Check data quality objective frequency and completeness data

Usage

checkMWRfrecom(frecomdat, warn = TRUE)

Arguments

frecomdat: input data frame
warn: logical to return warnings to the console (default)

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.

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

Examples

library(dplyr)
#> 
#> Attaching package: ‘dplyr’
#> The following objects are masked from ‘package:stats’:
#> 
#>     filter, lag
#> The following objects are masked from ‘package:base’:
#> 
#>     intersect, setdiff, setequal, union

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)
#> Running checks on data quality objectives for frequency and completeness...
#> 	Checking column names... OK
#> 	Checking all required columns are present... OK
#> 	Checking for non-numeric values... OK
#> 	Checking for values outside of 0 and 100... OK
#> 	Checking Parameter formats... OK
#> 	Checking empty columns... OK
#> 
#> All checks passed!
#> # A tibble: 8 × 7
#>   Parameter      `Field Duplicate` `Lab Duplicate` `Field Blank` `Lab Blank`
#>   <chr>                      <dbl>           <dbl>         <dbl>       <dbl>
#> 1 Water Temp                    10              10            NA          NA
#> 2 pH                            10              10            NA          NA
#> 3 DO                            10              NA            NA          NA
#> 4 Sp Conductance                10              10            NA          10
#> 5 TP                            10               5            10           5
#> 6 Nitrate                       10               5            10           5
#> 7 Ammonia                       10               5            10           5
#> 8 E.coli                        10               5            10           5
#> # ℹ 2 more variables: `Spike/Check Accuracy` <dbl>, `% Completeness` <dbl>