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update TADA_CheckRequiredFields and TADA_AutoClean #557

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Dec 23, 2024
Merged

update TADA_CheckRequiredFields and TADA_AutoClean #557

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a6da94c
update TADA_CheckRequiredFields
cristinamullin Dec 17, 2024
e86259e
use dataRetrieval:::create_dateTime to create ActivityStartDateTime i…
cristinamullin Dec 17, 2024
16ee669
Update TADA_CheckRequiredFields.Rd
cristinamullin Dec 17, 2024
0c5ff57
Update RequiredCols.R
hillarymarler Dec 17, 2024
883f23a
Update Utilities.R
hillarymarler Dec 17, 2024
2494bbd
Update Utilities.R
hillarymarler Dec 17, 2024
7880454
Update TADA_RandomTestingData.Rd
hillarymarler Dec 17, 2024
878d562
update error message to include function name
cristinamullin Dec 17, 2024
0a27060
Update TADA_CheckRequiredFields.Rd
cristinamullin Dec 17, 2024
96b6626
Merge branch '556-test-failure-when-tada_randomtestingdata-provides-n…
cristinamullin Dec 23, 2024
f776a29
update docs
cristinamullin Dec 23, 2024
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39 changes: 28 additions & 11 deletions R/RequiredCols.R
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Expand Up @@ -341,32 +341,47 @@ TADA_GetTemplate <- function() {



#' TADA Module 1 Required Fields Check
#' TADA Required Fields Check
#'
#' This function checks if all required fields for TADA Module 1 are
#' included in the input dataframe.
#' This function checks if all fields required to run TADA functions are included in the input dataframe. It is used in the TADA Shiny application to test user supplied files for compatibility with the application.
#'
#' @param .data A dataframe
#'
#' @return Boolean result indicating whether or not the input dataframe contains all of the TADA profile fields.
#' @return Boolean result, TRUE or FALSE, indicating whether or not the input dataframe contains all of the required fields. If FALSE, an error will be returned that includes the names of all missing columns.
#'
#' @export
#'
#' @examples
#' \dontrun{
#' # Find web service URLs for each Profile using WQP User Interface (https://www.waterqualitydata.us/)
#' # Example WQP URL: https://www.waterqualitydata.us/#statecode=US%3A09&characteristicType=Nutrient&startDateLo=04-01-2023&startDateHi=11-01-2023&mimeType=csv&providers=NWIS&providers=STEWARDS&providers=STORET
#'
#'
#' # Use TADA_ReadWQPWebServices to load the Station, Project, and Phys-Chem Result profiles
#' stationProfile <- TADA_ReadWQPWebServices("https://www.waterqualitydata.us/data/Station/search?statecode=US%3A09&characteristicType=Nutrient&startDateLo=04-01-2023&startDateHi=11-01-2023&mimeType=csv&zip=yes&providers=NWIS&providers=STEWARDS&providers=STORET")
#' physchemProfile <- TADA_ReadWQPWebServices("https://www.waterqualitydata.us/data/Result/search?statecode=US%3A09&characteristicType=Nutrient&startDateLo=04-01-2023&startDateHi=11-01-2023&mimeType=csv&zip=yes&dataProfile=resultPhysChem&providers=NWIS&providers=STEWARDS&providers=STORET")
#' projectProfile <- TADA_ReadWQPWebServices("https://www.waterqualitydata.us/data/Project/search?statecode=US%3A09&characteristicType=Nutrient&startDateLo=04-01-2023&startDateHi=11-01-2023&mimeType=csv&zip=yes&providers=NWIS&providers=STEWARDS&providers=STORET")
#'
#'
#' # Join all three profiles using TADA_JoinWQPProfiles
#' TADAProfile <- TADA_JoinWQPProfiles(FullPhysChem = physchemProfile, Sites = stationProfile, Projects = projectProfile)
#'
#' # Run TADA_CheckRequiredFields
#' CheckRequirements_TADAProfile <- TADA_CheckRequiredFields(TADAProfile)
#'
#' # Run TADA_CheckRequiredFields, returns error message, 'The dataframe does not contain the required fields: ActivityStartDateTime'
#' TADA_CheckRequiredFields(TADAProfile)
#'
#' # Add missing col
#' TADAProfile1 <- dataRetrieval:::create_dateTime(df = TADAProfile,
#' date_col = "ActivityStartDate",
#' time_col = "ActivityStartTime.Time",
#' tz_col = "ActivityStartTime.TimeZoneCode",
#' tz = "UTC")
#'
#' review_TADAProfile1 = TADAProfile1 %>% dplyr::select(c("ActivityStartDate",
#' "ActivityStartTime.Time",
#' "ActivityStartTime.TimeZoneCode",
#' "ActivityStartDateTime",
#' "ActivityStartTime.TimeZoneCode_offset"))
#'
#' # re-run TADA_CheckRequiredFields, returns TRUE
#' TADA_CheckRequiredFields(TADAProfile1)
#' }
#'
TADA_CheckRequiredFields <- function(.data) {
Expand All @@ -380,8 +395,10 @@ TADA_CheckRequiredFields <- function(.data) {
if (all(require.originals %in% colnames(.data)) == TRUE) {
TRUE
} else {
stop("The dataframe does not contain the required fields.")
}
missingcols <- base::setdiff(require.originals, colnames(.data))
stop("The dataframe does not contain the required fields: ",
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paste(as.character(missingcols),
collapse = ", ")) }
}


