Explore all variables and generate an HTML or PDF summary report

Analyses a data frame or tibble, summarising all continuous, date and categorical variables, missing data and duplicate values, and produces an HTML or PDF report.

Usage

explorer(
  data,
  output_file = NULL,
  format = c("html", "pdf"),
  progress = TRUE,
  id_var = NULL
)

Arguments

data: A data frame or tibble to explore.
output_file: The name of the output file. Default uses <df_name>_report.html or .pdf
format: Output format, either "html" (default) or "pdf".
progress: If TRUE (default), show a progress bar while building the report.
id_var: Character vector of column names to treat as IDs (not summarised).

Value

Outputs an html or PDF summary. Output in PDF typically takes longer.

For PDF output, a LaTeX distribution must be installed. TinyTeX is recommended. To install, run:

install.packages("tinytex")
tinytex::install_tinytex()

Examples

if (FALSE) { # \dontrun{
# Build example data from mtcars with some factors and a date column:
  cars_example <- mtcars %>%
    dplyr::mutate(
      across(c(vs, am, gear, carb, cyl), as.factor),
      date_var = as.Date("2025-06-01") +
        sample(-300:300, nrow(mtcars), replace = TRUE),
      id = dplyr::row_number()
    )
# To run explorer:
  explorer(mtcars)                  # with progress bar
  explorer(mtcars, progress = FALSE) # omit progress bar
  explorer(mtcars, format = "pdf")   # PDF output
  explorer(mtcars, format = "pdf", id_var = "id")   # Identify ID variable
} # }