Introduction
This is a big concept in R.
To help make sense of the possibilities, it can be useful to consider the dimensionality of the input and output of the various functions.
Vector-in, scalar-out
We already saw functions that take in a vector and return a single, scalar-like value:
> v <- 1:5
> length(v)
#> [1] 5
> sum(v)
#> [1] 15
Many statistical functions are also in this category, such as mean().
For logical vectors, there are all() and any().
Vector-in, vector-out
Many functions in R will operate on entire vectors, often giving vector output.
This includes most of the mathematical functions:
> sq <- c(4, 9, 16, 25)
> sqrt(sq) # square root
#> [1] 2 3 4 5
This is not just concise and convenient, avoiding the need for loops, list comprehensions or recursion, which are common in other languages.
In R, vector functions often run much faster than those techniques.
For sorting a vector, there is sort() to return the values and order() to return the indices:
> v <- c("I", "am", "not", "in", "order")
> sort(v)
#> [1] "am" "I" "in" "not" "order"
> order(v)
#> [1] 2 1 4 3 5
The default is to sort in ascending order.
Specify decreasing = TRUE if necessary, or use rev() to reverse an existing vector.
v <- c("I", "am", "not", "in", "order")
sort(v, decreasing = TRUE)
#> [1] "order" "not" "in" "I" "am"
rev(1:4)
#> [1] 4 3 2 1
There are also functions to produce cumulative vector outputs, operating on the input vector left-to-right:
> cumsum(1:5)
#> [1] 1 3 6 10 15 # sums
> cumprod(1:5)
#> [1] 1 2 6 24 120 # equivalent to factorials
Multiple-vectors-in, vector-out
An extension of this concept can also be used to compare vectors.
For example, consider the pairwise-max function pmax():
> v
#> [1] 2 7 9
> w
#> [1] 3 1 5
> pmax(v, w)
#> [1] 3 7 9 # max of each pairwise comparison
Instructions
You're an avid bird watcher that keeps track of how many birds have visited your garden in the last seven days.
You have six tasks, all dealing with the numbers of birds that visited your garden.
1. Check how many birds visited today
Implement the today() function to return how many birds visited your garden today. The bird counts are ordered by day, with the first element being the count of the oldest day, and the last element being today's count.
birds_per_day <- c(2, 5, 0, 7, 4, 1)
today(birds_per_day)
# => 1
2. Increment today's count
Implement the increment_todays_count() function to increment today's count:
birds_per_day <- c(2, 5, 0, 7, 4, 1)
increment_todays_count(birds_per_day)
# => c(2, 5, 0, 7, 4, 2)
3. Check if there was a day with no visiting birds
Implement the has_day_without_birds() function that returns TRUE if there was a day at which zero birds visited the garden; otherwise, return FALSE:
birds_per_day <- c(2, 5, 0, 7, 4, 1)
has_day_without_birds(birds_per_day)
# => true
4. Calculate the number of visiting birds for the first number of days
Implement the count_for_first_days() function that returns the number of birds that have visited your garden from the start of the week, but limit the count to the specified number of days from the start of the week.
birds_per_day <- c(2, 5, 0, 7, 4, 1)
count_for_first_days(birds_per_day, 4)
# => 14
5. Calculate the number of busy days
Some days are busier that others. A busy day is one where five or more birds have visited your garden.
Implement the busy_days() function to return the number of busy days:
birds_per_day <- c(2, 5, 0, 7, 4, 1)
busy_days(birds_per_day)
# => 2
6. Calculate the running total of bird visits over the last week
You are curious how many birds in total have visited so far this week.
Calculate cumulative totals for each day.
running_total(c(7, 6, 5, 4, 3, 2, 1))
#> [1] 7 13 18 22 25 27 28
7. Sort day names by how busy they are
You suspect that bird visits are affected by patterns of nearby road traffic, so different on weekends versus weekdays.
Sort the day abbreviations in descending order of how many birds visited.
day_names <- c("Mon", "Tue", "Wed", "Thu", "Fri", "Sat", "Sun")
birds_per_day <- c(5, 2, 4, 6, 0, 9, 8)
busy_days_of_week(birds_per_day, day_names)
#> [1] "Sat" "Sun" "Thu" "Mon" "Wed" "Tue" "Fri"
Learning Exercise
