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Tibble

A modern re-imagining of the data frame

Install / Use

/learn @tidyverse/Tibble
About this skill

Quality Score

0/100

Supported Platforms

Universal

README

<!-- README.md is generated from README.Rmd. Please edit that file -->

tibble <img src="man/figures/logo.png" align="right" alt="Hexagonal logo for the R package ‘tibble’, styled with a sci-fi theme. The word ‘TIBBLE’ appears at the top in a futuristic font, and below it is a stylized table with colored bars resembling columns and rows, set against a starry space background." />

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Overview

A tibble, or tbl_df, is a modern reimagining of the data.frame, keeping what time has proven to be effective, and throwing out what is not. Tibbles are data.frames that are lazy and surly: they do less (i.e. they don’t change variable names or types, and don’t do partial matching) and complain more (e.g. when a variable does not exist). This forces you to confront problems earlier, typically leading to cleaner, more expressive code. Tibbles also have an enhanced print() method which makes them easier to use with large datasets containing complex objects.

If you are new to tibbles, the best place to start is the tibbles chapter in R for data science.

Installation

# The easiest way to get tibble is to install the whole tidyverse:
install.packages("tidyverse")

# Alternatively, install just tibble:
install.packages("tibble")

# Or the the development version from GitHub:
# install.packages("pak")
pak::pak("tidyverse/tibble")

Usage

library(tibble)

Create a tibble from an existing object with as_tibble():

data <- data.frame(a = 1:3, b = letters[1:3], c = Sys.Date() - 1:3)
data
#>   a b          c
#> 1 1 a 2025-06-18
#> 2 2 b 2025-06-17
#> 3 3 c 2025-06-16

as_tibble(data)
#> # A tibble: 3 × 3
#>       a b     c         
#>   <int> <chr> <date>    
#> 1     1 a     2025-06-18
#> 2     2 b     2025-06-17
#> 3     3 c     2025-06-16

This will work for reasonable inputs that are already data.frames, lists, matrices, or tables.

You can also create a new tibble from column vectors with tibble():

tibble(x = 1:5, y = 1, z = x^2 + y)
#> # A tibble: 5 × 3
#>       x     y     z
#>   <int> <dbl> <dbl>
#> 1     1     1     2
#> 2     2     1     5
#> 3     3     1    10
#> 4     4     1    17
#> 5     5     1    26

tibble() does much less than data.frame(): it never changes the type of the inputs (e.g. it keeps list columns as is), it never changes the names of variables, it only recycles inputs of length 1, and it never creates row.names(). You can read more about these features in vignette("tibble").

You can define a tibble row-by-row with tribble():

tribble(
  ~x, ~y,  ~z,
  "a", 2,  3.6,
  "b", 1,  8.5
)
#> # A tibble: 2 × 3
#>   x         y     z
#>   <chr> <dbl> <dbl>
#> 1 a         2   3.6
#> 2 b         1   8.5

Related work

The tibble print method draws inspiration from data.table, and frame. Like data.table::data.table(), tibble() doesn’t change column names and doesn’t use rownames.


Code of Conduct

Please note that the tibble project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.

View on GitHub
GitHub Stars742
CategoryDevelopment
Updated14h ago
Forks135

Languages

R

Security Score

85/100

Audited on Apr 8, 2026

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