Tibbles

A tibble is the tidyverse's modern version of a data frame. It is a data frame — every data-frame function works on it — with a few changes that make it friendlier.

library(tibble)

people <- tibble(
  name = c("Ada", "Linus", "Grace"),
  age = c(36, 28, 45),
  age_months = age * 12
)
people

# A tibble: 3 × 3
  name    age age_months
  <chr> <dbl>      <dbl>
1 Ada      36        432
2 Linus    28        336
3 Grace    45        540

Differences from a plain data frame:

• Better printing — shows the dimensions and each column's type (<chr> text, <dbl> number, <int> integer, <lgl> logical, <fct> factor, <date> date), and only prints the first 10 rows of large tables, so your console isn't flooded.
• Columns can refer to earlier columns while creating the tibble, as age_months does.
• Stricter behaviour — no partial matching of column names, and df[, "col"] always returns a tibble, never silently a vector.

Converting

library(tibble)

df <- data.frame(x = 1:2, y = c("a", "b"))
as_tibble(df)

# A tibble: 2 × 2
      x y
  <int> <chr>
1     1 a
2     2 b

as.data.frame() converts back if a function needs a plain data frame.

Row-by-row construction

tribble() lays data out in rows, which is handy for small lookup tables:

library(tibble)

tribble(
  ~code, ~country,
  "NG",  "Nigeria",
  "PE",  "Peru"
)

# A tibble: 2 × 2
  code  country
  <chr> <chr>
1 NG    Nigeria
2 PE    Peru

glimpse(df) (from dplyr or tibble) shows a transposed overview — every column with its type and first values — ideal for wide datasets.