As of winter of 2022 - 2023, trying to wear my hat in a sustainable way :)

I'm eager to understand how people gets good artists in problem solving. Visual and lingvistic embodiments of mathematical objects are what matters me a lot.

Becoming a qualified Data Analyst is my goal number one at the moment. That's why I constantly document the most essential tricks of Python libraries:

• Waters of networkx and igraph
• Waters of numpy
• Vizualization of numpy arrays with numpyviz

Check out my gotchas:

• Visual embodiments applied in explanation of concept of numpy axis, like this or this
• 2.5x speedup of itertools.combinations()
• How to speed up np.array(<iterable>) up to 4 times?
• A simple way to speed up aritmetics of arrays even more
• what happens when we try to optimize data with unbalanced types?
• vectorised way to create a graph with an image's pixel
• C-level based way to find connected components using Python
• How to vectorise iteration of consecutive sublists in 1D arrays or 2D arrays
• how to efficiently replace nonzero elements?
• splitting groups vs summing groups
• application of single search/binary search in both Python and C levels