Package 'MassWateR'

Description

Analyze trends by date in results file

Usage

anlzMWRdate(
  res = NULL,
  param,
  acc = NULL,
  sit = NULL,
  fset = NULL,
  thresh,
  group = c("site", "locgroup", "all"),
  threshlab = NULL,
  threshcol = "tan",
  site = NULL,
  resultatt = NULL,
  locgroup = NULL,
  dtrng = NULL,
  ptsize = 2,
  repel = FALSE,
  labsize = 3,
  expand = c(0.05, 0.1),
  confint = FALSE,
  palcol = "Set2",
  yscl = "auto",
  sumfun = yscl,
  colleg = FALSE,
  ttlsize = 1.2,
  runchk = TRUE,
  warn = TRUE
)

Arguments

Details

Results are shown for the selected parameter as continuous line plots over time. Specifying group = "site" plot a separate line for each site. Specifying group = "locgroup" will summarize results across sites in the locgroup argument based on the value passed to sumfun or yscl if no value is passed to sumfun. The site metadata file must be passed to the `sit` argument to use this option. Specifying group = "all" will summarize results across sites for each date based on the value passed to sumfun or yscl if no value is passed to sumfun. Summarized results will include confidence intervals if confint = TRUE and they can be calculated (i.e., more than one point is used in the summary and data are summarized using group as "locgroup" or "all").

Threshold lines applicable to marine or freshwater environments can be included in the plot by using the thresh argument. These thresholds are specific to each parameter and can be found in the thresholdMWR file. Threshold lines are plotted only for those parameters with entries in thresholdMWR and only if the value in `Result Unit` matches those in thresholdMWR. The threshold lines can be suppressed by setting thresh = 'none'. A user-supplied numeric value can also be used for the thresh argument to override the default values. An appropriate label must also be supplied to threshlab if thresh is numeric.

Any acceptable color palette for from RColorBrewer for the points and lines can be used for palcol, which is passed to the palette argument in scale_color_brewer. These could include any of the qualitative color palettes, e.g., "Set1", "Set2", etc. The continuous and diverging palettes will also work, but may return color scales for points and lines that are difficult to distinguish. The palcol argument does not apply if group = "all".

The y-axis scaling as arithmetic (linear) or logarithmic can be set with the yscl argument. If yscl = "auto" (default), the scaling is determined automatically from the data quality objective file for accuracy, i.e., parameters with "log" in any of the columns are plotted on log10-scale, otherwise arithmetic. Setting yscl = "linear" or yscl = "log" will set the axis as linear or log10-scale, respectively, regardless of the information in the data quality objective file for accuracy.

Similarly, the data will be summarized appropriately for group (only applies if group is not site) based on the value passed to sumfun. The default if no value is provided to sumfun is to use the appropriate summary based on the value provided to yscl. If yscl = "auto" (default), then sumfun = "auto", and the mean or geometric mean is used for the summary based on information in the data quality objective file for accuracy. Using yscl = "linear" or yscl = "log" will default to the mean or geometric mean summary if no value is provided to sumfun. Any other appropriate value passed to sumfun will override the value passed to yscl. Valid summary functions for sumfun include "auto", "mean", "geomean", "median", "min", or "max").

Any entries in resdat in the "Result Value" column as "BDL" or "AQL" are 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.

Value

A ggplot object that can be further modified.

Examples

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

# results data
resdat <- readMWRresults(respth)

# accuracy path
accpth <- system.file('extdata/ExampleDQOAccuracy.xlsx', 
     package = 'MassWateR')

# accuracy data
accdat <- readMWRacc(accpth)

# site data path
sitpth <- system.file('extdata/ExampleSites.xlsx', package = 'MassWateR')

# site data
sitdat <- readMWRsites(sitpth)

# select sites
anlzMWRdate(res = resdat, param = 'DO', acc = accdat, group = 'site', thresh = 'fresh',
     site = c("ABT-026", "ABT-077"))

Description

Analyze results with maps

Usage

anlzMWRmap(
  res = NULL,
  param,
  acc = NULL,
  sit = NULL,
  fset = NULL,
  site = NULL,
  resultatt = NULL,
  locgroup = NULL,
  dtrng = NULL,
  ptsize = 4,
  repel = TRUE,
  labsize = 3,
  palcol = "Greens",
  palcolrev = FALSE,
  sumfun = "auto",
  crs = 4326,
  zoom = 11,
  addwater = "medium",
  watercol = "lightblue",
  maptype = NULL,
  buffdist = 2,
  scaledist = "km",
  northloc = "tl",
  scaleloc = "br",
  latlon = TRUE,
  ttlsize = 1.2,
  runchk = TRUE,
  warn = TRUE
)

Arguments

Details

This function creates a map of summarized results for a selected parameter at each monitoring site. By default, all dates for the parameter are averaged. Options to filter by site, date range, and result attribute are provided. Only sites with spatial information in the site metadata file are plotted and a warning is returned for those that do not have this information. The site labels are also plotted next to each point. The labels can be suppressed by setting labsize = NULL.

Any acceptable color palette from RColorBrewer can be used for palcol, which is passed to the palette argument in scale_fill_distiller. These could include any of the sequential color palettes, e.g., "Greens", "Blues", etc. The diverging and qualitative palettes will also work, but may return uninterpretable color scales. The palette can be reversed by setting palcolrev = TRUE.

The default value for crs is EPSG 4326 for the WGS 84 projection in decimal degrees. The crs argument is passed to st_as_sf and any acceptable CRS appropriate for the data can be used.

The results shown on the map represent the parameter summary for each site within the date range provided by dtrng. If sumfun = "auto" (default), the mean is used where the distribution is determined automatically from the data quality objective file for accuracy, i.e., parameters with "log" in any of the columns are summarized with the geometric mean, otherwise arithmetic. Any other valid summary function will be applied if passed to sumfun ("mean", "geomean", "median", "min", "max"), regardless of the information in the data quality objective file for accuracy.

Using addwater = "medium" (default) will include lines and polygons of natural water bodies defined using the National Hydrography Dataset (NHD). The level of detail can be changed to low or high using addwater = "low" or addwater = "high", respectively. Use addwater = NULL to not show any water features.

A base map can be plotted using the maptype argument and is obtained from the annotation_map_tile function of ggspatial. The zoom value specifies the resolution of the map. Use higher values to download map tiles with greater resolution, although this increases the download time. The maptype argument describes the type of base map to download. Acceptable options include "cartolight", "cartodark", "osm", or "hotstyle". Use maptype = NULL to suppress the base map.

The area around the summarized points can be increased or decreased using the buffdist argument. This creates a buffered area around the bounding box for the points, where the units are kilometers.

A north arrow and scale bar are also placed on the map as defined by the northloc and scaleloc arguments. The placement for both can be chosen as "tl", "tr", "bl", or "br" for top-left, top-right, bottom-left, or bottom-right respectively. Setting either of the arguments to NULL will suppress the placement on the map.

Value

A ggplot object that can be further modified.

