The quality control functions in MassWateR can be used once the required data are successfully imported into R (see the data input and checks vignette for an overview). The required data includes the results data file that describe the monitoring data and the data quality objective files for accuracy, frequency, and completeness. The example data files included with the package are imported here to demonstrate how to use the quality control functions:
library(MassWateR)
# import results data
respth <- system.file("extdata/ExampleResults.xlsx", package = "MassWateR")
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!
# import data quality objectives for accuracy
accpth <- system.file("extdata/ExampleDQOAccuracy.xlsx", package = "MassWateR")
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!
# import data quality objectives for frequency and completeness
frecompth <- system.file("extdata/ExampleDQOFrequencyCompleteness.xlsx", package = "MassWateR")
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!
Creating the review report
The qcMWRreview()
function compiles a review report as a
Word document for all quality control checks included in the MassWateR
package. The report shows several tables, including the data quality
objectives files for accuracy, frequency, and completeness, summary
results for all accuracy checks, summary results for all frequency
checks, summary results for all completeness checks, and individual
results for all accuracy checks. The report uses individual table
functions described in the sections below to return the results, which
include tabMWRacc()
, tabMWRfre()
, and
tabMWRcom()
.
The workflow for using this function is to import the required data
(results and data quality objective files, as above) and to fix any
errors noted on import prior to creating the review report. The function
can be used with inputs as paths to the relevant files or as data frames
returned by readMWRresults()
, readMWRacc()
,
and readMWRfrecom()
. For the former, the full suite of data
checks can be evaluated with runkchk = T
(default) or
suppressed with runchk = F
, as explained in the relevant
help files. In the latter case, downstream analyses may not work if data
are formatted incorrectly.
The report can be created as follows by including the required files and specifying an output directory where the Word document is saved (a temporary directory is used here). Once the function is done running, a message indicating success and where the file is located is returned. The Word file can be further edited by hand as needed.
qcMWRreview(res = resdat, acc = accdat, frecom = frecomdat, warn = FALSE, output_dir = tempdir())
#> Report created successfully! File located at /tmp/RtmprcMq4z/qcreview.docx
As a convenience, the input files can also be passed to the
qcMWRreview()
function as a named list using the
fset
argument. This eliminates the need to individually
specify the input arguments.
# names list of inputs
fsetls <- list(
res = resdat,
acc = accdat,
frecom = frecomdat
)
qcMWRreview(fset = fsetls, output_dir = tempdir())
Note that the warnings are suppressed above with
warn = FALSE
. By default, this argument is set to
TRUE
to view the warnings in the R console after the report
is created. The warnings indicate notable concerns to consider for the
input data that may need to be addressed. Details on these warnings are
described in the sections below for each quality control table.
Optional arguments for qcMWRreview()
that can be changed
as needed include specifying the file name with
output_file
, suppressing the raw data summaries at the end
of the report with rawdata = FALSE
, and changing the table
font sizes (dqofontsize
for the data quality objectives on
the first page, tabfontsize
for the remainder).
Quality control for accuracy
The quality control checks for accuracy assess several
characteristics of the data in the results file by referencing
appropriate values in the data quality objectives file for accuracy. In
short, the accuracy checks evaluate field blanks, lab blanks, field
duplicates, lab duplicates, lab spikes, and instrument checks. The
accuracy checks require results data (as in resdat
above)
and data quality objectives files for accuracy (accdat
) and
frequency and completeness (frecomdat
).
The tabMWRacc()
function is used to create tabular
results for the accuracy checks for each parameter. The function can be
used with inputs as paths to the relevant files or as data frames
returned by readMWRresults()
, readMWRacc()
,
and readMWRfrecom
. For the former, the full suite of data
checks can be evaluated with runkchk = T
(default) or
suppressed with runchk = F
, as explained in the data
inputs and checks vignette. In the latter case, downstream analyses
may not work if data are formatted incorrectly. Also note that accuracy
is only evaluated on parameters that are shared between the results file
and the data quality objectives accuracy file. A warning is returned if
there are parameters that do not match. The warnings can be suppressed
by setting warn = FALSE
.
The tabMWRacc()
function can return three types of
tables as specified with the type
argument:
"individual"
, "summary"
, or
"percent"
. The individual tables are specific to each type
of accuracy check for each parameter (e.g., field blanks, lab blanks,
etc.). The summary table summarizes all accuracy checks by the number of
checks and how many hit/misses are returned for each across all
parameters. The percent table is similar to the summary table, but
showing only percentages with appropriate color-coding for hit/misses.
The data quality objectives file for frequency and completeness is also
required if type = "summary"
or
type = "percent"
.
For type = "individual"
, the quality control tables for
accuracy are retrieved by specifying the check with the
accchk
argument. The accchk
argument can be
used to specify one of the following values to retrieve the relevant
tables: "Field Blanks"
, "Lab Blanks"
,
"Field Duplicates"
, "Lab Duplicates"
, or
"Lab Spikes / Instrument Checks"
. Below shows how to
retrieve each table using the data frames from above for the results and
quality objectives file for accuracy. The warnings are suppressed with
warn = FALSE
.
