illi4 / titanic_dataset

An analysis of titanic dataset from Kaggle using Python pandas and mathplotlib. Includes the definition of questions to be answered, detailed description of the exploratory steps, and communication of conclusions.

Titanic dataset analysis

The aim of this project is to analyse the Kaggle Titanic dataset, which includes the following steps:

1. Defining the list of questions to be answered with data analysis.
2. Data wrangling (including its cleansing and adding additional fields) to allow for more convenient consumption of the data and making analysis possible.
3. Data exploration and effective communication of the exploratory steps.
4. Summarising conclusions.

Questions

1. What was the distribution of age across the passengers? Was it different between men and women?
2. What was the distribution of ticket fares? What were the average and the most expensive tickets? How much would this average and the most expensive tickets worth now?
3. Can we detect the port where the richest passengers embarked? How much would the median price for this subset of passengers worth now?
4. What was the survival rate for men, women and children? Was sex correlated to survival rate?
5. What was the survival rate among different ticket classes? Was ticket class correlated to survival rate?

Results

The results are saved in the Jupyter notebook file in the repository. An html version is available here.