I just completed your MatplotLib tutorial. It was great. I created a complete file of all you demonstrated. This satisfied two objectives. (1) I learned by doing and (2) by adding comments to the code as I went it will be a reference on how to do things in the future. Excellent class - keep up the good work (I'm starting the Seaborn tutorial now.
Great tutorial, thanks. Pretty close to perfect balance between describing too much and not describing enough... didn't feel like any of my time waste wasted, nor was I left confused. Cheers.
Just found out you had this selection of lectures on Python package functionalities and they rock big time! Thanks for the work you put into them and I look forward to other ones.
Thanks Derek. very helpful content especially the narration style is friendly and enhances the ability to absorb more information from what's being said!! Thanks a lot.
@@derekbanas I'm learning Data Science and Business Analytics. Saw your tutorial first time, subscribed now and hopefully will find more such amazing content. Really appreciate your efforts Man. Cheers!
10:22 "who tips 1 dollar and 1 cent?" rows 0 and 1 tipped to round the total_bill+tip to an even number AKA the best way to tip. In fact, 24.59% of the dataset tipped to an even number
Wow you’re a true legend. Keeping up the promise to teach the community is very hard, yet you always ensure to achieve it. Thanks a ton. I will checkout this video. Also I checked the description of this video and one of the next items mentioned therein was Scrapy, May I ask if you could start with base as BeautifulSoup and then build on scrapy? Because BeautifulSoup is simple yet powerful, it forces the programmer to do all the work with good understanding of web scraping. Also another request. Once you find time please check the possibilities of making tutorial on PyQtGraph. Thanks😇
I do my best to fulfill promises :) Yes I think BeautifulSoup would be great to cover. I've made videos on it in the past, but they could use an update. I'm looking into PyQtGraph
Hi Derek nice explanatory video. I'm wondering if you can make a tutorial on scikit learn. It would be a big help. Since your explanations are well fitted in my head. lol
strange that the box plot category doesnt show a box plot. a box plot finds the median which is the central line in that box. then if you slice the data set there, and find the median between the minimum and the median, you get teh lower quartile. and the median from the median to the maximum for the higher quartile. the quartiles and the standard deviation shouldnt be the same thing. the standard deviation for a normal set should be + - 34% from the median. not sure if im wrong, if the program is wrong, or if you are wrong.
Just what I wanted. Take lots of love, master. One more thing, which one would you prefer? Seaborn or matplotlib for basic visualization in data analysis.
Thank you so much for the content I subscribed to. Is it possible to assign a palette to the Hexagon Distribution chart? I tried it like this: g = sns.jointplot( x = "Price" , y = "Rank" , data = df , kind = "hex", height=10, palette= "husl") -- but the palette didn't worked, colours did not changed. :)
Hi, Derek. I want to thank you for your great work, it saved me a lot of time! But I also have a question - when I'm tryint to set a sns style, I'm getting an error: 'str' object is not callable. Do you have any idea, how to deal with it?
how to use aggregate functions(count, sum ,min, max) while plotting in seaborn. for example I want to count some value in y axis again some value in x axis
Hello, I have a question for corr() when we were using it in Heatmaps @ 34:00 I received an error while using .corr() in the line > crash_mx = crash_df.corr() > crash_mx It was a ValueError stating the it could not convert string to float for the abbrev columns. > ValueError: could not convert string to float: 'AL' I was able to kinda solve this by telling it to only take in numeric datatypes using pandas > numeric_columns = crash_df.select_dtypes(include=['number']).columns > crash_mx = crash_df[numeric_columns].corr() but is there a better way of doing this? or did I make a dumb mistake- Thanks for creating this video!
Isn't pyplot, also built on matplotlib, and also attempts to simplify it's use by including panda, etc? When would you use seaborn vs just matplotlib? BTW, seaborn/panda can be used offline, but if you use Jupyter, everything, including the data, must be connected to the internet?
00:00 Intro
00:28 Setup
02:17 Import Data & Datasets
04:22 Distribution Plot
06:53 Joint Plot
08:19 Hexagon Distribution
08:36 KDE Plot
09:06 Pair Plot
12:05 Rug Plot
13:05 Styling
17:42 Bar Plot
19:35 Count Plot
20:41 Box Plot
23:17 Violin Plot
24:42 Strip Plot
26:50 Swarm Plot
28:07 Palettes
32:18 Heatmaps
38:33 Cluster Map
42:11 Pair Grid
46:57 Facet Grid
54:47 Regression Plots
Dear Sir,
I can not find the CSV file for practicing. would you please tell me how do I get this file??
@@md.ashikmahamud5412 put the csv file in the same folder of your project.
@@md.ashikmahamud5412 check github.com and search for the csv file then download, copy then paste to the jupyter folder
Great tutorial. Appreciate you going into detail on the various options.
If you're looking at the comments to see if this is worth your time, I can assure you that it is. Loads of value obtained from this video! Great job.
