ggpp (version 0.5.8-1)

stat_fmt_tb: Select and slice a tibble nested in data

Description

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,
  ...
)

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.

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.

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.

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.

See Also

See geom_table for details on how tables respond to mapped aesthetics and table themes. For details on predefined table themes see ttheme_gtdefault.

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))