Fill results data as BDL or AQL with appropriate values
Arguments
- resdat
results data as returned by
readMWRresults- param
character string to filter results and check if a parameter in the
"Characteristic Name"column in the results file is also found in the data quality objectives file for accuracy, see details- accdat
data.framefor data quality objectives file for accuracy as returned byreadMWRacc- warn
logical to return warnings to the console (default)
Value
resdat filtered by param with any entries in "Result Value" as "BDL" or "AQL" replaced with appropriate values in the "Quantitation Limit" column, if present, otherwise the "MDL" or "UQL" columns from the data quality objectives file for accuracy are used. Values as "BDL" use one half of the appropriate limit. Output only includes rows with the activity type as "Field Msr/Obs" or "Sample-Routine".
Details
The param argument is used to identify the appropriate "MDL" or "UQL" values in the data quality objectives file for accuracy. A warning is returned to the console if the accuracy file does not contain the appropriate information for the parameter. Results will be filtered by param regardless of any warning.
Examples
# results file path
respth <- system.file('extdata/ExampleResults.xlsx', package = 'MassWateR')
# 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!
# accuracy path
accpth <- system.file('extdata/ExampleDQOAccuracy.xlsx',
package = 'MassWateR')
# accuracy data
accdat <- readMWRacc(accpth)
#> Running checks on data quality objectives for accuracy...
#> Checking column names... OK
#> Checking all required columns are present... OK
#> Checking column types... OK
#> Checking no "na" in Value Range... OK
#> Checking for text other than <=, ≤, <, >=, ≥, >, ±, %, AQL, BQL, log, or all... OK
#> Checking overlaps in Value Range... OK
#> Checking gaps in Value Range... OK
#> Checking Parameter formats... OK
#> Checking for missing entries for unit (uom)... OK
#> Checking if more than one unit (uom) per Parameter... OK
#> Checking acceptable units (uom) for each entry in Parameter... OK
#> Checking empty columns... OK
#>
#> All checks passed!
# apply to total phosphorus
utilMWRlimits(resdat, accdat, param = 'TP')
#> # A tibble: 48 × 18
#> `Monitoring Location ID` `Activity Type` `Activity Start Date`
#> <chr> <chr> <dttm>
#> 1 ABT-026 Sample-Routine 2022-05-15 00:00:00
#> 2 ABT-077 Sample-Routine 2022-05-15 00:00:00
#> 3 ABT-301 Sample-Routine 2022-05-15 00:00:00
#> 4 ABT-312 Sample-Routine 2022-05-15 00:00:00
#> 5 DAN-013 Sample-Routine 2022-05-15 00:00:00
#> 6 ELZ-004 Sample-Routine 2022-05-15 00:00:00
#> 7 HOP-011 Sample-Routine 2022-05-15 00:00:00
#> 8 NSH-002 Sample-Routine 2022-05-15 00:00:00
#> 9 ABT-026 Sample-Routine 2022-06-12 00:00:00
#> 10 ABT-062 Sample-Routine 2022-06-12 00:00:00
#> # ℹ 38 more rows
#> # ℹ 15 more variables: `Activity Start Time` <chr>,
#> # `Activity Depth/Height Measure` <chr>, `Activity Depth/Height Unit` <chr>,
#> # `Activity Relative Depth Name` <chr>, `Characteristic Name` <chr>,
#> # `Result Value` <dbl>, `Result Unit` <chr>, `Quantitation Limit` <chr>,
#> # `QC Reference Value` <chr>, `Result Measure Qualifier` <chr>,
#> # `Result Attribute` <chr>, `Sample Collection Method ID` <chr>, …
# apply to E.coli
utilMWRlimits(resdat, accdat, param = 'E.coli')
#> # A tibble: 12 × 18
#> `Monitoring Location ID` `Activity Type` `Activity Start Date`
#> <chr> <chr> <dttm>
#> 1 ABT-077 Sample-Routine 2022-06-13 00:00:00
#> 2 ABT-162 Sample-Routine 2022-06-13 00:00:00
#> 3 ABT-077 Sample-Routine 2022-06-27 00:00:00
#> 4 ABT-162 Sample-Routine 2022-06-27 00:00:00
#> 5 ABT-077 Sample-Routine 2022-07-18 00:00:00
#> 6 ABT-162 Sample-Routine 2022-07-18 00:00:00
#> 7 ABT-077 Sample-Routine 2022-08-01 00:00:00
#> 8 ABT-162 Sample-Routine 2022-08-01 00:00:00
#> 9 ABT-077 Sample-Routine 2022-08-15 00:00:00
#> 10 ABT-162 Sample-Routine 2022-08-15 00:00:00
#> 11 ABT-077 Sample-Routine 2022-08-29 00:00:00
#> 12 ABT-162 Sample-Routine 2022-08-29 00:00:00
#> # ℹ 15 more variables: `Activity Start Time` <chr>,
#> # `Activity Depth/Height Measure` <chr>, `Activity Depth/Height Unit` <chr>,
#> # `Activity Relative Depth Name` <chr>, `Characteristic Name` <chr>,
#> # `Result Value` <dbl>, `Result Unit` <chr>, `Quantitation Limit` <chr>,
#> # `QC Reference Value` <chr>, `Result Measure Qualifier` <chr>,
#> # `Result Attribute` <chr>, `Sample Collection Method ID` <chr>,
#> # `Project ID` <chr>, `Local Record ID` <chr>, `Result Comment` <chr>