Using Plotly, Bokeh and Altair for interactive visualizations in the blog posts

Using puzzle on tracing the high profile spy as excuse to showcase Markov Chains and demonstrate usage and properties e.g. Stationary distribution

On Github project Awesome Zsh plugins you can find 1700+ links to plugins, themes and Zsh plugin managers/frameworks. The number of tools listed on that page is high and it is difficult to get orientation which plugins gained already good reputation from Zsh users community. This post aims at identifying most popular tools where popularity is measured with the number of stars that Github users added to given plugin or tool.

Having several notebook-based projects behind you might result in mess in projects directory. Organize your Data Science project based on Jupyter notebooks in a way that one can navigate through it. Especially that “the one” will be most probably you in few months time. To achieve that: keep your projects’ directory clean, name the project in a descriptive way and take care of internal structure of the project.

Exploratory Data Analysis of the Kaggle’s “What’s cooking” competition dataset to get understanding what kind of data we are dealing with and get intuition of existing dependencies.

Python implementation of blockchain in few lines of code.

There is an exhaustive but curated list of Zsh plugins posted on GitHub project Awesome Zsh plugins. You can find there 800+ links to plugins, themes and Zsh plugin managers/frameworks. Even though it is a collection of awesome stuff the number is a bit high get orientation which plugins gained already good reputation from Zsh users community. In this post I will identify most popular plugins - those which have the highest number of stars.