What is kernel density estimation? And how to build a KDE plot in Python? | Seaborn KDEplot

This seaborn kdeplot video explains both what the kernel density estimation (KDE) is as well as how to make a kde plot within seaborn. After introducing how a KDE plot is built, I demo Python code for both the univariate and bivariate KDE plots with seaborn. I also discuss what kinds of kernel to choose and how to set bandwidth.
00:00 What is KDE?
1:03 How does KDE work?
2:05 Univariate KDEplot code
4:02 What is bandwidth?
5:35 How to read a bivariate KDEplot
6:09 Bivariate KDEplot code
8:34 Conclusion and up next
Github code:
github.com/kimfetti/Videos/bl...
#seaborn #dataviz

[@KimberlyFessel]

If you enjoyed 😄, please subscribe and check out my full "Introduction to Seaborn" playlist: ruclips.net/p/PLtPIclEQf-3cG31dxSMZ8KTcDG7zYng1j

[@laxmanbisht2638]

Great! I want to do KDE pot for a road network? Have your written this sort of code?

[@KimberlyFessel]

@@laxmanbisht2638 I haven't done KDE plots for networks, but that sounds interesting

[@snelethuhashibi8254]

Hi Kimberley, Do you know how I can label the KDE contours?

[@eatbreathedatascience9593]

Hi Kimberly, great video. Could tell me what you used to produce the slider for the bandwidth bw ? Thanks very much. !

[@Tntpker]

Arguably the most underrated video on RUclips.

[@KimberlyFessel]

So glad you enjoyed it! This is the first public video I made for RUclips.

[@EvaPev]

Thank you very much for making the effort to visualise how the distributions add up. That made all the difference.

[@thomasdehee9626]

Thanks you SO MUCH
I bumped into this concept in a Python course and was looking for a concise explaination about KDE and was getting really anxious as anything I was finding was overly complicated
You have been really clear and concise, amazing !
Suscribed

[@raulrubiocastillo]

This helped me to better understand and apply the KDE concept to my statistical work, Kim. Thanks a lot

[@ethanspitips5903]

Great video on getting started with KDE plots in seaborn! Super easy to follow along, understand, and replicate the plots in a notebook. Nice job :)

[@KimberlyFessel]

Thanks much! Great to hear you could easily follow along 😄

[@22niloc]

Excellent - Very clear and extremely comprehensible. I"mcurrently studying DataViz with seaborn and your tutorial has just made sense of KDE.

[@jayantdikshit4181]

One of the best series on Seaborn. Thanks for making such a great content!!!

[@KimberlyFessel]

Excellent -- glad you are enjoying it!

[@jamesdyer4934]

Thank you for answering in the first 30 seconds exactly what a KDE is in simple, clear terms. I was then able to understand all of the following.

[@shubhamjain3028]

The content is pure gold. Please don't stop making more videos. Your channel will be on top one day I am sure

[@KimberlyFessel]

Thanks so much and glad you enjoyed the video!

[@zphyr3737]

There is hidden great genius in this simple explanation of this complicated topic. I love it

[@jon7187]

The de-jargon-ification of terms is reason enough to watch. The visuals and step by step walkthroughs are the reason I subscribed!

[@KimberlyFessel]

Awesome -- thanks!

[@paulaaimar5555]

Amazing video! You explain some complex concepts very well, thank you so much, keep making this videos please! You are the best!

[@KimberlyFessel]

Thanks very much! So glad to hear you enjoyed the video, and I definitely will keep making more 😄

[@balajikannan7393]

Whoa...by far the crisp and concise explanation on KDE. I enjoyed learning and replicating it. Thanks.👍

[@KimberlyFessel]

Awesome -- glad you enjoyed and were able to replicate! 😄

[@yuxrazafar8532]

Thank you so much! It helped me alot in understanding the underlying concept. I couldn't find other tutorials for kde that teaches so on point!

[@KimberlyFessel]

So glad that helped you - cheers! 😀

[@colemanvollrath7180]

Excellent video! Thanks so much Kimberly!

