Skip to contents

Check continuous monitoring data

Source: R/checkASRcont.R
checkASRcont.Rd

Check continuous monitoring data

Usage

checkASRcont(contdat)

Arguments

contdat

input data frame for results

Value

contdat is returned as is if no errors are found, otherwise an informative error message is returned prompting the user to make the required correction to the raw data before proceeding.

Details

This function is used internally within readASRcont to run several checks on the input data to verify correct formatting before downstream analysis.

The input data can use either of two formats:

  • Separate columns: Date, Time, and at least one parameter column

  • Combined column: DateTime, and at least one parameter column

The following checks are made:

  • Column names: Should include only Date, Time, DateTime, and at least one parameter column that matches the Parameter column in paramsASR

  • Required columns are present: Either Date + Time or DateTime are required for downstream analysis and upload to WQX

  • At least one parameter column is present: At least one parameter column that matches the Parameter column in paramsASR is required for downstream analysis and upload to WQX

  • Date format (separate columns only): Should be in a format recognized by lubridate::ymd() (e.g. "2024-06-01")

  • Time format (separate columns only): Should be parseable by lubridate::parse_date_time() using 24-hour ("16:30:33"), 12-hour AM/PM ("4:30:33 PM"), or Excel-prefixed ("1899-12-31 16:30:33") formats

  • DateTime format (combined column only): Should be parseable by lubridate::parse_date_time() using 24-hour or 12-hour AM/PM formats (e.g. "2024-06-01 16:30:33" or "2024-06-01 4:30:33 PM")

  • Missing values: No missing values in any columns

  • Parameter columns should be numeric: All parameter columns should be numeric values

Examples

contpth <- system.file('extdata/ExampleCont1.xlsx', package = 'AquaSensR')

contdat <- utilASRimportcont(contpth)

checkASRcont(contdat)
#> Running checks on continuous data...
#> 	Checking column names... OK
#> 	Checking Date, Time are present... OK
#> 	Checking at least one parameter column is present... OK
#> 	Checking date format... OK
#> 	Checking time format... OK
#> 	Checking for missing values... OK
#> 	Checking parameter columns for non-numeric values... OK
#> 
#> All checks passed!
#> # A tibble: 927 × 9
#>    Date       Time  `Water Temp_C` DO_pctsat DO_mg_l Conductivity_uS_cm TDS_mg_l
#>    <chr>      <chr>          <dbl>     <dbl>   <dbl>              <dbl>    <dbl>
#>  1 2024-08-14 13:5…           24.2      76.9    6.44               410.      266
#>  2 2024-08-14 13:5…           24.2      76.7    6.43               410.      266
#>  3 2024-08-14 13:5…           24.2      76.6    6.42               410.      266
#>  4 2024-08-14 13:5…           24.2      76.5    6.41               410.      266
#>  5 2024-08-14 13:5…           24.2      76.3    6.4                409       266
#>  6 2024-08-14 13:5…           24.2      76.3    6.39               409.      266
#>  7 2024-08-14 13:5…           24.2      76.2    6.39               409.      266
#>  8 2024-08-14 13:5…           24.2      76.1    6.38               409.      266
#>  9 2024-08-14 13:5…           24.2      76.5    6.41               404.      262
#> 10 2024-08-14 13:5…           24.2      77.6    6.5                399.      259
#> # ℹ 917 more rows
#> # ℹ 2 more variables: Salinity_ppt <dbl>, pH_SU <dbl>