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
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.
@@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.
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
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 ....
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.
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.
@@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!
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.
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. ua-cam.com/video/Y0Brf2l8Ysc/v-deo.html
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?
@@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 ;)
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.
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
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!
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!
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.
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
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.
Thanks a lot Rob ! Any suggestions to create Concept Maps, Mind Maps or Entity Relashionships diagrams, for Data Governance purposes ?
I love to watch Rob Mulla! All these plots are so beautiful! Thanks for summarizing them. Respect🤟
Glad you liked it! Appreciate the compliment.
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...
Cool video, opened my eyes to Plotly
Excelente vídeo, es cosa de empezar a practicar, hasta encontrar lo mejor para el trabajo que hay que hacer.
Muchas gracias!
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?
Great video, exactly what I was looking for and positive energy to boot, appreciated.
Didn’t know that charts can be so much fun, awesome video!
Which is best for plotting live data from exchanges?
Depends. How live?
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. 🙌
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.
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.
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!
great way to introduce all the packages available , now i know the gg plot equivalent in python
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?
We can change Pandas plotting backend to Plotly if one need interactive chart
where is proplot?
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!
That was a good video. I subscribed
Thanks!
Bokeh is not working when ssl integrated. Can anyone help
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.
You earned my subscription, good sir!
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.
Excellent video. Thanks!
Glad you liked it!
Вот это сразу лайк. Контент интересный и полезный. Для моего исследования в самый раз
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.
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. ua-cam.com/video/Y0Brf2l8Ysc/v-deo.html
Oh. I guess that’s the way it’s pronounced. Thanks for the feedback.
Plotly Express is awesome! that it what i need! thank you !
Glad you found what you were looking for!
For real time app which is the bettet
Thanks for this video, i have been enjoyed a lot, i'm subscribed yet!
Really appreciate that!
Thanks for knowlege and entertain.
i hope to learn much more.
Glad you were both entertained and learned! That’s my goal.
Love your work. PX😍
Thanks Gabriel! Glad you enjoy it.
I used vispy for plotting real time data.
bokeh looks fun
It is!
content is good but those to b quirky jokes are not
Mf you got a public "investing" folder you're so corny you're in no position to be making fun of anyone
I like it, it doesn't feel boring. Watch some indians if you don't like people with humour.
How will I find racists in those channels..@@AnonYmouS00816..
Thank you
That was so helpful
Glad it helped! Thanks so much for the comment.
Best is mataplot can make live diagramms ....( moving lines iver time.)
Great video
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?
Sir plz make an amazing series about visualization in python and some other important graph 😊
great content! thanks you Rob!
Thanks for watching.
Where is Pygal?
I have closed your video… Just kidding, very nice explanation with lively humor. Thanks
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 ;)
You are like Stevie T* but in the world of data
(* a Canadian electric guitar blogger worth checking out if you haven't already)
So violin plots should not be called twat plots…
Thanks Bro. Good Infos....
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.
Wheee i need to focus first as i beginner
import seaborn as sb
really a fan of pandas aren't you?🤣
1:24 Really...? I'm outta here.
You love it.
No, I was born in 1991
Yellowbrick
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.
I was born in 2003😂😂
I am beginner a in python
cringe
Yep
Excellent content, stupid explanation