Examples

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

# results data
resdat <- readMWRresults(respth)

# accuracy path
accpth <- system.file('extdata/ExampleDQOAccuracy.xlsx', package = 'MassWateR')

# accuracy data
accdat <- readMWRacc(accpth)

# site data path
sitpth <- system.file('extdata/ExampleSites.xlsx', package = 'MassWateR')

# site data
sitdat <- readMWRsites(sitpth)


# map with NHD water bodies
anlzMWRmap(res = resdat, param = 'DO', acc = accdat, sit = sitdat, addwater = 'medium')

Description

Analyze outliers in results file

Usage

anlzMWRoutlier(
  res = NULL,
  param,
  acc = NULL,
  fset = NULL,
  type = c("box", "jitterbox", "jitter"),
  group,
  dtrng = NULL,
  repel = TRUE,
  outliers = FALSE,
  labsize = 3,
  fill = "lightgrey",
  alpha = 0.8,
  width = 0.8,
  yscl = "auto",
  ttlsize = 1.2,
  runchk = TRUE,
  warn = TRUE
)

Arguments

Details

Outliers are defined following the standard ggplot definition as 1.5 times the inter-quartile range of each boxplot. The data frame returned if outliers = TRUE may vary based on the boxplot groupings defined by group.

Specifying type = "box" (default) will produce standard boxplots. Specifying type = "jitterbox" will produce boxplots with non-outlier observations jittered on top. Specifying type = "jitter" will suppress the boxplots and show only the jittered points and the outliers.

Specifying group = "week" will group the samples by week of year using an integer specifying the week. Note that there can be no common month/day indicating the start of the week between years and an integer is the only way to compare summaries if the results data span multiple years.

The y-axis scaling as arithmetic (linear) or logarithmic can be set with the yscl argument. If yscl = "auto" (default), the scaling is determined automatically from the data quality objective file for accuracy, i.e., parameters with "log" in any of the columns are plotted on log10-scale, otherwise arithmetic. Setting yscl = "linear" or yscl = "log" will set the axis as linear or log10-scale, respectively, regardless of the information in the data quality objective file for accuracy.

Any entries in resdat in the "Result Value" column as "BDL" or "AQL" are 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.

Value

A ggplot object that can be further modified if outliers = FALSE, otherwise a data frame of outliers is returned.

Examples

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

# results data
resdat <- readMWRresults(respth)

# accuracy path
accpth <- system.file('extdata/ExampleDQOAccuracy.xlsx', 
     package = 'MassWateR')

# accuracy data
accdat <- readMWRacc(accpth)

# outliers by month
anlzMWRoutlier(res = resdat, param = 'DO', acc = accdat, group = 'month')

# outliers by site
anlzMWRoutlier(res = resdat, param = 'DO', acc = accdat, group = 'site')

# outliers by site, May through July 2021 only
anlzMWRoutlier(res = resdat, param = 'DO', acc = accdat, group = 'site', 
     dtrng = c('2022-05-01', '2022-07-31'))

# outliers by month, type as jitterbox
anlzMWRoutlier(res = resdat, param = 'DO', acc = accdat, group = 'month', type = 'jitterbox')

# outliers by month, type as jitter
anlzMWRoutlier(res = resdat, param = 'DO', acc = accdat, group = 'month', type = 'jitter')

# data frame output
anlzMWRoutlier(res = resdat, param = 'DO', acc = accdat, group = 'month', outliers = TRUE)

Description

Analyze outliers in results file for all parameters

Usage

anlzMWRoutlierall(
  res = NULL,
  acc = NULL,
  fset = NULL,
  fig_height = 4,
  fig_width = 8,
  format = c("word", "png"),
  output_dir,
  output_file = NULL,
  type = c("box", "jitterbox", "jitter"),
  group,
  dtrng = NULL,
  repel = TRUE,
  outliers = FALSE,
  labsize = 3,
  fill = "lightgrey",
  alpha = 0.8,
  width = 0.8,
  yscl = "auto",
  ttlsize = 1.2,
  runchk = TRUE,
  warn = TRUE
)

Arguments

Details

This function is a wrapper to anlzMWRoutlier to create plots for all parameters with appropriate data in the water quality monitoring results

Value

A word document named outlierall.docx (or name passed to output_file) if format = "word" or separate png files for each parameter if format = "png" will be saved in the directory specified by output_dir

Examples

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

# results data
resdat <- readMWRresults(respth)

# accuracy path
accpth <- system.file('extdata/ExampleDQOAccuracy.xlsx', 
     package = 'MassWateR')

# accuracy data
accdat <- readMWRacc(accpth)


# create word output
anlzMWRoutlierall(resdat, accdat, group = 'month', format = 'word', output_dir = tempdir())

# create png output
anlzMWRoutlierall(resdat, accdat, group = 'month', format = 'png', output_dir = tempdir())

Description

Analyze seasonal trends in results file

Usage

anlzMWRseason(
  res = NULL,
  param,
  acc = NULL,
  sit = NULL,
  fset = NULL,
  thresh,
  group = c("month", "week"),
  type = c("box", "jitterbox", "bar", "jitterbar", "jitter"),
  threshlab = NULL,
  threshcol = "tan",
  site = NULL,
  resultatt = NULL,
  locgroup = NULL,
  dtrng = NULL,
  confint = FALSE,
  fill = "lightblue",
  alpha = 0.8,
  width = 0.8,
  yscl = "auto",
  sumfun = yscl,
  ttlsize = 1.2,
  runchk = TRUE,
  warn = TRUE
)

Arguments

Details

Summaries of a parameter are shown as boxplots if type = "box" or as barplots if type = "bar". Points can be jittered over the boxplots by setting type = "jitterbox" or jittered over the barplots by setting type = "jitterbar". Setting type = "jitter" will show only the jittered points. For type = "bar" or type = "jitterbar", 95% confidence intervals can also be shown if confint = TRUE and they can be estimated (i.e., more than one result value per bar and sumfun is "auto", "mean", or "geomean").

Specifying group = "week" will group the samples by week of year using an integer specifying the week. Note that there can be no common month/day indicating the start of the week between years and an integer is the only way to compare summaries if the results data span multiple years.

Threshold lines applicable to marine or freshwater environments can be included in the plot by using the thresh argument. These thresholds are specific to each parameter and can be found in the thresholdMWR file. Threshold lines are plotted only for those parameters with entries in thresholdMWR and only if the value in `Result Unit` matches those in thresholdMWR. The threshold lines can be suppressed by setting thresh = 'none'. A user-supplied numeric value can also be used for the thresh argument to override the default values. An appropriate label must also be supplied to threshlab if thresh is numeric.

The y-axis scaling as arithmetic (linear) or logarithmic can be set with the yscl argument. If yscl = "auto" (default), the scaling is determined automatically from the data quality objective file for accuracy, i.e., parameters with "log" in any of the columns are plotted on log10-scale, otherwise arithmetic. Setting yscl = "linear" or yscl = "log" will set the axis as linear or log10-scale, respectively, regardless of the information in the data quality objective file for accuracy.

Similarly, the data will be summarized if type is "bar" or "jitterbar" based on the value passed to sumfun. The default if no value is provided to sumfun is to use the appropriate summary based on the value provided to yscl. If yscl = "auto" (default), then sumfun = "auto", and the mean or geometric mean is used for the summary based on information in the data quality objective file for accuracy. Using yscl = "linear" or yscl = "log" will default to the mean or geometric mean summary if no value is provided to sumfun. Any other appropriate value passed to sumfun will override the value passed to yscl. Valid summary functions for sumfun include "auto", "mean", "geomean", "median", "min", or "max").

Any entries in resdat in the "Result Value" column as "BDL" or "AQL" are 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.

Value

A ggplot object that can be further modified.