tabMWRacc(res = resdat, acc = accdat, frecom = frecomdat, type = "individual", accchk = "Field Blanks", warn = FALSE)
Parameter |
Date |
Site |
Result |
Threshold |
Hit/Miss |
---|---|---|---|---|---|
Ammonia |
|||||
2022-05-15 |
BDL |
0.1 mg/l |
|||
2022-06-12 |
BDL |
0.1 mg/l |
|||
2022-07-17 |
BDL |
0.1 mg/l |
|||
2022-07-17 |
BDL |
0.1 mg/l |
|||
2022-08-14 |
BDL |
0.1 mg/l |
|||
2022-08-14 |
BDL |
0.1 mg/l |
|||
2022-09-11 |
BDL |
0.1 mg/l |
|||
E.coli |
|||||
2022-06-13 |
BDL |
1 MPN/100ml |
|||
2022-07-18 |
BDL |
1 MPN/100ml |
|||
2022-08-01 |
BDL |
1 MPN/100ml |
|||
2022-08-29 |
BDL |
1 MPN/100ml |
|||
Nitrate |
|||||
2022-05-15 |
BDL |
0.05 mg/l |
|||
2022-06-12 |
BDL |
0.05 mg/l |
|||
2022-06-12 |
BDL |
0.05 mg/l |
|||
2022-07-17 |
BDL |
0.05 mg/l |
|||
2022-07-17 |
BDL |
0.05 mg/l |
|||
2022-08-14 |
BDL |
0.05 mg/l |
|||
2022-09-11 |
BDL |
0.05 mg/l |
|||
TP |
|||||
2022-05-15 |
BDL |
0.01 mg/l |
|||
2022-05-15 |
BDL |
0.01 mg/l |
|||
2022-06-12 |
BDL |
0.01 mg/l |
|||
2022-06-12 |
BDL |
0.01 mg/l |
|||
2022-07-17 |
BDL |
0.01 mg/l |
|||
2022-07-17 |
BDL |
0.01 mg/l |
|||
2022-07-17 |
0.01 mg/l |
0.01 mg/l |
MISS |
||
2022-08-14 |
BDL |
0.01 mg/l |
|||
2022-08-14 |
BDL |
0.01 mg/l |
|||
2022-09-11 |
BDL |
0.01 mg/l |
|||
2022-09-11 |
BDL |
0.01 mg/l |
tabMWRacc(res = resdat, acc = accdat, frecom = frecomdat,type = "individual", accchk = "Lab Blanks", warn = FALSE)
Parameter |
Date |
Sample ID |
Result |
Threshold |
Hit/Miss |
---|---|---|---|---|---|
Ammonia |
|||||
2022-05-15 |
BDL |
0.1 mg/l |
|||
2022-06-12 |
BDL |
0.1 mg/l |
|||
2022-07-17 |
BDL |
0.1 mg/l |
|||
2022-07-17 |
0.1 mg/l |
0.1 mg/l |
MISS |
||
2022-08-14 |
BDL |
0.1 mg/l |
|||
2022-08-14 |
BDL |
0.1 mg/l |
|||
2022-09-11 |
BDL |
0.1 mg/l |
|||
Nitrate |
|||||
2022-05-15 |
BDL |
0.05 mg/l |
|||
2022-06-12 |
BDL |
0.05 mg/l |
|||
2022-07-17 |
BDL |
0.05 mg/l |
|||
2022-08-14 |
BDL |
0.05 mg/l |
|||
2022-09-11 |
BDL |
0.05 mg/l |
|||
Sp Conductance |
|||||
2022-05-15 |
7 uS/cm |
50 uS/cm |
|||
2022-05-15 |
7.4 uS/cm |
50 uS/cm |
|||
2022-05-15 |
7.7 uS/cm |
50 uS/cm |
|||
2022-05-15 |
8.6 uS/cm |
50 uS/cm |
|||
2022-06-12 |
8.9 uS/cm |
50 uS/cm |
|||
2022-06-12 |
9 uS/cm |
50 uS/cm |
|||
2022-06-12 |
10.1 uS/cm |
50 uS/cm |
|||
2022-06-12 |
10.9 uS/cm |
50 uS/cm |
|||
2022-06-12 |
13 uS/cm |
50 uS/cm |
|||
2022-07-17 |
4 uS/cm |
50 uS/cm |
|||
2022-07-17 |
4 uS/cm |
50 uS/cm |
|||
2022-07-17 |
5.8 uS/cm |
50 uS/cm |
|||
2022-07-17 |
6 uS/cm |
50 uS/cm |
|||
2022-08-14 |
2.5 uS/cm |
50 uS/cm |
|||
2022-08-14 |
3 uS/cm |
50 uS/cm |
|||
2022-08-14 |
80 uS/cm |
50 uS/cm |
MISS |
||
2022-08-14 |
3.9 uS/cm |
50 uS/cm |
|||
2022-09-11 |
4 uS/cm |
50 uS/cm |
|||
2022-09-11 |
4.1 uS/cm |
50 uS/cm |
|||
2022-09-11 |
4.7 uS/cm |
50 uS/cm |
|||
2022-09-11 |
5.9 uS/cm |
50 uS/cm |
|||
TP |
|||||
2022-05-15 |
BDL |
0.01 mg/l |
|||
2022-06-12 |
BDL |
0.01 mg/l |
|||
2022-07-17 |
BDL |
0.01 mg/l |
|||
2022-08-14 |
BDL |
0.01 mg/l |
|||
2022-09-11 |
BDL |
0.01 mg/l |
tabMWRacc(res = resdat, acc = accdat, frecom = frecomdat, type = "individual", accchk = "Field Duplicates", warn = FALSE)
Parameter |
Date |
Site |
Initial Result |
Dup. Result |
Diff./RPD |
Hit/Miss |
---|---|---|---|---|---|---|
Ammonia |
||||||
2022-05-15 |
ABT-312 |
BDL |
BDL |
0% RPD |
||
2022-05-15 |
DAN-013 |
BDL |
BDL |
0% RPD |
||
2022-06-12 |
ABT-301 |
BDL |
0.2 mg/l |
67% RPD |
MISS |
|
2022-09-11 |
ABT-301 |
BDL |
BDL |
0% RPD |
||
DO |
||||||
2022-05-15 |
ABT-026 |
7.58 mg/l |
7.6 mg/l |
0% RPD |
||
2022-05-15 |
ELZ-004 |
5.81 mg/l |
5.94 mg/l |
2% RPD |
||
2022-05-15 |
NSH-002 |
8.32 mg/l |
8.33 mg/l |
0% RPD |
||
2022-06-12 |
ABT-062 |
8.56 mg/l |
8.56 mg/l |
0% RPD |
||
2022-06-12 |
ABT-237 |
7.81 mg/l |
8.1 mg/l |
4% RPD |
||
2022-06-12 |
HOP-011 |
7.8 mg/l |
7.79 mg/l |
0% RPD |
||
2022-07-17 |
ABT-062 |
7.59 mg/l |
