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.
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 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😄
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!
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'])
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.
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