Titanic_Statistics

Overview:

The Titanic Statistics project is a detailed analysis of the Titanic accident. The project uses Python programming along with various libraries to extract data from a CSV database file and save the output as CSV files. It also utilizes Flask, Jinja, Pandas, Numpy, and Openpyxl to handle web framework, template data flow, formatting, and dealing with xlsx files.

Features:

• Data Extraction: The project can extract data from a CSV database file and save the output as CSV files.
• Web Framework: Flask is used to apply a web framework which enables Python to deal with HTML, CSS, and JS files.
• Template Data Flow: Jinja is used to handle the flow of templates data between all HTML pages.
• Data Formatting: Numpy is used to handle the formatting of the output and control how it flows.
• Working with xlsx Files: The project utilizes Openpyxl to handle xlsx files, allowing for easy data manipulation.
• Gender Analysis: The code can find and separate all males and females from the given dataset.
• Survivor Analysis: The project identifies and presents only the survivor data.
• Child Analysis: It can find all the lost children under or equal to the age of 17.
• Passenger Analysis: The code provides the total number of passengers and the number of survivors.
• Survival Percentage: The project calculates and displays the percentage of survivors.

Summary:

The Titanic Statistics project is a comprehensive analysis of the Titanic accident. It utilizes Python programming and various libraries to extract and manipulate data from a CSV database file. The project offers features such as data extraction, web framework implementation, template data flow, data formatting, and handling of xlsx files. Additionally, it provides analysis on gender, survival, child passengers, and overall passenger statistics. Accessible through a web interface, the project allows users to easily explore and understand the statistics related to the Titanic accident.