7.59 mg/l |
0% RPD |
||
2022-07-17 |
ABT-237 |
5.92 mg/l |
5.92 mg/l |
0% RPD |
||
2022-08-14 |
ABT-237 |
5.89 mg/l |
5.9 mg/l |
0% RPD |
||
2022-09-11 |
ABT-026 |
7.7 mg/l |
7.7 mg/l |
0% RPD |
||
2022-09-11 |
HOP-011 |
8.36 mg/l |
8.35 mg/l |
0% RPD |
||
E.coli |
||||||
2022-07-18 |
ABT-162 |
276 MPN/100ml |
276 MPN/100ml |
0% logRPD |
||
2022-08-15 |
ABT-077 |
231 MPN/100ml |
276 MPN/100ml |
3% logRPD |
||
Nitrate |
||||||
2022-06-12 |
ABT-301 |
3.65 mg/l |
3.35 mg/l |
9% RPD |
||
2022-07-17 |
ABT-077 |
0.72 mg/l |
0.73 mg/l |
1% RPD |
||
pH |
||||||
2022-05-15 |
ABT-026 |
7.19 s.u. |
7.2 s.u. |
0.01 s.u. |
||
2022-05-15 |
ELZ-004 |
6.95 s.u. |
7.08 s.u. |
0.13 s.u. |
||
2022-05-15 |
NSH-002 |
7.23 s.u. |
7.25 s.u. |
0.02 s.u. |
||
2022-06-12 |
ABT-062 |
7.26 s.u. |
7.26 s.u. |
0 s.u. |
||
2022-06-12 |
ABT-237 |
7.1 s.u. |
7.11 s.u. |
0.01 s.u. |
||
2022-06-12 |
HOP-011 |
6.86 s.u. |
6.82 s.u. |
0.04 s.u. |
||
2022-07-17 |
ABT-062 |
8.02 s.u. |
8.01 s.u. |
0.01 s.u. |
||
2022-07-17 |
ABT-237 |
7.28 s.u. |
7.28 s.u. |
0 s.u. |
||
2022-08-14 |
ABT-237 |
7.28 s.u. |
7.28 s.u. |
0 s.u. |
||
2022-09-11 |
ABT-026 |
7.13 s.u. |
7.14 s.u. |
0.01 s.u. |
||
2022-09-11 |
HOP-011 |
6.92 s.u. |
6.84 s.u. |
0.08 s.u. |
||
Sp Conductance |
||||||
2022-05-15 |
ABT-026 |
585 uS/cm |
586 uS/cm |
0% RPD |
||
2022-05-15 |
ELZ-004 |
375 uS/cm |
375 uS/cm |
0% RPD |
||
2022-05-15 |
NSH-002 |
524 uS/cm |
525 uS/cm |
0% RPD |
||
2022-06-12 |
ABT-062 |
579 uS/cm |
579 uS/cm |
0% RPD |
||
2022-06-12 |
ABT-237 |
740 uS/cm |
740 uS/cm |
0% RPD |
||
2022-06-12 |
HOP-011 |
731 uS/cm |
731 uS/cm |
0% RPD |
||
2022-07-17 |
ABT-062 |
831 uS/cm |
831 uS/cm |
0% RPD |
||
2022-07-17 |
ABT-237 |
1222 uS/cm |
1221 uS/cm |
0% RPD |
||
2022-08-14 |
ABT-237 |
1497 uS/cm |
1489 uS/cm |
1% RPD |
||
2022-09-11 |
ABT-026 |
738 uS/cm |
675 uS/cm |
9% RPD |
||
2022-09-11 |
HOP-011 |
865 uS/cm |
865 uS/cm |
0% RPD |
||
TP |
||||||
2022-05-15 |
ABT-312 |
0.03 mg/l |
0.03 mg/l |
0 mg/l |
||
2022-05-15 |
DAN-013 |
0.04 mg/l |
0.04 mg/l |
0 mg/l |
||
2022-06-12 |
ABT-301 |
0.03 mg/l |
0.03 mg/l |
0 mg/l |
||
2022-07-17 |
ABT-077 |
0.04 mg/l |
0.02 mg/l |
0.02 mg/l |
MISS |
|
2022-09-11 |
ABT-301 |
0.03 mg/l |
0.03 mg/l |
0 mg/l |
||
Water Temp |
||||||
2022-05-15 |
ABT-026 |
22.4 deg C |
22.4 deg C |
0 deg C |
||
2022-05-15 |
ELZ-004 |
22.2 deg C |
22.2 deg C |
0 deg C |
||
2022-05-15 |
NSH-002 |
23.3 deg C |
23.3 deg C |
0 deg C |
||
2022-06-12 |
ABT-062 |
21.1 deg C |
21.1 deg C |
0 deg C |
||
2022-06-12 |
ABT-237 |
18.7 deg C |
18.7 deg C |
0 deg C |
||
2022-06-12 |
HOP-011 |
18.4 deg C |
18.4 deg C |
0 deg C |
||
2022-07-17 |
ABT-062 |
25.6 deg C |
25.6 deg C |
0 deg C |
||
2022-07-17 |
ABT-237 |
20.8 deg C |
20.8 deg C |
0 deg C |
||
2022-08-14 |
ABT-237 |
18.8 deg C |
18.8 deg C |
0 deg C |
||
2022-09-11 |
ABT-026 |
20.5 deg C |
20.5 deg C |
0 deg C |
||
2022-09-11 |
HOP-011 |
19.3 deg C |
19.3 deg C |
0 deg C |
tabMWRacc(res = resdat, acc = accdat, frecom = frecomdat, type = "individual", accchk = "Lab Duplicates", warn = FALSE)
Parameter |
Date |
Sample ID |
Initial Result |
Dup. Result |
Diff./RPD |
Hit/Miss |
---|---|---|---|---|---|---|
Ammonia |
||||||
2022-05-15 |
0.21 mg/l |
0.21 mg/l |
0% RPD |
|||
2022-05-15 |
BDL |
BDL |
0% RPD |
|||
2022-06-12 |
0.1 mg/l |
0.1 mg/l |
0% RPD |
|||
2022-06-12 |
0.19 mg/l |
0.19 mg/l |
0% RPD |
|||
2022-07-17 |
BDL |
BDL |
0% RPD |
|||
2022-07-17 |
BDL |
BDL |
0% RPD |
|||
2022-08-14 |
BDL |
BDL |
0% RPD |
|||
2022-08-14 |
BDL |
BDL |
0% RPD |
|||
2022-09-11 |
BDL |
BDL |
0% RPD |
|||
2022-09-11 |
BDL |
BDL |
0% RPD |
|||
E.coli |
||||||
2022-06-13 |
547.5 MPN/100ml |
579.4 MPN/100ml |
1% logRPD |
|||
2022-07-18 |
88 MPN/100ml |
167 MPN/100ml |
13% logRPD |
|||
2022-08-01 |
114.5 MPN/100ml |
160.7 MPN/100ml |
7% logRPD |
|||
2022-08-29 |
42.8 MPN/100ml |
