Titanic Survival Predictor

The Titanic Survival Predictor is a simple Demonstration of predictive analysis written in python and using SKlearn for prediction, and Pandas and Seaborn to work with the data model.

As shown below the program works by asking the user to create an imaginary passenger on the titanic with attributes like gender, age, and ticket price.

The Program then compares the user's input attributes to that of real titanic survives to predict that persons are likely to survive based on those characteristics.

The program uses a CSV file with real information on the passengers on the titanic including whether they survive or not.  

The program works by first using Pandas to interpret the data.  Then after the user inputs the fake passenger the program uses SKlearn to predict the passenger's survival using the data from pandas.  It is then output as a percent from 0 to 1.