https://github.com/deep-diver/data-analysis-on-titanic

applying data analysis on titanic data sheet
https://github.com/deep-diver/data-analysis-on-titanic

data-analysis titanic-data

Last synced: 18 days ago
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applying data analysis on titanic data sheet

• Host: GitHub
• URL: https://github.com/deep-diver/data-analysis-on-titanic
• Owner: deep-diver
• Created: 2017-08-02T08:31:50.000Z (over 7 years ago)
• Default Branch: master
• Last Pushed: 2017-11-16T00:58:33.000Z (about 7 years ago)
• Last Synced: 2024-10-04T13:42:22.181Z (3 months ago)
• Topics: data-analysis, titanic-data
• Language: Jupyter Notebook
• Size: 482 KB
• Stars: 2
• Watchers: 2
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Data Analysis on Titanic Data Set

## Contents

* About Project

* About the Data Set

* Resources

* Dependencies

## About Project

This project has 2 different purposes. The first one is to pratice performing data analysis, especially on well-knwon data set so that it is easier to be proven myself. The scond purpose is to be familiar with python when performing data analysis including using plotting, math, data frame libraries. The end goal of this project is mainly focused on predicting a passenger's survivability.

## About the Data Set

The data set includes 891 entries (observations), and each entry has 11 different variables to describe a passenger. 

* survival : Survival (0 = No, 1 = Yes)

* pclass : Ticket class (1 = 1st/Upper, 2 = 2nd/Middle, 3 = 3rd/Lower)

* sex : Sex

* Age : Age in years

* sibsp : # of siblings / spouses aboard the Titanic (siblings = brother/sister/stepbrother/stepsister, spouse = husband/wife)

* parch : # of parents / children aboard the Titanic (parent = mother/father, child = daughter/son/stepdaughter/stepson)

* some children travelled only with a nanny, therefore parch=0 for them

* ticket : Ticket number

* fare : Passenger fare

* cabin : Cabin number

* embarked : Port of Embarkation (C = Cherbourg, Q = Queenstown, S = Southampton)

## Resources

* titanic-analysis.ipynb: IPython (Jupyter Notebook)

* titanic-data.csv: Titanic Data set formatted in csv style

## Dependencies

* pandas: data frame library

* numpy: mathmatical library + somewhat data frame library 

* matplotlib: plotting library