Add Rows to a Tibble

add_row() adds one or more rows of data to an existing data frame.

library(tibble)
# create a tibblestudents <- tibble(Name = c("Alice", "Bob", "Charlie"),                   Age = c(20, 22, 21),                   Enrolled = c(TRUE, FALSE, TRUE))students

Output:
# A tibble: 3 × 3
  Name      Age Enrolled
  <chr>   <dbl> <lgl>
1 Alice      20 TRUE
2 Bob        22 FALSE
3 Charlie    21 TRUE

# add two more students' information as two extra rowsstudents %>%   add_row(    Name = c("Tom", "Mary"), Age = c(28, 18), Enrolled = c(F, T))

Output:
# A tibble: 5 × 3
  Name      Age Enrolled
  <chr>   <dbl> <lgl>
1 Alice      20 TRUE
2 Bob        22 FALSE
3 Charlie    21 TRUE
4 Tom        28 FALSE
5 Mary       18 TRUE

Absent variables will create NA values.

students %>%   add_row(    # the missing column "Enrolled" is filled with 'NA' in the output    Name = c("Tom", "Mary"), Age = c(28, 18))

Output:
# A tibble: 5 × 3
  Name      Age Enrolled
  <chr>   <dbl> <lgl>
1 Alice      20 TRUE
2 Bob        22 FALSE
3 Charlie    21 TRUE
4 Tom        28 NA
5 Mary       18 NA

Use .before (or .after) to specify the first tibble’s row index where the second tibble should be inserted. (These arguments are also available in add_column() and mutate() to specify new columns’ position.)

students %>%   add_row(    Name = c("Tom", "Mary"), Age = c(28, 18),     # insert the 2nd tibble before the 1st tibble's 3rd row    .before = 3)

Output:
# A tibble: 5 × 3
  Name      Age Enrolled
  <chr>   <dbl> <lgl>
1 Alice      20 TRUE
2 Bob        22 FALSE
3 Tom        28 NA
4 Mary       18 NA
5 Charlie    21 TRUE

You can directly combine two tibbles by rows.

# create a second tibble to combine by rowsmore_students <- tibble(Name = c("Tom", "Jack", "Clement"),                         Age = c(28, 22, 34),                         Enrolled = c(F, F, T))
# combine the two tibblesstudents %>% add_row(more_students, .before = 3)

Output:
# A tibble: 6 × 3
  Name      Age Enrolled
  <chr>   <dbl> <lgl>
1 Alice      20 TRUE
2 Bob        22 FALSE
3 Tom        28 FALSE
4 Jack       22 FALSE
5 Clement    34 TRUE
6 Charlie    21 TRUE

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