xlsx-based Data viewer on a matrix-like R object

Invokes a xlsx-implemented viewer for a more handsome look of matrix-like R objects especially under Linux.

Usage

xview(
  dfr,
  name = NULL,
  large = FALSE,
  font = "Carlito",
  font_size = 11,
  headerBackground = "#7dcea0",
  stripColor = "#fadbd8",
  digits = 3,
  row.names = FALSE
)

Arguments

dfr: an R object which can be coerced to a data frame with non-zero numbers of rows and columns.
name: Optional: name of the temporarily saved file (without file extension, see examples). May be useful if several files are opened in Excel to differentiate between them.
large: Logical: If the data set is large, the procedure becomes very time-consuming. With large = TRUE a faster procedure (based on csv instead of Excel) is used that may be suitable for large datasets. However, the result does not look quite as nice as in Excel.
font: character of the font which should be used. Font must be installed in the operating system
font_size: Numeric value of font size for displaying the results
headerBackground: hex code for background color of the column header, see https://htmlcolorcodes.com/
stripColor: hex code for striped color of the rows, see https://htmlcolorcodes.com/
digits: numerical value of decimal places to round to. If NULL, the values are not rounded.
row.names: logical value indicating whether the row names of dfr are to be written along with dfr. Only works for csv files, i.e., if large = TRUE.

Details

The R-based data viewer under Linux is not very clear and descriptive. A better display can be achieved by temporarily saving the data object as a formatted Excel file and then opening it with Excel or Libre Office. For this purpose, functions of the R package openxlsx2 are used internally. Please note that the procedure can be very slow for larger data sets. In this case, use the option large = TRUE which generates only a csv file instead of a formatted Excel file, which is considerably faster for large data sets. It is recommended to use large = TRUE for data sets with more than 1000 lines.

Examples

if (FALSE) { # \dontrun{
xview(mtcars)
xview(mtcars, name = "mtcars")
} # }