Merge pull request #1527 from rstudio/nanoplot-boxplot

Add the `"boxplot"` type of nanoplot

R/modify_columns.R

@@ -2154,16 +2154,16 @@ cols_add <- function(
 #' the `options` argument).  A guide on the left-hand side of the plot area will
 #' appear on hover and display the minimal and maximal *y* values.
 #'
-#' There are two types of nanoplots available: `"line"` and `"bar"`. A line plot
-#' shows individual data points and has smooth connecting lines between them to
-#' allow for easier scanning of values. You can opt for straight-line
-#' connections between data points, or, no connections at all (it's up to you).
-#' You can even eschew the data points and just have a simple line. Regardless
-#' of how you mix and match difference plot layers, the plot area focuses on the
-#' domain of the data points with the goal of showing you the overall trend of
-#' the data. The data you feed into a line plot can consist of a single vector
-#' of values (resulting in equally-spaced *y* values), or, you can supply two
-#' vectors representative of *x* and *y*.
+#' There are three types of nanoplots available: `"line"`, `"bar"`, `"boxplot"`.
+#' A line plot shows individual data points and has smooth connecting lines
+#' between them to allow for easier scanning of values. You can opt for
+#' straight-line connections between data points, or, no connections at all
+#' (it's up to you). You can even eschew the data points and just have a simple
+#' line. Regardless of how you mix and match difference plot layers, the plot
+#' area focuses on the domain of the data points with the goal of showing you
+#' the overall trend of the data. The data you feed into a line plot can consist
+#' of a single vector of values (resulting in equally-spaced *y* values), or,
+#' you can supply two vectors representative of *x* and *y*.
 #'
 #' A bar plot is built a little bit differently. The focus is on evenly-spaced
 #' bars (requiring a single vector of values) that project from a zero line,
@@ -2173,6 +2173,10 @@ cols_add <- function(
 #' each. A guide on the left-hand side of the plot area will display the minimal
 #' and maximal *y* values on hover.
 #'
+#' Every box plot will take the collection of values for a row and construct the
+#' plot horizontally. This is essentially a standard box-and-whisker diagram
+#' where outliers are automatically displayed outside the left and right fences.
+#'
 #' While basic customization options are present in the `cols_nanoplot()`, many
 #' more opportunities for customizing nanoplots on a more granular level are
 #' possible with the [nanoplot_options()] helper function. That function should
@@ -2208,15 +2212,16 @@ cols_add <- function(
 #'
 #' @param plot_type *The type of nanoplot to display*
 #'
-#'   `singl-kw:[line|bar]` // *default:* `"line"`
+#'   `singl-kw:[line|bar|boxplot]` // *default:* `"line"`
 #'
-#'   Nanoplots can either take the form of a line plot (using `"line"`) or a bar
-#'   plot (with `"bar"`). A line plot, by default, contains layers for a data
-#'   line, data points, and a data area. Each of these can be deactivated by
-#'   using [nanoplot_options()]. With a bar plot, the always visible layer is
-#'   that of the data bars. Furthermore, a line plot can optionally take in *x*
-#'   values through the `columns_x_vals` argument whereas a bar plot ignores any
-#'   data representing the independent variable.
+#'   Nanoplots can either take the form of a line plot (using `"line"`), a bar
+#'   plot (with `"bar"`), or a box plot (`"boxplot"`). A line plot, by default,
+#'   contains layers for a data line, data points, and a data area. Each of
+#'   these can be deactivated by using [nanoplot_options()]. With a bar plot,
+#'   the always visible layer is that of the data bars. Furthermore, a line plot
+#'   can optionally take in *x* values through the `columns_x_vals` argument
+#'   whereas bar plots and box plots both ignore any data representing the
+#'   independent variable.
 #'
 #' @param plot_height *The height of the nanoplots*
 #'
@@ -2679,7 +2684,7 @@ cols_nanoplot <- function(
     data,
     columns,
     rows = everything(),
-    plot_type = c("line", "bar"),
+    plot_type = c("line", "bar", "boxplot"),
     plot_height = "2em",
     missing_vals = c("gap", "zero", "remove"),
     autoscale = FALSE,