Run quality control completeness checks for water quality monitoring results

Usage

qcMWRcom(res = NULL, frecom = NULL, fset = NULL, runchk = TRUE, warn = TRUE)

Arguments

res: character string of path to the results file or data.frame for results returned by readMWRresults
frecom: character string of path to the data quality objectives file for frequency and completeness or data.frame returned by readMWRfrecom
fset: optional list of inputs with elements named res, acc, frecom, sit, or wqx overrides the other arguments
runchk: logical to run data checks with checkMWRresults and checkMWRfrecom, applies only if res or frecom are file paths
warn: logical to return warnings to the console (default)

Value

The output shows the completeness checks from the combined files. Each row applies to a completeness check for a parameter. The datarec and qualrec columns show the number of data records and qualified records, respectively. The datarec column specifically shows only records not for quality control by excluding those as duplicates, blanks, or spikes in the count. The standard column shows the relevant percentage required for the quality control check from the quality control objectives file, the complete column shows the calculated completeness taken from the input data, and the met column shows if the standard was met by comparing if complete is greater than or equal to standard.

Details

The function can be used with inputs as paths to the relevant files or as data frames returned by readMWRresults and readMWRfrecom. For the former, the full suite of data checks can be evaluated with runkchk = T (default) or suppressed with runchk = F. In the latter case, downstream analyses may not work if data are formatted incorrectly. For convenience, a named list with the input arguments as paths or data frames can be passed to the fset argument instead. See the help file for utilMWRinput.

Note that frequency is only evaluated on parameters in the Parameter column in the data quality objectives frequency and completeness file. A warning is returned if there are parameters in Parameter in the frequency and completeness file that are not in Characteristic Name in the results file.

Similarly, parameters in the results file in the Characteristic Name column that are not found in the data quality objectives frequency and completeness file are not evaluated. A warning is returned if there are parameters in Characteristic Name in the results file that are not in Parameter in the frequency and completeness file.

Examples

##
# using file paths

# results path
respth <- system.file('extdata/ExampleResults.xlsx', package = 'MassWateR')

# frequency and completeness path
frecompth <- system.file('extdata/ExampleDQOFrequencyCompleteness.xlsx', 
     package = 'MassWateR')

qcMWRcom(res = respth, frecom = frecompth)
#> Running checks on results data...
#> 	Checking column names... OK
#> 	Checking all required columns are present... OK
#> 	Checking valid Activity Types... OK
#> 	Checking Activity Start Date formats... OK
#> 	Checking depth data present... OK
#> 	Checking for non-numeric values in Activity Depth/Height Measure... OK
#> 	Checking Activity Depth/Height Unit... OK
#> 	Checking Activity Relative Depth Name formats... OK
#> 	Checking values in Activity Depth/Height Measure > 1 m / 3.3 ft... OK
#> 	Checking Characteristic Name formats... OK
#> 	Checking Result Values... OK
#> 	Checking for non-numeric values in Quantitation Limit... OK
#> 	Checking QC Reference Values... OK
#> 	Checking for missing entries for Result Unit... OK
#> 	Checking if more than one unit per Characteristic Name... OK
#> 	Checking acceptable units for each entry in Characteristic Name... OK
#> 
#> All checks passed!
#> Running checks on data quality objectives for frequency and completeness...
#> 	Checking column names... OK
#> 	Checking all required columns are present... OK
#> 	Checking for non-numeric values... OK
#> 	Checking for values outside of 0 and 100... OK
#> 	Checking Parameter formats... OK
#> 	Checking empty columns... OK
#> 
#> All checks passed!
#> # A tibble: 8 × 6
#>   Parameter      datarec qualrec standard complete met  
#>   <chr>            <int>   <int>    <dbl>    <dbl> <lgl>
#> 1 Ammonia             43       0       90    100   TRUE 
#> 2 DO                  49       0       90    100   TRUE 
#> 3 E.coli              12       0       90    100   TRUE 
#> 4 Nitrate             20       0       90    100   TRUE 
#> 5 Sp Conductance      49       0       90    100   TRUE 
#> 6 TP                  48       5       90     89.6 FALSE
#> 7 Water Temp          49       0       90    100   TRUE 
#> 8 pH                  49       0       90    100   TRUE 

##
# using data frames

# results data
resdat <- readMWRresults(respth)
#> Running checks on results data...
#> 	Checking column names... OK
#> 	Checking all required columns are present... OK
#> 	Checking valid Activity Types... OK
#> 	Checking Activity Start Date formats... OK
#> 	Checking depth data present... OK
#> 	Checking for non-numeric values in Activity Depth/Height Measure... OK
#> 	Checking Activity Depth/Height Unit... OK
#> 	Checking Activity Relative Depth Name formats... OK
#> 	Checking values in Activity Depth/Height Measure > 1 m / 3.3 ft... OK
#> 	Checking Characteristic Name formats... OK
#> 	Checking Result Values... OK
#> 	Checking for non-numeric values in Quantitation Limit... OK
#> 	Checking QC Reference Values... OK
#> 	Checking for missing entries for Result Unit... OK
#> 	Checking if more than one unit per Characteristic Name... OK
#> 	Checking acceptable units for each entry in Characteristic Name... OK
#> 
#> All checks passed!

# frequency and completeness data
frecomdat <- readMWRfrecom(frecompth)
#> Running checks on data quality objectives for frequency and completeness...
#> 	Checking column names... OK
#> 	Checking all required columns are present... OK
#> 	Checking for non-numeric values... OK
#> 	Checking for values outside of 0 and 100... OK
#> 	Checking Parameter formats... OK
#> 	Checking empty columns... OK
#> 
#> All checks passed!

qcMWRcom(res = resdat, frecom = frecomdat)
#> # A tibble: 8 × 6
#>   Parameter      datarec qualrec standard complete met  
#>   <chr>            <int>   <int>    <dbl>    <dbl> <lgl>
#> 1 Ammonia             43       0       90    100   TRUE 
#> 2 DO                  49       0       90    100   TRUE 
#> 3 E.coli              12       0       90    100   TRUE 
#> 4 Nitrate             20       0       90    100   TRUE 
#> 5 Sp Conductance      49       0       90    100   TRUE 
#> 6 TP                  48       5       90     89.6 FALSE
#> 7 Water Temp          49       0       90    100   TRUE 
#> 8 pH                  49       0       90    100   TRUE