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13 changes: 12 additions & 1 deletion R/Utilities.R
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Expand Up @@ -224,7 +224,6 @@ TADA_AutoClean <- function(.data) {
# execute function after checks are passed



# check to make sure columns do not already exist and capitalize fields with known synonyms that
# only differ in caps
print("TADA_Autoclean: creating TADA-specific columns.")
Expand Down Expand Up @@ -272,6 +271,18 @@ TADA_AutoClean <- function(.data) {
.data$TADA.ResultMeasure.MeasureUnitCode <- toupper(.data$ResultMeasure.MeasureUnitCode)
}

if ("ActivityStartDateTime" %in% colnames(.data)) {
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@cristinamullin cristinamullin Dec 17, 2024 •
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I'd like to add ActivityStartDateTime and convert times zones in our autoclean function here in the same format/way as the DR functions do. This is needed in cases where in the TADAShiny app, a user brings their own data file that was not downloaded using either EPATADA or dataRetrieval, but has all other required cols. It should replicate any additional things dataRetrieval readWQPdata does to a df.

Data retrieval produces "2022-06-08 16:00:00" while my code below produces "2023-05-11 11:45:00 UTC". DR also converts times and time zones to UTC, but that's not included in the value here. The time zone conversion and addition of ActivityStartDateTime occurs even when attributes are ignored (which is fine, we need that col):

  results.DR <- dataRetrieval::readWQPdata(WQPquery,
    dataProfile = "resultPhysChem",
    ignore_attributes = TRUE
  )

I'd like to understand this piece of dataretreival better. If there is a stand along function that can change all date/time fields to UTC and also creates this ActivityStartDate col (and does anything else that is happening behind the scenes), we could leverage that here instead.

@ldecicco-USGS do you have any advice on this topic? Can you please point us to the location in your code where this occurs? I did a quick search of your repo but couldn't find it. Thanks!

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The internal code is here;
https://github.com/DOI-USGS/dataRetrieval/blob/main/R/importWQP.R#L223
(you can call it, you'd just need to do a triple colon: dataRetrieval:::create_dateTime)

offsetLibrary is a dataframe saved in sysdata.rda
You can see where and how it gets called here:
https://github.com/DOI-USGS/dataRetrieval/blob/main/R/importWQP.R#L160

Let me know if there's something unclear

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Thank you! This really helped me understand how to interpret both the ActivityStartDateTime and offset cols (these starting showing up in TADA df's for the first time last month: ActivityStartTime.TimeZoneCode_offset and ActivityEndTime.TimeZoneCode_offset) that are returned from dataRetrieval. For dataRetrieval users, I think it might be more user friendly to include a column titled ActivityStartDateTime.TimeZoneCode (UTC in this case) instead of the ActivityStartTime.TimeZoneCode_offset (which includes number of hours). As is, the target time zone for ActivityStartDateTime (a function input here) is not documented anywhere in the returned df (see review_TADAProfile1 below). Alternatively, UTC could potentially be included in ActivityStartDateTime but that might break people workflows (e.g. "2023-05-11 11:45:00 UTC"). I am going to create a separate issue in TADA repo to document this issue and discuss how to address it. Is this something you are potentially interested in updating in dataRetrieval?

