Pipes and functions in R

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.title[
# Pipes and functions in R
]
.author[
### INFO 5940 <br /> Cornell University
]

---

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# Using the pipe operator

---

> Using the [`penguins`](https://github.com/allisonhorst/palmerpenguins) dataset, calculate the average body mass for Adelie penguins on different islands.

1. Filter `penguins` to only keep observations where the species is  "Adelie"
1. Group the filtered `penguins` data frame by island
1. Summarize the grouped and filtered `penguins` data frame by calculating the average body mass

---

## Intermediate steps

```r
penguins_1 <- filter(penguins, species == "Adelie")
penguins_2 <- group_by(penguins_1, island)
(penguins_3 <- summarize(penguins_2, body_mass = mean(body_mass_g, na.rm = TRUE)))
```

```
## # A tibble: 3 × 2
##   island    body_mass
##   <fct>         <dbl>
## 1 Biscoe        3710.
## 2 Dream         3688.
## 3 Torgersen     3706.
```

---

## Overwrite the original

```r
penguins <- filter(penguins, species == "Adelie")
penguins <- group_by(penguins, island)
(penguins <- summarize(penguins, body_mass = mean(body_mass_g, na.rm = TRUE)))
```

```
## # A tibble: 3 × 2
##   island    body_mass
##   <fct>         <dbl>
## 1 Biscoe        3710.
## 2 Dream         3688.
## 3 Torgersen     3706.
```

---

## Function composition

```r
summarize(
  group_by(
    filter(
      penguins,
      species == "Adelie"
    ),
    island
  ),
  body_mass = mean(body_mass_g, na.rm = TRUE)
)
```

```
## # A tibble: 3 × 2
##   island    body_mass
##   <fct>         <dbl>
## 1 Biscoe        3710.
## 2 Dream         3688.
## 3 Torgersen     3706.
```

---

## Function composition

```r
summarize(group_by(filter(penguins, species == "Adelie"), island), body_mass = mean(body_mass_g, na.rm = TRUE))
```

```
## # A tibble: 3 × 2
##   island    body_mass
##   <fct>         <dbl>
## 1 Biscoe        3710.
## 2 Dream         3688.
## 3 Torgersen     3706.
```

---

## Piping

```r
penguins %>%
  filter(species == "Adelie") %>%
  group_by(island) %>%
  summarize(body_mass = mean(body_mass_g, na.rm = TRUE))
```

```
## # A tibble: 3 × 2
##   island    body_mass
##   <fct>         <dbl>
## 1 Biscoe        3710.
## 2 Dream         3688.
## 3 Torgersen     3706.
```

---

<img src="../../../../../../../../img/Pipe_baking_magrittr_backAssign.gif" width="50%" style="display: block; margin: auto;" />

.footnote[Source: [Arthur Welle](https://github.com/arthurwelle/VIS/blob/master/Pipe_Cake/Pipe_baking_magrittr_backAssign.gif)]

---

class: inverse, middle

# Functions

---

## Functions

* Easy to reuse
* Self-documenting
* Easy-ier to debug

--

.task[

If you have copied and pasted a block of code more than twice, convert it to a function

]

---

## Function components

* Name
* Arguments
* Body

---

## Rescale function

```r
rescale01 <- function(x) {
  rng <- range(x, na.rm = TRUE)
  (x - rng[1]) / (rng[2] - rng[1])
}

rescale01(c(0, 5, 10))
## [1] 0.0 0.5 1.0
rescale01(c(-10, 0, 10))
## [1] 0.0 0.5 1.0
rescale01(c(1, 2, 3, NA, 5))
## [1] 0.00 0.25 0.50   NA 1.00
```

* Name
* Arguments
* Body

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---

## What is that?

```r
pythagorean <- function(a, b){
  hypotenuse <- sqrt(a^2 + b^2)
  return(hypotenuse)
}
```

* Name
* Arguments
* Body

<div class="countdown" id="timer_633da548" style="right:0;bottom:0;" data-warnwhen="0">
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---

## How to use a function

.small[

```r
# print the output of the function
pythagorean(a = 3, b = 4)
```

```
## [1] 5
```

```r
# save the output as a new object
(tri_c <- pythagorean(a = 3, b = 4))
```

```
## [1] 5
```

```r
# what happens to the hypotenuse from inside the function?
pythagorean(a = 3, b = 4)
```

```
## [1] 5
```

```r
hypotenuse
```

```
## Error in eval(expr, envir, enclos): object 'hypotenuse' not found
```
]

