Silvia Canelón

Our illustrated penguins have reached the tibble package! The photo backdrop is a snowy Antarctic wonderland featuring a Gentoo penguin with outstretched flippers

Photo by James Eades on Unsplash

tibble: info

A `tibble` is much like the `dataframe` in base R,
but optimized for use in the Tidyverse.

tibble: exercise

Let’s take a look at the differences!

# try each of these commands in the console and see if 
# you can spot the differences!

as_tibble(penguins)
as.data.frame(penguins)

as_tibble(penguins) |> head(4)

# A tibble: 4 × 8
  species island    bill_length_mm bill_depth_mm flipper_length_mm body_mass_g
  <fct>   <fct>              <dbl>         <dbl>             <int>       <int>
1 Adelie  Torgersen           39.1          18.7               181        3750
2 Adelie  Torgersen           39.5          17.4               186        3800
3 Adelie  Torgersen           40.3          18                 195        3250
4 Adelie  Torgersen           NA            NA                  NA          NA
# ℹ 2 more variables: sex <fct>, year <int>

as.data.frame(penguins) |> head(4)

  species    island bill_length_mm bill_depth_mm flipper_length_mm body_mass_g
1  Adelie Torgersen           39.1          18.7               181        3750
2  Adelie Torgersen           39.5          17.4               186        3800
3  Adelie Torgersen           40.3          18.0               195        3250
4  Adelie Torgersen             NA            NA                NA          NA
     sex year
1   male 2007
2 female 2007
3 female 2007
4   <NA> 2007

What differences do you see?

You might see a tibble prints:

variable classes
only 10 rows
only as many columns as can fit on the screen
NAs are highlighted in console so they’re easy to spot (font highlighting and styling in tibble)

Not so much a concern in an R Markdown file, but noticeable in the console

This enhanced print method makes it easier to work with large datasets

There are a couple of other main differences, namely in subsetting and recycling

Check them out in vignette("tibble")

vignette("tibble")

tibble: info

A `tibble` is much like the `dataframe` in base R,
but optimized for use in the Tidyverse.

R for Data Science: Ch 10 Tibbles

Package documentation: https://tibble.tidyverse.org

tibble: exercise

Let’s take a look at the differences!

What differences do you see?