Computer programming as a form of problem solving
library(tidyverse)
library(palmerpenguins)
](/media/xkcd_computer_problems_hu55ba9557378da78e502c51283e783c6a_101369_c0a2af25f1a550fc68480a73f80eecc9.webp)
Computers are not mind-reading machines. They are very efficient at certain tasks, and can perform calculations thousands of times faster than any human. But they are also very dumb: they can only do what you tell them to do. If you are not explicit about what you want the computer to do, or you misspeak and tell the computer to do the wrong thing, it will not correct you.
In order to translate your goal for the program into clear instructions for the computer, you need to break the problem down into a set of smaller, discrete chunks that can be followed by the computer (and also by yourself/other humans).
Decomposing problems using penguins
library(tidyverse)
library(palmerpenguins)
glimpse(x = penguins)
## Rows: 344
## Columns: 8
## $ species <fct> Adelie, Adelie, Adelie, Adelie, Adelie, Adelie, Adel…
## $ island <fct> Torgersen, Torgersen, Torgersen, Torgersen, Torgerse…
## $ bill_length_mm <dbl> 39.1, 39.5, 40.3, NA, 36.7, 39.3, 38.9, 39.2, 34.1, …
## $ bill_depth_mm <dbl> 18.7, 17.4, 18.0, NA, 19.3, 20.6, 17.8, 19.6, 18.1, …
## $ flipper_length_mm <int> 181, 186, 195, NA, 193, 190, 181, 195, 193, 190, 186…
## $ body_mass_g <int> 3750, 3800, 3250, NA, 3450, 3650, 3625, 4675, 3475, …
## $ sex <fct> male, female, female, NA, female, male, female, male…
## $ year <int> 2007, 2007, 2007, 2007, 2007, 2007, 2007, 2007, 2007…
The penguins dataset includes measurements for penguin species from islands in the Palmer Archipelago. Let’s answer the following questions by decomposing the problem into a series of discrete steps we can tell R to follow.
What is the average body mass of an Adelie penguin?
Think about what we need to have the computer do to answer this question:
- First we need to identify the input, or the data we’re going to analyze.
- Next we need to select only the observations which are Adelie penguins.
- Finally we need to calculate the average value, or mean, of
body_mass_g.
Here’s how we tell the computer to do this:
data("penguins")
penguins_adelie <- filter(.data = penguins, species == "Adelie")
summarize(.data = penguins_adelie, avg_mass = mean(body_mass_g, na.rm = TRUE))
## # A tibble: 1 × 1
## avg_mass
## <dbl>
## 1 3701.
The first line of code copies the penguins data frame from the hard drive into memory so we can actively work with it. The second line create a new data frame called penguins_adelie that only contains the observations in penguins which are Adelie penguins. The third line summarizes the new data frame and calculates the mean value for the body_mass_g variable.
What is the average body mass of a penguin for each species?
Exercise: decompose the question into a discrete set of tasks to complete using R.
Click for the solution
- First we need to identify the input, or the data we’re going to analyze.
- Next we need to group the observations together by their value for
species, so we can make separate calculations for each category. - Finally we need to calculate the average value, or mean, of body mass for penguins of each species.
Here’s how we tell the computer to do this:
data("penguins")
penguins_species <- group_by(.data = penguins, species)
summarize(.data = penguins_species, avg_mass = mean(body_mass_g, na.rm = TRUE))
## # A tibble: 3 × 2
## species avg_mass
## <fct> <dbl>
## 1 Adelie 3701.
## 2 Chinstrap 3733.
## 3 Gentoo 5076.
What is the average bill length and body mass for each Adelie penguin by sex?
Exercise: decompose the question into a discrete set of tasks to complete using R.
Click for the solution
- Use
penguinsas the input - Filter
penguinsto only keep observations where the species is “Adelie”. - Group the filtered
penguinsdata frame by sex. - Summarize the grouped and filtered
penguinsdata frame by calculating the average bill length and body mass.
data("penguins")
penguins_adelie <- filter(.data = penguins, species == "Adelie")
penguins_adelie_sex <- group_by(.data = penguins_adelie, sex)
summarize(
.data = penguins_adelie_sex,
bill = mean(bill_length_mm, na.rm = TRUE),
avg_mass = mean(body_mass_g, na.rm = TRUE)
)
## # A tibble: 3 × 3
## sex bill avg_mass
## <fct> <dbl> <dbl>
## 1 female 37.3 3369.
## 2 male 40.4 4043.
## 3 <NA> 37.8 3540
References
- Artwork by Allison Horst
Session Info
sessioninfo::session_info()
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## language (EN)
## collate en_US.UTF-8
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