "20mm", "Tow.csv"),
                     col_types = cols_only(StationID="c", TowTime="c", Tide="d", BottomDepth="d", TowNum="d"))%>%
              rename(Time=TowTime)%>%
              mutate(
                Time = parse_date_time(Time, "%m/%d/%Y %H:%M:%S", tz="America/Los_Angeles"),
                # Correct a few erroneous times (most likely not recorded in military time format)
                Time = if_else(hour(Time) %in% 1:2, Time + hours(12), Time)
              )%>%
              group_by(StationID)%>% # StationID really is sampleID
              mutate(Retain=if_else(Time==min(Time), TRUE, FALSE))%>% # Only keep bottom depth, tide, and time info for the first tow of each day (defined by time or tow number below)
              ungroup()%>%
              filter(Retain)%>%
              select(-Retain)%>%
              group_by(StationID)%>%
              mutate(Retain=if_else(TowNum==min(TowNum), TRUE, FALSE))%>%
              ungroup()%>%
              filter(Retain)%>%
              select(-Retain, -TowNum),
            by="StationID")%>%
  select(Station, Temperature=Temp, Conductivity=TopEC, Conductivity_bottom = BottomEC, Secchi,
         Notes=Comments, Latitude, Longitude, Date,
         Time, Depth=BottomDepth, Tide)%>%
  mutate(Datetime = parse_date_time(if_else(is.na(Time), NA_character_, paste0(Date, " ", hour(Time), ":", minute(Time))), "%Y-%m-%d %H:%M", tz="America/Los_Angeles"))%>%
  mutate(Tide=recode(as.character(Tide), `4`="Flood", `3`="Low Slack", `2`="Ebb", `1`="High Slack"),
         Source = "20mm",
         Depth = Depth*0.3048)%>% # Convert feet to meters
  left_join(twentymm_stations, by="Station", suffix=c("_field", ""))%>%
  mutate(Field_coords=case_when(
    is.na(Latitude) & !is.na(Latitude_field) ~ TRUE,
    is.na(Longitude) & !is.na(Longitude_field) ~ TRUE,
    TRUE ~ FALSE),
    Latitude=if_else(is.na(Latitude), Latitude_field, Latitude),
    Longitude=if_else(is.na(Longitude), Longitude_field, Longitude))%>%
  select(Source, Station, Latitude, Longitude, Field_coords, Date, Datetime, Depth, Tide, Secchi, Temperature, Conductivity, Conductivity_bottom, Notes)


usethis::use_data(twentymm, overwrite = TRUE)