AE 10: Writing functions

Packages

We will use the following packages in this application exercise.

• tidyverse: For data import, wrangling, and visualization.
• nycflights13: For data sets.

library(tidyverse)
library(nycflights13)

Vector function: fizzbuzz

Fizz buzz is a children’s game that teaches about division. Players take turns counting incrementally, replacing any number divisible by three with the word “fizz” and any number divisible by five with the word “buzz”.

We will write a vector function that helps the user play fizzbuzz by calculating the correct response for any possible combination of divisors.

Function requirements

The function you write should adhere to the following requirements:

• Three arguments/inputs
  • nums: A vector of “integers”¹
  • div1: An integer value (default value is 3)
  • div2: An integer value (default value is 5)
• Output: A vector of characters
  • If the number is divisible by div1, return "Fizz".
  • If the number is divisible by div2, return "Buzz".
  • If the number is divisible by div1 and div2, return "FizzBuzz".
  • Otherwise, return the number as a character.

Tip

We have not yet covered explicit iterative operations. There is no need to use a for loop, apply() or map() functions, or any other explicit iteration. Instead, use your existing knowledge of vectorized operations and functions to write the function.

A helpful hint about modular division

%% is modular division. It returns the remainder left over after the division, rather than a floating point number.

5 / 3

[1] 1.666667

5 %% 3

[1] 2

# add code here

Test the function

Test your function to ensure it produces the correct results.

• Create a sequence of integers between 1 and 30
• Use the function to calculate the fizzbuzz response for each number and the default rules (divisors 3 and 5). Store the output as a vector object.
• Use the function to calculate the fizzbuzz response for each number and the divisors 3 and 4. Store the output as a vector object.
• Repeat your tests, but this time store the results as columns in a data frame along with the original value. Write the operation using mutate().

# test on a vector of numbers
test_nums <- 1:30

# output is a character vector
# add code here

# implement function within a data frame using mutate()
# add code here

Data frame functions

nycflights13 is an R package that contains several data tables containing information about all flights that departed from NYC (e.g. EWR, JFK and LGA) to destinations in the United States, Puerto Rico, and the American Virgin Islands) in 2013. In total it includes 336,776 flights.

Use the datasets from nycflights13 to write the following functions.

Find all flights that were cancelled (i.e. is.na(arr_time)) or delayed by more than an hour

# add code here

flights |> filter_severe()

Error in filter_severe(flights): could not find function "filter_severe"

Count the number of cancelled flights and the number of flights delayed by more than an hour

# add code here

flights |> group_by(dest) |> summarize_severe()

Error in summarize_severe(group_by(flights, dest)): could not find function "summarize_severe"

Find all flights that were cancelled or delayed by more than a user supplied number of hours

# add code here

flights |> filter_severe(hours = 2)

Error in filter_severe(flights, hours = 2): could not find function "filter_severe"

Summarize the weather to compute the minimum, mean, and maximum, of a user supplied variable

# add code here

weather |> summarize_weather(temp)

Error in summarize_weather(weather, temp): could not find function "summarize_weather"

Convert the user supplied variable that uses clock time (e.g., dep_time, arr_time, etc.) into a decimal time (i.e. hours + (minutes / 60))

Finding the quotient

%/% is integer division. It returns the quotient of the division, rather than a floating point number.

5 / 3

[1] 1.666667

5 %/% 3

[1] 1

# add code here

flights |> standardize_time(sched_dep_time)

Error in standardize_time(flights, sched_dep_time): could not find function "standardize_time"

Acknowledgments

• Data frame function exercises are drawn from R for Data Science

Footnotes

1. You can interpret this literally as an integer type in R, but here I use “integer” in a mathematical sense. The function should work for any numeric type, including integers, doubles, and complex numbers, as long as the value represents a whole number.