Hugo0133/Spaceship-Titanic dataset hosted on Hugging Face and contributed by the HF Datasets community

Dataset used in the Spaceship Titanic competiton.

Personal records for approximately 8,700 passengers.

space_titanic.csv: - PassengerId - A unique identifier assigned to each passenger. - HomePlanet - The planet from which the passenger departed, usually their home planet or place of permanent residence. - CryoSleep - Indicates whether the passenger chose to be placed in suspended animation for the duration of the voyage. - Cabin - The cabin number assigned to the passenger's accommodation. - Destination - The planet where the passenger will disembark. - Age - The passenger's age. - VIP - Indicates whether the passenger paid for VIP service during the voyage. - RoomService - The amount the passenger has been charged for room service. - FoodCourt - The amount the passenger has been charged at the food court. - ShoppingMall - The amount the passenger has been charged at the shopping mall. - Spa - The amount the passenger has been charged for services at the spa. - VRDeck - The amount the passenger has been charged for using the VR deck. - Name - The passenger's name. - Transported - Indicates whether the passenger was transported to another dimension.

Dataset

This dataset was created by Sanchi Batra

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Dataset

This dataset was created by Jsm

Released under Apache 2.0

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Did my best to clean and fill null values as accurately as possible. Added 5 new features. For me, it increased the performance of my models by 1-3% when compared to just filling the null values with the mean.

Cleaned and imputed data 2.csv: - 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. (Removed) - Transported - Whether the passenger was transported to another dimension. This is the target, the column you are trying to predict.

New Features: - Grouped - Whether the passenger is travelling alone or in a group. - Deck - Passenger's deck. - Side - Port or Starboard. - Has_expenses - Has the passenger spent any money. - Is_embryo - Is the passenger an embryo (0 yrs of age).

StevenSch12/spaceship-titanic-train dataset hosted on Hugging Face and contributed by the HF Datasets community

Dataset

This dataset was created by Zain Ali

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Dataset

This dataset was created by Muhammad Firdaus

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StevenSch12/spaceship-titanic-test dataset hosted on Hugging Face and contributed by the HF Datasets community

Dataset

This dataset was created by shamiul islam shifat

Released under Apache 2.0

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Context

Dataset is final solution for dealing with missing values in the Spaceship Titanic competition. Kaggle Notebook: https://www.kaggle.com/sardorabdirayimov/best-way-of-dealing-with-missing-values-titanic-2/

Dataset

This dataset was created by John Mitchell

Released under CC BY-SA 3.0

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Dataset

This dataset was created by Janbolter Junior Ramos Falcon

Released under Apache 2.0

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Starship Titanic Lore

At the heart of our Galaxy, an advanced civilization of which we know nothing has built the biggest, most beautiful starship ever: the Starship Titanic. The Starship Titanic was conceived and designed as the most luxurious Galacticruiser ever built. On its maiden voyage, the biggest, most beautiful, most technologically advanced interstellar Etherliner ever built unexpectedly crashes. Into your house. You find your way on board. It is like no alien spaceship… See the full description on the dataset page: https://huggingface.co/datasets/Naphula/Starship_Titanic.

Dataset

This dataset was created by Nabarungos

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Dataset

This dataset was created by Abdul Rahman Aziz

Released under Database: Open Database, Contents: Database Contents

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This dataset is a prepared dataset for the Spaceship Titanic competition. It has new features like CabinDeck and GroupSize, all missing values have been imputed and all the categorical features have been encoded. It also has 5 folds for cross-validation. You can essentially load the dataset and use it straight out of the box.

The following features have been engineered: - GroupId - GroupSize - CabinDeck - CabinNum - CabinSide - TotalExpense - Columns which indicate whether the feature was missing or not for RoomService, FoodCourt, ShoppingMall, Cabin, VIP and TotalExpense. These columns have the suffix _missing. In case of TotalExpense, the values are obtained by not skipping missing values in the expenditure columns.

See the column descriptions for more information.

There are 4 pairs of files, a train and test file in each pair: - train_prepared.csv and test_prepared.csv: These files do not have the CabinNum and GroupId features that can be extracted from Cabin and PassengerId respectively. - train_prepared_cabinnum_le.csv and test_prepared_cabinnum_le.csv: These files have the CabinNum feature label encodedin addition to all the features in the first two files. - train_prepared_groupid_le.csv and test_prepared_groupid_le.csv: These files have the GroupId feature label encoded in addition to all the features in the first two files. - train_prepared_both_le.csv and test_prepared_both_le.csv: These files have both the CabinNum and GroupId features label encoded in addition to all the features in the first two files

Dataset

This dataset was created by maxluuu

Released under MIT

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Dataset

This dataset was created by ANNAPA REDDY Vasu

Released under CC0: Public Domain

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Dataset

This dataset was created by hemanth ganesh villuri

Released under CC0: Public Domain

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