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Identify, remove, or replace NaNs

Source: R/nan_filter.R
nan_filter.Rd

Replaces NaNs in the primary data with the chosen value or removes rows containing NaNs

Usage

nan_filter(
  dat,
  project,
  x = NULL,
  replace = FALSE,
  remove = FALSE,
  rep.value = "mean",
  over_write = FALSE
)

Arguments

dat

Primary data containing information on hauls or trips. Table in the FishSET database contains the string 'MainDataTable'.

project

Project name.

x

Character string of variables to remove or replace NaNs.

replace

Logical, If TRUE, NaNs are replaced. Defaults to FALSE.

remove

Logical, if TRUE, removes the entire row of the dataset where NaN is present. Defaults to FALSE.

rep.value

Value to replace all NaNs in a numeric column. Defaults to the mean value of the column. Other options include "median" or a numeric value, e.g. rep.value = 0.

over_write

Logical, If TRUE, saves data over previously saved data table in the FishSET database. Defaults to FALSE.

Value

If replace and remove are FALSE then a statement of whether NaNs are found is returned. If either replace or remove

is TRUE the modified primary dataset is returned.

Details

To check for NaNs across dat run the function specifying only dat (nan_filter(dataset, project)). The function will return a statement of which variables, if any, contain NaNs. To remove NaNs, use remove = TRUE. All rows containing NaNs in x will be removed from dat. To replace NaNs, use replace = TRUE. If both replace and remove are TRUE then replace is used. If replace is FALSE and rep.value is not defined, then NaNs are replaced with mean value. The modified dataset will be returned if replace = TRUE or remove = TRUE. Save the modified data table to the FishSET database by setting over_write = TRUE).

Examples

if (FALSE) {
nan_filter(pcodMainDataTable, 'pcod', 'OFFICIAL_TOTAL_CATCH_MT')

mod.dat <- nan_filter(pcodMainDataTable, 'pcod', 'OFFICIAL_TOTAL_CATCH_MT', 
                      replace = TRUE)
                      
mod.dat <- nan_filter(pcodMainDataTable, 'pcod', 'OFFICIAL_TOTAL_CATCH_MT',
                      replace = TRUE, rep.value = 0)
                      
mod.dat <- nan_filter(pcodMainDataTable, 'pcod', 'OFFICIAL_TOTAL_CATCH_MT', 
                      remove = TRUE)
}