WiSe 2023/24 GitHub Project Group 7

Authors

• Máté Benke (mate.benke@tu-dortmund.de)
• Mia Macarena Bedarf (mia.bedarf@tu-dortmund.de)
• Guy Loïc Sabze (guy-loic.sabze@tu-dortmund.de)
• Johanna Hohmann (johanna.hohmann@tu-dortmund.de)
• Neo Hong (neo.hong@tu-dortmund.de)
• Helen Meyer zu Altenschildesche (helen.meyer-zu-altenschildesche@tu-dortmund.de)

Files

titanic.csv

The original dataset.

preprocessing.R

Preprocesses the data (Task 1).

titanic_cleaned.Rds

Contains the preprocessed dataset. Can be loaded with: dataset <- readRDS("titanic_cleaned.Rds")

utils.R

Functions used for analysis (Task 2).

helpers.R

Internal helper functions that are only called from utils.R (Task 2).

documentation/*

Documentation for utils.R, helpers.R and preprocessing.R (analysis.R only calls functions) (Task 3).

analysis.R

Main file that calls preprocessing.R, then calls functions from utils.R to analyse the data (Task 4).

Rplots.pdf

The plots that analysis.R produces as a pdf export.

How to run

It is enough to run analysis.R as this will call preprocessing.R and generate a new titanic_cleaned.Rds which it reads the data from. The working directory has to be set to WiSe-2023-24 (the base folder of the repository) beforehand so it can find the function scripts and the csv file.

Insights

We discussed our conclusions from the data in this issue.