40.4 MPN/100ml |
2% logRPD |
|||
Nitrate |
||||||
2022-05-15 |
0.37 mg/l |
0.38 mg/l |
3% RPD |
|||
2022-06-12 |
0.17 mg/l |
0.17 mg/l |
0% RPD |
|||
2022-06-12 |
3.65 mg/l |
3.63 mg/l |
1% RPD |
|||
2022-06-12 |
BDL |
BDL |
0% RPD |
|||
2022-07-17 |
1.29 mg/l |
1.29 mg/l |
0% RPD |
|||
2022-07-17 |
BDL |
BDL |
0% RPD |
|||
2022-07-17 |
BDL |
BDL |
0% RPD |
|||
2022-08-14 |
2.69 mg/l |
2.69 mg/l |
0% RPD |
|||
2022-08-14 |
5.22 mg/l |
5.24 mg/l |
0% RPD |
|||
2022-09-11 |
1.51 mg/l |
1.5 mg/l |
1% RPD |
|||
pH |
||||||
2022-05-15 |
7.11 s.u. |
7.09 s.u. |
0.02 s.u. |
|||
2022-05-15 |
7.18 s.u. |
7.09 s.u. |
0.09 s.u. |
|||
2022-05-15 |
7.19 s.u. |
7.09 s.u. |
0.1 s.u. |
|||
2022-06-12 |
7.12 s.u. |
7.19 s.u. |
0.07 s.u. |
|||
2022-06-12 |
7.13 s.u. |
7.19 s.u. |
0.06 s.u. |
|||
2022-06-12 |
7.21 s.u. |
7.19 s.u. |
0.02 s.u. |
|||
2022-06-12 |
7.27 s.u. |
7.19 s.u. |
0.08 s.u. |
|||
2022-07-17 |
7.48 s.u. |
7.37 s.u. |
0.11 s.u. |
|||
2022-07-17 |
7.54 s.u. |
7.37 s.u. |
0.17 s.u. |
|||
2022-07-17 |
7.54 s.u. |
7.37 s.u. |
0.17 s.u. |
|||
2022-07-17 |
7.54 s.u. |
7.37 s.u. |
0.17 s.u. |
|||
2022-08-14 |
7.64 s.u. |
7.32 s.u. |
0.32 s.u. |
|||
2022-08-14 |
7.65 s.u. |
7.32 s.u. |
0.33 s.u. |
|||
2022-08-14 |
7.68 s.u. |
7.32 s.u. |
0.36 s.u. |
|||
2022-09-11 |
7.07 s.u. |
6.74 s.u. |
0.33 s.u. |
|||
2022-09-11 |
7.16 s.u. |
6.74 s.u. |
0.42 s.u. |
|||
2022-09-11 |
7.34 s.u. |
6.74 s.u. |
0.6 s.u. |
MISS |
||
Sp Conductance |
||||||
2022-05-15 |
599 uS/cm |
609 uS/cm |
2% RPD |
|||
2022-05-15 |
605 uS/cm |
609 uS/cm |
1% RPD |
|||
2022-05-15 |
606 uS/cm |
609 uS/cm |
0% RPD |
|||
2022-06-12 |
600 uS/cm |
608 uS/cm |
1% RPD |
|||
2022-06-12 |
602 uS/cm |
608 uS/cm |
1% RPD |
|||
2022-06-12 |
606 uS/cm |
608 uS/cm |
0% RPD |
|||
2022-07-17 |
793 uS/cm |
802 uS/cm |
1% RPD |
|||
2022-07-17 |
900 uS/cm |
802 uS/cm |
12% RPD |
|||
2022-07-17 |
796 uS/cm |
802 uS/cm |
1% RPD |
|||
2022-07-17 |
801 uS/cm |
802 uS/cm |
0% RPD |
|||
2022-08-14 |
1062 uS/cm |
1066 uS/cm |
0% RPD |
|||
2022-08-14 |
1062 uS/cm |
1066 uS/cm |
0% RPD |
|||
2022-08-14 |
1063 uS/cm |
1066 uS/cm |
0% RPD |
|||
2022-08-14 |
1065 uS/cm |
1066 uS/cm |
0% RPD |
|||
2022-09-11 |
761 uS/cm |
766 uS/cm |
1% RPD |
|||
2022-09-11 |
765 uS/cm |
766 uS/cm |
0% RPD |
|||
2022-09-11 |
774 uS/cm |
766 uS/cm |
1% RPD |
|||
TP |
||||||
2022-05-15 |
0.01 mg/l |
0.01 mg/l |
0 mg/l |
|||
2022-05-15 |
0.03 mg/l |
0.02 mg/l |
0.01 mg/l |
|||
2022-05-15 |
0.06 mg/l |
0.06 mg/l |
0% RPD |
|||
2022-06-12 |
0.04 mg/l |
0.04 mg/l |
0 mg/l |
|||
2022-06-12 |
0.04 mg/l |
0.04 mg/l |
0 mg/l |
|||
2022-06-12 |
0.06 mg/l |
0.06 mg/l |
0% RPD |
|||
2022-06-12 |
BDL |
BDL |
0 mg/l |
|||
2022-07-17 |
0.04 mg/l |
0.04 mg/l |
0 mg/l |
|||
2022-07-17 |
0.05 mg/l |
0.05 mg/l |
0% RPD |
|||
2022-07-17 |
BDL |
BDL |
0 mg/l |
|||
2022-08-14 |
0.03 mg/l |
0.03 mg/l |
0 mg/l |
|||
2022-08-14 |
0.05 mg/l |
0.05 mg/l |
0% RPD |
|||
2022-08-14 |
0.09 mg/l |
0.09 mg/l |
0% RPD |
|||
2022-09-11 |
0.04 mg/l |
0.04 mg/l |
0 mg/l |
|||
2022-09-11 |
0.04 mg/l |
0.04 mg/l |
0 mg/l |
|||
2022-09-11 |
0.05 mg/l |
0.05 mg/l |
0% RPD |
|||
Water Temp |
||||||
2022-05-15 |
21.7 deg C |
21.8 deg C |
0.1 deg C |
|||
2022-05-15 |
21.8 deg C |
21.8 deg C |
0 deg C |
|||
2022-05-15 |
21.8 deg C |
21.8 deg C |
0 deg C |
|||
2022-06-12 |
20.2 deg C |
20.2 deg C |
0 deg C |
|||
2022-06-12 |
20.2 deg C |
20.2 deg C |
0 deg C |
|||
2022-06-12 |
20.3 deg C |
20.2 deg C |
0.1 deg C |
|||
2022-06-12 |
20.3 deg C |
20.2 deg C |
0.1 deg C |
|||
2022-07-17 |
23 deg C |
22.9 deg C |
0.1 deg C |
|||
2022-07-17 |
23 deg C |
22.9 deg C |
0.1 deg C |
|||
2022-07-17 |
23.1 deg C |
22.9 deg C |
0.2 deg C |
|||
2022-08-14 |
20.8 deg C |
20.7 deg C |
0.1 deg C |
|||
2022-08-14 |
20.8 deg C |
20.7 deg C |
0.1 deg C |
|||
2022-08-14 |
20.9 deg C |
20.7 deg C |
0.2 deg C |
|||
2022-08-14 |
