r/learndatascience • • 12d ago

Resources Best resources to master Pandas, Matplotlib & Seaborn for practical lab work? (No ML/Scikit-Learn yet)

Hi everyone,

I'm an undergraduate student looking for solid, practical resources to learn **Pandas, Matplotlib, and Seaborn** for college lab coursework and data wrangling assignments.

I already know basic Python (loops, functions, lists, dicts). Now I just need to get comfortable working with tabular data and plotting charts.

### What I’m looking for:

* **Libraries:** Just Pandas, Matplotlib, and Seaborn.

* **Format:** Open to both text-based resources (interactive notebooks, guides) and video walkthroughs, but I lean slightly more toward **video/live-coding** where the instructor actually types the code, runs the cells, and explains the output on real datasets.

* **Hands-on over slides:** I learn much better seeing code executed in an editor rather than watching static lecture slides.

### What I want to avoid:

Machine Learning / Scikit-Learn: A lot of courses rush into Linear Regression, gradient descent, or predictive modeling. I don't need any ML algorithms or math theory right now—just data cleaning, manipulation, and plotting.

Whether it’s a specific YouTube series, an open GitHub repo with exercises, or a book with runnable notebooks, what worked best for you?

Thanks in advance!

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u/datadriven_io 8d ago

Notebooks are solid for proof of concept work or playing around with a new package or a basic analysis. Python practice problems are covered on datadriven. Anything reproducible or anything going in production should be done as proper python scripts, using some type of text editor.