Examples

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

# results data
resdat <- readMWRresults(respth)

# accuracy path
accpth <- system.file('extdata/ExampleDQOAccuracy.xlsx', 
     package = 'MassWateR')

# accuracy data
accdat <- readMWRacc(accpth)

# site data path
sitpth <- system.file('extdata/ExampleSites.xlsx', package = 'MassWateR')

# site data
sitdat <- readMWRsites(sitpth)

# seasonal trends by month, boxplot
anlzMWRseason(res = resdat, param = 'DO', acc = accdat, thresh = 'fresh', group = 'month', 
     type = 'box')

# seasonal trends by week, boxplot
anlzMWRseason(res = resdat, param = 'DO', acc = accdat, thresh = 'fresh', group = 'week', 
     type = 'box')

# seasonal trends by month, May to July only
anlzMWRseason(res = resdat, param = 'DO', acc = accdat, thresh = 'fresh', group = 'month', 
     type = 'bar', dtrng = c('2022-05-01', '2022-07-31'))
     
# seasonal trends by month, barplot
anlzMWRseason(res = resdat, param = 'DO', acc = accdat, thresh = 'fresh', group = 'month', 
     type = 'bar')

# seasonal trends by week, barplot
anlzMWRseason(res = resdat, param = 'DO', acc = accdat, thresh = 'fresh', group = 'week', 
     type = 'bar')
     
# seasonal trends by location group, requires sitdat
anlzMWRseason(res = resdat, param = 'DO', acc = accdat, sit = sitdat, thresh = 'fresh', 
     group = 'month', type = 'box', locgroup = 'Assabet')

Description

Analyze data by sites in results file

Usage

anlzMWRsite(
  res = NULL,
  param,
  acc = NULL,
  sit = NULL,
  fset = NULL,
  type = c("box", "jitterbox", "bar", "jitterbar", "jitter"),
  thresh,
  threshlab = NULL,
  threshcol = "tan",
  site = NULL,
  resultatt = NULL,
  locgroup = NULL,
  dtrng = NULL,
  confint = FALSE,
  fill = "lightgreen",
  alpha = 0.8,
  width = 0.8,
  yscl = "auto",
  sumfun = yscl,
  byresultatt = FALSE,
  ttlsize = 1.2,
  runchk = TRUE,
  warn = TRUE
)

Arguments

Details

Summaries of a parameter for each site are shown as boxplots if type = "box" or as barplots if type = "bar". Points can be jittered over the boxplots by setting type = "jitterbox" or jittered over the barplots by setting type = "jitterbar". Setting type = "jitter" will show only the jittered points. For type = "bar" or type = "jitterbar", 95% confidence intervals can also be shown if confint = TRUE and they can be estimated (i.e., more than one result value per bar and sumfun is "auto", "mean", or "geomean").

Threshold lines applicable to marine or freshwater environments can be included in the plot by using the thresh argument. These thresholds are specific to each parameter and can be found in the thresholdMWR file. Threshold lines are plotted only for those parameters with entries in thresholdMWR and only if the value in `Result Unit` matches those in thresholdMWR. The threshold lines can be suppressed by setting thresh = 'none'. A user-supplied numeric value can also be used for the thresh argument to override the default values. An appropriate label must also be supplied to threshlab if thresh is numeric.

The y-axis scaling as arithmetic (linear) or logarithmic can be set with the yscl argument. If yscl = "auto" (default), the scaling is determined automatically from the data quality objective file for accuracy, i.e., parameters with "log" in any of the columns are plotted on log10-scale, otherwise arithmetic. Setting yscl = "linear" or yscl = "log" will set the axis as linear or log10-scale, respectively, regardless of the information in the data quality objective file for accuracy.

Similarly, the data will be summarized if type is "bar" or "jitterbar" based on the value passed to sumfun. The default if no value is provided to sumfun is to use the appropriate summary based on the value provided to yscl. If yscl = "auto" (default), then sumfun = "auto", and the mean or geometric mean is used for the summary based on information in the data quality objective file for accuracy. Using yscl = "linear" or yscl = "log" will default to the mean or geometric mean summary if no value is provided to sumfun. Any other appropriate value passed to sumfun will override the value passed to yscl. Valid summary functions for sumfun include "auto", "mean", "geomean", "median", "min", or "max").

Any entries in resdat in the "Result Value" column as "BDL" or "AQL" are 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.

The byresultatt argument can be used to group sites separately by result attributes. For example, sites with E. coli samples can be grouped by "Dry" or "Wet" conditions if present in the "Result Attribute" column. Filtering by sites first using the site argument is advised to reduce the amount of data that are plotted. The grouping can be filtered further by passing appropriate values in the "Result Attribute" column to the resultatt argument. Note that specifying result attributes with resultatt and setting byresultatt = FALSE will filter the plot data by the result attributes but will not plot the results separately.

Value

A ggplot object that can be further modified.

Examples

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

# results data
resdat <- readMWRresults(respth)

# accuracy path
accpth <- system.file('extdata/ExampleDQOAccuracy.xlsx', 
     package = 'MassWateR')

# accuracy data
accdat <- readMWRacc(accpth)

# site data path
sitpth <- system.file('extdata/ExampleSites.xlsx', package = 'MassWateR')

# site data
sitdat <- readMWRsites(sitpth)

# site trends, boxplot
anlzMWRsite(res = resdat, param = 'DO', acc = accdat, type = 'box', thresh = 'fresh')

# site trends, barplot
anlzMWRsite(res = resdat, param = 'DO', acc = accdat, type = 'bar', thresh = 'fresh')

# site trends, May to July only
anlzMWRsite(res = resdat, param = 'DO', acc = accdat, type = 'box', thresh = 'fresh',
     dtrng = c('2022-05-01', '2022-07-31'))
     
# grouping by result attribute
anlzMWRsite(res = resdat, param = 'DO', acc = accdat, type = 'box', thresh = 'fresh',
     site = c('ABT-062', 'ABT-077'), byresultatt = TRUE)
     
# site trends by location group, requires sitdat
anlzMWRsite(res = resdat, param = 'DO', acc = accdat, sit = sitdat, type = 'box', 
     thresh = 'fresh', locgroup = 'Assabet')

Description

Check data quality objective accuracy data

Usage

checkMWRacc(accdat, warn = TRUE)

Arguments

Details

This function is used internally within readMWRacc to run several checks on the input data for completeness and conformance to WQX requirements

The following checks are made:

• Column name spelling: Should be the following: Parameter, uom, MDL, UQL, Value Range, Field Duplicate, Lab Duplicate, Field Blank, Lab Blank, Spike/Check Accuracy

• Columns present: All columns from the previous check should be present

• Column types: All columns should be characters/text, except for MDL and UQL

• Value Range column na check: The character string "na" should not be in the Value Range column, "all" should be used if the entire range applies

• Unrecognized characters: Fields describing accuracy checks should not include symbols or text other than $<=$, $\leq$, $<$, $>=$, $\geq$, $>$, $\pm$, "%", "BDL", "AQL", "log", or "all"

• Overlap in Value Range column: Entries in Value Range should not overlap for a parameter (excludes ascending ranges)

• Gap in Value Range column: Entries in Value Range should not include a gap for a parameter, warning only

• Parameter: Should match parameter names in the Simple Parameter or WQX Parameter columns of the paramsMWR data

• Units: No missing entries in units (uom), except pH which can be blank

• Single unit: Each unique Parameter should have only one type for the units (uom)

• Correct units: Each unique Parameter should have an entry in the units (uom) that matches one of the acceptable values in the Units of measure column of the paramsMWR data

• Empty columns: Columns with all missing or NA values will return a warning

Value

accdat 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.

