drop_na_if: Condition based dropping of columns with missing values

In Nelson-Gon/mde: Missing Data Explorer

Condition based dropping of columns with missing values

Description

"drop_na_if" provides a simple way to drop columns with missing values if they meet certain criteria/conditions.

Usage

drop_na_if(
  df,
  sign = "gteq",
  percent_na = 50,
  keep_columns = NULL,
  grouping_cols = NULL,
  target_columns = NULL,
  ...
)

Arguments

df	A data.frame object
sign	Character. One of gteq,lteq,lt,gt or eq which refer to greater than(gt) or equal(eq) or less than(lt) or equal to(eq) respectively.
percent_na	The percentage to use when dropping columns with missing values
keep_columns	Columns that should be kept despite meeting the target percent_na criterion(criteria)
grouping_cols	For dropping groups that meet a target criterion of percent missingness.
target_columns	If working on grouped data, drop all columns that meet target or only a specific column.
...	Other arguments to "percent_missing"

Value

A data.frame object with columns that meet the target criteria dropped.

See Also

percent_missing

Examples

head(drop_na_if(airquality, percent_na = 24))
#drop columns that have less tan or equal to 4%
head(drop_na_if(airquality,sign="lteq", percent_na = 4))
# Drop all except with greater than ie equal to 4% missing but keep Ozone
head(drop_na_if(airquality, sign="gteq",percent_na = 4, 
keep_columns = "Ozone"))
# Drop groups that meet a given criterion
grouped_drop <- structure(list(ID = c("A", "A", "B", "A", "B"), Vals = c(4, NA, 
NA, NA, NA), Values = c(5, 6, 7, 8, NA)), row.names = c(NA, -5L),
 class = "data.frame")
 drop_na_if(grouped_drop,percent_na = 67,grouping_cols = "ID")

Nelson-Gon/mde documentation built on March 23, 2022, 10:58 p.m.