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Find duplicate rows based on specific columns

Source: R/dta_duplicates.R
dta_duplicates.Rd

dta_duplicates() identifies and returns duplicate rows in a dataframe or tibble, based on the specified columns.

Usage

dta_duplicates(dat, .columns = names(dat))

Arguments

dat

A dataframe or tibble.

.columns

A set of column names to check for duplicates. Defaults to all columns.

Value

A dataframe or tibble containing only the duplicate rows based on the specified column(s).

Examples

# Create a data frame for demonstration

df <- data.frame(
  id = c(14, 20, 12, 32, 14, 23, 15, 12, 30, 14),
  name = c(
   "Mary", "Mark", "Faith", "David", "Mary", "Daniel", "Christine",
   "Johnson", "Elizabeth", "Mary"
  ),
  age = c(21, 18, 25, 17, 21, 24, 21, 19, 20, 21)
)
dta_gtable(df)



  
id
      name
      age
    
14
Mary
21
20
Mark
18
12
Faith
25
32
David
17
14
Mary
21
23
Daniel
24
15
Christine
21
12
Johnson
19
30
Elizabeth
20
14
Mary
21

# return duplicated rows by all the columns in the data frame

result <- dta_duplicates(df)
dta_gtable(result)



  
id
      name
      age
    
14
Mary
21
14
Mary
21
14
Mary
21

# return duplicated rows by the column `id`

result2 <- dta_duplicates(df, .columns = id)
dta_gtable(result2)



  
id
      name
      age
    
14
Mary
21
12
Faith
25
14
Mary
21
12
Johnson
19
14
Mary
21

# A second demo data frame

df2 <- data.frame(
 gender = c(
   "Male", "Female", "Female", "Male", "Male", "Female", "Male", "Female"
 ),
 education = c(
   "Masters", "Bachelor", "Bachelor", "Masters", "Doctorate", "Masters",
   "Bachelors", "Masters"
 ),
 age = c(25, 30, 30, 25, 40, 25, 40, 25)
)
dta_gtable(df2)



  
gender
      education
      age
    
Male
Masters
25
Female
Bachelor
30
Female
Bachelor
30
Male
Masters
25
Male
Doctorate
40
Female
Masters
25
Male
Bachelors
40
Female
Masters
25

# return duplicated rows based to the columns 'gender' and 'education'

result2 <- dta_duplicates(df2, .columns = c(gender, education))
dta_gtable(result2)



  
gender
      education
      age
    
Male
Masters
25
Female
Bachelor
30
Female
Bachelor
30
Male
Masters
25
Female
Masters
25
Female
Masters
25