Examples

# accuracy path
accpth <- system.file('extdata/ExampleDQOAccuracy.xlsx', 
     package = 'MassWateR')

# accuracy data with no checks
accdat <- readxl::read_excel(accpth, na = c('NA', ''), col_types = 'text')
accdat <- dplyr::mutate(accdat, dplyr::across(-c(`Value Range`), ~ dplyr::na_if(.x, 'na'))) 
      
checkMWRacc(accdat)

Description

Check data quality objective frequency and completeness data

Usage

checkMWRfrecom(frecomdat, warn = TRUE)

Arguments

Details

This function is used internally within readMWRfrecom to run several checks on the input data for frequency and completeness and conformance to WQX requirements

The following checks are made:

• Column name spelling: Should be the following: Parameter, Field Duplicate, Lab Duplicate, Field Blank, Lab Blank, Spike/Check Accuracy, % Completeness

• Columns present: All columns from the previous check should be present

• Non-numeric values: Values entered in columns other than the first should be numeric

• Values outside of 0 - 100: Values entered in columns other than the first should not be outside of 0 and 100

• Parameter: Should match parameter names in the Simple Parameter or WQX Parameter columns of the paramsMWR data

• Empty columns: Columns with all missing or NA values will return a warning

Value

frecomdat 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.

Examples

library(dplyr)

frecompth <- system.file('extdata/ExampleDQOFrequencyCompleteness.xlsx', 
     package = 'MassWateR')

frecomdat <- suppressMessages(readxl::read_excel(frecompth, 
      skip = 1, na = c('NA', 'na', ''), 
      col_types = c('text', 'numeric', 'numeric', 'numeric', 'numeric', 'numeric', 'numeric')
    )) %>% 
    rename(`% Completeness` = `...7`)
    
checkMWRfrecom(frecomdat)

Description

Check water quality monitoring results

Usage

checkMWRresults(resdat, warn = TRUE)

Arguments

Details

This function is used internally within readMWRresults to run several checks on the input data for completeness and conformance to WQX requirements.

The following checks are made:

• Column name spelling: Should be the following: Monitoring Location ID, Activity Type, Activity Start Date, Activity Start Time, Activity Depth/Height Measure, Activity Depth/Height Unit, Activity Relative Depth Name, Characteristic Name, Result Value, Result Unit, Quantitation Limit, QC Reference Value, Result Measure Qualifier, Result Attribute, Sample Collection Method ID, Project ID, Local Record ID, Result Comment

• Columns present: All columns from the previous check should be present

• Activity Type: Should be one of Field Msr/Obs, Sample-Routine, Quality Control Sample-Field Blank, Quality Control Sample-Lab Blank, Quality Control Sample-Lab Duplicate, Quality Control Sample-Lab Spike, Quality Control-Calibration Check, Quality Control-Meter Lab Duplicate, Quality Control-Meter Lab Blank

• Date formats: Should be mm/dd/yyyy and parsed correctly on import

• Depth data present: Depth data should be included in Activity Depth/Height Measure or Activity Relative Depth Name for all rows where Activity Type is Field Msr/Obs or Sample-Routine

• Non-numeric Activity Depth/Height Measure: All depth values should be numbers, excluding missing values

• Activity Depth/Height Unit: All entries should be ft, m, or blank

• Activity Relative Depth Name: Should be either Surface, Bottom, Midwater, Near Bottom, or blank (warning only)

• Activity Depth/Height Measure out of range: All depth values should be less than or equal to 1 meter / 3.3 feet or entered as Surface in the Activity Relative Depth Name column (warning only)

• Characteristic Name: Should match parameter names in the Simple Parameter or WQX Parameter columns of the paramsMWR data (warning only)

• Result Value: Should be a numeric value or a text value as AQL or BDL

• Non-numeric Quantitation Limit: All values should be numbers, excluding missing values

• QC Reference Value: Should be a numeric value or a text value as AQL or BDL

• Result Unit: No missing entries in Result Unit, except pH which can be blank

• Single Result Unit: Each unique parameter in Characteristic Name should have only one entry in Result Unit (excludes entries for lab spikes reported as % or % recovery)

• Correct Result Unit: Each unique parameter in Characteristic Name should have an entry in Result Unit that matches one of the acceptable values in the Units of measure column of the paramsMWR data (excludes entries for lab spikes reported as % or % recovery)

Value

resdat 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. Checks with warnings can be fixed at the discretion of the user before proceeding.

Examples

library(dplyr)

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

resdat <- suppressWarnings(readxl::read_excel(respth, na = c('NA', 'na', ''), guess_max = Inf)) %>% 
  dplyr::mutate_if(function(x) !lubridate::is.POSIXct(x), as.character)
             
checkMWRresults(resdat)

Description

Check site metadata file

Usage

checkMWRsites(sitdat)

Arguments

Details

This function is used internally within readMWRsites to run several checks on the input data for completeness and conformance to WQX requirements

The following checks are made:

• Column name spelling: Should be the following: Monitoring Location ID, Monitoring Location Name, Monitoring Location Latitude, Monitoring Location Longitude, Location Group

• Columns present: All columns from the previous check should be present

• Missing longitude or latitude: No missing entries in Monitoring Location Latitude or Monitoring Location Longitude

• Non-numeric latitude values: Values entered in Monitoring Location Latitude must be numeric

• Non-numeric longitude values: Values entered in Monitoring Location Longitude must be numeric

• Positive longitude values: Values in Monitoring Location Longitude must be negative

• Missing Location ID: No missing entries for Monitoring Location ID

Value

sitdat 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.

Examples

library(dplyr)

sitpth <- system.file('extdata/ExampleSites.xlsx', package = 'MassWateR')

sitdat <- readxl::read_excel(sitpth, na = c('NA', 'na', ''))
    
checkMWRsites(sitdat)

Description

Check water quality exchange (wqx) metadata input

Usage

checkMWRwqx(wqxdat, warn = TRUE)

Arguments

Details

This function is used internally within readMWRwqx to run several checks on the input data for conformance with downstream functions

The following checks are made:

• Column name spelling: Should be the following: Parameter, Sampling Method Context, Method Speciation, Result Sample Fraction, Analytical Method, Analytical Method Context

• Columns present: All columns from the previous check should be present

• Unique parameters: Values in Parameter should be unique (no duplicates)

• Parameter: Should match parameter names in the Simple Parameter or WQX Parameter columns of the paramsMWR data (warning only)

Value

wqxdat 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. Checks with warnings can be fixed at the discretion of the user before proceeding.

