View source: R/library--data_prep--filter_tools--outlier_tools.R
removeOutliers | R Documentation |
Add column with NA values where the data was flagged
removeOutliers(DF, Messure, Filtcol, outputColName)
DF |
DF containing the columns Measure and Filtcol |
Messure |
The original measurement we want to keep inliers for |
Filtcol |
the column containing the Boolean info needed to remove outliers |
outputColName |
the name for the clean column |
DF with new column without the flagged values
data(Example_data, package = "Covid19Wastewater")
Example_data$site = "Madison"
df_data <- computeJumps(Example_data)
ranked_data <- rankJumps(df_data)
ranked_quantile_data <- computeRankQuantiles(ranked_data)
classied_data <- flagOutliers(ranked_quantile_data, 9)
removeOutliers(classied_data, sars_cov2_adj_load_log10, FlaggedOutlier, sars_adj_log10_Filtered)
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