A lighterweight alternative to renv is to use Posit Public Package Manage (https://packagemanager.posit.co/) with a pinned date. That doesn't help if you're installing packages from a mix of places, but if you're only using CRAN packages it lets you get everything as of a fixed date. And of course on the web side you have shiny (https://shiny.posit.co), which now also comes in a python flavour. - Source: Hacker News / 4 months ago

Sometimes the war is lost even before the battle begins. During grad school, I wrote a whole bunch of web apps entirely in R using Shiny. It was clunky as hell, but yeah, it worked. I went looking for what's up with Shiny these days and found this - https://shiny.posit.co/ So yeah, full on pivot into python. Pip install shiny. Alright! "No web development skills required. Develop web apps entirely in R I mean... - Source: Hacker News / 11 months ago

Python's pandas, NumPy, and SciPy libraries offer powerful functionality for data manipulation, while matplotlib, seaborn, and plotly provide versatile tools for creating visualizations. Similarly, in R, you can use dplyr, tidyverse, and data.table for data manipulation, and ggplot2, lattice, and shiny for visualization. These packages enable you to create insightful visualizations and perform statistical analyses... Source: about 1 year ago

We work along side bio-statisticians and data analysts, from my experience in this world I recommend to build some plots/graphs in R based on some information you find appealing. After you have some work to show off to potential employers , learn Shiny and publish those graphs online as your portfolio. Source: about 1 year ago

One of the most difficult yet most fun projects I’ve done. Using Shiny to make an app, all coded in R! Source: over 1 year ago

To some extent it extends the concept of tasks which only can be reasonably executed after the completion of other ones (though results of branches eventually may join each other) and offers an additional assisting birds' eye visual of projects. So far, I'm aware about the documentation on worg interfacing org-taskjuggler and taskjuggler, as well as a video tutorial interfacing gnuplot instead. Source: about 1 year ago

Gnuplot is a program to plot diagrams. The Commands issued to use it don't change regardless if it is used in Linux/Windows/MacOS and it comes with less dependencies than a Spread sheet, or a statistics program. This is why I started to Become comfortable with it, and venture out some of its features. Here, "conditional plot" referred to "the diagram only displays a Thing/uses a pixel if the value in the table... Source: over 1 year ago

Or, does drawing diagrams refers to plotting data, but neither using matplotlib, nor gnuplot (export to .svg, .pdf, .png; pstricks, tikz to mention a few options)? Source: over 1 year ago

There may the occasion you actually need the data from a publication, and want to plot them altogether with data newly collected data in one diagram in common. An overlay, though possible, can become tricky (scaling, centering, alignment, etc.) and plotting all data in a diagram generated from scratch (gnuplot/octave, matplotlib, Origin, ...) exported as an illustration in the usual formats (.pdf/.png), or... Source: over 1 year ago

Have you looked at the graphing capabilities of Octave or Gnuplot? Gnuplot in particular has a lot of options, and a GUI for those who want it. Source: over 1 year ago