Examples

library(dplyr)

wqxpth <- system.file('extdata/ExampleWQX.xlsx', package = 'MassWateR')

wqxdat <- readxl::read_excel(wqxpth, na = c('NA', 'na', ''), col_types = 'text')
    
checkMWRwqx(wqxdat)

Description

Format data quality objective accuracy data

Usage

formMWRacc(accdat)

Arguments

Details

This function is used internally within readMWRacc to format the input data for downstream analysis. The formatting includes:

• Minor formatting for units: For conformance to WQX, e.g., ppt is changed to ppth, s.u. is changed to NA in uom

• Convert Parameter: All parameters are converted to Simple Parameter in paramsMWR as needed

• Remove unicode: Remove or replace unicode characters with those that can be used in logical expressions in qcMWRacc, e.g., replace $\geq$ with $>=$

• Convert limits to numeric: Convert MDL and UQL columns to numeric

Value

A formatted data frame of the data quality objectives file for accuracy

Examples

accpth <- system.file('extdata/ExampleDQOAccuracy.xlsx', package = 'MassWateR')

accdat <- readxl::read_excel(accpth, na = c('NA', ''))
accdat <- dplyr::mutate(accdat, dplyr::across(-c(`Value Range`), ~ dplyr::na_if(.x, 'na')))

formMWRacc(accdat)

Description

Format data quality objective frequency and completeness data

Usage

formMWRfrecom(frecomdat)

Arguments

Details

This function is used internally within readMWRfrecom to format the input data for downstream analysis. The formatting includes:

• Convert Parameter: All parameters are converted to Simple Parameter in paramsMWR as needed

Value

A formatted data frame of the data quality objectives file for frequency and completeness

Examples

library(dplyr)

frecompth <- system.file('extdata/ExampleDQOFrequencyCompleteness.xlsx', 
     package = 'MassWateR')

frecomdat <- suppressMessages(readxl::read_excel(frecompth, 
      skip = 1, na = c('NA', 'na', ''), 
      col_types = c('text', 'numeric', 'numeric', 'numeric', 'numeric', 'numeric', 'numeric')
    )) %>% 
    rename(`% Completeness` = `...7`)
    
formMWRfrecom(frecomdat)

Description

Format water quality monitoring results

Usage

formMWRresults(resdat, tzone = "America/Jamaica")

Arguments

Details

This function is used internally within readMWRresults to format the input data for downstream analysis. The formatting includes:

• Fix date and time inputs: Activity Start Date is converted to YYYY-MM-DD as a date object, Actvity Start Time is convered to HH:MM as a character to fix artifacts from Excel import

• Minor formatting for Result Unit: For conformance to WQX, e.g., ppt is changed to ppth, s.u. is changed to NA

• Convert characteristic names: All parameters in Characteristic Name are converted to Simple Parameter in paramsMWR as needed

Value

A formatted data frame of the water quality monitoring results file

Examples

library(dplyr)

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

resdat <- suppressWarnings(readxl::read_excel(respth, na = c('NA', 'na', ''), guess_max = Inf)) %>% 
  dplyr::mutate_if(function(x) !lubridate::is.POSIXct(x), as.character)
  
formMWRresults(resdat)

Description

Format WQX metadata input

Usage

formMWRwqx(wqxdat)

Arguments

Details

This function is used internally within readMWRwqx to format the input data for downstream analysis. The formatting includes:

• Convert characteristic names: All parameters in Characteristic Name are converted to Simple Parameter in paramsMWR as needed

Value

A formatted data frame of the WQX metadata file

Examples

library(dplyr)

wqxpth <- system.file('extdata/ExampleWQX.xlsx', package = 'MassWateR')

wqxdat <- suppressWarnings(readxl::read_excel(wqxpth, na = c('NA', 'na', ''), col_types = 'text'))
  
formMWRwqx(wqxdat)

Description

Master parameter list and units for Characteristic Name column in results data

Usage

paramsMWR

Format

A data.frame

Details

This information is used to verify the correct format of input data and for formatting output data for upload to WQX. A column showing the corresponding WQX names is also included.

Examples

paramsMWR

Description

Run quality control accuracy checks for water quality monitoring results

Usage

qcMWRacc(
  res = NULL,
  acc = NULL,
  frecom = NULL,
  fset = NULL,
  runchk = TRUE,
  warn = TRUE,
  accchk = c("Field Blanks", "Lab Blanks", "Field Duplicates", "Lab Duplicates",
    "Lab Spikes / Instrument Checks"),
  suffix = "%"
)

Arguments

Details

The function can be used with inputs as paths to the relevant files or as data frames returned by readMWRresults and readMWRacc. 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 accuracy is only evaluated on parameters in the Parameter column in the data quality objectives accuracy file. A warning is returned if there are parameters in Parameter in the accuracy 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 accuracy 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 accuracy file.

The data quality objectives file for frequency and completeness is used to screen parameters in the results file for inclusion in the accuracy tables. Parameters with empty values in the frequency and completeness table are not returned.

Value

The output shows the accuracy checks from the input files returned as a list, with each element of the list corresponding to a specific accuracy check specified with accchk.

Examples

##
# using file paths

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

# accuracy path
accpth <- system.file('extdata/ExampleDQOAccuracy.xlsx', package = 'MassWateR')

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

qcMWRacc(res = respth, acc = accpth, frecom = frecompth)

Description

Run quality control completeness checks for water quality monitoring results

Usage

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

Arguments

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.

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.

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)

##
# using data frames

# results data
resdat <- readMWRresults(respth)

# frequency and completeness data
frecomdat <- readMWRfrecom(frecompth)

qcMWRcom(res = resdat, frecom = frecomdat)

Description

Run quality control frequency checks for water quality monitoring results

Usage

qcMWRfre(
  res = NULL,
  acc = NULL,
  frecom = NULL,
  fset = NULL,
  runchk = TRUE,
  warn = TRUE
)

Arguments

Details

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. 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.

Value

The output shows the frequency checks from the input 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.

Examples

##
# using file paths

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

# dqo accuracy data path
accpth <- system.file('extdata/ExampleDQOAccuracy.xlsx', package = 'MassWateR')

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

qcMWRfre(res = respth, acc = accpth, frecom = frecompth)

##
# using data frames

# results data
resdat <- readMWRresults(respth)

# accuracy data
accdat <- readMWRacc(accpth)

# frequency and completeness data
frecomdat <- readMWRfrecom(frecompth)

qcMWRfre(res = resdat, acc = accdat, frecom = frecomdat)

Description

Create the quality control review report

Usage

qcMWRreview(
  res = NULL,
  acc = NULL,
  frecom = NULL,
  fset = NULL,
  output_dir,
  output_file = NULL,
  rawdata = TRUE,
  dqofontsize = 7.5,
  tabfontsize = 9,
  padding = 0,
  warn = TRUE,
  runchk = TRUE
)

Arguments

Details

The 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 the individual table functions (which can be used separately) to return the results, which include tabMWRacc, tabMWRfre, and tabMWRcom. The help files for each of these functions can be consulted for a more detailed explanation of the quality control checks.

The workflow for using this function is to import the required data (results and data quality objective files) and to fix any errors noted on import prior to creating the review report. Additional warnings that may be of interest as returned by the individual table functions can be returned in the console by setting warn = TRUE.

Optional arguments 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).

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. 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.

Value

A compiled review report named qcreview.docx (or name passed to output_file) will be saved in the directory specified by output_dir

Examples

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

# dqo accuracy data path
accpth <- system.file('extdata/ExampleDQOAccuracy.xlsx', package = 'MassWateR')

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

# results data
resdat <- readMWRresults(respth)

# accuracy data
accdat <- readMWRacc(accpth)

# frequency and completeness data
frecomdat <- readMWRfrecom(frecompth)


# create report
qcMWRreview(res = resdat, acc = accdat, frecom = frecomdat, output_dir = tempdir())

Description

Read data quality objectives for accuracy from an external file

Usage

readMWRacc(accpth, runchk = TRUE, warn = TRUE)

Arguments

Details

Data are imported with read_excel and checked with checkMWRacc.

