Thursday, 15 August 2013

Creating a Quick Report with knitr, xtable, R Markdown, Pandoc (and some OpenBLAS Benchmark Results)

To cut a long story short, I always wanted to write professional-looking documents (technical reports and potentially my thesis) with R codes. No more copy and paste. No more Microsoft Word. At the same time, I don't feel comfortable with LaTeX. Somehow I found a workaround with knitr, xtable, R Markdown and Pandoc.

I must say that my solution is far from perfect as I haven't mastered the document layout configuration yet. But I did manage to get some satisfactory results (well, from a seasoned MS Word user's point of view) with minimal R Markdown, xtable and knitr codes.

Instead of showing some dummy results, I created a simple report on R-25 benchmark results with two versions of OpenBLAS (ver. 0.2.6-1: the default, 2-threaded version on my Linux and ver. 0.2.8-1: the latest, multi-threaded version which had been made available recently). In short, the latest OpenBLAS performed slightly better in most of the R-25 tests but two. For more details, download the full pdf here.

The code-generated report looks like this ...


... which I think is pretty enough for a quick report. When I look at the source R Markdown file which is nothing but geeky plain text (see below), I just can't find words to describe the awesomeness of knitr + xtable + pandoc. Thank you very much Yihui, RStudio team, David, Charles and John.


The codes are available on Github. This was my first attempt to code a report, the code structure isn't pretty enough for showcase but I had commented as much as possible. I hope you enjoy this blog post and give this code-generated report routine a try!

Updated (21 Aug 2012): A basic 4-step example can be found here.
Updated (01 Feb 2014): The basic 4-step example is now here.

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  14. This is a fantastic guide for anyone looking to streamline their reporting process! Combining knitr, xtable, R Markdown, and Pandoc is a powerful way to create comprehensive and professional reports efficiently. Your inclusion of OpenBLAS benchmark results adds a practical layer that can be incredibly useful for those optimizing performance.

    I’m curious—what were some of the most challenging aspects of integrating these tools into a cohesive reporting workflow? Any tips for newcomers on avoiding common pitfalls?
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  15. This is an incredibly useful guide for generating reports using knitr and R Markdown! I love how you’ve combined these powerful tools to streamline the reporting process. The inclusion of xtable for table formatting is a great touch, and it's impressive to see the application of OpenBLAS benchmarks within this context. Your step-by-step approach makes it accessible for users of all levels, and I appreciate the practical examples you’ve provided. It would be interesting to hear more about any specific challenges you encountered while integrating these tools and how you resolved them. Thanks for sharing this valuable resource—it's sure to enhance the workflow for many in the R community

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