Thank you for the nice compliment :) I tried to do my best
10:22 the total bill was 16.99, so the extra cent makes it an even bill.
loved the video, very useful
I just completed your MatplotLib tutorial. It was great. I created a complete file of all you demonstrated. This satisfied two objectives. (1) I learned by doing and (2) by adding comments to the code as I went it will be a reference on how to do things in the future.
Excellent class - keep up the good work (I'm starting the Seaborn tutorial now.
Very well explained at a great pace. I gained a lot from this 1 hour tutorial. Thank you!
I've read the video's description.
I've seen linear algebra and calculus too.
You will be a life saver, Derek.
Keep it up!
I'm trying to do my best 😁
Wow ... Thank you so much again ... I was looking for both latest matplotlib and seaborn tutorial ... You did both !!!! What a coincidence !!!
Thank you 😁 Plotly is coming next so we can interact with our plots!
Omg i was about to ask the same !!!! 🔥🔥🔥 Thank you so much !!!!
Thanks a LOT Derek!
Have been waiting for this one!
You are a LEGEND🙏
I'm very happy that I could help! Plotly is next
This is probably the greatest tutorial I have watched. Great work, and thank you for putting the time into this!
Thank you for taking the time to tell me you liked it :) I appreciate it!
Thank you so much for taking the time to make this video! Great introduction to data visualization, will be using my learnings for my M.S. thesis!
This intro to Seaborn is amazing. Thank you so much for this!
Thank you very much :) Happy I could help
Great tutorial, thanks. Pretty close to perfect balance between describing too much and not describing enough... didn't feel like any of my time waste wasted, nor was I left confused. Cheers.
It couldn't have been better!!! You are a legend! Perfect pace, well at least for me
Thank you for taking the time to tell me you enjoyed it :) I appreciate it!
S tier tutorial, fast and to the point. Love your content Derek. Thank you!
Amazing tutorial. It helped me step up my exploratory data analisis, specially the pair+facet grid.
Just found out you had this selection of lectures on Python package functionalities and they rock big time! Thanks for the work you put into them and I look forward to other ones.
Thank you Happy to be of help :)
Very well done tutorial! Thank you so much, you deserve a thumb up!
Thank you :) I'm happy I could help
One of the best videos on seaborn
Excellent tutorials and to the points. Loving it the way you explain. Thank you, Derek.
Thanks Derek. very helpful content especially the narration style is friendly and enhances the ability to absorb more information from what's being said!! Thanks a lot.
Thank you :) I'm very happy that you enjoyed it
@@derekbanas I'm learning Data Science and Business Analytics. Saw your tutorial first time, subscribed now and hopefully will find more such amazing content. Really appreciate your efforts Man. Cheers!
10:22 "who tips 1 dollar and 1 cent?"
rows 0 and 1 tipped to round the total_bill+tip to an even number AKA the best way to tip. In fact, 24.59% of the dataset tipped to an even number
A very detailed, organised and concise tutorial - Kudos.
Thank you for taking the time to write me a nice message 😁 I appreciate it
One of the best !!!! Really enjoyed watching this.
Awesome tutorial, thanks a million times!
Amazing content, simple and straight to the point. Thank you!
Thank you for taking the time to tell me you found it useful
Thanku so much Derek for a wonderful seaborn tutorial. It was in-depth,interesting.🥰
Thank you for taking the time to tell me you enjoyed it :) I appreciate it!
Thank you soo much,
Thank you soo much,
It help me a lott
You are a Legend....
this is an awesome tutorial on Seaborn! Thanks a lot
Thank you for the nice compliment :)
Great tutorial man! Helped me a lot!
I love the way you say data.
Wow you’re a true legend. Keeping up the promise to teach the community is very hard, yet you always ensure to achieve it. Thanks a ton.
I will checkout this video. Also I checked the description of this video and one of the next items mentioned therein was Scrapy, May I ask if you could start with base as BeautifulSoup and then build on scrapy? Because BeautifulSoup is simple yet powerful, it forces the programmer to do all the work with good understanding of web scraping.
Also another request. Once you find time please check the possibilities of making tutorial on PyQtGraph.
Thanks😇
I do my best to fulfill promises :) Yes I think BeautifulSoup would be great to cover. I've made videos on it in the past, but they could use an update. I'm looking into PyQtGraph
Derek Banas thanks 😊
Hi! How are you? I hope you are doing well. I can’t believe that I just found your channel today. Thank you very much for all your content.
I'm always doing great even with a broken foot :) I hope you are doing well also. I'm very happy that you are enjoying the videos
Great video Derek!!
Thank you very much :)
Very nice crash course on seaborn, looking for more videos like this.
Thank you :) I have one for pretty much every data science library
Hi Derek nice explanatory video. I'm wondering if you can make a tutorial on scikit learn. It would be a big help. Since your explanations are well fitted in my head. lol
Nice tutorial, seaborn is one of my favourite labrary
how to show compact letter display (a, ab, b, bc)to show which one are significantly difference on x-axis when plotting in seaborn?
Great lesson for all. Thanks a lot.
Thanks a LOT Derek SIR!
You are a LEGEND🙏
it was so perfect and useful
good luck
Thanks Derek! Awesome video!
