04-workflow_code_style.Rmd

# Workflow: code style

> "Good coding style is like correct punctuation: you can \ \  manage without it, butitsuremakesthingseasiertoread." — Tidyverse Style Guide

**Learning objectives:**
  
-   Use the styler package to apply style rules.
-   Select good variable names.
-   Appropriately utilize spaces ` ` between mathematical operators.
-   Apply the `|>` operator to make our code more readable.

## Use styler {-}

{styler} 📦 by Lorenz Walthert helps quickly apply styles

-   Install with `install.packages("styler")`
-   Use via RStudio’s command palette
    -   **Cmd/Ctrl + Shift + P** to open pallette
    -   Type **“styler”** to see all styler shortcuts

## Names {-}

Names should use only:

1. lowercase letters
2. numbers 
3. underscore

## Use snake_case for names {-}

`snake_case` = preferred style

```{r eval=FALSE}
# Strive for:
short_flights <- flights |> filter(air_time < 60)

# Avoid:
SHORTFLIGHTS <- flights |> filter(air_time < 60)
```

## Names should be descriptive {-}

-   Good: Long, descriptive names
    -   Easy to understand
-   Bad: Concise names
    -   Fast to type, but RStudio autocompletes long names anyway

Be consistent with related names!


## Spaces {-}

Spaces around:

-   Math operators (except `^`)
-   Assignment operator (`<-`)

```{r eval=FALSE}
# Strive for
z <- (a + b)^2 / d

# Avoid
z<-( a + b ) ^ 2/d
```

## Spaces in function calls {-}

-   No spaces inside/outside parentheses
-   Spaces after commas (like regular English)

```{r eval=FALSE}
# Strive for
mean(x, na.rm = TRUE)

# Avoid
mean (x ,na.rm=TRUE )
```

## Use extra spaces for alignment {-}

```{r eval=FALSE}
flights |> 
  mutate(
    speed      = air_time / distance,
    dep_hour   = dep_time %/% 100,
    dep_minute = dep_time %%  100
  )
```


## Pipes: Spacing {-}

```{r eval=FALSE}
# Strive for space before |>, end line with |>
flights |> 
  filter(!is.na(arr_delay), !is.na(tailnum)) |> 
  count(dest)

# Avoid
flights|>filter(!is.na(arr_delay), !is.na(tailnum))|>count(dest)
```

Easier to:

1. add new steps
2. rearrange existing steps
3. modify elements within a step
4. to get a 50,000 ft view by skimming the verbs on the left-hand side

## Pipes: Newlines {-}

-   Put named arguments on newline
-   Put unnamed arguments on one line if they fit

```{r eval=FALSE}
# Strive for
flights |>  
  group_by(tailnum) |> 
  summarize(
    delay = mean(arr_delay, na.rm = TRUE),
    n = n()
  )

# Avoid
flights |>
  group_by(
    tailnum
  ) |> 
  summarize(delay = mean(arr_delay, na.rm = TRUE), n = n())
```

## Pipes: Indentation {-}

```{r eval=FALSE}
# Strive for 
flights |>  
  group_by(tailnum) |> 
  summarize(
    delay = mean(arr_delay, na.rm = TRUE),
    n = n()
  )

# Avoid
flights|>
  group_by(tailnum) |> 
  summarize(
             delay = mean(arr_delay, na.rm = TRUE), 
             n = n()
           )

flights|>
  group_by(tailnum) |> 
  summarize(
  delay = mean(arr_delay, na.rm = TRUE), 
  n = n()
  )
```

## Pipes: Breaking the rules {-}

OK to shirk some rules to fit on one line 

```{r eval = FALSE}
# This fits compactly on one line
df |> mutate(y = x + 1)

# While this takes up 4x as many lines, it's easily extended to 
# more variables and more steps in the future
df |> 
  mutate(
    y = x + 1
  )
```

## Pipe length {-}

-   Limit to 10-15 lines
-   Break up into smaller sub-tasks
    -   Give each task an informative name

## ggplot2 spacing {-}

Same rules for `+` as for `|>`

```{r eval=FALSE}
flights |> 
  group_by(month) |> 
  summarize(
    delay = mean(arr_delay, na.rm = TRUE)
  ) |> 
  ggplot(aes(month, delay)) +
  geom_point() + 
  geom_line()
```

## ggplot2 spacing 2 {-}

```{r eval=FALSE}
flights |> 
  group_by(dest) |> 
  summarize(
    distance = mean(distance),
    speed = mean(air_time / distance, na.rm = TRUE)
  ) |> 
  ggplot(aes(distance, speed)) +
  geom_smooth(
    method = "loess",
    span = 0.5,
    se = FALSE, 
    color = "white", 
    size = 4
  ) +
  geom_point()
```

## Sectioning comments {-}

Use sectioning comments (**Cmd/Ctrl + Shift + R**) to break up long files

```{r load-data-comment}
 # Load data --------------------------------------

 # Plot data --------------------------------------
```


## Exercises {-}

1. Restyle the following pipelines following the guidelines above.

```{r exercises, eval=FALSE}
flights|>filter(dest=="IAH")|>group_by(year,month,day)|>summarize(n=n(),
delay=mean(arr_delay,na.rm=TRUE))|>filter(n>10)

flights|>filter(carrier=="UA",dest%in%c("IAH","HOU"),sched_dep_time>
0900,sched_arr_time<2000)|>group_by(flight)|>summarize(delay=mean(
arr_delay,na.rm=TRUE),cancelled=sum(is.na(arr_delay)),n=n())|>filter(n>10)
```