20.9 deg C |
20.7 deg C |
0.2 deg C |
|||
2022-09-11 |
20.6 deg C |
20.5 deg C |
0.1 deg C |
|||
2022-09-11 |
20.7 deg C |
20.5 deg C |
0.2 deg C |
|||
2022-09-11 |
20.7 deg C |
20.5 deg C |
0.2 deg C |
tabMWRacc(res = resdat, acc = accdat, frecom = frecomdat, type = "individual", accchk = "Lab Spikes / Instrument Checks", warn = FALSE)
Parameter |
Date |
Sample ID |
Spike/Standard |
Result |
Diff./Accuracy |
Hit/Miss |
---|---|---|---|---|---|---|
Ammonia |
||||||
2022-05-15 |
100 % recovery |
86 % recovery |
86% |
|||
2022-06-12 |
100 % recovery |
94 % recovery |
94% |
|||
2022-06-12 |
100 % recovery |
106 % recovery |
106% |
|||
2022-07-17 |
100 % recovery |
92 % recovery |
92% |
|||
2022-07-17 |
100 % recovery |
108 % recovery |
108% |
|||
2022-08-14 |
100 % recovery |
96 % recovery |
96% |
|||
2022-08-14 |
100 % recovery |
102 % recovery |
102% |
|||
2022-09-11 |
100 % recovery |
88 % recovery |
88% |
|||
2022-09-11 |
100 % recovery |
89 % recovery |
89% |
|||
Nitrate |
||||||
2022-05-15 |
100 % recovery |
99 % recovery |
99% |
|||
2022-06-12 |
100 % recovery |
95 % recovery |
95% |
|||
2022-06-12 |
100 % recovery |
97 % recovery |
97% |
|||
2022-06-12 |
100 % recovery |
105 % recovery |
105% |
|||
2022-07-17 |
100 % recovery |
99 % recovery |
99% |
|||
2022-07-17 |
100 % recovery |
101 % recovery |
101% |
|||
2022-07-17 |
100 % recovery |
125 % recovery |
125% |
MISS |
||
2022-08-14 |
100 % recovery |
103 % recovery |
103% |
|||
2022-08-14 |
100 % recovery |
109 % recovery |
109% |
|||
2022-09-11 |
100 % recovery |
101 % recovery |
101% |
|||
pH |
||||||
2022-05-15 |
7.02 s.u. |
7 s.u. |
-0.02 s.u. |
|||
2022-05-15 |
7.02 s.u. |
7.03 s.u. |
+0.01 s.u. |
|||
2022-05-15 |
7.02 s.u. |
7.09 s.u. |
+0.07 s.u. |
|||
2022-05-15 |
7.02 s.u. |
7.11 s.u. |
+0.09 s.u. |
|||
2022-06-12 |
7 s.u. |
7.01 s.u. |
+0.01 s.u. |
|||
2022-06-12 |
7 s.u. |
7.05 s.u. |
+0.05 s.u. |
|||
2022-06-12 |
7 s.u. |
7.06 s.u. |
+0.06 s.u. |
|||
2022-06-12 |
7 s.u. |
7.06 s.u. |
+0.06 s.u. |
|||
2022-06-12 |
7 s.u. |
7.07 s.u. |
+0.07 s.u. |
|||
2022-07-17 |
7 s.u. |
7.05 s.u. |
+0.05 s.u. |
|||
2022-07-17 |
7 s.u. |
7.06 s.u. |
+0.06 s.u. |
|||
2022-07-17 |
7 s.u. |
7.06 s.u. |
+0.06 s.u. |
|||
2022-07-17 |
7 s.u. |
7.06 s.u. |
+0.06 s.u. |
|||
2022-07-17 |
7 s.u. |
7.4 s.u. |
+0.4 s.u. |
MISS |
||
2022-08-14 |
7 s.u. |
6.99 s.u. |
-0.01 s.u. |
|||
2022-08-14 |
7 s.u. |
7.07 s.u. |
+0.07 s.u. |
|||
2022-08-14 |
7 s.u. |
7.09 s.u. |
+0.09 s.u. |
|||
2022-09-11 |
7 s.u. |
7.01 s.u. |
+0.01 s.u. |
|||
2022-09-11 |
7 s.u. |
7.06 s.u. |
+0.06 s.u. |
|||
2022-09-11 |
7 s.u. |
7.06 s.u. |
+0.06 s.u. |
|||
Sp Conductance |
||||||
2022-05-15 |
1000 uS/cm |
975 uS/cm |
-25 uS/cm |
|||
2022-05-15 |
1000 uS/cm |
977 uS/cm |
-23 uS/cm |
|||
2022-05-15 |
1000 uS/cm |
985 uS/cm |
-15 uS/cm |
|||
2022-05-15 |
1000 uS/cm |
991 uS/cm |
-9 uS/cm |
|||
2022-06-12 |
1000 uS/cm |
978 uS/cm |
-22 uS/cm |
|||
2022-06-12 |
1000 uS/cm |
979 uS/cm |
-21 uS/cm |
|||
2022-06-12 |
1000 uS/cm |
979 uS/cm |
-21 uS/cm |
|||
2022-06-12 |
1000 uS/cm |
983 uS/cm |
-17 uS/cm |
|||
2022-06-12 |
1000 uS/cm |
987 uS/cm |
-13 uS/cm |
|||
2022-07-17 |
1000 uS/cm |
984 uS/cm |
-16 uS/cm |
|||
2022-07-17 |
1000 uS/cm |
988 uS/cm |
-12 uS/cm |
|||
2022-07-17 |
1000 uS/cm |
997 uS/cm |
-3 uS/cm |
|||
2022-08-14 |
1000 uS/cm |
991 uS/cm |
-9 uS/cm |
|||
2022-08-14 |
1000 uS/cm |
991 uS/cm |
-9 uS/cm |
|||
2022-08-14 |
1000 uS/cm |
992 uS/cm |
-8 uS/cm |
|||
2022-08-14 |
1000 uS/cm |
992 uS/cm |
-8 uS/cm |
|||
2022-08-14 |
1000 uS/cm |
996 uS/cm |
-4 uS/cm |
|||
2022-09-11 |
1000 uS/cm |
986 uS/cm |
-14 uS/cm |
|||
2022-09-11 |
1000 uS/cm |
989 uS/cm |
-11 uS/cm |
|||
2022-09-11 |
1000 uS/cm |
990 uS/cm |
-10 uS/cm |
|||
2022-09-11 |
1000 uS/cm |
993 uS/cm |
-7 uS/cm |
|||
TP |
||||||
2022-05-15 |
100 % recovery |
100 % recovery |
