JuliaConnectoR VS rmarkdown

Awesome resource!! On my side, I found the opposite R package to use Julia directly in R (https://github.com/stefan-m-lenz/JuliaConnectoR). In your opinion, what would be the most efficient?

If you're not already aware of and using RMarkdown, make learning it a priority. I use both R and Python extensively. Although Jupyter Notebooks have utility, RMarkdown is the superior tool for the most flexibility in reporting.

So it should be rendering this file for me? https://github.com/rstudio/rmarkdown/blob/main/tests/rmd/two-authors.Rmd

This is an R Markdown document. Markdown is a simple formatting syntax for authoring HTML, PDF, and MS Word documents. For more details on using R Markdown see .

The polished package now supports Rmarkdown documents that use the shiny runtime. This includes flexdashboard!

The package ggplot2 in R platform is a good choice. You can make any type of figure, here are some examples, https://www.r-graph-gallery.com/heatmap.html . Combined with rmarkdown (https://rmarkdown.rstudio.com/), you can combine together all of the steps together -- data input, data cleaning, data analysis, the final report of various formats, PDF, HTML, Word, PowerPoint, or journal articles. See here https://github.com/rstudio/rticles

One option for Markdown-esque input and Latex output is RMarkdown. RStudio does a nice job of allowing you to write markdown, embed references, code cells, and visualizations. I used it in grad school and only rarely had to drop down to Latex to do something more customized.

https://rmarkdown.rstudio.com/

If you are not familiar with Shiny, it is an R package that makes it easy to build interactive web apps straight from R. You can host standalone apps on a webpage or embed them in R Markdown documents or build dashboards.

What are you writting the research paper in? One way is to use Rmarkdown so that you can easily integrate the results. Rmarkdown is generally a really good tool, so it pays of to learn it anyway.