100+ datasets found
  1. Titanic Dataset

    • kaggle.com
    Updated Apr 30, 2024
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    Sakshi Satre (2024). Titanic Dataset [Dataset]. https://www.kaggle.com/datasets/sakshisatre/titanic-dataset
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Apr 30, 2024
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Sakshi Satre
    License

    Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
    License information was derived automatically

    Description

    The dataset containing information about passengers aboard the Titanic is one of the most famous datasets used in data science and machine learning. It was created to analyze and understand the factors that influenced survival rates among passengers during the tragic sinking of the RMS Titanic on April 15, 1912.

    https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F19517213%2Fd4016c159f1ad17cb30d8905192fe9d7%2Ftitanic-ship_1027017-11.avif?generation=1711562371875068&alt=media" alt="">

    Data Description :-

    The dataset is often used for predictive modeling and statistical analysis to determine which factors (such as socio-economic status, age, gender, etc.) were associated with a higher likelihood of survival. It contains 1309 rows and 14 columns.

    Columns : -

    • Pclass: Ticket class indicating the socio-economic status of the passenger. It is categorized into three classes: 1 = Upper, 2 = Middle, 3 = Lower.

    • Survived: A binary indicator that shows whether the passenger survived (1) or not (0) during the Titanic disaster. This is the target variable for analysis.

    • Name: The full name of the passenger, including title (e.g., Mr., Mrs., etc.).

    • Sex: The gender of the passenger, denoted as either male or female.

    • Age: The age of the passenger in years.

    • SibSp: The number of siblings or spouses aboard the Titanic for the respective passenger.

    • Parch: The number of parents or children aboard the Titanic for the respective passenger.

    • Ticket: The ticket number assigned to the passenger.

    • Fare: The fare paid by the passenger for the ticket.

    • Cabin: The cabin number assigned to the passenger, if available.

    • Embarked: The port of embarkation for the passenger. It can take one of three values: C = Cherbourg, Q = Queenstown, S = Southampton.

    • Boat: If the passenger survived, this column contains the identifier of the lifeboat they were rescued in.

    • Body: If the passenger did not survive, this column contains the identification number of their recovered body, if applicable.

    • Home.dest: The destination or place of residence of the passenger.

    These descriptions provide a detailed understanding of each column in the Titanic dataset subset, offering insights into the demographic, travel, and survival-related information recorded for each passenger.

  2. Titanic Dataset

    • kaggle.com
    Updated Apr 20, 2023
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    Sajid (2023). Titanic Dataset [Dataset]. https://www.kaggle.com/datasets/dbdmobile/tita111
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Apr 20, 2023
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Sajid
    Description

    https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F11299784%2F6530245ff6b6d097af8cb56c86b79943%2Fpxfuel.jpg?generation=1682007437079315&alt=media" alt="">The Titanic dataset is a widely used dataset that contains information on the passengers who were aboard the Titanic when it sank on its maiden voyage in 1912. The dataset includes features such as age, sex, passenger class, and fare paid, as well as whether or not the passenger survived the sinking. The dataset is often used for machine learning and data analysis tasks, such as predicting survival based on passenger characteristics or exploring patterns in the data. The Titanic dataset is a classic example of data analysis and is a great starting point for those new to data science.

    The Titanic dataset is available in CSV format and contains two files, one for training and one for testing. The training file is used to build the machine learning model, while the testing file is used to test the performance of the model.

    Column Description

    PassengerId: unique identifier for each passenger Survived: whether the passenger survived (1) or not (0) Pclass: passenger class (1 = 1st class, 2 = 2nd class, 3 = 3rd class) Name: name of the passenger Sex: gender of the passenger Age: age of the passenger (in years) SibSp: number of siblings or spouses aboard the Titanic Parch: number of parents or children aboard the Titanic Ticket: ticket number Fare: passenger fare Cabin: cabin number Embarked: port of embarkation (C = Cherbourg, Q = Queenstown, S = Southampton)

    MIT License

    Copyright (c) [2023] [Md Kazi Sajiduddin]

    Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

    The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

    THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

  3. h

    titanic-dataset

    • huggingface.co
    Updated Sep 26, 2024
    + more versions
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    Brian Su (2024). titanic-dataset [Dataset]. https://huggingface.co/datasets/BrianSuToronto/titanic-dataset
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Sep 26, 2024
    Authors
    Brian Su
    License

    Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
    License information was derived automatically

    Description

    BrianSuToronto/titanic-dataset dataset hosted on Hugging Face and contributed by the HF Datasets community

  4. f

    Titanic

    • rochester.figshare.com
    application/csv
    Updated Aug 12, 2024
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    Aabha Pandit; Alois Romanowski; Heather Owen (2024). Titanic [Dataset]. http://doi.org/10.60593/ur.d.26462215.v1
    Explore at:
    application/csvAvailable download formats
    Dataset updated
    Aug 12, 2024
    Dataset provided by
    University of Rochester
    Authors
    Aabha Pandit; Alois Romanowski; Heather Owen
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    Titanic Dataset (for Machine Learning)The Titanic dataset is a classic and widely used dataset for machine learning and data analysis. It contains information about the passengers of the RMS Titanic, which tragically sank on its maiden voyage on April 15, 1912. The dataset provides details about each passenger, including their demographics, ticket information, and survival status. This dataset is often used to demonstrate and practice various machine learning techniques, particularly classification.This dataset is divided into two: training set & testing set.Dataset Variables:PassengerId: count for each passengerSurvived: 0 = No; 1 = YesName: name of passengerSex: passenger's sexAge: passenger's ageSibSp: number of siblings/spouses abroad the TitanicParch: number of parents/children abroad the TitanicTicket: ticket numberFare: passenger fareCabin: cabin numberEmbarked: port where passenger embarked (C = Cherbourg; Q = Queenstown; S = Southampton)

  5. titanic dataset

    • kaggle.com
    Updated Jun 15, 2022
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    Pushpraj Namdev (2022). titanic dataset [Dataset]. https://www.kaggle.com/datasets/pushprajnamdev/titanic-dataset
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jun 15, 2022
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Pushpraj Namdev
    Description

    Dataset

    This dataset was created by Pushpraj Namdev

    Contents

  6. titanic dataset

    • kaggle.com
    Updated Jun 1, 2022
    + more versions
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    Ryan Selesnik (2022). titanic dataset [Dataset]. https://www.kaggle.com/datasets/ryanselesnik/titanic-dataset
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jun 1, 2022
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Ryan Selesnik
    Description

    Dataset

    This dataset was created by Ryan Selesnik

    Contents

  7. f

    Titanic

    • figshare.com
    csv
    Updated Jul 27, 2025
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    Sam El-Kamand (2025). Titanic [Dataset]. http://doi.org/10.6084/m9.figshare.29614667.v1
    Explore at:
    csvAvailable download formats
    Dataset updated
    Jul 27, 2025
    Dataset provided by
    figshare
    Authors
    Sam El-Kamand
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    Version of the titanic dataset used in ggEDA manuscript.Can be loaded from the datarium R package (datarium::titanic.raw). Originally published by the British Board of Trade in 1990. If you use, please cite:British Board of Trade. Report on the Loss of the ’Titanic’ (S.S.). Allan Sutton Publishing, Gloucester, UK, 1990. British Board of Trade Inquiry Report (reprint).Alboukadel Kassambara. datarium: Data Bank for Statistical Analysis and Visualization, 2019. URL https://CRAN.R-project.org/package=datarium. R package version 0.1.0.

  8. A

    ā€˜Titanic-Dataset (train.csv)’ analyzed by Analyst-2

    • analyst-2.ai
    Updated Nov 12, 2021
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2021). ā€˜Titanic-Dataset (train.csv)’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/kaggle-titanic-dataset-train-csv-d701/832937de/?iid=019-246&v=presentation
    Explore at:
    Dataset updated
    Nov 12, 2021
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Analysis of ā€˜Titanic-Dataset (train.csv)’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/hesh97/titanicdataset-traincsv on 12 November 2021.

