A data preprocessing and feature engineering script for a machine learning pipeline is prepared.

FEATURE ENGINEERING

Business Problem: A data preprocessing and feature engineering script for a machine learning pipeline needs to be prepared. It is expected that the dataset will be ready for modelling when passed through this script.

Story of the Dataset:
The dataset is the dataset of the people who were in the Titanic shipwreck. It consists of 768 observations and 12 variables. The target variable is specified as "Survived";

0: indicates the person's inability to survive.

1: refers to the survival of the person.

ATTRIBUTES:

PassengerId: ID of the passenger

Survived: Survival status (0: not survived, 1: survived)

Pclass: Ticket class (1: 1st class (upper), 2: 2nd class (middle), 3: 3rd class(lower))

Name: Name of the passenger

Sex: Gender of the passenger (male, female)

Age: Age in years

Sibsp: Number of siblings/spouses aboard the Titanic
Sibling = Brother, sister, stepbrother, stepsister
Spouse = Husband, wife (mistresses and fiances were ignored)

Parch: Number of parents/children aboard the Titanic
Parent = Mother, father
Child = Daughter, son, stepdaughter, stepson
Some children travelled only with a nanny , therefore Parch = 0 for them.

Ticket: Ticket number # Fare: Passenger fare

Cabin: Cabin number

Embarked: Port of embarkation (C = Cherbourg, Q = Queenstown, S = Southampton)

REFERENCE: Data Science and ML Boot Camp, 2021, Veri Bilimi Okulu (https://www.veribilimiokulu.com/)