sumvar (version 0.1)

dup: Explore duplicate and missing data

Description

Provides an integer value for the number of duplicates found within a variable The function accepts an input from a dplyr pipe "%>%" and outputs the results as a tibble.

eg. example_data %>% dup(variable)

Usage

dup(data, var = NULL)

Value

A tibble with the number and percentage of duplicate values found, and the number of missing values (NA), together with percentages.

Arguments

data

The data frame or tibble

var

The variable to assess

Examples

example_data <- dplyr::tibble(id = 1:200, age = round(rnorm(200, mean = 30, sd = 50), digits=0))
example_data$age[sample(1:200, size = 15)] <- NA  # Replace 15 values with missing.
dup(example_data, age)
# It is also possible to pass a whole database to dup and it will explore all variables.
example_data <- dplyr::tibble(age = round(rnorm(200, mean = 30, sd = 50), digits=0),
                              sex = sample(c("Male", "Female"), 200, TRUE),
                              favourite_colour = sample(c("Red", "Blue", "Purple"), 200, TRUE))
example_data$age[sample(1:200, size = 15)] <- NA  # Replace 15 values with missing.
example_data$sex[sample(1:200, size = 32)] <- NA  # Replace 32 values with missing.
dup(example_data)