clarify callout box on type conversion for sliced rows of data frames…

…; add info to instructor notes

_episodes_rmd/01-starting-with-data.Rmd

@@ -288,24 +288,6 @@ patient_1 <- dat[1, ]
 max(patient_1)
 ```
 
-> ## Forcing Conversion
->
-> The code above may give you an error in some R installations,
-> since R does not automatically convert a sliced row of a `data.frame` to a vector.
-> (Confusingly, sliced columns are automatically converted.)
-> If this happens, you can use the `as.numeric` command to convert the row of data to a numeric vector:
->
-> `patient_1 <- as.numeric(dat[1, ])`
->
-> `max(patient_1)`
->
-> You can also check the `class` of each object:
->
-> `class(dat[1, ])`
->
-> `class(as.numeric(dat[1, ]))`
-{: .callout}
-
 We don't actually need to store the row in a variable of its own.
 Instead, we can combine the selection and the function call:
 
@@ -327,6 +309,17 @@ median(dat[, 7])
 sd(dat[, 7])
 ```
 
+> ## Forcing Conversion
+>
+> Note that R may return an error when you attempt to perform similar calculations on 
+> sliced *rows* of data frames. This is because some functions in R automatically convert 
+> the object type to a numeric vector, while others do not (e.g. `max(dat[1, ])` works as 
+> expected, while `mean(dat[1, ])` returns an error). You can fix this by including an 
+> explicit call to `as.numeric()`, e.g. `mean(as.numeric(dat[1, ]))`. By contrast, 
+> calculations on sliced *columns* always work as expected, since columns of data frames 
+> are already defined as vectors.
+{: .callout}
+
 What if we need the maximum inflammation for all patients, or the average for each day?
 As the diagram below shows, we want to perform the operation across a margin of the data frame:
 

_extras/guide.md

@@ -105,6 +105,15 @@ line and this should resolve the issue.
 *   Provide shortcut for the assignment operator (`<-`) (RStudio: Alt+- on
     Windows/Linux; Option+- on Mac).
 
+*   When performing operations on sliced rows of data frames, be aware that some 
+    functions in R automatically convert the object type to a numeric vector, while 
+    others do not. For example, `max(dat[1, ])` works as expected, while `mean(dat[1, ])` 
+    returns an error. You can fix this by including an explicit call to `as.numeric()`, 
+    for example `mean(as.numeric(dat[1, ]))`. This issue is also mentioned in a callout 
+    box in the lesson materials, since it is unexpected and can create confusion when 
+    simple examples fail (by contrast, operations on sliced columns of data frames always 
+    work as expected, since columns of data frames are already vectors).
+
 ## [Addressing Data]({{ page.root }}/10-supp-addressing-data/)
 
 *   Note that the data frame `dat` is not the same set of data as in other lessons.