Seaborn heatmap | How to make a heatmap in Python Seaborn and adjust the heatmap style
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- Опубліковано 25 чер 2024
- The Seaborn heatmap is a simple visual that allows you to display tables of data through color. This Seaborn heatmap tutorial motivates the use of heatmaps and explains how to make a heatmap in Python Seaborn. Using an example pandas dataframe, I describe the basics of building a Seaborn Python heatmap, how to transpose a heatmap, and how to use pandas and Seaborn to create a correlation matrix heatmap. I discuss the importance of choosing a good color palette and how you can change the Seaborn heatmap color. I show you how to add Seaborn heatmap annotations as well as how to change the format of your annotations to remove scientific notation. Lastly, I provide additional styling tips to change the Seaborn heatmap tick labels and draw lines between the heatmap rectangles.
0:00 Introduction and overview
0:49 Heatmap Basics
5:35 Color Palette
7:48 Annotations
10:25 Additional Styling
11:47 Conclusion
Github code:
github.com/kimfetti/Videos/bl...
#seaborn #dataviz - Наука та технологія
If you enjoyed 😄, please subscribe and check out my full "Introduction to Seaborn" playlist: ua-cam.com/play/PLtPIclEQf-3cG31dxSMZ8KTcDG7zYng1j.html
Well done, superbly presented Kim
This is incredibly underrated. Thank you, you've spared me a whole night of headaches :)
Oh wow -- so glad I could help!
This is just awesome never seen visualization explanations which is so crisp and easy to understand
Thank you Kimberly for this invaluable videos. I will definitely go through all of them.
This tutorial was done really well, thanks for sharing your knowledge so clearly and enthusiastically :)
This was the best video that I found about using Seaborn heatmaps. Thank you Kimberly. subscribed.
Thank you, Kimberly! So helpful.
Excellent video, well explained and to the point! Saved me a lot of frustration 🙂
Oh excellent! Very glad to hear you were spared some frustration!
indeed, you simplified everything so perfectly.
Awesome explanation. You made heat map super easy ☺️✌️
Brilliant! I've loathed seaborn until this moment. The docs always seem helpful for every case except the one on which I'm working.
Oh awesome! The more I use Seaborn, the more I appreciate all the cool features. But you're right -- the docs don't always do it justice!
Thank you very much Kimberly, I love your videos!
Why thank you! 😊
This is the best video on the heatmap, your presentation was superb looking for more videos
Oh, thank you! Very glad to hear you enjoyed it, and I will continue making other videos as well.
How come you have so few subscribers. Your explanations are simply awesome. I really hope your channel grows.
Thanks Kim,
God bless you.
Thanks!
Just discovered you today. Firstly, I love you! Secondly, top quality presentation. Super content in terms of quality, and breadth, expert ans succinctly delivered. Subscribed!
Hi there 👋-- Welcome and thanks for subscribing! Glad to hear you enjoyed the video!
So much informative video. I was not aware of groupby in python but this cleared all. Thank You very much mam
Really useful for me as i thought making Heatmaps were difficult but it made it very easy
Very happy to hear this -- glad this video could help!
This is a very useful and well-explained video. Thank you!
Most welcome! Glad to hear you liked it!
This is perfect video on heatmap I saw,man I was tired searching the whole net for a proper video
Awww - thank you! So glad it helped and that you found what you were looking for!
Excellent Video, keep them coming!
You got it! And thanks very much 😀
Great video, thanks a lot :)
Awesome!!! Nicely explained.
Thanks so much - cheers!
WoOOooooWw It was Really useful for me! Thankew so much. Thanks for Github link also you made drawing charts sooooo easy!
So glad to hear the video and GitHub link helped!
Spot on!!
Thank you! Glad you liked it 😀
fantastic ! what a video !!!
Thank you - glad you enjoyed it!
Liked and subscribed. Just found your channel today on my first official research to learn Seaborn. And I’m glad I did.
Let’s do this, it looks really cool 😊
Right on! ⚡ Happy to have you subscribed and hoping you are enjoying seaborn!
A million thanks. 🙏
Most welcome! 😄
very helpful, Thanks
Your video is very useful, thank you very much!!