100% |
|||
2022-05-15 |
100 % recovery |
101 % recovery |
101% |
|||
2022-05-15 |
100 % recovery |
103 % recovery |
103% |
|||
2022-06-12 |
100 % recovery |
100 % recovery |
100% |
|||
2022-06-12 |
100 % recovery |
104 % recovery |
104% |
|||
2022-06-12 |
100 % recovery |
104 % recovery |
104% |
|||
2022-07-17 |
100 % recovery |
105 % recovery |
105% |
|||
2022-07-17 |
100 % recovery |
105 % recovery |
105% |
|||
2022-07-17 |
100 % recovery |
110 % recovery |
110% |
|||
2022-08-14 |
100 % recovery |
99 % recovery |
99% |
|||
2022-08-14 |
100 % recovery |
99 % recovery |
99% |
|||
2022-08-14 |
100 % recovery |
101 % recovery |
101% |
|||
2022-09-11 |
100 % recovery |
97 % recovery |
97% |
|||
2022-09-11 |
100 % recovery |
99 % recovery |
99% |
|||
2022-09-11 |
100 % recovery |
99 % recovery |
99% |
|||
Water Temp |
||||||
2022-05-15 |
21.8 deg C |
21.8 deg C |
+0 deg C |
|||
2022-05-15 |
21.8 deg C |
21.8 deg C |
+0 deg C |
|||
2022-05-15 |
21.8 deg C |
21.9 deg C |
+0.1 deg C |
|||
2022-05-15 |
21.8 deg C |
21.9 deg C |
+0.1 deg C |
|||
2022-06-12 |
22.5 deg C |
22.6 deg C |
+0.1 deg C |
|||
2022-06-12 |
22.5 deg C |
22.6 deg C |
+0.1 deg C |
|||
2022-06-12 |
22.5 deg C |
22.7 deg C |
+0.2 deg C |
|||
2022-07-17 |
22.7 deg C |
22.6 deg C |
-0.1 deg C |
|||
2022-07-17 |
22.7 deg C |
22.7 deg C |
+0 deg C |
|||
2022-07-17 |
22.7 deg C |
22.7 deg C |
+0 deg C |
|||
2022-07-17 |
22.7 deg C |
25 deg C |
+2.3 deg C |
MISS |
||
2022-07-17 |
22.7 deg C |
22.9 deg C |
+0.2 deg C |
|||
2022-08-14 |
23.1 deg C |
23.1 deg C |
+0 deg C |
|||
2022-08-14 |
23.1 deg C |
23.4 deg C |
+0.3 deg C |
|||
2022-08-14 |
23.1 deg C |
23.4 deg C |
+0.3 deg C |
|||
2022-09-11 |
22.8 deg C |
22.8 deg C |
+0 deg C |
|||
2022-09-11 |
22.8 deg C |
22.8 deg C |
+0 deg C |
|||
2022-09-11 |
22.8 deg C |
22.9 deg C |
+0.1 deg C |
|||
2022-09-11 |
22.8 deg C |
23 deg C |
+0.2 deg C |
For type = "summary"
, the function summarizes all
accuracy checks by counting the number of quality control checks, number
of misses, and percent acceptance for each parameter. All accuracy
checks are used and the accchk
argument does not apply.
tabMWRacc(res = resdat, acc = accdat, frecom = frecomdat, type = "summary", warn = FALSE)
Type |
Parameter |
Number of QC Checks |
Number of Misses |
% Acceptance |
---|---|---|---|---|
Field Duplicates |
||||
Ammonia |
4 |
1 |
75 % |
|
DO |
11 |
0 |
100 % |
|
E.coli |
2 |
0 |
100 % |
|
Nitrate |
2 |
0 |
100 % |
|
pH |
11 |
0 |
100 % |
|
Sp Conductance |
11 |
0 |
100 % |
|
TP |
5 |
1 |
80 % |
|
Water Temp |
11 |
0 |
100 % |
|
Lab Duplicates |
||||
Ammonia |
10 |
0 |
100 % |
|
E.coli |
4 |
0 |
100 % |
|
Nitrate |
10 |
0 |
100 % |
|
pH |
17 |
1 |
94 % |
|
Sp Conductance |
17 |
0 |
100 % |
|
TP |
16 |
0 |
100 % |
|
Water Temp |
17 |
0 |
100 % |
|
Field Blanks |
||||
Ammonia |
7 |
0 |
100 % |
|
E.coli |
4 |
0 |
100 % |
|
Nitrate |
7 |
0 |
100 % |
|
TP |
11 |
1 |
91 % |
|
Lab Blanks |
||||
Ammonia |
7 |
1 |
86 % |
|
E.coli |
0 |
- |
- |
|
Nitrate |
5 |
0 |
100 % |
|
Sp Conductance |
21 |
1 |
95 % |
|
TP |
5 |
0 |
100 % |
|
Lab Spikes / Instrument Checks |
||||
Ammonia |
9 |
0 |
100 % |
|
Nitrate |
10 |
1 |
90 % |
|
pH |
20 |
1 |
95 % |
|
Sp Conductance |
21 |
0 |
100 % |
|
TP |
15 |
0 |
100 % |
|
Water Temp |
19 |
1 |
95 % |
For type = "percent"
, the function returns a similar
table as for the summary option, except only the percentage of checks
that pass for each parameter are shown in wide format. Cells are
color-coded based on the percentage of checks that have passed using the
percent thresholds from the % Completeness
column of the
data quality objectives file for frequency and completeness. Parameters
without an entry for % Completeness
are not color-coded and
an appropriate warning is returned. All accuracy checks are used and the
accchk
argument does not apply.