Value

A formatted data frame of data quality objectives for completeness that can be used for downstream analysis

Examples

accpth <- system.file('extdata/ExampleDQOAccuracy.xlsx', package = 'MassWateR')

accdat <- readMWRacc(accpth)
head(accdat)

Description

Read data quality objectives for frequency and completeness from an external file

Usage

readMWRfrecom(frecompth, runchk = TRUE, warn = TRUE)

Arguments

Details

Data are imported with read_excel and checked with checkMWRfrecom.

Value

A formatted data frame of data quality objectives for frequency and completeness that can be used for downstream analysis

Examples

frecompth <- system.file('extdata/ExampleDQOFrequencyCompleteness.xlsx', 
     package = 'MassWateR')

frecomdat <- readMWRfrecom(frecompth)
head(frecomdat)

Description

Read water quality monitoring results from an external file

Usage

readMWRresults(respth, runchk = TRUE, warn = TRUE, tzone = "America/Jamaica")

Arguments

Details

Date are imported with read_excel, checked with checkMWRresults, and formatted with formMWRresults.

Value

A formatted water quality monitoring results data frame that can be used for downstream analysis

See Also

readMWRresultsview for troubleshooting import checks

Examples

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

resdat <- readMWRresults(respth)
head(resdat)

Description

Create summary spreadsheet of unique values for each column in the water quality results file to check for data mistakes prior to running the readMWRresults function

Usage

readMWRresultsview(
  respth,
  columns = NULL,
  output_dir,
  output_file = NULL,
  maxlen = 8
)

Arguments

Details

Acceptable options for the columns argument include any of the column names in the results file. The default setting (NULL) will show every column in the results file.

The output of this function can be useful to troubleshoot the checks when importing the water quality monitoring result file with readMWRresults (see https://massbays-tech.github.io/MassWateR/articles/MassWateR.html#data-import-and-checks).

Value

Creates a spreadsheet at the location specified by output_dir. Each column shows the unique values.

Examples

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

# all columns
readMWRresultsview(respth, output_dir = tempdir())

# parameters and units
readMWRresultsview(respth, columns = c('Characteristic Name', 'Result Unit'),
   output_dir = tempdir())

Description

Read site metadata from an external file

Usage

readMWRsites(sitpth, runchk = TRUE)

Arguments

Details

Data are imported with read_excel and checked with checkMWRsites.

Value

A formatted data frame of site metadata that can be used for downstream analysis

Examples

sitpth <- system.file('extdata/ExampleSites.xlsx', package = 'MassWateR')

sitdat <- readMWRsites(sitpth)
head(sitdat)

Description

Read water quality exchange (wqx) metadata input from an external file

Usage

readMWRwqx(wqxpth, runchk = TRUE, warn = TRUE)

Arguments

Details

Date are imported with read_excel, checked with checkMWRwqx.

Value

A formatted data frame that can be used for downstream analysis

Examples

wqxpth <- system.file('extdata/ExampleWQX.xlsx', package = 'MassWateR')

wqxdat <- readMWRwqx(wqxpth)
head(wqxdat)

Description

Create a formatted table of quality control accuracy checks

Usage

tabMWRacc(
  res = NULL,
  acc = NULL,
  frecom = NULL,
  fset = NULL,
  runchk = TRUE,
  warn = TRUE,
  accchk = c("Field Blanks", "Lab Blanks", "Field Duplicates", "Lab Duplicates",
    "Lab Spikes / Instrument Checks"),
  type = c("individual", "summary", "percent"),
  pass_col = "#57C4AD",
  fail_col = "#DB4325",
  suffix = "%",
  caption = TRUE
)

Arguments

Details

The function can be used with inputs as paths to the relevant files or as data frames returned by readMWRresults and readMWRacc. 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. 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.

Also note that accuracy is only evaluated on parameters that are shared between the results file and data quality objectives file for accuracy. A warning is returned for parameters that do not match between the files. This warning can be suppressed by setting warn = FALSE.

The 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 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".

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.

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.

Inputs for the results and data quality objectives for accuracy are processed internally with qcMWRacc and the same arguments are accepted for this function, in addition to others listed above.

Value

A flextable object with formatted results.

Examples

##
# using file paths

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

# accuracy path
accpth <- system.file('extdata/ExampleDQOAccuracy.xlsx', 
     package = 'MassWateR')

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

# table as individual
tabMWRacc(res = respth, acc = accpth, frecom = frecompth, type = 'individual', 
     accchk = 'Field Blanks')

Description

Create a formatted table of quality control completeness checks

Usage

tabMWRcom(
  res = NULL,
  frecom = NULL,
  fset = NULL,
  runchk = TRUE,
  warn = TRUE,
  pass_col = "#57C4AD",
  fail_col = "#DB4325",
  digits = 0,
  suffix = "%",
  parameterwd = 1.15,
  noteswd = 3
)

Arguments

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, as explained in the relevant help files. 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.

Also note that completeness is only evaluated on parameters that are shared between the results file and data quality objectives file for frequency and completeness. A warning is returned for parameters that do not match between the files. This warning can be suppressed by setting warn = FALSE.

A summary table showing the number of data records, number of qualified records, and percent completeness is created. 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.

Inputs for the results and data quality objectives for frequency and completeness are processed internally with qcMWRcom and the same arguments are accepted for this function, in addition to others listed above.

Value

A flextable object with formatted results showing summary counts for all completeness checks for each parameter.

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')

tabMWRcom(res = respth, frecom = frecompth)

##
# using data frames

# results data
resdat <- readMWRresults(respth)

# frequency and completeness data
frecomdat <- readMWRfrecom(frecompth)

tabMWRcom(res = resdat, frecom = frecomdat)

Description

Create a formatted table of quality control frequency checks

Usage

tabMWRfre(
  res = NULL,
  acc = NULL,
  frecom = NULL,
  fset = NULL,
  runchk = TRUE,
  warn = TRUE,
  type = c("summary", "percent"),
  pass_col = "#57C4AD",
  fail_col = "#DB4325",
  digits = 0,
  suffix = "%"
)

Arguments

Details

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. 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.

Also note that completeness is only evaluated on parameters that are shared between the results file and data quality objectives file for frequency and completeness. A warning is returned for parameters that do not match between the files. This warning 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" or a color-coded table showing similar information as percentages for each parameter is provided if type = "percent".

Inputs for the results and data quality objectives for accuracy and frequency and completeness are processed internally with qcMWRcom and the same arguments are accepted for this function, in addition to others listed above.

Value

A flextable object with formatted results.

Examples

##
# using file paths

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

# dqo accuracy data path
accpth <- system.file('extdata/ExampleDQOAccuracy.xlsx', package = 'MassWateR')

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

# table as summary
tabMWRfre(res = respth, acc = accpth, frecom = frecompth, type = 'summary')

# table as percent
tabMWRfre(res = respth, acc = accpth, frecom = frecompth, type = 'percent')

##
# using data frames

# results data
resdat <- readMWRresults(respth)

# accuracy data
accdat <- readMWRacc(accpth)

# frequency and completeness data
frecomdat <- readMWRfrecom(frecompth)

# table as summary
tabMWRfre(res = resdat, acc = accdat, frecom = frecomdat, type = 'summary')

# table as percent
tabMWRfre(res = resdat, acc = accdat, frecom = frecomdat, type = 'percent')

Description

Create and save tables in a single workbook for WQX upload

Usage

tabMWRwqx(
  res = NULL,
  acc = NULL,
  sit = NULL,
  wqx = NULL,
  fset = NULL,
  output_dir,
  output_file = NULL,
  warn = TRUE,
  runchk = TRUE
)

Arguments

Details

This function will export a single Excel workbook with three sheets, named "Project", "Locations", and "Results". The output is populated with as much content as possible based on information in the input files. The remainder of the information not included in the output will need to be manually entered before uploading the data to WQX. All required columns are present, but individual rows will need to be verified for completeness. It is the responsibility of the user to verify this information is complete and correct before uploading the data.

