dataschool

Learn the differences between Jupyter Notebook, JupyterLab, IPython, Colab, and other related terms

→ What is the Anaconda distribution & why do people use it?
→ How is it related to conda & Miniconda?
→ As a Data Scientist, which of these should I be familiar with?

Use Python to solve this classic probability puzzle that has stumped mathematicians and Nobel Prize winners!

Learn how to use the power of GPT to interact with your private documents. All using Python, all 100% private, all 100% free!

Learn how to use pandas, requests, and regular expressions ("regex") to create a dataset of every Python version and its release date!

Learn the 25 most useful keyboard shortcuts for Jupyter Notebook and JupyterLab (including hidden gems 💎) so that you can speed up your workflow!

Learn how to use Python's f-strings for substitution and formatting, and then combine those features to solve a real-world pandas problem!

50 short videos to help you sharpen your scikit-learn skills and learn best practices for Machine Learning

Need help with your code? Use this step-by-step process to ask great Stack Overflow questions that will get answered quickly!

Want to contribute to an open source project? Follow this detailed visual guide to make your first contribution TODAY!

If you want to combine multiple datasets into a single pandas DataFrame, you'll need to use the "merge" function. In this video, you'll learn exactly what happens during a merge operation, as well as how to use the four different types of joins. By the end of the video, you'll be fully prepared to merge your own DataFrames!

Learn how to correctly encode categorical features using one-hot encoding so that you can include them in your Machine Learning model!

There are two ways to select a Series from a DataFrame: "dot notation" and "bracket notation" (square brackets). Find out which one you should use, and why!

60+ tricks that will save you time and energy every time you use pandas! New tricks added daily. Up-to-date with the latest version of pandas (0.25).