Cartopy VS plotly

Cartopy

Cartopy - A cartographic Python library with matplotlib support.

There is not really much to it, really. Everything is done in python, with use of standard libraries, of which probably most important in this case is cartopy https://scitools.org.uk/cartopy/docs/latest/ This is the latest cartopy tutorial I was able to find: https://www.youtube.com/watch?v=ivmd3RluMiw

Cartopy is a great lib that has a ton of utilities for those purposes. It is a little bit tricky to use at first but you can get really nice visualizations. I recommend installing it using with a conda env because its dependencies with other libraries.

- Cartopy: https://github.com/SciTools/cartopy

Made with: Cartopy, imageio and good 'ol Matplotlib (all Python libraries)

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.