The workflow for using this function is to import the required data (results, data quality objectives file for accuracy, site metadata, and wqx metadata) and to fix any errors noted on import prior to creating the output. The function can be used with inputs as paths to the relevant files or as data frames returned by readMWRresults, readMWRacc, readMWRsites, and readMWRwqx. 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. 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.

The name of the output file can also be changed using the output_file argument, the default being wqxtab.xlsx. Warnings can also be turned off or on (default) using the warn argument. This returns any warnings when data are imported and only applies if the file inputs are paths.

Value

An Excel workbook named wqxtab.xlsx (or name passed to output_file) will be saved in the directory specified by output_dir. The workbook will include three sheets names "Projects", "Locations", and "Results".

Examples

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

# dqo accuracy data path
accpth <- system.file('extdata/ExampleDQOAccuracy.xlsx', package = 'MassWateR')

# site data path
sitpth <- system.file('extdata/ExampleSites.xlsx', package = 'MassWateR')

# wqx data path
wqxpth <- system.file('extdata/ExampleWQX.xlsx', package = 'MassWateR')

# results data
resdat <- readMWRresults(respth)

# accuracy data
accdat <- readMWRacc(accpth)

# site data
sitdat <- readMWRsites(sitpth)

# wqx data
wqxdat <- readMWRwqx(wqxpth)

# create workbook
tabMWRwqx(res = resdat, acc = accdat, sit = sitdat, wqx = wqxdat, output_dir = tempdir())

Description

Master thresholds list for analysis of results data

Usage

thresholdMWR

Format

A data.frame of 28 rows and 10 columns

Details

This file includes appropriate threshold values of water quality parameters for marine and freshwater environments based on state standards or typical ranges in Massachusetts.

Examples

thresholdMWR

Description

Filter results data by parameter, date range, site, result attributes, and/or location group

Usage

utilMWRfilter(
  resdat,
  sitdat = NULL,
  param,
  dtrng = NULL,
  site = NULL,
  resultatt = NULL,
  locgroup = NULL,
  alllocgroup = FALSE,
  allresultatt = FALSE
)

Arguments

Value

resdat filtered by param, dtrng, site, resultatt, and/or locgroup, otherwise resdat filtered only by param if other arguments are NULL

Examples

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

# results data
resdat <- readMWRresults(respth)

# site data path
sitpth <- system.file('extdata/ExampleSites.xlsx', package = 'MassWateR')

# site data
sitdat <- readMWRsites(sitpth)

# filter by parameter, date range
utilMWRfilter(resdat, param = 'DO', dtrng = c('2022-06-01', '2022-06-30'))

# filter by parameter, site
utilMWRfilter(resdat, param = 'DO', site = c('ABT-026', 'ABT-062', 'ABT-077'))

# filter by parameter, result attribute
utilMWRfilter(resdat, param = 'DO', resultatt = 'DRY')

# filter by parameter, location group, date range
utilMWRfilter(resdat, param = 'DO', sitdat = sitdat, 
     locgroup = 'Assabet', dtrng = c('2022-06-01', '2022-06-30'))

Description

Filter results data to surface measurements

Usage

utilMWRfiltersurface(resdat)

Arguments

Details

This function is used internally for all analysis functions

Value

resdat filtered by Activity Depth/Height Measure less than or equal to 1 meter or 3.3 feet or Activity Relative Depth Name as "Surface"

Examples

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

# results data
resdat <- readMWRresults(respth)

# filter surface data
utilMWRfiltersurface(resdat)

Description

Prep results data for frequency checks

Usage

utilMWRfre(resdat, param, accdat, warn = TRUE)

Arguments

Details

This function is similar to utilMWRlimits with some additional processing appropriate for creating the frequency table in tabMWRfree. 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.

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. Values not in the "Value Range" column of the accuracy file are removed from the output.

Examples

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

# results data
resdat <- readMWRresults(respth)

# accuracy path
accpth <- system.file('extdata/ExampleDQOAccuracy.xlsx', 
     package = 'MassWateR')

# accuracy data
accdat <- readMWRacc(accpth)

# apply to total phosphorus
utilMWRfre(resdat, accdat, param = 'TP')

# apply to E.coli
utilMWRfre(resdat, accdat, param = 'E.coli')

Description

Load external file from remote source, fail gracefully

Usage

utilMWRhttpgrace(remote_file)

Arguments

Value

The external file as an RData object

Examples

# fails gracefully
utilMWRhttpgrace('http://httpbin.org/status/404')

# imports data or fails gracefully
fl <- 'https://github.com/massbays-tech/MassWateRdata/raw/main/data/streamsMWR.RData'
utilMWRhttpgrace(fl)

Description

Utility function to import data as paths or data frames

Usage

utilMWRinput(
  res = NULL,
  acc = NULL,
  frecom = NULL,
  sit = NULL,
  wqx = NULL,
  fset = NULL,
  runchk = TRUE,
  warn = TRUE
)

Arguments

Details

The function is used internally by others to import data from paths to the relevant files or as data frames returned by readMWRresults, readMWRacc, readMWRfrecom, readMWRsites, or readMWRwqx. For the former, the full suite of data checks can be evaluated with runkchk = T (default) or suppressed with runchk = F.

The fset argument can used in place of the preceding arguments. The argument accepts a list with named elements as res, acc, frecom, sit, or wqx, where the elements are either character strings of the path or data frames to the corresponding inputs. Missing elements will be interpreted as NULL values. This argument is provided as convenience to apply a single list as input versus separate inputs for each argument.

Any of the arguments for the data files can be NULL, used as a convenience for downstream functions that do not require all.

Value

A five element list with the imported results, data quality objective files, site metadata, and wqx metadata, named "resdat", "accdat", "frecomdat", "sitdat", and "wqxdat", respectively.

Examples

##
# using file paths

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

# accuracy path
accpth <- system.file('extdata/ExampleDQOAccuracy.xlsx', package = 'MassWateR')

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

# site path
sitpth <- system.file('extdata/ExampleSites.xlsx', package = 'MassWateR')

# wqx path
wqxpth <- system.file('extdata/ExampleWQX.xlsx', package = 'MassWateR')

inp <- utilMWRinput(res = respth, acc = accpth, frecom = frecompth, sit = sitpth, wqx = wqxpth)
inp$resdat
inp$accdat
inp$frecomdat
inp$sitdat
inp$wqxdat

##
# using data frames

# results data
resdat <- readMWRresults(respth)

# accuracy data
accdat <- readMWRacc(accpth)

# frequency and completeness data
frecomdat <- readMWRfrecom(frecompth)

# site data
sitdat <- readMWRsites(sitpth)

# wqx data
wqxdat <- readMWRwqx(wqxpth)

inp <- utilMWRinput(res = resdat, acc = accdat, frecom = frecomdat, sit = sitdat, wqx = wqxpth)
inp$resdat
inp$accdat
inp$frecomdat
inp$sitdat
inp$wqxdat

##
# using fset as list input

# input with paths to files
fset <- list(
  res = respth, 
  acc = accpth, 
  frecom = frecompth,
  sit = sitpth, 
  wqx = wqxpth
)
utilMWRinput(fset = fset)

Description

Check if required inputs are present for a function

Usage

utilMWRinputcheck(inputs)

Arguments

Value

NULL if all inputs are present, otherwise an error message indicating which inputs are missing

Examples

inputchk <- formals(tabMWRcom)
inputchk$res <- system.file('extdata/ExampleResults.xlsx', package = 'MassWateR')
inputchk$frecom <- system.file('extdata/ExampleDQOFrequencyCompleteness.xlsx', 
  package = 'MassWateR')

utilMWRinputcheck(inputchk)

Description

Fill results data as BDL or AQL with appropriate values

Usage

utilMWRlimits(resdat, param, accdat, warn = TRUE)

Arguments

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.

