I will review the Titanic Passenger List dataset from Kaggle

I will review the Titanic Passenger List dataset from Kaggle. Here’s a step-by-step approach:
Dataset Familiarization
Step 1: Understand the structure and contents of the dataset
Dataset Description: The Titanic Passenger List dataset contains information about the passengers on the Titanic. The key variables include:
• Passenger Id: Unique ID for each passenger
• Survived: Survival status (0 = No, 1 = Yes)
• Pclass: Ticket class (1 = 1st, 2 = 2nd, 3 = 3rd)
• Name: Passenger name
• Sex: Gender of the passenger
• Age: Age of the passenger
• SibSp: Number of siblings/spouses aboard the Titanic
• Parch: Number of parents/children aboard the Titanic
• Ticket: Ticket number
• Fare: Ticket fare
• Cabin: Cabin number
• Embarked: Port of embarkation (C = Cherbourg, Q = Queenstown, S = Southampton)
Step 2: Identify key variables and data types
• Numerical variables: Passenger Id, Survived, Pclass, Age, SibSp, Parch, Fare
• Categorical variables: Name, Sex, Ticket, Cabin, Embarked
Initial Data Exploration
Step 1: Quick review of the dataset
We will look at the first few rows of the dataset to understand its structure and contents.
Step 2: Look for obvious patterns, trends, or anomalies
We will perform the following initial checks:
• Summary statistics for numerical variables (mean, median, standard deviation, etc.)
• Frequency counts for categorical variables
• Check for missing values
Insight Identification
Step 1: Note initial insights
We will note any immediate observations from the dataset, such as:
• Distribution of survival rates
• Age distribution of passengers
• Relationship between ticket class and survival rate
• Gender distribution and its impact on survival
• Fare distribution and its correlation with ticket class
Technical Report Writing
Introduction
The Titanic Passenger List dataset provides information about the passengers aboard the Titanic, including demographic details, ticket information, and survival status. The purpose of this review is to conduct an initial exploration of the dataset to identify key insights and potential areas for further analysis.
Observations
Based on the initial exploration, we will present our findings, supported by basic visualizations (e.g., histograms, bar charts) and summary statistics.
Conclusion
We will summarize our observations and suggest potential areas for further analysis, such as exploring the impact of socio-economic status on survival rates or examining family relationships among passengers.
https://hng.tech/hire