Select and slice a tibble nested in data

stat_fmt_tb selects, reorders and/or renames columns and or rows of a tibble nested in data. It can also apply user supplied functions to data columns. This stat is intended to be used to pre-process tibble objects mapped to the label aesthetic before adding them to a plot with geom_table.

Usage

stat_fmt_tb(
  mapping = NULL,
  data = NULL,
  geom = "table",
  tb.vars = NULL,
  tb.rows = NULL,
  tb.funs = list(),
  digits = 3,
  position = "identity",
  table.theme = NULL,
  table.rownames = FALSE,
  table.colnames = TRUE,
  table.hjust = 0.5,
  parse = FALSE,
  na.rm = FALSE,
  show.legend = FALSE,
  inherit.aes = TRUE,
  ...
)

Arguments

mapping: The aesthetic mapping, usually constructed with aes or aes_. Only needs to be set at the layer level if you are overriding the plot defaults.
data: A layer specific dataset - only needed if you want to override the plot defaults.
geom: The geometric object to use display the data
tb.vars, tb.rows: character or numeric vectors, optionally named, used to select and/or rename the columns or rows in the table returned.
tb.funs: named list of functions to be applied to data columns.
digits: integer indicating the number of significant digits to be retained in data. Use digits = Inf to skip.
position: The position adjustment to use for overlapping points on this layer
table.theme: NULL, list or function A 'gridExtra' ttheme definition, or a constructor for a ttheme or NULL for default.
table.rownames, table.colnames: logical flag to enable or disabling printing of row names and column names.
table.hjust: numeric Horizontal justification for the core and column headings of the table.
parse: If TRUE, the labels will be parsed into expressions and displayed as described in ?plotmath.
na.rm: a logical indicating whether NA values should be stripped before the computation proceeds.
show.legend: logical. Should this layer be included in the legends? NA, the default, includes if any aesthetics are mapped. FALSE never includes, and TRUE always includes.
inherit.aes: If FALSE, overrides the default aesthetics, rather than combining with them. This is most useful for helper functions that define both data and aesthetics and shouldn't inherit behaviour from the default plot specification, e.g. borders.
...: other arguments passed on to layer. This can include aesthetics whose values you want to set, not map. See layer for more details.

Value

A plot layer instance. Using as output data a copy of the input data in which the data frames mapped to label have been modified.

Details

One or more functions to be applied can be passed in a named list to parameter `tb.funs`. Functions are matched by name to columns, after column selection and renaming have been applied.

Computed variables

The output of sequentially applying slice with tb.rows as argument and select with tb.vars to a list variable list mapped to label and containing a single tibble per row in data.

Examples

my.df <-
  tibble::tibble(
    x = c(1, 2),
    y = c(0, 4),
    group = c("A", "B"),
    tbs = list(a = tibble::tibble(Xa = 1:6, Y = rep(c("x", "y"), 3)),
               b = tibble::tibble(Xb = 1:3, Y = "x"))
  )

ggplot(my.df, aes(x, y, label = tbs)) +
  stat_fmt_tb() +
  expand_limits(x = c(0,3), y = c(-2, 6))


# Hide column names, diplay row names
ggplot(my.df, aes(x, y, label = tbs)) +
  stat_fmt_tb(table.colnames = FALSE,
              table.rownames = TRUE) +
  expand_limits(x = c(0,3), y = c(-2, 6))


# Use a theme for the table
ggplot(my.df, aes(x, y, label = tbs)) +
  stat_fmt_tb(table.theme = ttheme_gtlight) +
  expand_limits(x = c(0,3), y = c(-2, 6))


# selection and renaming by column position
ggplot(my.df, aes(x, y, label = tbs)) +
  stat_fmt_tb(tb.vars = c(value = 1, group = 2),
               tb.rows = 1:3) +
  expand_limits(x = c(0,3), y = c(-2, 6))


# apply functions to columns
ggplot(my.df, aes(x, y, label = tbs)) +
  stat_fmt_tb(tb.vars = c(value = 1, group = 2),
               tb.rows = 1:3,
               tb.funs = list(group = function(x) {sprintf("italic(%s)", x)},
                              value = function(x) {ifelse(x > 2, "bold(zz)", x)}),
               parse = TRUE) +
  expand_limits(x = c(0,3), y = c(-2, 6))


# selection, reordering and renaming by column position
ggplot(my.df, aes(x, y, label = tbs)) +
  stat_fmt_tb(tb.vars = c(group = 2, value = 1),
              tb.rows = 1:3) +
  expand_limits(x = c(0,3), y = c(-2, 6))


# selection and renaming, using partial matching to column name
ggplot(my.df, aes(x, y, label = tbs)) +
  stat_fmt_tb(tb.vars = c(value = "X", group = "Y"),
              tb.rows = 1:3) +
  expand_limits(x = c(0,3), y = c(-2, 6))

Select and slice a tibble nested in `data`