Wonderful -- glad this video was useful for you!
amazing and to the point
Thank you so much
tidy and useful video, thanks
Excellent - glad you enjoyed it!
Hello! Thank you for your awesome content!
By the way, I still have one question: is there a way to format xticklabels and yticklabels? Like setting the fontsize and so on, like you did with annot_kws for the content within the heatmap?
This girl is amazing
you deserve more subs
Oh thank you - slowly but surely!
Crystal clear explanation. Thanks Kim. Wound you upload a video for generating a "MASK" for the upper or lower triangle?
That's a great suggestion. I almost included mask but then decided not to for timing reasons. Maybe I will make a Seaborn Q&A video in the future! For now, I do have a bit of code to show what the mask argument does as the second question here: github.com/kimfetti/Videos/blob/master/Seaborn/Q_and_A/11_heatmap_Q_and_A.ipynb Hope that helps!
Amazing and wonderful , clean, crispy and crystal . Admire you from my heart. If it wont disturb you, would make a humble request on how to view the entire cmap list , for picking the liked one .. May god bless you to attain great heights .. Thanks and appreciating your effort and spirit you put up . .... Thanks and warm regards ..
Thank you so much. Your tutorial is best but they usually don't appear in the youtube search result. Hope your channel will reach to more students,
So glad you enjoyed this tutorial. And comments like these definitely help with UA-cam rankings -- so thank YOU! 👍
thx for describe
Muito bom!!!! Obrigado pela aula!!!
Excelente--de nada 😀
Thank you. Super helpful.
Is there anyway to add asterisk ✳️ for correlations above 60% and less than -60% on the heatmap?
Thank you mam.
Thank you for the video! I'm working on a heatmap and I'd like to change the order of the Y axis (essentially just invert the numbers). I'm using a pandas data frame to make my heatmap. Any advise? So far my googling has not gotten me too far! :)
thank you so much maam
Is it possible to sort the pd.crosstab data? So that more frequent boxes occur towards top left of the plot? Thanks
Good
Thanks for your awesome videos. What is the use of Heatmaps with R values for all input variables in your example? Are we identifying dependent variables to avoid confounding for regression, like cylinders and mpeg? Is it possible to have corr matrix heatmap for a specific output column and multiple input variables, without writing multi line codes!!
Good questions! Yes, one of the big uses for the correlation maps is that before building a linear regression model, say, you could see how correlated your dependent variables were with each other and potential drop variables that are highly correlated with one another or decide to use regularization. Or you might look to see which dependent variables are correlated with your independent variable to know which features to include in your regression model. Or just to do exploratory analysis and notice trends. Lots of options!
Regarding your second question: yes, this is possible through the Seaborn heatmap's mask argument. The main idea of mask is that you can make some of the heatmap's rectangles blank. So you could potentially mask all the rows you didn't want with just a few lines of code, but you would then need to do additional styling like removing some of the tick labels, etc. There's an example of the mask near the bottom of this notebook if you want to check it out: github.com/kimfetti/Videos/blob/master/Seaborn/Q_and_A/11_heatmap_Q_and_A.ipynb
This only works if your columns are titled with one word or words separated by underscores. If one of your columns for example is named "Area Name" then try adding it after .groupby('origin') and it just throws errors up.
Hi thank you for your video, i learnt alot from it. however, i am trying to include more than 2 paramters into the heatmap now, which I am having difficulties with. For example, i want to group by origin and model, while looking at the values for cylinders and displacement in the heatmap. Could i get some advice whether it is possible?
Very interesting question! I tested it out, and Seaborn does allow multi-indexed pandas dataframes (e.g. grouped by multiple categories). Seaborn will just hyphenate the row names; for example, if I group by origin and model year, the row names would be "europe-70" or "usa-82". You just have to make sure to input a pandas dataframe not a series, and the other thing to watch out for is scale. For example, if I look at average cylinders and average displacement, my heatmap won't show much information for average cylinders since the values are much smaller than average displacement. I added some additional code to my GitHub as a demo: github.com/kimfetti/Videos/blob/master/Seaborn/Q_and_A/11_heatmap_Q_and_A.ipynb
Hi, Can you make a video on the dynamic heatmap, a real-time heatmap in which values change in some time interval?
