Session 29 - Exploratory Data Analysis | Data Analysis Process | DSMP 2022-23

Session 29 - Exploratory Data Analysis | Data Analysis Process | DSMP 2022-23-------------------------------------------------------------------------------------------------------------------------------------------------------
Enroll in this Programme from our Website - learnwith.campusx.in/
KZbin Playlist - • CampusX Data Science M...
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Task Links
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colab.research.google.com/dri...
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Notebook Links
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colab.research.google.com/dri...
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Dataset Link
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drive.google.com/drive/folder...
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| Time stamp |
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0:00 Start
5:34 Session Start
11:25 Titanic Data Description
4:20 Why Do EDA
20:20 Column Types
23:10 Steps for EDA
26:00 Doubts
27:18 Univariate Analysis
32:40 Steps of doing Univariate Analysis on Numerical columns
36:45 Univariate Analysis on column Age
46:13 Univariate Analysis on column fare
54:45 Doubt
56:48 Steps of doing Univariate Analysis on Categorical columns
59:05 Univariate Analysis on column Survived
1:01:39 Univariate Analysis on column PClass
1:03:43 Univariate Analysis on column 'Sex', SibP, Parch
1:10:28 Doubt
1:12:35 Steps of doing Bivariate Analysis
1:29:59 Age vs Survival Bivariate Analysis
1:35:30 Doubt
1:36:40 Feature Engineering on Fare col
2:13:48 PClass vs Deck
2:20:42 End Session Doubt
#datanalytics #eda #exploratorydataanalysis #FeatureEngineering

[@burak9002]

I didn't understand what he says but appreciate his efforts. He contributed a lot to my perspective. Love from Turkey

[@vagrawal032]

mene khi aur data science ka course liya but pdta mein yha se ho thank you nistish sir aap jo content bna kar dete ho koi aur nhi de skta hai thank you so much sir

[@prabinkoirala5604]

very detailed amazing teaching

[@ajithpoojary5148]

Thank you. You are the best

[@chinmaymathur2430]

That was too good and now I understand how things in EDA are done. I want to understand multivariate analysis.

[@TheWierdVibe]

Great video sir❤

[@ashtar4894]

Superb content

[@Soman89]

Best Ever Explanation

[@tahseenabbas52]

Thank you so much 🧡

[@4signup452]

Thanks

[@user-zb9hz7dm2f]

Best of the Best

[@user-xt6dr9xj9d]

You are gem.

[@trishanudas6430]

The best

[@yasink18]

Bhai its so helpful.. I am looking for such kind of video.. Thank you so much🎉🎉

[@iam.naofil]

2:03:00 replacements = { 'Rev.': 'Other', 'Dr.': 'Other', 'Col.': 'Other', 'Dona.': 'Other', 'the.': 'Other', 'Jonkheer': 'Other', 'Major':'Other', 'Capt.': 'Other' } df['Title'] = df['Title'].replace(replacements)

[@akashgautam1909]

In case of replacing multiple titles, we can use replace function of series instead of string's.

[@noneone6207]

A GOD !!! A GOD!!! THANK YOU !!! THANK YOU VERY VERY MUCH !!!! LOVE YOU DUDE❤

[@gouravsinha268]

For the individual fare calculations can I groupby 'Ticket' and apply count function on it to get the number of individuals travelling on a ticket (because by SibSp and Parch addition only, we might miss the non SibSp/Parch person's travelling on same ticket) and then divide the fare column with that to get the individual fare?

[@rohandarji4942]

list banake for loop laga diya hota sir for replacing titles to others

[@amanrawat4908]

If we have multiple features(20+)and we want to visualise for eda . Which Graph to use ..

[@anshmatto2480]

why don't we handle categorical variables by doing label encoding

[@video_cilps]

Video start 5:00

[@princeprasad5733]

1:24:10 still they says that they are equal to men. but jab marne ke bare aye to ye hota ha.......

[@anshmatto2480]

please reply

[@luvofficial6216]

Nitish, if I enroll in the course, do I get previous lectures recording (paid wali) and doubt clearing support or not? Plz Ans..

[@campusx-official]

You will get

[@DeepSingh-gp7pk]

I confuse hindi or english .I learn data analysis in Hindi language but interview will in English language

[@memeserror2023]

same doubt from my side

[@numberphile6935]

Bro with such a mindset tujhe interview calls bhi nhi milenge

[@ghulamhussainjunejo2587]

ye to zulam he male zyada mar gaye

[@legendbuddys66]

face aisa bana diya tha bhai ne jab bande jyada bache ya bandiya....that was 🤣🤣🤣🤣🤣