Solution

```{r exercises solution, eval=FALSE}
flights |> # space before/ after pipe and the last thing on a line
  filter(dest == "IAH") |> # indent twice, space between operators
  group_by(year, month, day) |> # space after comma
  summarize( # nam
    n     = n(), # add spaces so that all the = line up
    delay = mean(arr_delay, na.rm = TRUE)
    ) |> 
  filter(n > 10)


flights |> 
  filter(
         carrier        == "UA", 
         dest           %in% c("IAH","HOU"),
         sched_dep_time > 900,
         sched_arr_time < 2000
         ) |> 
  group_by(flight) |> 
  summarize(
            delay = mean(arr_delay, na.rm=TRUE),
            cancelled = sum(is.na(arr_delay)),
            n = n()
            ) |> 
  filter(n > 10)
```


## Meeting Videos {-}

### Cohort 5 {-}

`r knitr::include_url("https://www.youtube.com/embed/JW1DilkJ3-0")`

<details>
  <summary> Meeting chat log </summary>
  
```
00:12:57	Jon Harmon (jonthegeek):	https://en.wikipedia.org/wiki/The_Treachery_of_Images
00:16:47	Jon Harmon (jonthegeek):	https://cran.r-project.org/package=magrittr
00:20:53	Jon Harmon (jonthegeek):	https://smile.amazon.com/Mathematical-Notation-Guide-Engineers-Scientists/dp/1466230525/ref=sr_1_2?keywords=Mathematical+Notation&qid=1641665745&sr=8-2
00:22:16	Jon Harmon (jonthegeek):	|>
00:23:04	Ryan Metcalf:	And, is this the “Walrus” operator? `:=`
00:23:19	Jon Harmon (jonthegeek):	%>%
00:23:28	Jon Harmon (jonthegeek):	|>
00:24:14	Jon Harmon (jonthegeek):	a |> f()
00:24:23	Jon Harmon (jonthegeek):	f(a)
00:41:01	Becki R. (she/her):	Ryan, can you put a link to the video in the chat?
00:42:27	Jon Harmon (jonthegeek):	a %>% myfun(a = 10, b = .)
00:42:59	Jon Harmon (jonthegeek):	a |> myfun(a = 10, b = .)
00:43:00	Ryan Metcalf:	Jenny Bryant Youtube Video: https://youtu.be/4MfUCX_KpdE
00:43:07	Becki R. (she/her):	Thanks
00:44:57	Jon Harmon (jonthegeek):	a %>% myfun(arg1 = 10, arg2 = .)
00:45:48	Jon Harmon (jonthegeek):	a %>% myfun(arg2 = .)
00:47:40	Federica Gazzelloni:	https://www.r-bloggers.com/2021/05/the-new-r-pipe/
00:50:00	Jon Harmon (jonthegeek):	https://twitter.com/hadleywickham/status/1359852563726819332
00:51:58	Federica Gazzelloni:	https://community.rstudio.com/t/why-is-r-core-creating-a-new-pipe-operator/89020
01:03:35	Federica Gazzelloni:	you can use: set.seed(123) with some numbers inside to recall the same random set
01:03:56	Federica Gazzelloni:	set.seed(123)
01:04:06	Federica Gazzelloni:	rnorm(100)…
01:08:46	Jon Harmon (jonthegeek):	a <- a %>%
a %<>%
01:10:41	Jon Harmon (jonthegeek):	mtcars <- head(mtcars)
01:10:50	Jon Harmon (jonthegeek):	mtcars <- mtcars %>% head()
01:10:57	Jon Harmon (jonthegeek):	mtcars %<>% head()
01:13:56	Becki R. (she/her):	Where is the signup list for presenting chapters?
```
</details>

### Cohort 6 {-}

`r knitr::include_url("https://www.youtube.com/embed/jwnQkHtUiOY")`

<details>
  <summary> Meeting chat log </summary>
  
```
00:09:32	Marielena Soilemezidi:	=
00:26:49	Daniel Adereti:	Yes, I agree. It appears the dot allows to insert any argument
00:52:38	Daniel Adereti:	Thanks Marielena, also share Shannon's thoughts, pipes had always been taught like a must use operator, glad to see it is meant to be selective
00:55:20	Daniel Adereti:	works for me too, it is quite a large chapter
00:55:39	Daniel Adereti:	Sorry, my mic seems problematic, hence my typing
```
</details>

### Cohort 7 {-}

`r knitr::include_url("https://www.youtube.com/embed/wlYh2KewQcI")`

<details>
  <summary> Meeting chat log </summary>
```
00:21:34	Oluwafemi Oyedele:	https://towardsdatascience.com/understanding-the-native-r-pipe-98dea6d8b61b
00:22:15	Christine (she/her):	Thanks, Oluwafemi!
00:22:51	Oluwafemi Oyedele:	https://stackoverflow.com/questions/67633022/what-are-the-differences-between-rs-new-native-pipe-and-the-magrittr-pipe
00:37:22	Oluwafemi Oyedele:	https://github.com/daranzolin/ViewPipeSteps
00:49:42	timnewby:	https://towardsdatascience.com/an-introduction-to-the-pipe-in-r-823090760d64 Talks a bit about when pipes work well and when they might not
00:50:13	Oluwafemi Oyedele:	http://127.0.0.1:22120/session/Rvig.11e05a207606.html
01:03:47	Dolleen Osundwa:	thank you Kumar
```
</details>

`r knitr::include_url("https://www.youtube.com/embed/LHYUEAXaYoM")`


### Cohort 8 {-}

`r knitr::include_url("https://www.youtube.com/embed/uEYKR3xs4Y0")`

`r knitr::include_url("https://www.youtube.com/embed/MvzrbyCuFLw")`