Seaborn histplot | How to make a Seaborn histogram plot with Python code

[@sprachenwelt]

Kimberly, these are really great videos. At higher age, I am hitting University again for DH and python, pandas and co are giving me a hard time. You make it all look so easy, and it functions with me. Thank you so much. God bless you and have a good start into 2023.

[@rakeshkumarkuwar6053]

Thanks Kimberly, for making such a detailed video on each plots. Loved the whole playlist :)

[@kaduflutist]

Thanks so much for the wonderful video tutorial. You have what it takes to teach and speak clearly whatever the subject is. Awesome!

[@wluedi]

On KZbin, in a class that I am taking online, the written documentation, everything associated with these packages are a steaming pile of 💩. Your videos and your way of presenting this material is the best thing that I have seen anywhere. There really is no comparison. You have an amazing gift in teaching this material. If you did a subscription website about data science and all these packages, I would subscribe gladly. I think a lot of people would. Excellent work. Some of the best datasci or even comsci teaching videos that I have ever seen.

[@amanpatyal2187]

playing with keywords is always a great deal, beautiful explanation of all useful keywords.....

[@KimberlyFessel]

Glad you enjoyed it!

[@GregThatcher]

Thanks!

[@KimberlyFessel]

You’re very welcome! Thanks for the support - cheers! 😀

[@olakwiecinska6471]

Thank you so much for your hard work put into this video! It helped me a lot :)

[@KimberlyFessel]

Oh wonderful! Very glad to hear my video was helpful! 😄

[@gnaneshgn8341]

So cool and easy to learn...Nice Explanation ..please do more .Thank you..!!

[@HR97BH]

Ur lectures are awesome....😍 Keep going🔥

[@KimberlyFessel]

Thank you! And will do 🔥😎

[@digigoliath]

Quick & to the point! Sweet!! TQVM.

[@KimberlyFessel]

Thanks! Glad you enjoyed this video! 😄

[@anshu_DS]

You kept it so simple . Nice Explanation :):)

[@KimberlyFessel]

Thank you - I do my best to break it down and keep it simple! 😄

[@enriquealvaro4991]

your videos are amazing!!! thank you

[@KimberlyFessel]

So glad you like them - cheers!

[@jawuku3885]

Thank you for the videos! Is it possible to make a 3D plot of the bivariate data, using a histplot or KDE plot, so for example you would see "mountain" peaks for high frequencies, and "lowlands" for low frequencies?

[@AlfredoBevacqua]

Thank you very much Kimberly :)

[@KimberlyFessel]

You're very welcome! 😄

[@rishidixit7939]

In case of the Bivariate Histogram can that be converted to 3D Histogram and viewed ?

[@KimberlyFessel]

Not much 3D plotting in Seaborn as far as I know. Matplotlib does offer some though: kzbin.info/www/bejne/naLSfX99nMeYd6c

[@emanabdelhaleem7561]

Thank you I think that the series would be much better if it was distinguished when and why to use these different graphs and what do they mean statistically

[@KimberlyFessel]

Thanks for watching and thanks for the tip! I've definitely considered doing more videos about selecting an appropriate visualization technique. 👍

[@_guzheng7585]

Thanks for this video. You're amazing. It helps a lot.

[@KimberlyFessel]

So glad you enjoyed the video and that it helped!

[@Xzizia92]

Thank you for an interesting and well put tutorial on how to use Seaborn! I have one question regarding the Hue. I get this error when calling for a column name that has 8 different words in it.ValueError: The following variable cannot be assigned with wide-form data: `hue`. Any idea why this is happening? When I'm plotting a sns.relplot with the same data it works fine

[@sobersabin]

hello madam, i have version 10, how can upgrade to 11.can you please tell me.

[@KimberlyFessel]

Hi -- do you use pip? If so you can run "pip install seaborn -U" to upgrade to the latest version in your Terminal or Shell. Or you can run "!pip install seaborn -U" from within a Jupyter Notebook.

[@johanestebangaleanocarvaja8941]

hey! how can I create a histogram with the horizontal axis as the data and the vertical axis as the absolut frecuency?? If anyone can help me I will be very grateful, thanks in advance!

[@KimberlyFessel]

Hi there - the seaborn histplot has an argument called "stat" that may be helpful. The default is stat='count', which just counts up the number of observations in each bin. But you also have the options of 'frequency', 'percent', 'probability', and 'density'. See the seaborn docs (seaborn.pydata.org/generated/seaborn.histplot.html) for more information. 😄

[@randagha3283]

Thank you for the amazing explanation, I have a qs: what plot should i use to view distribution? Only histogram?

[@KimberlyFessel]

You're welcome! The histogram is probably the most well known distribution plot, but there are a few others. The KDE plot is a way to see a smoothed-out, continuous approximation of your data's distribution function. (You can check out my KDE plot video if you want to learn more: kzbin.info/www/bejne/enTKgYWXfqmMjqM) Seaborn also has a rug plot, which is basically a histogram with a zero-width bar, and an ecdf plot that looks more at the cumulative distribution. I'm planning to also make a video about the Seaborn displot which combines all of these!

[@vinitasharma5025]

very useful video

[@KazimierzBecek]

Great!

[@LuisLopez-ns6yg]

Thank you :D

[@KimberlyFessel]

Most welcome! 😄

[@yousofahmad6790]

thanks a lot

[@muhammadzohaibkhan2707]

Thanks alot mam

[@KimberlyFessel]

You're very welcome!