## code to prepare `DATASET` dataset goes here
library(tidyverse)
transducers <-
structure(list(serial_no = c("440478", "440965", "440966"),
device_type = c("Rugged BaroTROLL",
"Rugged TROLL 200", "Rugged TROLL 200"),
device_site = c("Dry Creek Rancheria",
"Dry Creek Rancheria", "Dry Creek Rancheria"),
device_name = c("DCR Baro",
"DCR ED1", "DCR VR1"), firmware_version = c("1.01", "1.02", "1.02"
), reports = c("A", "TS", "TS")),
row.names = c(NA, -3L), class = c("tbl_df",
"tbl", "data.frame"))
usethis::use_data(transducers, overwrite = TRUE)
transducer_subsets_to_keep <- tibble(
datetime = seq(as_datetime("2016-01-01 00:00:00"),
as_datetime("2022-12-31 23:45:00"), by = "2 hours")
)
usethis::use_data(transducer_subsets_to_keep, overwrite = TRUE)
# MEASUREMENT UNITS -----------------------------------------------------------------------
# measurement unit conversions from lab data to wqx
# the process for creating this dataset is manual by looking
# the reported units and finding the appropriate entry on the excel file
# from the wqx.
measuremnt_units_lookup <- read_csv("data-raw/domain-values/measurement-units-lookup.csv")
usethis::use_data(measuremnt_units_lookup, overwrite = TRUE)
# CHARACTERISTIC NAMES -------------------------------------------------
characteristic_names_lookup <- read_csv("data-raw/domain-values/analyte-names-lookup.csv") %>%
filter(use_in_db)
usethis::use_data(characteristic_names_lookup, overwrite = TRUE)
# CHARACTERISTIC ATTRIBUTES ----------------------------------------------
characteristic_attributes <- read_csv("data-raw/domain-values/characteristic-attributes.csv")
usethis::use_data(characteristic_attributes, overwrite = TRUE)
# METHOD ID AND CONTEXT
method_id_and_context <- readr::read_csv("data-raw/domain-values/dcr-method-codes-lookup.csv")
usethis::use_data(method_id_and_context, overwrite = TRUE)
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