12  Saying what something is

Conversions are always written out. Nothing here converts a column on your behalf, because a column that quietly changes what it holds is the hardest kind of mistake to find later.

R

messy |> add(word = to_text(n)) |> add(digits = characters(word))

raw	n	word	digits
ann marie	7	7	1
bob	99	99	2

Python

messy >> add(word = to_text(col.n)) >> add(digits = characters(col.word))

raw	n	word	digits
ann marie	7	7	1
bob	99	99	2

Every conversion begins to_, and nothing else does: to_number, to_whole, to_text, to_date. Ask for the characters in a number without converting it first and you are told which conversion you wanted:

R

collect(messy |> add(size = characters(n)))

Error:
! 
illegal: `characters` counts the characters in text, and this is a number. Convert it first with `to_text(...)`
  |
2 |   then add [size] as characters([n])
  |                                  ^

Python

try:
    collect(messy >> add(size = characters(col.n)))
except GodError as refusal:
    print(refusal)

illegal: `characters` counts the characters in text, and this is a number. Convert it first with `to_text(...)`
  |
2 |   then add [size] as characters([n])
  |                                  ^

12.1 The four conversions

to_text, to_number, to_whole and to_date are the whole set. Each one says what it makes rather than what it takes, so there is nothing to remember about direction.

to_number gives a number that may have a decimal point. to_whole gives one that may not, and it truncates rather than rounding, which is worth knowing before you use it on money.

R

messy |>
  add(as_text = to_text(n), rounded = to_whole(to_number(n) / 2)) |>
  pick(n, as_text, rounded)

n	as_text	rounded
7	7	4
99	99	50

Python

(messy
  >> add(as_text = to_text(col.n), rounded = to_whole(to_number(col.n) / 2))
  >> pick(col.n, col.as_text, col.rounded))

n	as_text	rounded
7	7	4
99	99	50

A conversion that cannot be made is not a silent missing value in either language. The engine underneath decides what to do with to_number("abc"), and this is one of the few places where what you get depends on where the pipeline ran.

12.2 Between two ends

between is not a conversion, and it is here because it is the other word you reach for when a column has just become a number. It asks whether a value falls in a range.

R

sales |> keep(between(revenue, 150, 400)) |> sort(revenue)

region	product	revenue	cost
West	Gadget	150	50
West	Widget	200	50
West	Gadget	300	100

Python

sales >> keep(between(col.revenue, 150, 400)) >> sort(col.revenue)

region	product	revenue	cost
West	Gadget	150	50
West	Widget	200	50
West	Gadget	300	100

Both ends count, the way SQL and dplyr both have it, so nothing here needs checking against a manual.