ruviansh / titanicshinyapp

Using Kaggle's Titanic Training dataset and publishing in RStudio Shiny

README Introduction to Titanic set - Kaggle challenge

Disclosure

These are the files produced during a homework assignment of Coursera's MOOC Developing Data Products from Johns Hopkins University, where students could pick any dataset, and should produce a web app hosted on SaaS platform from RStudio shinyapss.io.

RStudio Shiny Server: https://dpaurelio.shinyapps.io/dpaurelio/ RPubs presentation: http://rpubs.com/dpaurelio/30378 GitHub Repo: https://github.com/diogoaurelio/titanicShinyApp

For more information about the several MOOCs comprised in this Specialization, please visit: https://www.coursera.org/specialization/jhudatascience/

For more information about RStudio Shinyapps.io visit: http://shiny.rstudio.com/articles/shinyapps.html

For more information about Kaggle Titanic challenge visit: https://www.kaggle.com/c/titanic-gettingStarted

Last but not least, if you are getting started with this challenge and R, here is a great tutorial from Trevor Stephens that inspired me to create this repo: http://trevorstephens.com/post/72916401642/titanic-getting-started-with-r

The scripts have been solely produced, tested and executed on MAC OS X 10.9.4, and RStudio Version 0.98.976.

Use it at your own discretion/responsability.

Guidelines to reproduce this project

To run locally this App on your computer you do NOT need to fork this repo. Please follow these instructions:

1. Install the necessary packages to run RStudio's Shiny Server locally. Please view the well documented requirements in the getting started page: http://shiny.rstudio.com/articles/shinyapps.html

2. Run the following command in the RStudio:

runGitHub( "titanicShinyApp", "diogoaurelio")

3. Voilá.

Project given Description

About this App

This is a very simple web application, which intends to provide some initiation in terms of Exploratory Analysis of the Training set of the Kaggle's Titanic dataset. I use only the Training Dataset to show the results.

As mentioned before, I strongly recommend checking Trevor Stephens blog to get more insights on R and some data analysis applied to this problem.

About Kaggle Titanic Challenge

Predict survival on the Titanic (with tutorials in Excel, Python, R, and an introduction to Random Forests)

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 challenge, we ask you to complete the analysis of what sorts of people were likely to survive. In particular, we ask you to apply the tools of machine learning to predict which passengers survived the tragedy.