    --- No further description of dataset provided by original source ---

    --- Original source retains full ownership of the source dataset ---

  9. h

    titanic

    • huggingface.co
    Updated Jun 1, 2024
    + more versions
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    Nikhil Kumar (2024). titanic [Dataset]. https://huggingface.co/datasets/nik20004/titanic
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jun 1, 2024
    Authors
    Nikhil Kumar
    License

    https://choosealicense.com/licenses/other/https://choosealicense.com/licenses/other/

    Description

    nik20004/titanic dataset hosted on Hugging Face and contributed by the HF Datasets community

  10. Titanic Dataset for GDSC - AI Model

    • kaggle.com
    Updated Apr 18, 2024
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    alirizaercan (2024). Titanic Dataset for GDSC - AI Model [Dataset]. https://www.kaggle.com/datasets/alirizaercan/titanic-dataset-for-gdsc-ai-model
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Apr 18, 2024
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    alirizaercan
    Description

    The Titanic Dataset for GDSC - AI Model

    This dataset contains information about the passengers and crew members who were on board the RMS Titanic, a British passenger liner that sank in the North Atlantic Ocean in the early hours of April 15, 1912, after striking an iceberg during her maiden voyage from Southampton to New York City. The sinking of the Titanic resulted in a large loss of life and remains one of the deadliest commercial peacetime maritime disasters in modern history.

    The dataset includes a variety of features about the passengers and crew members, such as:

    Passenger Class: Indicates the class (1st, 2nd, 3rd) that the passenger traveled in. Name: The passenger's name. Sex: The passenger's sex. Age: The passenger's age. SibSp: The number of siblings or spouses aboard the Titanic with the passenger. Parch: The number of parents or children aboard the Titanic with the passenger. Ticket: The passenger's ticket number. Fare: The passenger's fare. Cabin: The passenger's cabin number. Embarked: The port where the passenger embarked the Titanic. Survived: Whether the passenger survived the sinking of the Titanic (1 = survived, 0 = did not survive). What You Can Do With The Dataset

    The Titanic Dataset is a valuable resource for anyone interested in machine learning, data science, or the history of the Titanic. Here are some examples of what you can do with this dataset:

    Predict passenger survival: You can use the dataset to train a machine learning model to predict whether a passenger was more likely to survive the sinking of the Titanic based on features such as their class, sex, age, and number of relatives on board. Analyze factors that influenced survival rates: You can use the dataset to analyze the factors that influenced passenger survival rates. For example, you could look at how factors such as class, sex, and age affected a passenger's chances of survival. Build a classification model to identify passengers who were more likely to survive: You can use the dataset to build a classification model that can identify passengers who were more likely to survive the sinking of the Titanic. This model could be used to help us understand the factors that influenced survival rates and could also be used to improve the safety of passengers in future maritime disasters. Overall, the Titanic Dataset is a rich and informative dataset that can be used for a variety of purposes. If you are interested in machine learning, data science, or the history of the Titanic, then this dataset is a great resource to explore.

  11. h

    Titanic-Dataset

    • huggingface.co
    Updated Oct 21, 2024
    + more versions
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    Javier TomƔs Vicente (2024). Titanic-Dataset [Dataset]. https://huggingface.co/datasets/Javitron4257/Titanic-Dataset
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Oct 21, 2024
    Authors
    Javier TomƔs Vicente
    License

    https://choosealicense.com/licenses/cc/https://choosealicense.com/licenses/cc/

    Description

    Javitron4257/Titanic-Dataset dataset hosted on Hugging Face and contributed by the HF Datasets community

  12. f

    Titanic classification

    • figshare.com
    txt
    Updated Sep 19, 2020
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    Alvaro Rioboo (2020). Titanic classification [Dataset]. http://doi.org/10.6084/m9.figshare.12979220.v1
    Explore at:
    txtAvailable download formats
    Dataset updated
    Sep 19, 2020
    Dataset provided by
    figshare
    Authors
    Alvaro Rioboo
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    Titanic dataset for classification training.

