mde (version 0.3.2)

drop_na_if: 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

# NOT RUN {
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")
# }