Thank you :) I'm happy I could help
strange that the box plot category doesnt show a box plot.
a box plot finds the median which is the central line in that box. then if you slice the data set there, and find the median between the minimum and the median, you get teh lower quartile. and the median from the median to the maximum for the higher quartile.
the quartiles and the standard deviation shouldnt be the same thing. the standard deviation for a normal set should be + - 34% from the median.
not sure if im wrong, if the program is wrong, or if you are wrong.
thank you so much for this course, dude!
Excellent Presentation on Seaborn Sir 🙂 ,,.,.. I am your latest subscriber
Very clear !!! Thank you so much.
Amazing teaching. Thank you!
Great tutorial, dude. Helped me a lot
Thank you :) I'm very happy that I could help
This video was awesome! Thank you so much :)
Thank you very much :)
Thanks, Derek. Very Cool!
I'm very happy you liked it :)
@@derekbanas Can't wait for the plotly video!
Great tutorial. would you please do another tutorial and teach multiple sub-plots using Matplotlib and Seaborn. (use for loop to plot )
Thank u...Its really awesome...
Legit, awesome work.
Thank you 😁
Just what I wanted. Take lots of love, master. One more thing, which one would you prefer? Seaborn or matplotlib for basic visualization in data analysis.
I'm happy you liked it :) Matplotlib is used when you want a lot of control and Seaborn in other situations.
Alright gotcha. In that case seaborn is the one for me then. Thanks again
Top class. From Australia with love. KUDOS
Thank you very much :)
really desperately needed you to use that csv dataset!
Excellent video! Thank you very much
Amazing video !! Thanks for sharing your knowledge =)
Thank you for the nice compliment :) I'm happy I could help
Superb quality!
Thanks Eric.
Happy to help, but my names Derek :)
@@derekbanas I am extremely sorry.
That's no problem. I have a weird name that a lot of people mess up
Very nice. Big up
Awesome Derek ! Thanks
good explanation!
Always the best, in the world! 💯💯💯💯
Thank you very much :) I always try to do my best
As usually, amazing thanks a lot :)
Can you please show how to plot recision boundary with multiple features? Or how to plot linear regression with multiple features?
Really good tutorial!
very big thank u sir ❤❤
This is amazing, thanks!
great video
Fantastic tutorial.
Thank you very much :)
Hey Derek! I just wanted to know how to show whiskers in boxplot as standard deviation and not as a percentile division?
You can manipulate the whiskers using the whis parameter seaborn.pydata.org/generated/seaborn.boxplot.html
Brilliant explanation
Thank you Happy to be of help :)
Waiting for tutorial to chickens.
I can do 1 more live stream for the chickens if enough people up vote this comment? They are very cute and active now.
@@derekbanas omg plesse do it
Beautiful. pretending I understand what all the plots actually mean
Awesome!!! TQVM!!
You are amazing. Thank you!
You are very kind :) Happy I could help
Very useful. Amazing' thank you so much for this
Thank you very much :)
Support content💪
Thank you :)
Thanks man
Happy to help :)
thanks mr. for this video
I appreciate your video for us :) THank you :)
I’m very happy to be of help :)
Thanks!
thank you!
Thanks, That is great
Thank you very much :)
Thank you so much
Superbe ! 😊
thanks ❤
🔥
awesome !
Thank you so much for the content I subscribed to. Is it possible to assign a palette to the Hexagon Distribution chart? I tried it like this: g = sns.jointplot( x = "Price" , y = "Rank" , data = df , kind = "hex", height=10, palette= "husl") -- but the palette didn't worked, colours did not changed. :)
Does anyone know how you would label each data point so the dataframe values showed above each plot on the graphs?
Seems easier than matplotlib
Hi, Derek. I want to thank you for your great work, it saved me a lot of time! But I also have a question - when I'm tryint to set a sns style, I'm getting an error: 'str' object is not callable. Do you have any idea, how to deal with it?
may be you passed dataframe variable as a string
how to use aggregate functions(count, sum ,min, max) while plotting in seaborn.
for example I want to count some value in y axis again some value in x axis
What a legend
Merci Grandement (:
C'est un plaisir pour moi d'être en mesure d'aider
Hello, I have a question for corr() when we were using it in Heatmaps
@ 34:00
I received an error while using .corr() in the line
> crash_mx = crash_df.corr()
> crash_mx
It was a ValueError stating the it could not convert string to float for the abbrev columns.
> ValueError: could not convert string to float: 'AL'
I was able to kinda solve this by telling it to only take in numeric datatypes using pandas
> numeric_columns = crash_df.select_dtypes(include=['number']).columns
> crash_mx = crash_df[numeric_columns].corr()
but is there a better way of doing this? or did I make a dumb mistake-
Thanks for creating this video!
Thanks 😊
Happy to help 😁
Hey anyone know how I can create 2 separate box plots next to each other rather than one above the other?
Isn't pyplot, also built on matplotlib, and also attempts to simplify it's use by including panda, etc? When would you use seaborn vs just matplotlib?
BTW, seaborn/panda can be used offline, but if you use Jupyter, everything, including the data, must be connected to the internet?