Augmented vectors

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1. What does hms::hms(3600) return? How does it print? What primitive type is the augmented vector built on top of? What attributes does it use?

x <- hms::hms(3600)
class(x)

[1] "hms"      "difftime"

x

01:00:00

hms::hms returns an object of class class(x), and prints the time in %H:%M:%S format.

The primitive type is a double

typeof(x)

[1] "double"

The attributes is uses are “units” and “class”.

attributes(x)

$units
[1] "secs"

$class
[1] "hms"      "difftime"

2. Try and make a tibble that has columns with different lengths. What happens?

If I try to create a tibble with a scalar and column of a different length there are no issues, and the scalar is repeated to the length of the longer vector.

tibble(x = 1, y = 1:5)

However, if I try to create a tibble with two vectors of different lengths (other than one), the tibble function throws an error.

# tibble(x = 1:3, y = 1:4)
#> Error: Tibble columns must have consistent lengths, only values of length one are recycled: * Length 3: Column `x` * Length 4: Column `y`

3. Based on the definition above, is it OK to have a list as a column of a tibble?

If I didn’t already know the answer, what I would do is try it out. From the above, the error message was about vectors having different lengths. But there is nothing that prevents a tibble from having vectors of different types: doubles, character, integers, logical, factor, date. The later are still atomic, but they have additional attributes. So, maybe there won’t be an issue with a list vector as long as it is the same length.

tibble(x = 1:3, y = list("a", 1, list(1:3)))

It works! I even used a list with heterogeneous types and there wasn’t an issue. In following sections we’ll see that list vectors can be very useful: for example, when processing many different models.