Devil's advocacy

ex09_row-summaries.R

@@ -42,7 +42,7 @@ df <- tribble(
 #'
 #' One "tidy version" of `rowSums()` is to ... just stick `rowSums()` inside a
 #' tidyverse pipeline. You can use `rowSums()` and `rowMeans()` inside
-#' `mutate()`:
+#' `mutate()`, because they have a method for `data.frame`:
 df %>%
   mutate(t_sum = rowSums(select_if(., is.numeric)))
 
@@ -57,6 +57,31 @@ df %>%
 #' mix these in as we go. They are equally useful when expressing which
 #' variables should be forwarded to `.f` inside `pmap_*().`
 #'
+#' ## Devil's Advocate: can't you just use `rowMeans()` and `rowSums()` alone?
+#'
+#' This is a great point [raised by Diogo
+#' Camacho](https://twitter.com/DiogoMCamacho/status/996178967647412224). If
+#' `rowSums()` and `rowMeans()` get the job done, why put yourself through the
+#' pain of using `pmap()`, especially inside `mutate()`?
+#'
+#' There are a few reasons:
+#'
+#' * You might want to take the median or standard deviation instead of a mean
+#' or a sum. You can't assume that base R or an add-on package offers a row-wise
+#' implementation of every function you might need.
+#' * You might have several variables besides `name` that need to be retained,
+#' but that should not be forwarded to `rowSums()` or `rowMeans()`. A
+#' matrix-with-row-names grants you a reprieve for exactly one variable and that
+#' variable best not be integer, factor, date, or datetime. Because you must
+#' store it as character. It's not a general solution.
+#' * Correctness. If you extract the numeric columns or the variables whose
+#' names start with `"t"`, compute `rowMeans()` on them, and then column-binpd
+#' the result back to the data, you are responsible for making sure that the two
+#' objects are absolutely, positively row-aligned.
+#'
+#' I think it's important to have a general strategy for row-wise computation on
+#' a subset of the columns in a data frame.
+#'
 #' ## How to use an arbitrary function inside `pmap()`
 #'
 #' What if you need to apply `foo()` to rows and the universe has not provided a

ex09_row-summaries.md

@@ -31,7 +31,7 @@ df <- tribble(
 
 One “tidy version” of `rowSums()` is to … just stick `rowSums()` inside
 a tidyverse pipeline. You can use `rowSums()` and `rowMeans()` inside
-`mutate()`:
+`mutate()`, because they have a method for `data.frame`:
 
 ``` r
 df %>%
@@ -61,7 +61,35 @@ variables are of mixed type. These are just a few examples of the
 different ways to say “use `t1`, `t2`, and `t3`”, so we don’t try to sum
 or average `name`. I’ll continue to mix these in as we go. They are
 equally useful when expressing which variables should be forwarded to
-`.f` inside `pmap_*().`
+`.f` inside
+`pmap_*().`
+
+## Devil’s Advocate: can’t you just use `rowMeans()` and `rowSums()` alone?
+
+This is a great point [raised by Diogo
+Camacho](https://twitter.com/DiogoMCamacho/status/996178967647412224).
+If `rowSums()` and `rowMeans()` get the job done, why put yourself
+through the pain of using `pmap()`, especially inside `mutate()`?
+
+There are a few reasons:
+
+  - You might want to take the median or standard deviation instead of a
+    mean or a sum. You can’t assume that base R or an add-on package
+    offers a row-wise implementation of every function you might need.
+  - You might have several variables besides `name` that need to be
+    retained, but that should not be forwarded to `rowSums()` or
+    `rowMeans()`. A matrix-with-row-names grants you a reprieve for
+    exactly one variable and that variable best not be integer, factor,
+    date, or datetime. Because you must store it as character. It’s not
+    a general solution.
+  - Correctness. If you extract the numeric columns or the variables
+    whose names start with `"t"`, compute `rowMeans()` on them, and then
+    column-binpd the result back to the data, you are responsible for
+    making sure that the two objects are absolutely, positively
+    row-aligned.
+
+I think it’s important to have a general strategy for row-wise
+computation on a subset of the columns in a data frame.
 
 ## How to use an arbitrary function inside `pmap()`