Try these 5 Python libraries to simplify data visualization

Tired of Matplotlib's outdated approach? Discover these 5 powerful Python libraries that offer cleaner, more intuitive, and often more interactive ways to visualize your data.

Learn about:

◉ Plotly: For interactive and web-ready visualizations with minimal configuration.
◉ Seaborn: A statistical extension for Matplotlib that simplifies complex plots.
◉ Vega-Altair: A declarative grammar-based library for simple and scalable visualizations.
◉ Bokeh: Ideal for web-optimized visualizations of large datasets.
◉ Plotnine: A Python equivalent to ggplot2 for R users.

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Timeline:

Matplotlib is Garbage: (0:00​​​)
Plotly – Interactive and Web-Ready Visualization: (0:55)
Seaborn – Matplotlib's Statistical Extension: (1:37)
Vega-Altair – Declarative, Grammar-Based Visualization: (2:20)
Bokeh – Web-Optimized for Large Datasets: (3:00)
Plotnine – Python’s Answer to ggplot2: (4:09)
Conclusion: (4:41)

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#pythonlibraries #DataVisualization #python #Matplotlib #Plotly #Seaborn #Altair #Bokeh #Plot9 #datascience #pythonprogramming

[shubhamgattani]

Too many GIFs in this video....was very tough on my eyes!

[julianbaader]

Your conclusion says it all...

Why use one tool which performs mediocre at all tasks if you can use 5 tools for 5 different tasks.

Of course each single tool will outperform matplotlib at its respective tasks. But as a general catch all, matplotlib is adequate enough.

[Patrick-vvig]

Matplotlib is great. I don't get what he is on about.

[tuhin]

Why this video feels like "Made by AI" ?

[kejtos]

I have been using altair ever since I started using marimo notebooks, but it has been a struggle. I like the out of the box visuals, but it is sometimes so weird and basic things (like adding a line, or a legend) don't work as one would expect. Also finding information about it is much more difficult, but the documentation is a little bit better.

[HonkyTonkWhiteBoi]

Learn to code and you wont be crying through AI