This report is automatically generated with the R package knitr (version 1.40) .

source("R Functions/functions_QA data.R")


### LOAD DATA ###
#FIND AND REPLACE (Ctrl+F) 'WORKSHEET' WITH MORE APPROPRIATE NAME (e.g., 'CALFED_data')
#CHANGE 'FILENAME' & 'SHEETNAME' WITH ACTUAL NAMES
USGSFISH <- readxl::read_excel('Reeval_Impl_Goals_Linkage_Analysis/Data/Fish/USGSFISH.xlsx', sheet='Sheet1', guess_max = 30000)
nrow(USGSFISH) #number of rows should match the Excel file (minus the header row)
## [1] 507
### LIST COLUMNS TO BE USED, ADD USER DEFINED COLUMNS, & RENAME COLUMNS TO CEDEN STANDARDS ###
#Use 1.READ ME.xlsx, 'ColumnsForR' to list & identify columns that match corresponding CEDEN Standard columns
keep_cols <- c('SourceID','SourceRow', 'CitationCode (PUB ID)', 'ProgramName','ParentProjectName','ProjectCode','StationName','StationCode','TargetLatitude','TargetLongitude','SampleDate','CommonName','FinalID','NumberFishPerComp','Analyte','Unit','Result','ResQualCode','MDL','RL','WeightAvg g','TLMin mm','TLMax mm','TLAvgLength mm','SampleID','WBT','ProjectName (report title)','CollectionTime','TissueName (only filet or whole)','MethodName'
               )

#temp_cols <- c('') #Include columns that do not match CEDEN standards but may be useful (e.g., Unit columns for MDL & RL)
#temp_cols are removed before the data is merged with other datasets

USGSFISH_new <- USGSFISH %>%
  select( c(keep_cols) ) %>% #DO NOT CHANGE - selects columns specified above
  rename(
    #Rename USGSFISH columns to CEDEN format here: CEDEN 'COLUMNNAME' = USGSFISH 'COLUMNNAME'
    #DELETE COLUMN NAMES THAT DO NOT HAVE AN EQUIVALENT COLUMN IN THE USGSFISH
    'ProjectName' = 'ProjectName (report title)',
    'ResultQualCode' = 'ResQualCode',
    'TaxonomicName' = 'FinalID',
    'SampleTime' = 'CollectionTime',
    'TissueName' = 'TissueName (only filet or whole)',
    'Method' = 'MethodName',
    'CitationCode' = 'CitationCode (PUB ID)'
  ) %>%
  mutate(
    #Create Missing column or modify existing column here: CEDEN COLUMNNAME = 'SPECIFIED VALUE' or FUNCTION
    #DELTE COLUMN NAMES THAT DO NOT NEED TO BE CHANGED
    CoordSystem = NA_character_,
    CompositeRowID = NA_character_,
    BatchVerification = NA_character_,
    ComplianceCode = NA_character_,
    CompositeID = NA_character_,
    LabSubmissionCode = NA_character_,
    QACode = NA_character_,
    ResultComments = NA_character_
  )

nrow(USGSFISH_new)
## [1] 507
#str(USGSFISH_new) #just to check data class of different columns - e.g., is Date column in POSIX format?
#View(USGSFISH_new)


