vnlog VS plotly

For simple analyses (i.e. what most people do most of the time) doing this on the commandline gets you there faster. I use vnlog (https://github.com/dkogan/vnlog/). By the time you fired up your editor to write your Python code, I already have analyses and plots ready.

Alternative very appropriate for some uses cases: `vnl-join` from the vnlog toolkit (https://github.com/dkogan/vnlog). Uses the `join` tool from coreutils (works well, has been around forever), and `vnlog` for nice column labelling

There's also https://github.com/dkogan/vnlog/ which is a wrapper around the existing coreutils, so all the options work, and there's nothing to learn

And to improve the ergonomics, the vnlog wrappers are available to operate on field names, while retaining the internals of the core tools:

  https://github.com/dkogan/vnlog/

I sorta, kinda agree. Tools written in AWK (and friends) are indeed somewhat unmaintainable, but they're really close to being just right for a LOT of applications. The vnlog toolkit (https://github.com/dkogan/vnlog) adds just a little bit of syntactic sugar to the usual commandline tools to make processing scripts robust and easy to read and write. This was not my intent initially, but I now do most of my data processing with the shell and vnl-wrapped awk (and sort and join, ...) It's really nice. If you write stuff in awk, you should check it out. (Disclaimer: I'm the author)

Github: https://github.com/plotly/plotly.py

First we need to install the Plotly. To create some very dynamic graphics, this tool helps a lot.

my good dude wake up and smell the plotly. Knowing the ins and outs of matplotlib is helpful but doing interactive stuff with jupyter I always use plotly.

Plotly documentation (https://plotly.com/python/)

I don´t know your workflow, but I use 2 markdown based presentations: obsidian advance slides and Quarto presentations. The former is a plugin for Obsidian, which is the software I use to take all my notes, write my thesis, etc., so It makes it extremely easy to make presentations since all my information is in Obsidian. In the other hand, Quarto is a publishing system (articles, presentations, websites books) that can be easily integrated with python and R. This makes it supper convenient for showing my data to my PI since I can analyze my data and at the same time make a presentation for the data. Besides this, Quarto also integrates with my Zotero library, so I can insert citations. Lastly, one thing that made my Quarto presentations infinitely better that the powerpoints, Is that I can insert interactive graphs with plotly, so when I'm showing my data, my PI is able to explore the data inside the presentation.

Plotly GitHub repository: https://github.com/plotly/plotly.py

I'm using plotly.py now. This is why I love this community.

Depending on the nature of your reporting requirements, you could output a formatted Excel document with Python and a library such as openpyxl, and shove that into your SharePoint environment. This would be less dynamic than PBI reports can be, but may be sufficient. If you want viz as well, you can use something like ggplot or Plotly. Again, less dynamic than PBI for the same effort.