[@msarmad5217]

Wow. I am speechless. Haven't seen content of such quality on RUclips for a long time. Stumbled upon it and Learned a-lot today.
Kudus Kimberly!

[@KimberlyFessel]

Oh wow -- thank you! So glad you enjoyed the video and learned from it -- cheers!

[@puhozavrik]

So happy I found your channel! Amazing content, thank you

[@KimberlyFessel]

So happy you found my channel as well - welcome! 👋

[@rutwikhiwalkar9583]

I was struggling with visualizations and just came across the best series on YT, coincidence? I think not. Btw the series is amazing!

[@KimberlyFessel]

Excellent -- so glad to hear this series has been helpful to you!

[@charmendro]

Very well explained! Learned alot about KDE as a whole as well

[@KimberlyFessel]

Oh so good to hear that - KDE is pretty cool!

[@adamatkins8496]

such an underrated channel. thank you for uploading this quality content for free.

[@KimberlyFessel]

Why thank you! Glad you enjoyed the video 😄

[@Persona_Incognito]

This is a superb presentation! Thanks so much for posting it!

[@KimberlyFessel]

Oh, thank you! Glad to hear you enjoyed it. 😄

[@Esmeralda-ut1br]

I'm here to click the like button in every videos of this serie. Hehe these are very clear and concise. Like, like , like

[@t.t.cooperphd5389]

Finally, good videos on seaborn. Thank you!

[@KimberlyFessel]

You're welcome! Glad they are useful!

[@crbMKE]

Thanks! This helped me understand how the FSeq2 software works!

[@nyxhemera]

Presentation of KDE is really smooth and clear. Thx

[@KimberlyFessel]

Excellent - glad you found it helpful!

[@jongkargrinang8012]

Your all videos are very helpful. Thank you very much.

[@rajatgupta7344]

I wasted 2-3 days just clearing this. I got your video really to the point, explaining each and everything I need. Really appreciate yours affords. Thank you

[@KimberlyFessel]

Very glad to hear my video helped!

[@pedroluisalcazar9285]

Great Video!!!!! thanks, your explanations and the resources you use to make your concepts clear are great!!! so nice to have people like you on You Tube, Thanks, and best regards from Bolivia

[@pedroluisalcazar9285]

One more question please, what program you use to make that bandwith graph where you move the bandwith and see how the graph changes?

[@espua72]

good job on explaining this in such simple, easy to understand way. keep up the good work

[@KimberlyFessel]

Thank you! Will do!

[@juanpi.hojita]

This video saved my semester, thank you so much!

[@KimberlyFessel]

So good to hear. Glad it was helpful and good luck with the rest of your semester!

[@anagabrielamoralesona2579]

This video was clear, concise, and easy to follow and understand. Thanks! :)

[@KimberlyFessel]

So good to hear - glad it helped!

[@elastvd7503]

Great seaborn tutorial , thanks ❤

[@chicochinochao5493]

just started my python journey, very good tutorial on KDE plot

[@KimberlyFessel]

Glad you enjoyed it!

[@guganesan.ilavarasan]

This is actually amazing!

[@sriratna9211]

You don’t have idea how you helped me, thanks for the good work !

[@KimberlyFessel]

So good to hear! Very happy to help 😀

[@geekyprogrammer4831]

Perfect explanation of Kernel Density Function. I wish you have more subscribers in the upcoming future.

[@KimberlyFessel]

Thank you very much 👍So glad my explanation was clear!

[@arfanwicaksono8590]

really cool, the explanation is really easy to understand

[@KimberlyFessel]

So glad to hear it was helpful!

[@adityasahu96]

Such a simple and perfect explanation. Thank you

[@KimberlyFessel]

Awesome -- glad to hear you enjoyed the explanation!

[@Raiden_Amani]

Thank you so much. Was really looking for something more effective than a simple gaussian.

[@storyinmyhead]

clear and concise explanation, thanks kimberly!

[@KimberlyFessel]

You're very welcome -- glad it was helpful!

[@chibutza9092]

Great video! Very helpful.