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".

Examples

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

# results data
resdat <- readMWRresults(respth)

# accuracy path
accpth <- system.file('extdata/ExampleDQOAccuracy.xlsx', 
     package = 'MassWateR')

# accuracy data
accdat <- readMWRacc(accpth)

# apply to total phosphorus
utilMWRlimits(resdat, accdat, param = 'TP')

# apply to E.coli
utilMWRlimits(resdat, accdat, param = 'E.coli')

Description

Identify outliers in a numeric vector

Usage

utilMWRoutlier(x, logscl)

Arguments

Details

Outliers are identified as 1.5 times the interquartile range

Value

A logical vector equal in length to x indicating TRUE for outliers or FALSE for within normal range

Examples

x <- rnorm(20)
utilMWRoutlier(x, logscl = FALSE)

Description

Verify summary function

Usage

utilMWRsumfun(accdat, param, sumfun = "auto")

Arguments

Details

This function verifies appropriate summary functions are passed from sumfun. The mean or geometric mean output is used for sumfun = "auto" based on information in the data quality objective file for accuracy, i.e., parameters with "log" in any of the columns are summarized with the geometric mean, otherwise arithmetic. Using "mean" or "geomean" for sumfun will apply the appropriate function regardless of information in the data quality objective file for accuracy.

Value

Character indicating the appropriate summary function based on the value passed to sumfun.

Examples

# accuracy path
accpth <- system.file('extdata/ExampleDQOAccuracy.xlsx', 
     package = 'MassWateR')

# accuracy data
accdat <- readMWRacc(accpth)

# geomean auto
utilMWRsumfun(accdat, param = 'E.coli')

# mean force
utilMWRsumfun(accdat, param = 'E.coli', sumfun = 'mean')

# mean auto
utilMWRsumfun(accdat, param = 'DO')

# geomean force
utilMWRsumfun(accdat, param = 'DO', sumfun = 'geomean')

Description

Summarize a results data frame by a grouping variable

Usage

utilMWRsummary(dat, accdat, param, sumfun = "auto", confint)

Arguments

Details

This function summarizes a results data frame by an existing grouping variable using the function supplied to sumfun. The mean or geometric mean is used for sumfun = "auto" based on information in the data quality objective file for accuracy, i.e., parameters with "log" in any of the columns are summarized with the geometric mean, otherwise arithmetic. Using "mean" or "geomean" for sumfun will apply the appropriate function regardless of information in the data quality objective file for accuracy.

Value

A summarized data frame, a warning will be returned if the confidence interval cannot be estimated and confint = TRUE

Examples

library(dplyr)

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

# results data
resdat <- readMWRresults(respth)

# accuracy path
accpth <- system.file('extdata/ExampleDQOAccuracy.xlsx', 
     package = 'MassWateR')

# accuracy data
accdat <- readMWRacc(accpth)

# fill BDL, AQL
resdat <- utilMWRlimits(resdat = resdat, accdat = accdat, param = "DO")

dat <- resdat %>% 
  group_by(`Monitoring Location ID`)
 
# summarize sites by mean 
utilMWRsummary(dat, accdat, param = 'DO', sumfun = 'auto', confint = TRUE)

# summarize sites by minimum
utilMWRsummary(dat, accdat, param = 'DO', sumfun = 'min', confint = FALSE)

Description

Get threshold lines from thresholdMWR

Usage

utilMWRthresh(resdat, param, thresh, threshlab = NULL)

Arguments

Value

If thresh is not numeric and thresholds are available for param, a data.frame of relevant marine or freshwater thresholds, otherwise NULL. If thresh is numeric, a data.frame of the threshold with the appropriate label from threshlabel.

Examples

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

# results data
resdat <- readMWRresults(respth)

# get threshold lines
utilMWRthresh(resdat = resdat, param = 'E.coli', thresh = 'fresh')

# user-defined numeric threshold line
utilMWRthresh(resdat = resdat, param = 'TP', thresh = 5, threshlab = 'My threshold')

Description

Format the title for analyze functions

Usage

utilMWRtitle(
  param,
  accdat = NULL,
  sumfun = NULL,
  site = NULL,
  dtrng = NULL,
  resultatt = NULL,
  locgroup = NULL
)

Arguments

Details

All arguments are optional except param, appropriate text strings are appended to the param argument for all other optional arguments indicating the level of filtering used in the plot and data summary if appropriate

Value

A formatted character string used for the title in analysis plots

Examples

# no filters
utilMWRtitle(param = 'DO')

# filter by date only
utilMWRtitle(param = 'DO', dtrng = c('2021-05-01', '2021-07-31'))

# filter by all
utilMWRtitle(param = 'DO', site = 'test', dtrng = c('2021-05-01', '2021-07-31'), 
     resultatt = 'test', locgroup = 'test')
     
# title using summary 
accpth <- system.file('extdata/ExampleDQOAccuracy.xlsx', package = 'MassWateR')
accdat <- readMWRacc(accpth, runchk = FALSE)
utilMWRtitle(param = 'DO', accdat = accdat, sumfun = 'auto', site = 'test', 
     dtrng = c('2021-05-01', '2021-07-31'), resultatt = 'test', locgroup = 'test')

Description

Check if incomplete range in Value Range column

Usage

utilMWRvaluerange(accdat)

Arguments

Details

The function evaluates if an incomplete or overlapping range is present in the Value Range column of the data quality objectives file for accuracy

Value

A named vector of "gap", "nogap", or "overlap" indicating if a gap is present, no gap is present, or an overlap is present in the ranges provided by the value range for each parameter. The names correspond to the parameters.

Examples

# accuracy path
accpth <- system.file('extdata/ExampleDQOAccuracy.xlsx', 
     package = 'MassWateR')

# accuracy data with no checks
accdat <- readxl::read_excel(accpth, na = c('NA', ''), col_types = 'text')
accdat <- dplyr::mutate(accdat, dplyr::across(-c(`Value Range`), ~ dplyr::na_if(.x, 'na'))) 

utilMWRvaluerange(accdat)

Description

Get logical value for y axis scaling

Usage

utilMWRyscale(accdat, param, yscl = "auto")

Arguments

Value

A logical value indicating TRUE for log10-scale, FALSE for arithmetic (linear)

Examples

# accuracy path
accpth <- system.file('extdata/ExampleDQOAccuracy.xlsx', 
     package = 'MassWateR')

# accuracy data
accdat <- readMWRacc(accpth)

# log auto
utilMWRyscale(accdat, param = 'E.coli')

# linear force
utilMWRyscale(accdat, param = 'E.coli', yscl = 'linear')

# linear auto
utilMWRyscale(accdat, param = 'DO')

# log force
utilMWRyscale(accdat, param = 'DO', yscl = 'log')