### FORMAT COLUMN PARAMETERS ###

  # Standardize WBT (WaterBodyType) Groups - "River/Stream", "Estuary", "Drain/Canal", "Wetland", "Spring", "Slough", 
  #                                          "Pond",  "Lake/Reservoir", "Delta", "Forebay/Afterbay", "Not Recorded" #
unique(USGSFISH_new$WBT) #Identifies OLDNAMES
## [1] "River"       "Creek"       "Drain/Canal" "Slough"      "Gulch"       "Pond"       
## [7] "Lake"
#STANDARD CODE TO CHANGE GROUPING NAMES
USGSFISH_new <- USGSFISH_new %>%
  mutate(WBT = recode(WBT,
                      "River" = "River/Stream",
                      "Creek" = "River/Stream",
                      "Gulch" = "River/Stream",
                      "Lake" = "Lake/Reservoir"),
         #EXAMPLE FOR WHEN "OLDNAME" is 'NA' but we want a NEWNAME - if this example is deleted, also delete the comma after "Not Recorded" above
         WBT = case_when(is.na(WBT) ~ "Not Recorded", #Use "Not Recorded" when WBT value is NA
                         TRUE ~ WBT)                  #Keep original WBT value in all other cases
  ) %>%
  filter(WBT %are not% c("Lake/Reservoir", "Pond")) #checked and made sure no ponds or lakes where part of a river or the delta
unique(USGSFISH_new$WBT) #New naming structure for WBT Groupings
## [1] "River/Stream" "Drain/Canal"  "Slough"
  # Standardize TissueName Groups - "Fillet" or "Whole Body" #
unique(USGSFISH_new$TissueName)
## [1] "Whole fish"  "Liver"       "Soft tissue" "Fillet"      "Whole body"
USGSFISH_new <- USGSFISH_new %>%
  mutate(TissueName = recode(TissueName,
                             "Whole fish" = "Whole Body",
                             "Whole body" = "Whole Body"
                             )
         ) %>%
  filter(TissueName %in% c('Fillet','Whole Body'))
unique(USGSFISH_new$TissueName)
## [1] "Whole Body" "Fillet"
  # Standardize Analyte Groups - "Mercury, Total" (we consider Total Mercury and Methylmercury to be approx equal) #
unique(USGSFISH_new$Analyte)
## [1] "Mercury, Total"           "Monomethylmercury, Total"
USGSFISH_new <- USGSFISH_new %>%
  mutate( Analyte = recode(Analyte,
                           "Monomethylmercury, Total" = "Mercury, Total"
                           ) )
#Create 'Analyte' column from Analyte & Analyte_part2 columns - then delete Analyte_part2 column##
unique(USGSFISH_new$Analyte) #New naming structure for Analyte Groupings
## [1] "Mercury, Total"
  # Standardize ResultQualCode Groups - "ND", "DNQ", NA#
unique(USGSFISH_new$ResultQualCode) #Identifies OLDNAMES 
## [1] NA  "="
#Lauren to fix error: attempt to use zero-length variable name - maybe not needed
#USGSFISH_new <- USGSFISH_new %>%
#  mutate(ResultQualCode = recode(ResultQualCode,
#                              "" = NA_character_ #changes empty cells to NA - delete if not needed
#                                 ))
unique(USGSFISH_new$ResultQualCode) #New naming structure for ResultQualCode Groupings
## [1] NA  "="
  # Format Result Column to Numeric#
  # Check column for text - based on text user needs to decide what to do
if(!is.numeric(USGSFISH_new$Result)){
  old <-USGSFISH_new$Result
  new <-USGSFISH_new$Result
  new[grepl('<|[a-df-zA-DF-Z]', new)] <- NA #skip 'e' for exponential notation e.g., "8e-005"
  cat(paste0("'Result' column should be numeric but some cells contain ", grammaticList(setdiff(old, new)),"\n",
             ".\nACTIONS TAKEN:\n",
             "For numeric values with '<': 'ND' put in ResultQualCode column, numeric value moved to MDL column, & made Result blank.\n",
             "For NA's: 'ND' put in ResultQualCode column, MDL column value converted to mg/Kg, & made Result blank.\n\n"))
  USGSFISH_new <- USGSFISH_new %>%
    mutate(
      # Fixing numeric Result with '<'s
      MDL = if_else(grepl('<',Result), '.1', MDL),       # Only Results with '<' are '<0.1'
      MDL = if_else(grepl('NA',Result), '.00026', MDL),  # Only Results with NA's have MDL of 0.26 ng/g, so need to divide by 1000 to convert to mg/Kg
      ResultQualCode = if_else(grepl('<|NA',Result), 'ND', ResultQualCode),
      Result = if_else(grepl('<|NA',Result), NA_character_, Result),

      Result = as.numeric(Result)
    )

} else {
  cat("'Result' column is in numeric format\n")}
## 'Result' column should be numeric but some cells contain <.1 and NA
## .
## ACTIONS TAKEN:
## For numeric values with '<': 'ND' put in ResultQualCode column, numeric value moved to MDL column, & made Result blank.
## For NA's: 'ND' put in ResultQualCode column, MDL column value converted to mg/Kg, & made Result blank.
  # Format MDL Column to Numeric#
  # Check column for text - based on text user needs to decide what to do
if(!is.numeric(USGSFISH_new$MDL)){
  old <-USGSFISH_new$MDL
  new <- USGSFISH_new$MDL
  new[grepl('[a-df-zA-DF-Z]', new)] <- NA #skip 'e' for exponential notation e.g., "8e-005"
  #Print what text was found and what is being done
  cat(paste0("'MDL' column should be numeric but some cells contain ", grammaticList(setdiff(old, new)),
             ".\nACTIONS TAKEN:\n",
             "The 'ng/g' text dropped and value converted to mg/Kg.\n\n"))
  USGSFISH_new <- USGSFISH_new %>%
    mutate( #Do stuff to prep column to be converted to Numeric
      MDL = as.character(as.numeric(gsub(' ng/g','',MDL))/1000),  #drop the ng/g unit, convert to number to convert value to mg/Kg, convert back to character to match column class

