library(cheetahR)
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library(cheetahR)
# Render table
cheetah(iris)
# 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")
) )
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"))
) )
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 columnsThe 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"
)
)
) )
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