Download Here : https://colorstech.net/wp-content/uploads/2024/11/titanic.csv

The Titanic dataset is a classic dataset used in data science and machine learning, often for classification problems. It contains information about passengers on the Titanic, focusing on whether they survived the ship’s sinking or not.

Key Features:

1. PassengerId: Unique identifier for each passenger.
2. Survived: Target variable (0 = Did not survive, 1 = Survived).
3. Pclass: Passenger class (1 = First, 2 = Second, 3 = Third).
4. Name: Full name of the passenger.
5. Sex: Gender of the passenger.
6. Age: Age in years.
7. SibSp: Number of siblings/spouses aboard.
8. Parch: Number of parents/children aboard.
9. Ticket: Ticket number.
10. Fare: Ticket price.
11. Cabin: Cabin number (often contains missing values).
12. Embarked: Port of embarkation (C = Cherbourg, Q = Queenstown, S = Southampton).

Usage:

• Binary classification: Predict survival based on other features.
• Data cleaning: Handle missing values in Age, Cabin, etc.
• Feature engineering: Extract insights like family size (SibSp + Parch) or title from Name.
• Exploratory Data Analysis (EDA): Understand correlations between features and survival.

It’s a great dataset for learning about preprocessing, feature engineering, and building predictive models.