7 Python Data Visualization Libraries in 15 minutes
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- čas přidán 11. 06. 2024
- 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
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Intro to Pandas video: • A Gentle Introduction ...
Exploritory Data Analysis Video: • Exploratory Data Analy...
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#DataScience #Python #DataViz
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
What also makes bokeh cool is it's ability to handle big data better than some alternatives
That’s a good note I didn’t realize!
I love to watch Rob Mulla! All these plots are so beautiful! Thanks for summarizing them. Respect🤟
Glad you liked it! Appreciate the compliment.
this is an amazing overview, thank you very much for this video! I especially like that you are presenting in dark mode 🙂
Glad you liked it! I appreciate the feedback.
I don't know how you made this entertaining!
I was chuckling all the way through the video.
Haha. Thanks Brandon. Glad you enjoyed it.
Love the energy. Thanks!
Thanks a lot Rob ! Any suggestions to create Concept Maps, Mind Maps or Entity Relashionships diagrams, for Data Governance purposes ?
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.
Glad you enjoyed it! This video is a little more silly than my other ones
Great video, exactly what I was looking for and positive energy to boot, appreciated.
Altair's (two syllables, btw) syntax makes the most sense to me. Took me forever to understand how to unleash the power, though.
I didn’t realize that. I haven’t used it much before. Why is it so powerful?
@@robmulla For Altair, I would say the syntax follows the same logic than Seaborn, but the advantage is that you can make more beautiful and **interactive** plot that are easy to embed in a webpage.
Didn’t know that charts can be so much fun, awesome video!
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 scatter_map.....knew 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.
Glad you learned a few new things from this video. My hope was to show a lot of what's out there so you know it's there to use in the future.
@@robmulla and a great job you did. Thanks!
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
Thanks so much for the feedback. Glad you learned something new about interactive plots. 🙌
Nice. I was surprised that you did not include LUX at this cool overview.
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...
great way to introduce all the packages available , now i know the gg plot equivalent in python
Excelente vídeo, es cosa de empezar a practicar, hasta encontrar lo mejor para el trabajo que hay que hacer.
Muchas gracias!
great content! thanks you Rob!
Thanks for watching.
Can you add a plotly visualization to PowerPoint? I have been able to do this using a PNG of the graph, but would love to keep it interactive.
You earned my subscription, good sir!
Thanks for watching.
Thanks for knowlege and entertain.
i hope to learn much more.
Glad you were both entertained and learned! That’s my goal.
Thanks for this video, i have been enjoyed a lot, i'm subscribed yet!
Really appreciate that!
Sir plz make an amazing series about visualization in python and some other important graph 😊
Hi, I search to show a chart of data same as Nasdaq and it can update with new data live in real time. Can you tell me the best for that. I appreciate a lot.
Excellent video. Thanks!
Glad you liked it!
Вот это сразу лайк. Контент интересный и полезный. Для моего исследования в самый раз
Plotly Express is awesome! that it what i need! thank you !
Glad you found what you were looking for!
Thank you
That was so helpful
Glad it helped! Thanks so much for the comment.
That was a good video. I subscribed
Thanks!
Which is best for plotting live data from exchanges?
Depends. How live?
so nobody is gonna say something about those violin plots?? they look just like..... never mind!!
Niice video Maestro... Learning a lot from you!!
Kudos ....
🙊🙈 Thanks for watching.
Thanks. Would like a video on Panel.
We can change Pandas plotting backend to Plotly if one need interactive chart
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.
Glad you enjoyed it Somu! Trying to be a little less serious in this one.
There are MANY more than he reviewed here though, close to 50 now
@@cappy2112 holy crap
@@robmulla Please continue to be make videos like this😊
@@geekyprogrammer4831 Thanks so much! Funny that this video has the least views of all that I made so I figured people didn't like the funny videos. Maybe I'll give it another try!
Bokeh is not working when ssl integrated. Can anyone help
Love your work. PX😍
Thanks Gabriel! Glad you enjoy it.
Why is chart studio the new plotly import syntax?
I'm not sure if I'm following your question. Thanks for watching.
Did you ever make a video on dash then?
Thanks Bro. Good Infos....
bokeh looks fun
It is!
I used vispy for plotting real time data.
where is proplot?
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.
Really helpful!
I think the title of the video can be improved for greater reach :)
Thanks! I’m open to ideas for a new title. Any suggestions?
@@robmulla Sure..
"Matplotlib vs Seaborn vs Bokeh vs Plotly vs Plotnine vs Altair vs Pandas in 15 minutes"
"7 Python Data Visualization Libraries in 15 minutes"
"Data Visualization in Python - Quick Libraries Overview"
As you can see, my line of thought is that the main subject of the video - the libraries - is not in the title.. but should be, because its an informative video and not entertainment; even though you did make it entertaining ;)
How about Panel?
I haven’t heard of panel. Should I check it out?
My vote on panel and the holoviz family..
Part of Hvplot.
5:16 Ryu Nagase, product management director, consumer imaging group, Canon Corp, pronounces bokeh like okay, with a b on front. BOW-kay. Stress on the BOW. czcams.com/video/Y0Brf2l8Ysc/video.html
Oh. I guess that’s the way it’s pronounced. Thanks for the feedback.
content is good but those to b quirky jokes are not
Do you have any suggestion for plotting 2d data real-time... with new samples coming in every 100ms (via can-bus)?
I tried pyqtgraph, however with each new sample, the array took longer to display, and after just a couple minutes the lag was so bad that its not usable.
Any suggestions on a tool that can keep up with an ever increasing data array? To minimize RAM, I was thinking of appending each new sample to a csv file, and then have maplotlib continuously reload the file. But maybe vaex is better at working with a dynamically increasing large data array ? Or maybe gnuplot, mayavi?
I have closed your video… Just kidding, very nice explanation with lively humor. Thanks
Wheee i need to focus first as i beginner
next time do this and check what happens with your colleagues:
import pandas as plt
import numpy as pd
import matplotlib.pyplot as np
Don't hate on pie charts, but yes they are bad wherever more than 6 categories are grouped and tallied.
Agree to disagree?
now i want to hear you view on this. pie charts have treated me real good--the customers want them.
import seaborn as sb
Yellowbrick
I am beginner a in python
really a fan of pandas aren't you?🤣
So violin plots should not be called twat plots…
No, I was born in 1991
I was born in 2003😂😂
1:24 Really...? I'm outta here.
You love it.
cringe
Yep
Excellent content, stupid explanation
You are super cool!! Great content. My ranking: EDA: matplotlib, seaborn and pandas. PRESENTATIONS, DASHBOARDS AND WEBAPPS: Dash-plotly
So glad you like the content. Share with a friend or two! I totally agree with the seperation between EDA and presentation/dashboard libraries. Great point.