Convert a dataframe to a huxtable with nested rows and columns.

The assumption here is that the input data is a long format tidy dataframe with both rows and columns specified by values of the rowGroupVars and colGroupVars columns. The long format (sparse) table is translated into a nested tree of rows (using rowGroupVars) and a nested tree of columns (from colGroupVars). Individual data items are placed in the cell intersecting these two trees. If there are multiple matches an additional layer of grouping is added to the columns.

Usage

hux_tidy(
  tidyDf,
  rowGroupVars,
  colGroupVars,
  missing = "—",
  na = "—",
  displayRedundantColumnNames = FALSE,
  ...
)

Arguments

tidyDf

A dataframe with row groupings (as a set of columns) and column groupings (as a set of columns) and data, where the data is in a tidy format with a row per "cell" or cell group.

rowGroupVars

A dplyr::vars(...) column specification which will define how rows are grouped

colGroupVars

A dplyr::vars(...) column specification with defines how columns will be grouped

missing

If there is no content for a given rowGroup / colGroup combination then this character will be used as a placeholder

na

If there are NA contents then this character will be used.

displayRedundantColumnNames

if there is one column per column group the name of that column may be irrelevant (e.g. if there is a col_name, value fully tidy format) and col_name is in the colGroupVars list then the name of the column value is redundant and not displayed by default. However sometimes you want to display this if you have named it as something specific e.g. including the units. If there is more than one column per colGroup the column titles are needed and kept.

...

passed to hux_default_layout()

Value

a huxtable table