tabMWRacc(res = resdat, acc = accdat, frecom = frecomdat, type = "percent", warn = FALSE)
Parameter |
Field Duplicate |
Lab Duplicate |
Field Blank |
Lab Blank |
Spike/Check Accuracy |
---|---|---|---|---|---|
Ammonia |
75% |
100% |
100% |
86% |
100% |
DO |
100% |
- |
- |
- |
- |
E.coli |
100% |
100% |
100% |
- |
- |
Nitrate |
100% |
100% |
100% |
100% |
90% |
pH |
100% |
94% |
- |
- |
95% |
Sp Conductance |
100% |
100% |
- |
95% |
100% |
TP |
80% |
100% |
91% |
100% |
100% |
Water Temp |
100% |
100% |
- |
- |
95% |
The tabMWRacc()
function uses the
qcMWRacc()
function internally to create the table. This
function creates the raw summaries of accuracy from the input data.
Typically, qcMWRacc()
is not used by itself, but it is
explained here to demonstrate how the raw summaries can be obtained.
Below, the qcMWRacc()
function is executed with the data
frames for the results and quality objectives file for accuracy. As with
tabMWRacc
, the accchk
argument can be used to
return one to all of the checks. The results are returned as a list,
with each element of the list corresponding to a specific accuracy
check. Here, the lab duplicate checks are returned. The warnings are
also suppressed.
qcMWRacc(res = resdat, acc = accdat, frecom = frecomdat, accchk = "Lab Duplicates", warn = FALSE)
#> $`Lab Duplicates`
#> # A tibble: 91 × 7
#> Parameter Date `Sample ID` `Initial Result` `Dup. Result`
#> <chr> <dttm> <chr> <chr> <chr>
#> 1 Ammonia 2022-05-15 00:00:00 NA 0.21 mg/l 0.21 mg/l
#> 2 Ammonia 2022-05-15 00:00:00 NA BDL BDL
#> 3 Ammonia 2022-06-12 00:00:00 NA 0.1 mg/l 0.1 mg/l
#> 4 Ammonia 2022-06-12 00:00:00 NA 0.19 mg/l 0.19 mg/l
#> 5 Ammonia 2022-07-17 00:00:00 NA BDL BDL
#> 6 Ammonia 2022-07-17 00:00:00 NA BDL BDL
#> 7 Ammonia 2022-08-14 00:00:00 NA BDL BDL
#> 8 Ammonia 2022-08-14 00:00:00 NA BDL BDL
#> 9 Ammonia 2022-09-11 00:00:00 NA BDL BDL
#> 10 Ammonia 2022-09-11 00:00:00 NA BDL BDL
#> # ℹ 81 more rows
#> # ℹ 2 more variables: `Diff./RPD` <chr>, `Hit/Miss` <chr>
Quality control for frequency
The quality control checks for frequency are used to verify an
appropriate number of quality control samples have been collected or
analyzed for each parameter. These are checks on the quantity of samples
and not the values, as for the accuracy checks. The frequency checks
require results data (as in resdat
above), a data quality
objectives file for accuracy (as in accdat
), and a data
quality objectives file for frequency and completeness (as in
frecomdat
).
The tabMWRfre()
function is used to create tabular
results for the frequency checks for each parameter. The function can be
used with inputs as paths to the relevant files or as data frames
returned by readMWRresults()
, readMWRacc()
,
and readMWRfrecom()
. For the former, the full suite of data
checks can be evaluated with runkchk = T
(default) or
suppressed with runchk = F
, as explained in the data
inputs and checks vignette. In the latter case, downstream analyses
may not work if data are formatted incorrectly. Also note that
completeness is only evaluated on parameters that are shared between the
results file and the data quality objectives completeness file. A
warning is returned if there are parameters that do not match. The
warnings can be suppressed by setting warn = FALSE
.
The quality control tables for frequency show the number of records
that apply to a given check (e.g., Lab Blank, Field Blank, etc.)
relative to the number of “regular” data records (e.g., field samples or
measures) for each parameter. A summary of all frequency checks for each
parameter is provided if type = "summary"
. The function is
executed with the data frames for the results and quality objectives
file for frequency.