      MDL = as.numeric(new)
    )
} else {
  cat("'MDL' column is in numeric format\n")}
## 'MDL' column should be numeric but some cells contain 1.33 ng/g, 1.5 ng/g, 0.26 ng/g, and 0.07 ng/g.
## ACTIONS TAKEN:
## The 'ng/g' text dropped and value converted to mg/Kg.
  # Format RL Column to Numeric#  
  # Check column for text - based on text user needs to decide what to do
if(!is.numeric(USGSFISH_new$RL)){
  if(all(is.na(USGSFISH_new$RL))){
    USGSFISH_new <- USGSFISH_new %>%
      mutate( #Due stuff to prep column to be converted to Numeric
        RL = as.numeric(new)
        )
    cat("'RL' column is all blanks and was converted to numeric format\n")
  }else{
    old <-USGSFISH_new$RL
    new <-USGSFISH_new$RL
    new[grepl('[a-df-zA-DF-Z]', new)] <- NA #skip 'e' for exponential notation e.g., "8e-005"
    #Print what text was found and what is being done
    cat(paste0("'RL' column should be numeric but some cells contain ", grammaticList(setdiff(old, new)),
               ".\nACTIONS TAKEN:\n",
               "~explain here~.\n"))
    }
  }else{
  cat("'RL' column is in numeric format\n")}
## 'RL' column is all blanks and was converted to numeric format
  # Check if Result, MDL, & RL Columns all equal <NA> or 0 - these rows have no useful information
nrow(USGSFISH_new) #Number rows before
## [1] 381
#CODE BELOW REQUIRES USER TROUBLESHOOTING DEPENDING ON AVAILABLE COLUMNS AND SPREADSHEET SPECIFIC CONDITIONS#
USGSFISH_new <- USGSFISH_new %>%
  #Set 0 & negative values as blank
  mutate(Result = ifelse(Result <= 0, NA_real_, Result),
         MDL = ifelse(MDL <= 0, NA_real_, MDL),
         RL = ifelse(RL <= 0, NA_real_, RL))
na_results <- USGSFISH_new %>% #Record rows where Result, MDL, & RL all equal <NA>
  filter( is.na(Result) & is.na(MDL) & is.na(RL) )
#View(na_results)
USGSFISH_new <- anti_join(USGSFISH_new, na_results, by='SourceRow') #returns rows from USGSFISH_new not matching values in no_result
nrow(USGSFISH_new) #Number rows after
## [1] 381
  # Format Units Column - "mg/Kg ww" or "mg/Kg dw"
unique(USGSFISH_new$Unit) #Identifies OLDNAMES
## [1] "mg/kg"     "mg/kg; ww"
# If more than 1 unit colmn exists (e.g., for RL and MDL columns) see WQP script for example on merging into 1 column
USGSFISH_new <- USGSFISH_new %>%
  mutate(Unit = recode(Unit,
                       "mg/kg; ww" = "mg/Kg ww",
                       "mg/kg" = "mg/Kg")
  )
unique(USGSFISH_new$Unit) #New naming structure for Unit Groupings
## [1] "mg/Kg"    "mg/Kg ww"
  # Format Date and Time Column # - Lauren to fix issue with date. not showing up when time is a column; both don't merge date and time
# THE EXAMPLE CODE BELOW ASSUMES DATE AND TIME ARE IN SAME COLUMNS - IF TIME IS IN SEPERATE COLUMN LOOK AT AQ LINKAGE DATA TEMPLATE
USGSFISH_new <- USGSFISH_new %>%
  #rowise() %>%    # rowise is very slow - so used sapply to make this a rowise operation
  mutate(
    #If SampleDate & CollectioTIme are not in Character format by defualt, turn it into a character class so it exports better
    SampleDate = ifelse(sapply(SampleDate, is.character), SampleDate, as.character(as.Date(SampleDate))),
    SampleTime = ifelse(sapply(SampleTime, is.character), SampleTime, format(lubridate::ymd_hms(SampleTime), "%H:%M:%S")),
    #COMBINE DATE AND TIME INTO SampleDateTime COLUMN
    SampleDateTime = ifelse(!is.na(SampleTime), paste(SampleDate, SampleTime), paste(SampleDate, '00:00:00')),
    #FORMAT SampleDateTime COLUMN TO DATE FORMAT
    SampleDateTime = lubridate::ymd_hms(SampleDateTime)
  )