# Find web service URLs for each Profile using WQP User Interface (https://www.waterqualitydata.us/)
# Example WQP URL: https://www.waterqualitydata.us/#statecode=US%3A09&characteristicType=Nutrient&startDateLo=04-01-2023&startDateHi=11-01-2023&mimeType=csv&providers=NWIS&providers=STEWARDS&providers=STORET

# Use TADA_ReadWQPWebServices to load the Station, Project, and Phys-Chem Result profiles
stationProfile <- TADA_ReadWQPWebServices("https://www.waterqualitydata.us/data/Station/search?statecode=US%3A09&characteristicType=Nutrient&startDateLo=04-01-2023&startDateHi=11-01-2023&mimeType=csv&zip=yes&providers=NWIS&providers=STEWARDS&providers=STORET")
physchemProfile <- TADA_ReadWQPWebServices("https://www.waterqualitydata.us/data/Result/search?statecode=US%3A09&characteristicType=Nutrient&startDateLo=04-01-2023&startDateHi=11-01-2023&mimeType=csv&zip=yes&dataProfile=resultPhysChem&providers=NWIS&providers=STEWARDS&providers=STORET")
projectProfile <- TADA_ReadWQPWebServices("https://www.waterqualitydata.us/data/Project/search?statecode=US%3A09&characteristicType=Nutrient&startDateLo=04-01-2023&startDateHi=11-01-2023&mimeType=csv&zip=yes&providers=NWIS&providers=STEWARDS&providers=STORET")

# Join all three profiles using TADA_JoinWQPProfiles
TADAProfile <- TADA_JoinWQPProfiles(FullPhysChem = physchemProfile, Sites = stationProfile, Projects = projectProfile)

# Run TADA_CheckRequiredFields, returns error message, 'The dataframe does not contain the required fields: ActivityStartDateTime'
TADA_CheckRequiredFields(TADAProfile)

# Add missing col
TADAProfile1 <- dataRetrieval:::create_dateTime(df = TADAProfile, 
                                         date_col = "ActivityStartDate", 
                                         time_col = "ActivityStartTime.Time",
                                         tz_col = "ActivityStartTime.TimeZoneCode", 
                                         tz = "UTC")

review_TADAProfile1 = TADAProfile1 %>% dplyr::select(c("ActivityStartDate", 
                          "ActivityStartTime.Time", 
                          "ActivityStartTime.TimeZoneCode", 
                          "ActivityStartDateTime",
                          "ActivityStartTime.TimeZoneCode_offset"))

# re-run TADA_CheckRequiredFields, returns TRUE
TADA_CheckRequiredFields(TADAProfile1)

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created a separate issue here to continue the conversation: #558

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Just making sure we're both on the same page: In dataRetrieval, the default timezone is UTC set here:
https://github.com/DOI-USGS/dataRetrieval/blob/main/R/readWQPdata.R#L200
You can read about changing timezones here:
https://doi-usgs.github.io/dataRetrieval/reference/readWQPdata.html#arg-tz
This sets the time zone attribute of the POSIX object.

Like this:

library(dataRetrieval)
nameToUse <- "pH"
pHData <- readWQPdata(siteid = "USGS-04024315", 
                      characteristicName = nameToUse,
                      service = "ResultWQX")
attr(pHData$Activity_StartDateTime, "tzone")
[1] "UTC"
pHData$Activity_StartDateTime[1]
[1] "1975-09-27 15:50:00 UTC"

pHData2 <- readWQPdata(siteid = "USGS-04024315", 
                      characteristicName = nameToUse,
                      tz = "America/Chicago",
                      service = "ResultWQX")
attr(pHData2$Activity_StartDateTime, "tzone")
[1] "America/Chicago"
pHData2$Activity_StartDateTime[1]
[1] "1975-09-27 10:50:00 CDT"

So what you are asking for is a column that converts the offset number of hours to the timezone it was converted to?

Note there's also the link in the help to the OlsonNames() base R function which talks about how R handles timezones. The issue is that different operating systems and depending on where in the world the computer things you are will want different abbreviations for timezones (that's why using the OlsonNames is what has been working best for dataRetrieval).
https://rdrr.io/r/base/timezones.html

.data <- .data
} else {
# creates ActivityStartDateTime and ActivityStartTime.TimeZoneCode_offset
# this is only needed when dataRetrieval is not used to get WQP data
.data <- dataRetrieval:::create_dateTime(df = .data,
date_col = "ActivityStartDate",
time_col = "ActivityStartTime.Time",
tz_col = "ActivityStartTime.TimeZoneCode",
tz = "UTC")
}

# Transform "Dissolved oxygen (DO)" characteristic name to "DISSOLVED OXYGEN SATURATION" IF
# result unit is "%" or "% SATURATN".

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27 changes: 21 additions & 6 deletions man/TADA_CheckRequiredFields.Rd
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