karoldem/rekrutacja_2023

Rekrutacja do KNDS w 2023! Tutaj znajdziecie zadania i rozwiązania.

Competition I took part in once.

I present my humble project I sent to competition described below.

🚀🌌 Inspire us with your data analysis skills! 🚀🌌

Have you ever dreamed of traveling aboard a spaceship?

🚢Whether you are passionate about life sciences or a fan of sci-fi movies, we have a unique recruitment task for you to join our club! 📊📈 Your task is to explore, analyze and draw valuable conclusions from the "Spaceship Titanic" dataset. 🛸🌠 You need to discover as many interesting statistics and relationships between passenger characteristics as possible. You also need to visualize everything in graphs to further illustrate their nature, and then convincingly present and justify your conclusions. 💡📊

But it doesn't stop there! If you get even more curious and feel like using your analysis more broadly, a machine learning model predicting whether or not a particular passenger has been transported to another dimension would be welcome. 🤖🌌

This is a great opportunity to use your analytical skills, creativity and presentation skills. Fasten your seatbelts and embark with us on a journey into the depths of the cosmic abyss! 🚀🌌 How to share the solution?

1. Make a fork of this repository
2. Add all files included in the solution to the appropriate folder: spaceship_titanic/rozwiazania/<name>_<surname>/
3. Create a new Pull Request from your fork to this repository

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PassengerId - A unique Id for each passenger. Each Id takes the form gggg_pp where gggg indicates a group the passenger is travelling with and pp is their number within the group. People in a group are often family members, but not always.

HomePlanet - The planet the passenger departed from, typically their planet of permanent residence.

CryoSleep - Indicates whether the passenger elected to be put into suspended animation for the duration of the voyage. Passengers in cryosleep are confined to their cabins.

Cabin - The cabin number where the passenger is staying. Takes the form deck/num/side, where side can be either P for Port or S for Starboard.

Destination - The planet the passenger will be debarking to.

Age - The age of the passenger.

VIP - Whether the passenger has paid for special VIP service during the voyage.

RoomService, FoodCourt, ShoppingMall, Spa, VRDeck - Amount the passenger has billed at each of the Spaceship Titanic's many luxury amenities.

Name - The first and last names of the passenger.

Transported - Whether the passenger was transported to another dimension. This is the target, the column you want to predict if you decide to create a machine learning model (see task description).