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
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.
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'])
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😄
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
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!
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.😵😵
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.
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.
@@akashmanojchoudhary3290 df[diagnosis].value_counts.plot(kind='"bar") or sns.countplot(df['diagnosis'],hue=df['label_column']) or sns.countplot(df['diagnosis'])
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
Best video seen on EDA till date...Great Work!
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
ab kya kar rahe ho ?
@@sid_x_18 +1
Thoroughly enjoying this series. Thank you so much Nitish!
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)
groupby is not working for my case
thank you bhai
thanks bro
thankyou buddy
@@CatalystOfMisfortune i am facing the same problem
writing code in notebook alongside with you is a great way to learn things, thanks!
Every time amazing information comes.Thanks, sir
Yout videos are amazing 🔥🔥,
You are most underrated TH-camr😶
BEST VIDEO IN ENTIRE UNIVERSE FOR EDA
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.
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'])
hey, 26:10 (titanic.groupby('Embarked').mean()['Survived']*100) TypeError: agg function failed [how->mean,dtype->object] please help
@@VaishnaviShrivastava-z2b (titanic.groupby('Embarked')['Survived'].mean()*100)
Course Started : ML
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Lecture-11: 16/08/2024
Lecture-12: 16/08/2024
Lecture-13: 17/08/2024
Lecture-14: 17/08/2024
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Lecture-19: 21/08/2024
Lecture-20: 21/08/2024
Lecture-21: 22/08/2024
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😄
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
hey, 26:10 (titanic.groupby('Embarked').mean()['Survived']*100) TypeError: agg function failed [how->mean,dtype->object] please help
Beautiful way of doing EDA
Best Channel on the Earth to Learn Data Science from Scratch🔥🔥🔥🔥
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!
did you get the internship , i think you need to do more projects
great exxplanation
very in sensitive
Salute hai sir aapko kya padhate aap
EDA is really an art!
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.😵😵
Awesome content and explanation. Thank you!
didn't find better playlist than this TYSM❤️
Very informative lecture and great analysis
CampusX unmatched...Love from Pakistan
I think finding great insights will take u long long way
brother the way u explained i m loving it :)🙂
Best Video ever seen for ML
you are best sir
26:14 not sherlock holmes its being ACP Pradyuman from CID
tx a lot ...made easy to my learning ...
your videos are very helpfull
Awesome. Gave me a lot of insights.
Thankyou Sir
Thanks
you are the best sir.
At 16:25 which extension you have used to check for hue feature in distplot
shift+tab
thanxx nitish
Amazing explanation .. thanks
slight modification in code at 24:51 is---- (titanic.groupby('Pclass').mean('Survived')['Survived']*100).plot(kind='bar')
(titanic.groupby('Sex').mean('Survived')['Survived']*100)
(titanic.groupby('Embarked').mean('Survived')['Survived']*100)
Thanks a lot man
how to know which pair/tuples should be selected for the analysis
In scatter plot, where did you get df from? it should have been tips in hue, style and size.
Right
thank you
Thankyou so much Sir
awesome , 0 to HERO
Thank you very much sir. you are great
Pretty nice content. Thankyou!
25:17
The Boyz 😂
I am a big fan of you
awesome
free me premium quailty lactures
thank you sir
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 😢😢
coz that probability of survial in class 1,2,3 . they have no relation. so if survival probability is 0.6 in pclass1 then p(died) = 0.4
amazing video...
thanks alot brother
bande uhape ultakgaye sare... nice sir..😀😀
Didn't know that it is possible to load data using the seaborn library.
lol same
😂😂😂@@001_chandrikasarkar7
You cant load all dataset.you can load only inbuit dataset
I like ur videos
At 17:46 we can use this code:
sns.kdeplot(x='Age' ,data=titanic, hue='Survived')
great
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.
same doubt
have u found the ans ?
Survived
0->Dead 1->Survived
So, the mean will give Survived
titanic.groupby['Pclass'].mean()['Survived']
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.
same I also come across this
how to plot too many categorical values in seaborn, for eg- I've 150 diseases in diagnosis column. How to plot it?
can anyone help me with this?
@@akashmanojchoudhary3290 df[diagnosis].value_counts.plot(kind='"bar") or sns.countplot(df['diagnosis'],hue=df['label_column']) or sns.countplot(df['diagnosis'])
load dataset not working tried everything updating python,notebook what to do
guru
plz tell how to download csv file that use in this vedio
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()
barplot() takes from 0 to 1 positional arguments but 2 were given sir ye error a rha hai
this is bcz the seaborn libraby is updated now , you can check the seaborn documentation and understand that plotting function
sns.barplot(x=titanic['Pclass'],y=titanic['Age'])
8:11 You're using sex, smoker and size of someother dataset. It should be of tips but you've written df.
done
Done
Day2-
date:10/1/24
6:59 Now one thing I analyze girl are stingy because scatterplot proved...😅😂
Hindi sunkr, better feel hota h 😅
28:41
date 11 jan 2024
day 21
25:17, "clearly dikh raha hai ki female ko bachaya gaya, aur bande ludhak gae saare "🤣🤣🤣🤣🤣🤣🤣
Bande bahot ludak gye was personal hahahaahaha
Day-22
Done
not able to load dataset pls help
tips=sns.load_dataset("tips") not working
Have you got the solution?
I was also facing issue with loading flights and iris, try loading it multiple times , you'll get it
@@Engineer884 I have the solution, I was just asking if he needs it now.
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
I don't know but may be he used seaborn instead of pandas to load the data
tips hi likhna chahiye tha
done