Data Science has (unnecessarily) divided the world into two halves – R users and Python users. Irrelevant of the group you belong to, there’s one thing you have to admit – each language individually has libraries far superior to anything available in the alternative. For example, R Shiny is much easier ...

Shiny has been an R-exclusive framework from day one. Well, not anymore. At the recent Posit (RStudio) Conference, Posit’s CTO Joe Cheng announced Shiny for Python. Finally bringing the widely popular web framework to Python. As of August 2022, you really shouldn’t use Shiny for Python for mission-critical apps ...

Does Python have constants? Read our detailed guide to Python constants in 10 minutes.

Python 3.11 is expected to air in October 2022. What's new? Today we bring you 3 remarkable new Python 3.11 features.

You can now run Python in your browser with PyScript - Learn the basics and code two pages from scratch!

Let's compare Python 3.10 vs. Python 3.11 in an extensive benchmark test. Spoiler alert: Python 3.11 is up to 64% faster!

Hardcoded values are a terrible idea. Use configparser to read .ini configuration files in Python.

You should never hardcode Python app configuration data. YAML is an excellent alternative. Learn how to use it in a real Python app.

Still hardcoding values in Python apps? That's a terrible idea. Learn how to use JSON configuration files instead.

Data science is vastly different than programming. We use only four languages – R, Python, Julia, and SQL. Now, SQL is non-negotiable, as every data scientist must be proficient in it. Julia is still the new kid on the block. Many argue which is better – Python or R? But today, we ...