Thank you in advance.
Oooh -- that sounds fun! I'll definitely look into that. I have also been considering doing a series about Plotly so that we can interact with the visuals. Maybe I'll see if Plotly can do this. 😄
how do i animate seaborn heatmaps? i have a list that contains many heatmaps and want to aniamte them all.
Need to know from where you got the data set. It will really be helpful for beginner like me!!
Yes -- definitely good to know where the data is coming from. I typically use data from the Seaborn library itself for most of my videos. One of the first lines of code in this video, "cars = sns.load_dataset('mpg')" loads the car data from Seaborn and saves it in the dataframe called cars. 👍
Thank you for the wonderful explanation. Can you please make a next video on how to save the plot as image or pdf?
Whoa -- you read my mind! My next video IS about saving matplotlib figures. And the same code also works for seaborn plots. Video should be out early next week 😄
@@KimberlyFessel Awesome :) Thanks
Is this library a free one?
Mam please upload deep learning rare concepts, super useful for us and ML, and somehow to prepare for those stuff!
Thanks for the suggestion! I've been considering expanding out to more machine learning concepts. Hopefully at some point!
@@KimberlyFessel Yes Please!
Boxes in my heatmap are cut off from the top and bottom. any solution to that?
Yes! I almost included this in my video, but the problem should be fixed in the latest version of matplotlib. This issue occurred with matplotlib 3.1.1, but you can now upgrade your version of matplotlib and it should be fixed. If you don't want to upgrade, you can change the y-limits of your heatmap. After you make your heatmap, add the following code which will decrease the plot area of the heatmap:
bot, top = plt.ylim()
bot += 0.5
top -= 0.5
plt.ylim(bot, top)
I don't know much about Heatmap. I have a doubt. My main aim is to plot a Heatmap on an image. I have the x-cordinates and y-cordinates in a dataframe. How can I plot it? Is it possible?
Oh interesting! You want to overlay a heatmap on top of an picture image? I think you might have luck using matplotlib pyplot (plt): that is, plt.imshow() for the image part. This solution might help you get started: stackoverflow.com/questions/50091591/plotting-seaborn-heatmap-on-top-of-a-background-picture?rq=1 though you may need to adjust some things if you want elements at specific x- and y-coordinates.
@@KimberlyFessel Thank You
hey , nice video. Just a request, could you please touch upon the 'mask' argument a bit?
Yes -- good question! I almost included this option in the video but decided not to for time reasons. The mask argument lets you build heatmaps without some of the rectangles. The numpy array you pass to mask should be the same size as your heatmap dataframe/array. So if you have a = np.array([[1, 2, 3], [4, 5, 6]]) which is a 2x3 matrix, mask will also be 2x3 but will contain either True or False: True if you want to mask/remove the rectangle or False if you want the rectangle to appear. Let's say mask=np.array([[False, False, False], [True, True, True]]). Then only the top row of rectangles will show up if you do sns.heatmap(a, mask=mask). I also added your question to my Q&A doc if you want to see that code in action: github.com/kimfetti/Videos/blob/master/Seaborn/Q_and_A/11_heatmap_Q_and_A.ipynb
Hey Kimberly, it's really heartening that you replied. Thanks for that. Highly appreciated. 💛
How do I increase the size of the heat map in case I have lot of information
Sure thing - I usually update the size of my seaborn visuals with matplotlib. Include "from matplotlib import pyplot as plt" at the top of you code and then you can use plt.figure(figsize=(10, 8)), say, right about your heatmap code. That updates your figure to be 10 inches wide and 8 inches tall.
Mam plss make video on How to know which dataset to use which types of plot
Yes -- this is a great suggestion! I started working on a video like this last weekend but haven't fully figured out how I want it to go yet. I will keep working on it!
i want to take some of your personal training hours how i can reach to you?
I currently teach full time at a data science bootcamp called Metis, so I am not available for private training at this time. But I will continue posting more videos!
great videos mam.. where can i find the file used in the sample? thanks
oh sory i found it, its a built in datasets