Table Of Contents
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Objective
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Importing Packages and Collecting Data
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Data Profiilling & Preprocessing
- 3.1 Pre Profilling
- 3.2 Pre Processing
- 3.3 Post Profiling
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Analysis Through Data Visualization
- 4.1 What is the total Count of Survivals An Victims?
- 4.2 Which Gender has more Survival Rate?
- 4.3 What is Survival rate based on Person type(Male,female,child)
- 4.4 Did Economy Class had an impact on survival?
- 4.5 What is the survival Probality based on Embarkment of Passengers?
- 4.6 How is far distributed for the passenger?
- 4.7 What was Average Fare by Pclass & Embark location ?
- 4.8 Segment age in bins with size of 20. Also correlate Age with Survival.
- 4.9 Did solo Travelling has less chances of Survival?
- 4.10 How did total family size afected Survival Count?
- 4.11 How can you correlate Pclass/Age/Fare with survival rate/
- 4.12 Which feature had most impact on Survival rate?
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Conclusions
Objective:
The Objective here is to conduct Exploratory Data analysis( EDA) on Titanic Dataset in oreder to gather insights and eventually predicting survior on basics of factors like Class,Sex, Age, gender,Pcalss, etc.
Why EDA:
- An approach to summarize, visualize, and become intimately familiar with the important characteristics of a dataset.
- Defines and Refines the selection of feature variables that will be used for machine learining.
- Helps to find hedden insights .
- It privides the context needed to develop an appropriate model with minimun erroes.
About Events:
The RMS Titanic was a British passenger liner that sank in the North Atlantic Ocean in the early morning hours of 15 April 1912, after it collided with an iceberg during its maiden voyage from Southampton to New York City. THere were
an Estimated 2,224* passengers and crew aboard the ship, and more than 1,500 died, Making it one of the deadliest commercial Peacetime maritime disasters in morden History. The sensational tragedy shocked the international community and led to better safety regulations for ships.