Chapter 10: Where to Go from Here and Common PitfallsĬhapter 9: Reproducible Workflow with RMarkdown. Chapter 9: Reproducible Workflow with RMarkdown.Chapter 3: Exploring Your Data with Tables and Visuals.Select Variables and Filter Observations.Chapter 2: Working with and Cleaning Your Data.This is controlled by the argument linesep, which defaults to c("", "", "", "", "\\addlinespace"). A line space is added to every five rows by default. The default argument values are toprule = "\\toprule", midrule = "\\midrule", and bottomrule = "\\bottomrule". The table only has horizontal lines for the table header and the bottom row. There are no vertical lines in the table, but you can add these lines via the vline argument. The horizontal lines can be defined via arguments toprule, midrule, linesep, and bottomrule. You can set this option as a global R option so you do not need to set it for every single table, e.g., options( = ""). You can explicitly remove the vertical lines via the vline argument, e.g., knitr::kable(iris, vline = "") (the default is vline = "|"). Table columns are separated by vertical lines. Please note that when you need additional LaTeX packages such as booktabs for an R Markdown document, you have to declare these packages in YAML (see Section 6.4 for how).ĭepending on whether the argument booktabs is TRUE or FALSE (default), the table appearance is different. 17.7 Organize an R Markdown project into a research website with workflowr.17.6 Collaborate on Rmd documents through Google Drive with trackdown.17.3 Render R Markdown with rmarkdown::render().16.9 Write books and long-form reports with bookdown.16.8 R Markdown templates in R packages.16.6 The working directory for R code chunks.16.3 Read multiple code chunks from an external script (*).16.2 Read external scripts into a chunk.15.9.1 Generate data in R and read it in Asymptote.15.6.3 Write YAML data to a file and also display it.15.6.2 Include LaTeX code in the preamble.15.6 Write the chunk content to a file via the cat engine.15.3 Execute content conditionally via the asis engine.15.2 Run Python code and interact with Python.15.1 Register a custom language engine (*).14.9.3 Keep multiple copies of the cache.14.9.2 Invalidate the cache by changes in global variables.14.9.1 Invalidate the cache by changing code in the expression.14.9 A more transparent caching mechanism.14.8 Allow duplicate labels in code chunks (*).14.7 Use knitr::knit_expand() to generate Rmd source.14.6 Save a group of chunk options and reuse them (*).14.5 Modify a plot in a previous code chunk.
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