---

## Write a function

<img src="https://media.giphy.com/media/nVLg9q1hL6yre/giphy.gif" width="60%" style="display: block; margin: auto;" />

<div class="countdown" id="timer_633da681" style="right:0;bottom:0;" data-warnwhen="0">
<code class="countdown-time"><span class="countdown-digits minutes">10</span><span class="countdown-digits colon">:</span><span class="countdown-digits seconds">00</span></code>
</div>

---

class: inverse, middle

# Conditional execution

---

## Conditional execution

```r
if (condition) {
  # code executed when condition is TRUE
} else {
  # code executed when condition is FALSE
}
```

---

## Conditional execution

```r
if (this) {
  # do that
} else if (that) {
  # do something else
} else {
  # do something completely different
}
```

---

## Conditional execution and `cut()`

```r
penguins %>%
  select(body_mass_g) %>%
  mutate(
    body_mass_g_autobin = cut(body_mass_g, breaks = 5),
    body_mass_g_manbin = cut(body_mass_g,
      breaks = c(2700, 3600, 4500, 5400, 6300),
      labels = c("Small", "Medium", "Large", "Huge")
    )
  )
```

```
## # A tibble: 344 × 3
##    body_mass_g body_mass_g_autobin body_mass_g_manbin
##          <int> <fct>               <fct>             
##  1        3750 (3.42e+03,4.14e+03] Medium            
##  2        3800 (3.42e+03,4.14e+03] Medium            
##  3        3250 (2.7e+03,3.42e+03]  Small             
##  4          NA <NA>                <NA>              
##  5        3450 (3.42e+03,4.14e+03] Small             
##  6        3650 (3.42e+03,4.14e+03] Medium            
##  7        3625 (3.42e+03,4.14e+03] Medium            
##  8        4675 (4.14e+03,4.86e+03] Large             
##  9        3475 (3.42e+03,4.14e+03] Small             
## 10        4250 (4.14e+03,4.86e+03] Medium            
## # … with 334 more rows
```

---

## `if()` versus `if_else()`

```r
library(rcis)
data("gun_deaths")

(educ <- select(gun_deaths, education))
```

```
## # A tibble: 100,798 × 1
##    education   
##    <fct>       
##  1 BA+         
##  2 Some college
##  3 BA+         
##  4 BA+         
##  5 HS/GED      
##  6 Less than HS
##  7 HS/GED      
##  8 HS/GED      
##  9 Some college
## 10 <NA>        
## # … with 100,788 more rows
```

---

## `if()` versus `if_else()`

```r
educ_if <- educ %>%
  mutate(hsPlus = if(education == "Less than HS"){
    "Less than HS"
  } else{
    "HS+"
  })
```

```
## Error in `mutate()`:
## ! Problem while computing `hsPlus = if (...) NULL`.
## Caused by error in `if (education == "Less than HS") ...`:
## ! the condition has length > 1
```

---

## `if()` versus `if_else()`

```r
(educ_ifelse <- educ %>%
  mutate(hsPlus = if_else(
    condition = education == "Less than HS",
    true = "Less than HS",
    false = "HS+"
  )))
## # A tibble: 100,798 × 2
##    education    hsPlus      
##    <fct>        <chr>       
##  1 BA+          HS+         
##  2 Some college HS+         
##  3 BA+          HS+         
##  4 BA+          HS+         
##  5 HS/GED       HS+         
##  6 Less than HS Less than HS
##  7 HS/GED       HS+         
##  8 HS/GED       HS+         
##  9 Some college HS+         
## 10 <NA>         <NA>        
## # … with 100,788 more rows
```

---

## `if()` versus `if_else()`

```r
count(educ_ifelse, hsPlus)
## # A tibble: 3 × 2
##   hsPlus           n
##   <chr>        <int>
## 1 HS+          77553
## 2 Less than HS 21823
## 3 <NA>          1422
```

---

## Playing children's games

<img src="https://media.giphy.com/media/l2JJJJUUQBvUspZV6/giphy.gif" width="80%" style="display: block; margin: auto;" />

<div class="countdown" id="timer_633da3df" style="right:0;bottom:0;" data-warnwhen="0">
<code class="countdown-time"><span class="countdown-digits minutes">10</span><span class="countdown-digits colon">:</span><span class="countdown-digits seconds">00</span></code>
</div>