Use consistent indentation

episodes/02-func-R.Rmd

@@ -33,8 +33,8 @@ You can write your own functions in order to make repetitive operations using a
 
 ```{r, include=FALSE}
 my_function <- function(input) {
-# perform action and produce output
-return(output) # return output value
+  # perform action and produce output
+  return(output) # return output value
 }
 ```
 
@@ -177,10 +177,10 @@ Write a function called `edges` that returns a vector made up of just the first
 
 ```{r, echo=-1}
 edges <- function(v) {
-   first <- v[1]
-   last <- v[length(v)]
-   answer <- c(first, last)
-   return(answer)
+  first <- v[1]
+  last <- v[length(v)]
+  answer <- c(first, last)
+  return(answer)
 }
 dry_principle <- c("Don't", "repeat", "yourself", "or", "others")
 edges(dry_principle)

episodes/04-cond.Rmd

@@ -175,7 +175,7 @@ Two vertical bars, `||`, symbolize "or".
 
 ```{r}
 if (1 > 0 && -1 > 0) {
-    print("both parts are true")
+  print("both parts are true")
 } else {
   print("at least one part is not true")
 }
@@ -185,7 +185,7 @@ while `||` is true if either part is true:
 
 ```{r}
 if (1 > 0 || -1 > 0) {
-    print("at least one part is true")
+  print("at least one part is true")
 } else {
   print("neither part is true")
 }
@@ -239,11 +239,11 @@ To do this you'll use the R functions `boxplot` and `stripchart`.
 
 ```{r using-conditions-01, echo=-1}
 plot_dist <- function(x, threshold) {
-   if (length(x) > threshold) {
-       boxplot(x)
-   } else {
-       stripchart(x)
-   }
+  if (length(x) > threshold) {
+    boxplot(x)
+  } else {
+    stripchart(x)
+  }
 }
 dat <- read.csv("data/inflammation-01.csv", header = FALSE)
 plot_dist(dat[, 10], threshold = 10)     # day (column) 10
@@ -285,11 +285,11 @@ A histogram is made with the `hist` command in R.
 ```{r conditional-challenge-hist, fig.alt=c("A grey unlabeled boxplot chart showing the distrubution values between 2 and 9 with a mean at 6.", "A grey unlabeled histogram showing bimodal distribution between 2 and 9 with peaks at 2 and 6.", "A mostly blank strip chart showing five points at 3, 4, 6, 7, and 9"), echo=-1}
 plot_dist <- function(x, threshold, use_boxplot = TRUE) {
    if (length(x) > threshold && use_boxplot) {
-       boxplot(x)
+    boxplot(x)
    } else if (length(x) > threshold && !use_boxplot) {
-       hist(x)
+    hist(x)
    } else {
-       stripchart(x)
+    stripchart(x)
    }
 }
 dat <- read.csv("data/inflammation-01.csv", header = FALSE)

episodes/11-supp-read-write-csv.Rmd

@@ -152,8 +152,8 @@ carSpeeds <- read.csv(file = 'data/car-speeds.csv')
 # Replace 'Blue' with 'Green' in cars$Color without using the stringsAsFactors
 # or as.is arguments
 carSpeeds$Color <- ifelse(as.character(carSpeeds$Color) == 'Blue',
-                         'Green',
-                         as.character(carSpeeds$Color))
+                          'Green',
+                          as.character(carSpeeds$Color))
 # Convert colors back to factors
 carSpeeds$Color <- as.factor(carSpeeds$Color)
 ```
@@ -167,11 +167,12 @@ carSpeeds <- read.csv(file = 'data/car-speeds.csv')
 
 # Replace 'Blue' with 'Green' in cars$Color without using the stringsAsFactors
 # or as.is arguments
-carSpeeds$Color <-
-  ifelse(as.character(carSpeeds$Color) == 'Blue',
+carSpeeds$Color <- ifelse(
+  as.character(carSpeeds$Color) == 'Blue',
   'Green',
-  as.character(carSpeeds$Color))
-  
+  as.character(carSpeeds$Color)
+)
+
 # Convert colors back to factors
 carSpeeds$Color <- as.factor(carSpeeds$Color)
 ```
@@ -197,7 +198,7 @@ carSpeeds <- read.csv(
   stringsAsFactors = FALSE, 
   strip.white = TRUE,
   sep = ','
-  )
+)
 
 unique(carSpeeds$Color)
 ```

episodes/13-supp-data-structures.Rmd

@@ -302,7 +302,8 @@ Consider the following matrix:
 FOURS <- matrix(
   c(4, 4, 4, 4),
   nrow = 2,
-  ncol = 2)
+  ncol = 2
+)
 ```
 
 Given that `typeof(FOURS[1])` returns `"double"`, what would you expect