[@VikasKM]

Super simple and easy.. to the point. Must watch

[@KimberlyFessel]

Awesome -- glad you liked it!

[@azhar145]

Best explanation. Thank You.

[@amanvishnoi2721]

Thank You very much for this wonderful video

[@user-wr4yl7tx3w]

this is really well explained

[@sabarivishnujayanthanjaikr4653]

Perfect explanation. Thanks, Kimberly!

[@KimberlyFessel]

Excellent -- you're welcome!

[@deldridg]

Great tut and thank you. I might have a go at generating some multivariate KDE plots of K-means outputs to see how they might add some interpretative value. Many thanks from Sydney - Dave

[@supamdeepbains5172]

Thank you so much. You made it look very easy and clear :) good job!

[@KimberlyFessel]

So happy to hear that my video helped make the KDE more clear -- thanks!

[@diegoac090]

Helpful for my thesis, blessings to you

[@KimberlyFessel]

So glad to hear that -- best regards for your thesis!

[@ling6701]

Thanks, very good explanations, I needed this.

[@vallevaro3444]

You videos are amazing, thank you very much for your work

[@ankitbioinfo]

very nice. I learnt something new today from your video. Great!

[@KimberlyFessel]

Excellent - always a good day to learn something new! 😄 Cheers!

[@vladimirrav]

Outstanding presentation!!!

[@KimberlyFessel]

Thanks so much -- glad you liked it!

[@cristianalzateurrea1948]

Thank you!!!
The best video of KDE plot :)

[@KimberlyFessel]

Thank you! Very glad you enjoyed it

[@yvessantosborges3491]

I am form BR 🇧🇷. I liked the simplicity of the video and the material used - a lot of quality and accuracy: from basic to advanced.
CONGRATULATIONS

[@KimberlyFessel]

Hello 👋🏼 and thanks for stopping by. So glad to hear you enjoyed the video!

[@jihan6780]

Thank you! Great video.

[@andreazecchi812]

Kimberly, you are Simply the best! Greetings from Rome, in Italy👋

[@KimberlyFessel]

Thank you very much, Andrea! 👋

[@thesenate8268]

Great explanation and underrated channel.

[@KimberlyFessel]

Thanks much! 😄

[@ST-rq8gk]

What an awesome video, thank you!

[@KimberlyFessel]

So glad you enjoyed it -- cheers!

[@piiopolive7084]

This is an awesome video, thank you so much for sharing.

[@KimberlyFessel]

Why, thank you! Very glad you enjoyed it. 😄

[@imdadood5705]

Another banger!!!! Thank you for this!!

[@KimberlyFessel]

Most welcome! Always striving to make more #bangerz! 😄

[@FunkToFunkiest]

You 're great Kimberly!!

[@KimberlyFessel]

Thanks so much! Cheers 😀

[@fahadreda3060]

Nice video, very informative , Thanks Kimberly

[@KimberlyFessel]

Thank you!

[@MouradBENKADOUR]

nice tutorial about KDE

[@gouthamansaravanan7692]

Hi Kimberly, Thank you very much!!

[@JeffersonCanedo]

You gave me a great idea thanks teacher

[@luismisanmartin98]

Awesome video, subscribed!

[@KimberlyFessel]

Excellent -- thanks for subscribing!

[@xandrviking1113]

Thanks for the lessons ✌

[@KimberlyFessel]

Most welcome - cheers! 😀

[@junaidmughal3806]

great knowledge😀

[@aadilvalconi9972]

The only thing I was confused about was how to interpret or read the bivariate kdeplot.
'You can thing about ring as higher coming closer and lower being in the background"
Thank you for that explanation.

[@cyrilh7625]

Thank you very much! Very useful video:)

[@KimberlyFessel]

You're welcome -- glad it was helpful!

[@CraftyyAMV]

Amazing, thank you!

[@ozan4702]

Excellent, thank you.

[@Southpaw101]

very nice explanation!

[@KimberlyFessel]

Thank you!

[@lara.kattan]

Super helpful! Subscribed!

[@KimberlyFessel]

Thanks, Lara!!

