The goal of this repository is to provide an analysis using python for Kaggle's Data Science competitions .
Kaggle Competition | Titanic Machine Learning from Disaster
The sinking of the RMS Titanic is one of the most infamous shipwrecks in history. On April 15, 1912, during her maiden voyage, the Titanic sank after colliding with an iceberg, killing 1502 out of 2224 passengers and crew. This sensational tragedy shocked the international community and led to better safety regulations for ships.
One of the reasons that the shipwreck led to such loss of life was that there were not enough lifeboats for the passengers and crew. Although there was some element of luck involved in surviving the sinking, some groups of people were more likely to survive than others, such as women, children, and the upper-class.
In this contest, we ask you to complete the analysis of what sorts of people were likely to survive.
Show a simple example of an analysis of the Titanic disaster in Python using a full complement of PyData utilities.
- Who were the passengers on the Titanic? (Ages,Gender,Class,..etc)
- What deck were the passengers on and how does that relate to their class?
- Where did the passengers come from?
- Who was alone and who was with family?
- Did the deck have an effect on the passengers survival rate?
- Did having a family member increase the odds of surviving the crash?
- Importing Data with Pandas
- Cleaning Data
- Barplots
- KDE-Plots
- lmplots
Competition Website: http://www.kaggle.com/c/titanic-gettingStarted