--- title: "Get Started" output: rmarkdown::html_vignette vignette: > %\VignetteIndexEntry{Get Started} %\VignetteEngine{quarto::html} %\VignetteEncoding{UTF-8} --- ```{r, include = FALSE} knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) library(dplyr) ``` ```{r setup} library(cheetahR) ``` ## Your first table ```{r} # Render table cheetah(iris) ``` ## Customize columns ```{r} # 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. ```{r} # 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. ```{r} # 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" ) ) ) ) ```