[@harshagarwal8170]

thank you so much...... superb explanation

[@KimberlyFessel]

So glad you enjoyed it!

[@simbol5638]

Thank you, now I have a grab of what KDE actually do.

[@KimberlyFessel]

Excellent! Glad to hear that 😁

[@shubhamgawali8030]

what a Great explanation it was, I fall in love of knoweldge, subscribed channel, lot of respect from india

[@shubhamgawali8030]

I just have a one question for mpg dataset sns.histogram(cars.horsepower, kde=true) is it equal to the plot we obtained from sns.kdeplot(cars.horsepower)

[@KimberlyFessel]

Thanks very much for subscribing! And yes, you should get the same KDE plot; however, the sns.histplot(cars.horsepower, kde=True) will also give you a histogram under the KDE plot. The histplot will also likely truncate/cut the edges of your KDE plot.

[@botballreads8235]

extremely helpful thank you

[@KimberlyFessel]

Glad it helped!

[@vedant8048]

Keep up the Good Work !

[@KimberlyFessel]

Thanks, will do!

[@ethanrichardson885]

I'm new to data visualisation with Python, this was amazing, thank you!

[@KimberlyFessel]

So glad to hear that -- Python has made some serious gains in the data visualization department lately!

[@charmerhue]

very nice! thank you!

[@KimberlyFessel]

Excellent - glad you liked it!

[@rischoalfredo1591]

Thankyou Kimberly

[@Hannah-ic5wv]

Amazing, thank you.

[@KimberlyFessel]

Glad you liked it -- cheers!

[@abhinahi3383]

Quality Content

[@KimberlyFessel]

Thank you! 😀

[@laxmanbisht2638]

Excellent!

[@KimberlyFessel]

Thank you!

[@ivanrafaelvidaurrethofehrn9118]

Hi, many thanks for the videos! You have one new subscriber for sure. I have a question, is it possible to have in one graph the histogram of the hole population of the data and the kde of one variable of the same data on the same graph?

[@shreddersengupta7384]

Really great :)

[@KimberlyFessel]

Thank you! :)

[@Kuzmar48]

Hi Kimberly , Nice Video very well explained, just a quick question since im new to visualization, can do we integrate these KDE plots to a folium map?

[@vukasinviskovic9121]

Hi Kimberly, thanks for the great video. I just subbed your channel.
A quick question: Any tips on how you made possible what's going on at 4:28 and onwards? It reminds me of filtering in Tableau, but I have no idea how to do it with Python.

[@haniyehseyedalinezhad6902]

Thank you so much for this great video. Very well explained. I am just wondering how sensitive KDE is to sample size! What is the minimum number of data points required for a kernel density estimation to be considered acceptable? (My application needs KDE for univariate and bivariate cases)

[@awesomegaming6109]

This is great

[@KimberlyFessel]

So glad you enjoyed it!

[@josephkarpinski9586]

Great set of Python videos!
An idea, if you haven’t already done it.
Consider doing videos on running Python under VSCode and VSCode Insiders.
Think your viewers would find it of interest.
Best Regards...
👨‍💻👨‍💻👨‍💻

[@KimberlyFessel]

Thanks very much for the suggestion! Haven't done anything like that yet, so I'll consider it. Cheers! 😄

[@abcde7515]

greetings from Turkey

[@KimberlyFessel]

Merhaba 👋 -- Thanks for stopping by!

[@abcde7515]

@@KimberlyFessel Merhaba 😁😁😁 thank you teacher

[@BTae9293]

thank you

[@nassarzinho]

Great video! I would like to use the kde over a map, e.g., given a set of lat and lon, how to plot the kde using the map mask? Do you have any video teaching about it?

[@leidycastro3629]

I have the same question :/

[@tusharbedse9523]

Great Stuff! Please start content on ML too

[@KimberlyFessel]

Glad you liked it - and thank you for the suggestion!

[@katharinastck]

Thanks!

[@KimberlyFessel]

Amazing - thanks to you as well! Glad you liked the video 😁

[@Esmeralda-ut1br]

If I could I would give you 100k likes!! Even more