Goal of this Notebook:

• Investigation - whether passenger's features correlate with survival?
• Analysis of Titanic dataset.
• Finding the best working classifier for Titanic dataset.

This Notebook will show basic examples of:

• Investigation - whether passenger's features correlate with survival?

  • Importing libraries
  • Importing data with Pandas
  • Feature engineering
  • Determine passenger's features to test against survival¶

• Analysis of Titanic dataset

  • Plot/graph variables and mathematically exploration

• Machine Learing on Titanic dataset

  • Importing machine learning libraries
  • Data cleaning
  • Feature extraction
  • Classification algorithms
  • Visualization

Dependencies

• Numpy: It provides a high-performance multidimensional array and basic tools to compute with and manipulate these arrays.
• Pandas: For data manipulation and analysis.
• SciKit-Learn: Python machine learning library which features various classification, regression and clustering algorithms.
• Matplotlib: Python Plotting.
• Seaborn: Python's Statistical Data Visualization Library.
• Scipy: It provides a large number of functions that operate on numpy arrays and are useful for different types of scientific and engineering applications.

Overview of Titanic dataset

• survival: Survival; 0 = No, 1 = Yes
• pclass: Ticket class, a proxy for socio-economic status (SES); 1 = 1st (Upper), 2 = 2nd (Middle), 3 = 3rd (Lower)
• sex: Sex of passenger
• Age: Age in years
• sibsp: # of siblings / spouses aboard the Titanic
• parch: # of parents / children aboard the Titanic
• ticket: Ticket number
• fare: Passenger fare
• cabin: Cabin number
• embarked: Port of Embarkation; C = Cherbourg, Q = Queenstown, S = Southampton

Conclusions

• Investigation: Which passenger characteristics correlate with survival?

  • Passenger gender correlates with survival: Females were more likely to survive than males.
  • Passenger class correlates with survival: The higher the passenger's class, the more likely that he or she survived.

• Machine Learning on Titanic dataset

  • GradientBoostingClassifier can be used to find insights on the Titanic dataset.