Tutorial 23-Univariate, Bivariate and Multivariate Analysis- Part2 (EDA)-Data Science

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[himanshumangoli]

ur teaching skills are damn good man keep it up man lots of respect

[SwavimanKumar]

One small correction. That Hue is pronounced "Hiu" instead of "Hui". You are making absolutely great content. Love them all. Keep growing. (Y)

[sumantwankhede]

Just one tiny correction for Univariate x label should be Sepal Length ...all other good ..Thanks Krish

[krishnasahoo]

thank you so much for this..I dont know why I was unable to understand this concept. Thanks for this

[wasimshaikh]

X lab should have been 'Sepal length' instead of 'Petal Length'

[sengnawawnghkyeng]

The best explanation about these variates ...

[pbanerjee]

Great job. Your sincerity shows. Wonderful effort.

[sunitapatil]

you are grate sir .i am really grateful to your vedios thank you thank you so much sir.

[piushsingh]

univariate, bivariate and multivariate analysis should be done before data prep-processing or Reply...

[ratheesh_tabla]

May be I am wrong, should that be "sepal length" instead of "petal length" in xlabel? based on your plot variables or feature used for univariate analysis

[nabiltech]

So here are objective u can obtained by using this statistical method,

1)Which features have good impact for ur model
2)Which type of algorithms u should choos

[kalyanipadaraju]

Thank you so much sir . Great explanation

[tanujsharma]

sir i think there is 'sepal length' instead of 'petal length' in xlabel. am i wrong or right??

[Fallen]

Another easy way to do the bivaruate plot at 11:20 is sns.scatterplot(df['sepal_length'], df['sepal_width'], hue=df['species'])

[krishnakanthbandaru]

Hi I have a doubt these plots are ok for small datasets and interesting while learning but is these graphs helps when handling real time data or while working with real data science projects.

[rohithmn]

Thanks for the excellent tutorial..!
But this works well for classification problems. How shall we perform the similar analysis for Regression problem..!?

[venkateshbb]

Thanks for tutorial.Please arrange tutorials in proper sequential of related tutorials.

[marioluoni]

In the uni-variate analysis, why do you put all data points on the same level? By putting them onto different levels, e.g. by setting np.zeros_like()+0, np.zeros_like()+1 and np.zeros_like()+2, it will be very clear that these 3 data sets overlap very heavily as opposed to what you say @9:00 (unless I have misunderstood what you said there). Otherwise great lectures, thanks a lot!

[simanchalpatnaik]

Hi Krish, Why you are keeping the Y-axis as 0. In the previous lecture also it's not explained. In graph you just kept it as 0.
Please reply.

[sohamsarkar]

Isn't multivariant analysis a consolidated representation of bivariant analysis, where all possible combinations of bivariant analysis are represented together?