### REMOVE TEMPORARY COLUMNS ###
#USGSFISH_new <- USGSFISH_new %>%
#  select(-one_of(temp_cols)) #Remove temp columns since they are no longer needed
#View(USGSFISH_new)

## SAVE FORMATTED DATA AS EXCEL FILE ##
writexl::write_xlsx(USGSFISH_new, path='Reeval_Impl_Goals_Linkage_Analysis/Data/Fish/USGSFISH_ceden_format.xlsx')
# In excel, to convert SampleDate column to Date format
# 1 - Select the date column.
# 2 - Go to the Data-tab and choose "Text to Columns".
# 3 - On the first screen, leave radio button on "delimited" and click Next.
# 4 - Unselect any delimiter boxes (everything blank) and click Next.
# 5 - Under column data format choose Date, select YMD
# 6 - Click Finish.

The R session information (including the OS info, R version and all packages used):

    sessionInfo()
## R version 4.2.2 (2022-10-31 ucrt)
## Platform: x86_64-w64-mingw32/x64 (64-bit)
## Running under: Windows 10 x64 (build 22621)
## 
## Matrix products: default
## 
## locale:
## [1] LC_COLLATE=English_United States.utf8  LC_CTYPE=English_United States.utf8   
## [3] LC_MONETARY=English_United States.utf8 LC_NUMERIC=C                          
## [5] LC_TIME=English_United States.utf8    
## 
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods   base     
## 
## other attached packages:
##  [1] lubridate_1.8.0    plotly_4.10.0      readxl_1.4.1       actuar_3.3-0      
##  [5] NADA_1.6-1.1       forcats_0.5.2      stringr_1.4.1      dplyr_1.0.9       
##  [9] purrr_0.3.4        readr_2.1.2        tidyr_1.2.0        tibble_3.1.8      
## [13] ggplot2_3.3.6      tidyverse_1.3.2    fitdistrplus_1.1-8 survival_3.4-0    
## [17] MASS_7.3-58.1     
## 
## loaded via a namespace (and not attached):
##  [1] lattice_0.20-45     assertthat_0.2.1    digest_0.6.29       utf8_1.2.2         
##  [5] R6_2.5.1            cellranger_1.1.0    backports_1.4.1     reprex_2.0.2       
##  [9] evaluate_0.16       highr_0.9           httr_1.4.4          pillar_1.8.1       
## [13] rlang_1.0.5         lazyeval_0.2.2      googlesheets4_1.0.1 rstudioapi_0.14    
## [17] data.table_1.14.2   Matrix_1.5-1        splines_4.2.2       googledrive_2.0.0  
## [21] htmlwidgets_1.5.4   munsell_0.5.0       broom_1.0.1         compiler_4.2.2     
## [25] modelr_0.1.9        xfun_0.32           pkgconfig_2.0.3     htmltools_0.5.3    
## [29] tidyselect_1.1.2    fansi_1.0.3         viridisLite_0.4.1   crayon_1.5.1       
## [33] tzdb_0.3.0          dbplyr_2.2.1        withr_2.5.0         grid_4.2.2         
## [37] jsonlite_1.8.0      gtable_0.3.1        lifecycle_1.0.1     DBI_1.1.3          
## [41] magrittr_2.0.3      scales_1.2.1        writexl_1.4.0       cli_3.3.0          
## [45] stringi_1.7.8       fs_1.5.2            xml2_1.3.3          ellipsis_0.3.2     
## [49] generics_0.1.3      vctrs_0.4.1         expint_0.1-7        tools_4.2.2        
## [53] glue_1.6.2          hms_1.1.2           fastmap_1.1.0       colorspace_2.0-3   
## [57] gargle_1.2.0        rvest_1.0.3         knitr_1.40          haven_2.5.1
    Sys.time()
## [1] "2024-01-05 11:25:14 PST"