Get Started

library(cheetahR)

Your first table

# Render table
cheetah(iris)

Customize columns

# Change some feature of some columns in the data
cheetah(
  iris,
  columns = list(
    Sepal.Length = column_def(name = "Sepal_Length", width = 120),
    Sepal.Width = column_def(name = "Sepal_Width", width = 120),
    Petal.Length = column_def(name = "Petal_Length", width = 120),
    Petal.Width = column_def(name = "Petal_Width", width = 120),
    Species = column_def(name = "Species")
  )
)

Customize rownames

The default for the row names column is TRUE if present in the data; however, to modify it, include a column definition with “rownames” as the designated column name.

# Example of customizing rownames with color and width
cheetah(
  mtcars,
  columns = list(
    rownames = column_def(width = 150, style = list(color = "red"))
  )
)

Defining the column types

The column_type parameter in column_def() allows you to specify different types of columns. There are 6 possible options:

• "text": For text columns
• "number": For numeric columns
• "check": For checkbox columns
• "image": For image columns
• "radio": For radio button columns
• "multilinetext": For multiline text columns

The column_type parameter is optional. If it is not specified, the column type will be inferred from the data type.

# Using checkbox column type to indicate NA values
head(airquality, 10) %>%
  mutate(
    has_na = if_any(everything(), is.na),
    has_na = ifelse(has_na, "true", "false"),
    .before = 1
  ) %>%
  cheetah(
    columns = list(
      has_na = column_def(
        name = "Contains NA",
        column_type = "check",
        style = list(
          uncheckBgColor = "#FDD",
          checkBgColor = "rgb(255, 73, 72)",
          borderColor = "red"
        )
      )
    )
  )