Photo by Derek Oyen on Unsplash
Overview
In this data exploration, you will practice the following:
- Analyzing feature relationships using visualizations.
- Feature engineering
- Feature encoding
Throughout this exploration, when you're asked to use a new function or library, we'll usually provide a link to that function's documentation, or a tutorial related to it.
Introduction
As with our previous data explorations, this assignment uses Google Colab. For more information on using Google Colab, including how to submit assignments with it, please see the information in Data Exploration 01
Assignment
You're working on an exhibit for a local museum called "The Titanic Disaster". They've asked you to analyze the passenger manifests and see if you can find any interesting information for the exhibit.
The museum curator is particularly interested in why some people might have been more likely to survive than others.
Notes about the data
Column Information:
- Survived: Did the passenger survive? (0 = no, 1 = yes)
- Pclass: The passenger's ticket class. (1 = 1st, 2 = 2nd, 3 = 3rd)
- Name: The passenger's name
- Sex: The passenger's gender
- Age: The passenger's age in years
- SibSp: Count of the passenger's siblings and spouse also aboard.
- Parch: Count of the passenger's parents and children also aboard.
- Ticket: The passenger's ticket number
- Fare: The amount the passenger paid for their ticket.
- Cabin: The passenger's cabin id.
- Embarked: Where the passenger embarked from (C = Cherbourg, S = Southampton, Q = Queenstown)
Click on the Open In Colab button below to open a Google Colab notebook with the template for this assignment. Once you've completed the assignment, don't forget to take the corresponding quiz in Canvas.
Teacher's Solution
Once you have absolutely exhausted all of your best efforts in solving the data exploration problems, and you are stuck on where to go next, you can view the teacher's solution here.