EDA using Bivariate and Multivariate Analysis | Day 21 | 100 Days of Machine Learning 

Date : 27 July Status : Done ✅ Summary: Learn about bivariant and multivariate analysis , bivariant analysis means analysis two columns together , and multivariate means analysing two or more columns together. 1. Numerical Numerical ☘️ Scatterplot ☘️ Pair plot ☘️ Line plot 2. Numerical - Categorical ☘️Boxplot ☘️ Barplot ☘️ Distplot 3 Categorical Categorical ☘️Heatplot ☘️Clustermap

Best video seen on EDA till date...Great Work!

Course Started : ML Lecture-01: 14/08/2024 Lecture-02: 14/08/2024 Lecture-03: 14/08/2024 Lecture-04: 14/08/2024 Lecture-05: 14/08/2024 Lecture-06: 15/08/2024 Lecture-07: 15/08/2024 Lecture-08: 15/08/2024 Lecture-09: 15/08/2024 Lecture-10: 15/08/2024 Lecture-11: 16/08/2024 Lecture-12: 16/08/2024 Lecture-13: 17/08/2024 Lecture-14: 17/08/2024 Lecture-15: 18/08/2024 Lecture-16: 19/08/2024 Lecture-17: 20/08/2024 Lecture-18: 20/08/2024 Lecture-19: 21/08/2024 Lecture-20: 21/08/2024 Lecture-21: 22/08/2024

BEST VIDEO IN ENTIRE UNIVERSE FOR EDA

Yout videos are amazing 🔥🔥, You are most underrated RU-vidr😶

Thoroughly enjoying this series. Thank you so much Nitish!

Every time amazing information comes.Thanks, sir

I really enjoy the way you go deep in analysis

5:00, scatterplot might have updated, correct way: sns.scatterplot(x=tips['total_bill'],y=tips['tip']) 6:26, sns.scatterplot(x=tips['total_bill'],y=tips['tip'],hue=tips['sex']) 10:30 sns.barplot(x=titanic['Pclass'],y=titanic['Age']) 16:10 sns.displot(x =titanic['Age'],kde=True,stat='density',linewidth=0) 18:45 sns.histplot(titanic[titanic['Survived']==0]['Age'],kde=True, stat="density", linewidth=0,fill=False) sns.histplot(titanic[titanic['Survived']==1]['Age'],kde=True, stat="density", linewidth=0,fill=False)

writing code in notebook alongside with you is a great way to learn things, thanks!

Hello sir, amazing content. I had one request. Could you make a video on how to perform hypothesis testing in python while doing bivariate analysis? Would be really helpful to a lot of people. Thanks.

EDA is really an art!

20:00 distplot() is depreciated by seaborn . For kdeplot, which gives probability density, it is giving slightly different graph, which is calculated in above video

slight modification in code at 24:51 is---- (titanic.groupby('Pclass').mean('Survived')['Survived']*100).plot(kind='bar')

Best Channel on the Earth to Learn Data Science from Scratch🔥🔥🔥🔥

didn't find better playlist than this TYSM❤️

slight modification in code at 33:17 is new = flights.groupby('year').sum('passengers').reset_index() and sns.lineplot(x=new['year'],y=new['passengers'])

CampusX unmatched...Love from Pakistan

brother the way u explained i m loving it :)🙂

great exxplanation very in sensitive

Salute hai sir aapko kya padhate aap

Beautiful way of doing EDA

you are best sir

Best Video ever seen for ML

Very informative lecture and great analysis

Sir aap jo jo bhi dataset use krte ho please uski Excel file ka link description me de diya kro ese sahi se practice nhi ho pati and really your videos are so awesome😄

Thankyou Sir

I think finding great insights will take u long long way

your videos are very helpfull

awesome , 0 to HERO

26:14 not sherlock holmes its being ACP Pradyuman from CID

Awesome content and explanation. Thank you!

25:17 The Boyz 😂

Great explanation. I applied pair plot on a 17 column long dataset . And it showed me more than 100 plots. I don't know how to pick which one and understand.😵😵

Sir is your playlist of 100 days of Machine learning enough to Applying for internship in company? Or i need to do projects more upon these topics and practicals?Please suggest me. Thanks!

you are the best sir.

Awesome. Gave me a lot of insights.

tx a lot ...made easy to my learning ...

Thanks

19:18 why aren't the probabilities of dying and surviving not adding up to 1 ? My mind can't understand this fallacy. Koi samjaho please 😢😢

Didn't know that it is possible to load data using the seaborn library.

Amazing explanation .. thanks

Thank you very much sir. you are great

Pretty nice content. Thankyou!

bande uhape ultakgaye sare... nice sir..😀😀

At 16:25 which extension you have used to check for hue feature in distplot

Hey guys, an update on Seaborn. There is now a 'Future Warning' when ever you run the function 'distplot' saying that it will be discontinued in the future. So I did a little research and found a suitable replacement to it on stack overflow sns.histplot(x =titanic[titanic['Survived']==0]['Age'],kde=True,stat='density',bins = 50). You wont be able to turn off hist tho.

I am a big fan of you

free me premium quailty lactures thank you sir

thanxx nitish

thank you

amazing video...

awesome

thanks alot brother

I like ur videos

6:59 Now one thing I analyze girl are stingy because scatterplot proved...😅😂

done

great

At 17:46 we can use this code: sns.kdeplot(x='Age' ,data=titanic, hue='Survived')

how to know which pair/tuples should be selected for the analysis

guru

In scatter plot, where did you get df from? it should have been tips in hue, style and size.

load dataset not working tried everything updating python,notebook what to do

25:17, "clearly dikh raha hai ki female ko bachaya gaya, aur bande ludhak gae saare "🤣🤣🤣🤣🤣🤣🤣

Bande bahot ludak gye was personal hahahaahaha

Done

Day2- date:10/1/24

plz tell how to download csv file that use in this vedio

8:11 You're using sex, smoker and size of someother dataset. It should be of tips but you've written df.

Hindi sunkr, better feel hota h 😅

how to plot too many categorical values in seaborn, for eg- I've 150 diseases in diagnosis column. How to plot it?

barplot() takes from 0 to 1 positional arguments but 2 were given sir ye error a rha hai

I have one doubt, Survive have two value 0 and 1. titanic.groupby['Pclass'].mean() how to know whether this give information survived passenger or dead passenger.

date 11 jan 2024 day 21

28:41

slight modification in code 7:45 sns.scatterplot(x=tips['total_bill'], y=tips['tip'],hue=tips['sex'],style=tips['smoker'],size=tips['size']) plt.show()

not able to load dataset pls help tips=sns.load_dataset("tips") not working

sns.scatterplot(tips['total_bill'],tips['tip'],hue=df['sex'],style=df['smoker'],size=df['size']) sir shouldn't the smokers/size wala dataset be tips. you have written df. im confused here

Thankyou so much Sir