Creates dataframe(s) summarizing data quality — get_custom

get_custom_flags returns data frames that that summarize data quality control flags (one that summarizes at the data file level and one for each column). The summaries include all data with quality control flagging (a column name that ends in "_flag") and optionally any additional custom columns the user specifies, either by column name or number.

The use can specify which of the 2 data frames (or all as a list of dataframes) should be returned.

The number of each flag type for each column (A, AE, R, P) is reported. Unflagged columns are assumed to have only accepted (or missing) data. The total number of data points in the specified columns (and data flagging columns for) each .csv are also reported. NAs considered missing data. An Unweighted Relative Response (RRU) is calculated as the total number of accepted data points (A, AE, and data that are not flagged) divided by the total number of data points (excluding missing values) in all specified columns (and the flagged columns).

get_custom_flags(
  directory = here::here(),
  cols = (""),
  output = c("all", "files", "columns")
)

Arguments

directory: is the path to the data package .csv files (defaults to the current working directory).
cols: A comma delimited list of column names. If left unspecified, defaults to just flagged columns.
output: A string indicating what output should be provided. "columns" returns a summary table of QC flags and RRU values in each specified column for every data file. "files" returns a summary table of total QC flags and mean across each data file. "all" will return all three data frames in a single list.

Value

a dataframe with quality control summary information summarized at the specified level(s).

Details

Flagged columns must have names ending in "_flag". Missing values must be specified as NA. The function counts cells within "*_flag" columns that start with one of the flagging characters (A, AE, R, P) and ignores trailing characters and white spaces. For custom columns that do not include a specific flagging column, all non-missing (non-NA) values are considered Accepted (A).

The intent of get_custom_flags is for integration into reports on data quality, such as Data Release Reports (DRRs).

Examples

if (FALSE) { # \dontrun{

get_custom_flags("~/my_data_package_directory", cols = c("scientificName",
                                                         "locality"),
                                                         output="all")
cols <- colnames(read.csv("mydata.csv"))[c(1:4, 7, 10)]
get_custom_flags(cols = cols, output="files")
} # }