remove_empty: Return or remove variables or observations that are...

In datawizard: Easy Data Wrangling and Statistical Transformations

Return or remove variables or observations that are completely missing

Description

These functions check which rows or columns of a data frame completely contain missing values, i.e. which observations or variables completely have missing values, and either (1) returns their indices; or (2) removes them from the data frame.

Usage

empty_columns(x)

empty_rows(x)

remove_empty_columns(x)

remove_empty_rows(x)

remove_empty(x)

Arguments

x	A data frame.

Details

For character vectors, empty string values (i.e. "") are also considered as missing value. Thus, if a character vector only contains NA and ⁠""``, it is considered as empty variable and will be removed. Same applies to observations (rows) that only contain ⁠NAor""'.

Value

• For empty_columns() and empty_rows(), a numeric (named) vector with row or column indices of those variables that completely have missing values.

• For remove_empty_columns() and remove_empty_rows(), a data frame with "empty" columns or rows removed, respectively.

• For remove_empty(), both empty rows and columns will be removed.

Examples

tmp <- data.frame(
  a = c(1, 2, 3, NA, 5),
  b = c(1, NA, 3, NA, 5),
  c = c(NA, NA, NA, NA, NA),
  d = c(1, NA, 3, NA, 5)
)

tmp

# indices of empty columns or rows
empty_columns(tmp)
empty_rows(tmp)

# remove empty columns or rows
remove_empty_columns(tmp)
remove_empty_rows(tmp)

# remove empty columns and rows
remove_empty(tmp)

# also remove "empty" character vectors
tmp <- data.frame(
  a = c(1, 2, 3, NA, 5),
  b = c(1, NA, 3, NA, 5),
  c = c("", "", "", "", ""),
  stringsAsFactors = FALSE
)
empty_columns(tmp)

datawizard documentation built on Sept. 15, 2023, 9:06 a.m.