tabMWRfre(res = resdat, acc = accdat, frecom = frecomdat, type = "summary", warn = FALSE)
Type |
Parameter |
Number of Data Records |
Number of Dups/Blanks/Spikes |
Frequency % |
Hit/Miss |
---|---|---|---|---|---|
Field Duplicates |
|||||
Ammonia |
43 |
4 |
9% |
MISS |
|
DO |
49 |
11 |
22% |
||
E.coli |
12 |
2 |
17% |
||
Nitrate |
20 |
2 |
10% |
||
pH |
49 |
11 |
22% |
||
Sp Conductance |
49 |
11 |
22% |
||
TP |
48 |
5 |
10% |
||
Water Temp |
49 |
11 |
22% |
||
Lab Duplicates |
|||||
Ammonia |
43 |
10 |
23% |
||
E.coli |
12 |
4 |
33% |
||
Nitrate |
20 |
10 |
50% |
||
pH |
49 |
17 |
35% |
||
Sp Conductance |
49 |
17 |
35% |
||
TP |
48 |
16 |
33% |
||
Water Temp |
49 |
17 |
35% |
||
Field Blanks |
|||||
Ammonia |
43 |
7 |
16% |
||
E.coli |
12 |
4 |
33% |
||
Nitrate |
20 |
7 |
35% |
||
TP |
48 |
11 |
23% |
||
Lab Blanks |
|||||
Ammonia |
43 |
7 |
16% |
||
E.coli |
12 |
0 |
0% |
MISS |
|
Nitrate |
20 |
5 |
25% |
||
Sp Conductance |
49 |
21 |
43% |
||
TP |
48 |
5 |
10% |
||
Lab Spikes / Instrument Checks |
|||||
Ammonia |
43 |
9 |
21% |
||
Nitrate |
20 |
10 |
50% |
||
pH |
49 |
20 |
41% |
||
Sp Conductance |
49 |
21 |
43% |
||
TP |
48 |
15 |
31% |
||
Water Temp |
49 |
19 |
39% |
A color-coded table showing similar information as percentages for
each parameter is provided if type = "percent"
. Cells are
shown as green or red if the required frequency checks are met as
specified in the data quality objectives file.
tabMWRfre(res = resdat, acc = accdat, frecom = frecomdat, type = "percent", warn = FALSE)
Parameter |
Field Duplicate |
Lab Duplicate |
Field Blank |
Lab Blank |
Spike/Check Accuracy |
---|---|---|---|---|---|
Ammonia |
9% |
23% |
16% |
16% |
21% |
DO |
22% |
- |
- |
- |
- |
E.coli |
17% |
33% |
33% |
0% |
- |
Nitrate |
10% |
50% |
35% |
25% |
50% |
pH |
22% |
35% |
- |
- |
41% |
Sp Conductance |
22% |
35% |
- |
43% |
43% |
TP |
10% |
33% |
23% |
10% |
31% |
Water Temp |
22% |
35% |
- |
- |
39% |
The tabMWRfre()
function uses the
qcMWRfre()
function internally to create the table. This
function creates the raw summaries of frequency from the input data.
Typically, qcMWRfre()
is not used by itself, but it is
explained here to demonstrate how the raw summaries can be obtained.
Below, the qcMWRfre()
function is executed with the data
frames for the results and quality objectives file for frequency and
completeness. The warnings are suppressed.
qcMWRfre(res = resdat, acc = accdat, frecom = frecomdat, warn = FALSE)
#> # A tibble: 40 × 7
#> Parameter obs check count standard percent met
#> <chr> <int> <chr> <int> <dbl> <dbl> <lgl>
#> 1 Ammonia 43 Field Duplicate 4 10 9.30 FALSE
#> 2 Ammonia 43 Lab Duplicate 10 5 23.3 TRUE
#> 3 Ammonia 43 Field Blank 7 10 16.3 TRUE
#> 4 Ammonia 43 Lab Blank 7 5 16.3 TRUE
#> 5 Ammonia 43 Spike/Check Accuracy 9 5 20.9 TRUE
#> 6 DO 49 Field Duplicate 11 10 22.4 TRUE
#> 7 DO 49 Lab Duplicate 0 NA NA NA
#> 8 DO 49 Field Blank 0 NA NA NA
#> 9 DO 49 Lab Blank 0 NA NA NA
#> 10 DO 49 Spike/Check Accuracy 0 NA NA NA
#> # ℹ 30 more rows
The output shows the frequency checks from the combined files. Each
row applies to a frequency check for a parameter. The
Parameter
column shows the parameter, the obs
column shows the total records that apply to regular activity types, the
check
column shows the relevant activity type for each
frequency check, the count
column shows the number of
records that apply to a check, the standard
column shows
the relevant percentage required for the quality control check from the
quality control objectives file, and the met
column shows
if the standard was met by comparing if percent
is greater
than or equal to standard
.
Quality control for completeness
The quality control checks for completeness are used to assess the
number of regular samples relative to qualified samples that apply to
each parameter. Regular samples are those with
Field Msr/Obs
or Sample-Routine
in the
Activity Type
column of the results file and qualified
samples are those marked as Q
in the
Result Measure Qualifier
column of the results file. The
completeness checks require results data (as in resdat
above) and a data quality objectives file for frequency and completeness
(as in frecomdat
).
The tabMWRcom()
function is used to create a table that
shows the completeness percentages for each parameter. As explained in
the previous section, the function can be used with inputs as paths to
the relevant files or as data frames returned by
readMWRresults()
and read_frecom()
.
A summary table showing the number of data records, number of
qualified records, and percent completeness can be created with
tabMWRcom()
. The % Completeness
column shows
cells as green or red if the required percentage of observations for
completeness are present as specified in the data quality objectives
file. The Hit/Miss
column shows similar information but in
text format, i.e., MISS
is shown if the quality control
standard for completeness is not met. The function is also executed with
the data frames from above, since they have already passed the internal
checks.
tabMWRcom(res = resdat, frecom = frecomdat, warn = FALSE)
Parameter |
Number of Data Records |
Number of Qualified Records |
% Completeness |
Hit/ Miss |
Number of Censored Records |
Notes |
---|---|---|---|---|---|---|
Ammonia |
43 |
0 |
100% |
|||
DO |
49 |
0 |
100% |
|||
E.coli |
12 |
0 |
100% |
|||
Nitrate |
20 |
0 |
100% |
|||
pH |
49 |
0 |
100% |
|||
Sp Conductance |
49 |
0 |
100% |
|||
TP |
48 |
5 |
90% |
MISS |
||
Water Temp |
49 |
0 |
100% |
The tabMWRcom()
function uses the
qcMWRcom()
function internally to create the table. This
function creates the raw summaries of completeness from the input data.
Typically, qcMWRcom()
is not used by itself, but it is
explained here to demonstrate how the raw summaries can be obtained.
Below, the qcMWRcom()
function is executed with the data
frames for the results and quality objectives file for completeness. The
warnings are suppressed.
qcMWRcom(res = resdat, frecom = frecomdat, warn = FALSE)
#> # 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 pH 49 0 90 100 TRUE
#> 6 Sp Conductance 49 0 90 100 TRUE
#> 7 TP 48 5 90 89.6 FALSE
#> 8 Water Temp 49 0 90 100 TRUE
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
.