error_handling: Error Handling

In qol: Powerful 'SAS' Inspired Concepts for more Efficient Bigger Outputs

Error Handling

Description

resolve_intersection(): Compares if two vectors have intersecting values. If TRUE, removes the intersection values from the base vector

part_of_df(): Check if variable names are part of a data frame. If not, remove them from the given vector.

remove_doubled_values(): Remove values from a vector that appear more than once.

check_weight(): Check if a weight variable was provided. If TRUE, check whether it can be used else add a temporary weight variable.

Usage

resolve_intersection(base, vector_to_check, check_only = FALSE)

part_of_df(data_frame, var_names, check_only = FALSE)

remove_doubled_values(var_names)

check_weight(data_frame, var_names)

Arguments

base	The base vector from which to remove any intersecting values.
vector_to_check	The vector for which intersections should be checked.
check_only	Returns a list of invalid entries instead of a vector. Additionally it doesn't throw a warning.
data_frame	A data frame in which to look up variable names.
var_names	A character vector of variable names.

Value

Returns a vector or list.

Examples

# Resolve intersection between two vectors
vec1 <- c("a", "b", "c", "d")
vec2 <- c("e", "f", "a", "g")

vec1 <- resolve_intersection(vec1, vec2)

# Check if variables are part of a data frame
my_data   <- dummy_data(100)
var_names <- c("year", "state", "age", "test")

var_names <- my_data |> part_of_df(var_names)

# Remove doubled values
var_names <- c("year", "state", "state", "age")

var_names <- remove_doubled_values(var_names)

# Check the provided weight variable
var_names <- my_data |> check_weight("weight")

qol documentation built on March 11, 2026, 1:06 a.m.