**Overview**
The dataset is split into two parts:
- Training set (**train.csv**) – This contains passengers and their survival outcomes. You’ll use it to train your model.
- Test set (**test.csv**) – This has similar data but without survival labels. Your model will predict these.
- Additionally, you will find **sample_submission.csv**, a sample submission file in the correct format


## Data Dictionary

| Variable | Definition | Key |
| ------------- |:-------------:| -----:|
| Survival  | Survival |0 = No, 1 = Yes |
| Pclass     | Ticket class (proxy for socio-economic status)   |   1 = Upper, 2 = Middle, 3 = Lower |
| Sex | Passenger’s gender   |    Male / Female|
| Age | Age in years    |   Fractional if under 1 year |
| SibSp| Number of siblings/spouses aboard  |  - |
| Parch| Number of parents/children aboard   |  	- |
| Ticket| Ticket number	  |    	- |
| Fare| Passenger fare	   |   	- |
| Cabin|Cabin number  |   - |
| Embarked| Port of Embarkation  |    C = Cherbourg, Q = Queenstown, S = Southampton |


## Notes on Variables:
- *Pclass*: A proxy for socio-economic status (SES).
1st = Upper class
2nd = Middle class
3rd = Lower class

- *Age* : If less than 1 year old, the age is fractional. If estimated, it appears as xx.5.

- *SibSp* (Siblings/Spouses aboard):
Sibling = Brother, sister, stepbrother, stepsister
Spouse = Husband, wife (excluding fiancés and mistresses)

- *Parch* (Parents/Children aboard):
Parent = Mother, father
Child = Son, daughter, stepson, stepdaughter
Some children traveled only with a nanny, so parch = 0 for them.