7 Python Data Visualization Libraries in 15 minutes

In this video Rob, a Kaggle Grandmaster, quickly and humorously walks through each of the popular plotting and data visualization tools in python. These include bokeh, matplottlib, plotly, altir and seaborn. This video will give you an overview of each python package, what each does well and what they don't do well. Python is the #1 coding language for data science and has been growing over the years as an essential tool, especailly important for data visualization. Explained in a funny way every package is discussed in less than 15 minutes.

Timestamps:
00:00 Introduction
00:33 Matplotlib
02:46 Seaborn
05:10 Bokeh
07:50 Plotly Express
11:40 Plotnine
13:02 Altair
13:24 Pandas
14:09 Summary

#DataScience #Python #DataViz

[robmulla]

Because youtube doesn't seem to be showing my chapters in the videos here are the timeline links:
00:00 Introduction
00:33 Matplotlib
02:46 Seaborn
05:10 Bokeh
07:50 Plotly Express
11:40 Plotnine
13:02 Altair
13:24 Pandas
14:09 Summary

[brandonwarfield]

I don't know how you made this entertaining!
I was chuckling all the way through the video.

[gschnuuget]

this is an amazing overview, thank you very much for this video! I especially like that you are presenting in dark mode 🙂

[subbyspersonalvlog]

It was worth a lot in just one lovely video imparting so much of value as you present things vividly in a very attractive way. Given enough time, I enjoy watching all your videos, multiple times if need be.

[hfuhruhurr]

Altair's (two syllables, btw) syntax makes the most sense to me. Took me forever to understand how to unleash the power, though.

[milindankur]

I love to watch Rob Mulla! All these plots are so beautiful! Thanks for summarizing them. Respect🤟

[BarmitzvahNTC]

Nice. I was surprised that you did not include LUX at this cool overview.

[cedric]

What also makes bokeh cool is it's ability to handle big data better than some alternatives

[carlosernestocustodiocaden]

Excelente vídeo, es cosa de empezar a practicar, hasta encontrar lo mejor para el trabajo que hay que hacer.

[agnichatian]

If the GUI of my app is a web page, can I put these plots on it ? If so, can they be interactive ? i.e. process in Python, , render as web...

[martinnjeri]

so nobody is gonna say something about those violin plots?? they look just never mind!!
Niice video Maestro... Learning a lot from you!!
Kudos ....

[JoelHernandez-vskn]

Thank you very much!! Quick question, is there a way to add labels to specific percentiles of a box plot, lets say to median and 75th percentile?

[stuartberg]

I'll give a shout-out for my favorites: holoviews and hvplot.pandas, which are built on top of bokeh and matplotlib. They give you a high-level API that makes lots of standard plots quickly, but you're free to customize the plot yourself with the lower-level library (bokeh or matplotlib) if you need extra control.

[RHHS]

Thanks a lot Rob ! Any suggestions to create Concept Maps, Mind Maps or Entity Relashionships diagrams, for Data Governance purposes ?

[BrianKamanzi]

Great video, exactly what I was looking for and positive energy to boot, appreciated.

[TheSoonAnn]

great way to introduce all the packages available, now i know the gg plot equivalent in python

[kikfraben]

Didn’t know that charts can be so much fun, awesome video!

[mdd]

really helpful vid I mainly just plot in pandas like you said it saves you time lol but I did not know what I was missing out on with the interactive plots

[soumyadrip]

LMFAO did not know GMs are allowed to be that funny, JK, pog video editing skill.
Had no idea that Python had many visualization libraries.

[mschuer]

Thank you Rob, another great video. Was never aware that PlotNine existed, will have to check it out. Also want to dig more into Ploty's it existed but never used it...this gives me a reason to check it out. Keep the great videos coming please, they are very useful.