TADA_FindQCActivities: Check for Quality Control Samples

In USEPA/TADA: EPA TADA (Tools for Automated Data Analysis) R Package

Check for Quality Control Samples

Description

This function checks for and flags or removes samples denoted as quality control activities based on the 'ActivityTypeCode' column. The function will flag duplicate samples as "QC_duplicate", blank samples as "QC_blank", calibration or spiked samples as "QC_calibration", and other QC samples as "QC_other". All other samples are flagged as "Non_QC".

Usage

TADA_FindQCActivities(.data, clean = FALSE, flaggedonly = FALSE)

Arguments

.data	TADA dataframe which must include the column 'ActivityTypeCode'
clean	Character argument with options "none", "all", "duplicates", or "blanks", "calibrations", or "other". The default is clean = "none" which does not remove any rows of data. When clean = "all", any rows of data flagged as a Quality Control sample will be removed. When clean = "duplicates", any rows of data flagged as a duplicate Quality Control sample will be removed. When clean = "blanks", any rows of data flagged as a blank Quality Control sample will be removed. When clean = "calibrations", any rows of data flagged as a calibration check or spiked Quality Control sample will be removed. And when clean = "other", any rows of data flagged as some other type of Quality Control sample will be removed.
flaggedonly	Boolean argument; the default is flaggedonly = FALSE. When flaggedonly = TRUE, the function will filter the dataframe to show only the rows of data flagged as Quality Control samples.

Value

This function adds the column "TADA.ActivityType.Flag" to the dataframe which flags quality control samples based on the "ActivityTypeCode" column. When clean = "none", all flagged data are kept in the dataframe. When clean = "all", all flagged data are removed from the dataframe. When clean = "duplicates", data flagged as QC duplicates are removed from the dataframe. When clean = "blanks", data flagged as QC blanks are removed from the dataframe. When clean = "calibrations", data flagged as QC calibration checks or spikes are removed from the dataframe. When clean = "other", data flagged as other QC samples are removed from the dataframe. When flaggedonly = TRUE, the dataframe is filtered to show only the flagged data. When flaggedonly = FALSE, the full, cleaned dataframe is returned. The default is clean = "none" and flaggedonly = FALSE.

Examples

# Load example dataset:
data(Data_Nutrients_UT)

# Flag and keep all QC samples:
QC_flagged <- TADA_FindQCActivities(Data_Nutrients_UT)

# Flag QC samples and filter to flagged data only:
QC_flags_only <- TADA_FindQCActivities(Data_Nutrients_UT, flaggedonly = TRUE)

# Remove all QC samples:
QC_clean <- TADA_FindQCActivities(Data_Nutrients_UT, clean = TRUE)

USEPA/TADA documentation built on April 12, 2025, 1:47 p.m.