  13. RMS Titanic Passengers and Crew Complete List

    • encyclopedia-titanica.org
    json
    Updated Jan 27, 2025
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    Encyclopedia Titanica (2025). RMS Titanic Passengers and Crew Complete List [Dataset]. https://www.encyclopedia-titanica.org/titanic-passengers-and-crew/
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Jan 27, 2025
    Dataset authored and provided by
    Encyclopedia Titanicahttp://www.encyclopedia-titanica.org/
    License

    https://www.encyclopedia-titanica.org/copyright-and-permissions.htmlhttps://www.encyclopedia-titanica.org/copyright-and-permissions.html

    Description

    Who travelled on the Titanic? When she reached the open Atlantic on 11 April 1912, the Titanic carried 2,208 people however many more travelled on her: on the delivery trip from Belfast to Southampton, and on the short journeys to Cherbourg and Queenstown. This dataset includes everyone that travelled on the maiden voyage but also the delivery and passengers who were fortunate enough to disembark.

  14. Titanic: A Voyage into the Past

    • kaggle.com
    Updated Nov 20, 2023
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    Asher Mehfooz (2023). Titanic: A Voyage into the Past [Dataset]. https://www.kaggle.com/datasets/ashirzaki/titanic/discussion
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Nov 20, 2023
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Asher Mehfooz
    Description

    **Dataset Overview ** The Titanic dataset is a widely used benchmark dataset for machine learning and data science tasks. It contains information about passengers who boarded the RMS Titanic in 1912, including their age, sex, social class, and whether they survived the sinking of the ship. The dataset is divided into two main parts:

    Train.csv: This file contains information about 891 passengers who were used to train machine learning models. It includes the following features:

    PassengerId: A unique identifier for each passenger Survived: Whether the passenger survived (1) or not (0) Pclass: The passenger's social class (1 = Upper, 2 = Middle, 3 = Lower) Name: The passenger's name Sex: The passenger's sex (Male or Female) Age: The passenger's age Sibsp: The number of siblings or spouses aboard the ship Parch: The number of parents or children aboard the ship Ticket: The passenger's ticket number Fare: The passenger's fare Cabin: The passenger's cabin number Embarked: The port where the passenger embarked (C = Cherbourg, Q = Queenstown, S = Southampton) Test.csv: This file contains information about 418 passengers who were not used to train machine learning models. It includes the same features as train.csv, but does not include the Survived label. The goal of machine learning models is to predict whether or not each passenger in the test.csv file survived.

    **Data Preparation ** Before using the Titanic dataset for machine learning tasks, it is important to perform some data preparation steps. These steps may include:

    Handling missing values: Some of the features in the dataset have missing values. These values can be imputed or removed, depending on the specific task. Encoding categorical variables: Some of the features in the dataset are categorical variables, such as Pclass, Sex, and Embarked. These variables need to be encoded numerically before they can be used by machine learning algorithms. Scaling numerical variables: Some of the features in the dataset are numerical variables, such as Age and Fare. These variables may need to be scaled to ensure that they are on the same scale. Data Visualization

    Data visualization can be a useful tool for exploring the Titanic dataset and gaining insights into the data. Some common data visualization techniques that can be used with the Titanic dataset include:

    Histograms: Histograms can be used to visualize the distribution of numerical variables, such as Age and Fare. Scatter plots: Scatter plots can be used to visualize the relationship between two numerical variables. Box plots: Box plots can be used to visualize the distribution of a numerical variable across different categories, such as Pclass and Sex. Machine Learning Tasks

    The Titanic dataset can be used for a variety of machine learning tasks, including:

    Classification: The most common task is to use the train.csv file to train a machine learning model to predict whether or not each passenger in the test.csv file survived. Regression: The dataset can also be used to train a machine learning model to predict the fare of a passenger based on their other features. Anomaly detection: The dataset can also be used to identify anomalies, such as passengers who are outliers in terms of their age, social class, or other features.

  15. A

    ā€˜Titanic csv’ analyzed by Analyst-2

    • analyst-2.ai
    Updated Nov 16, 2021
    + more versions
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2021). ā€˜Titanic csv’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/kaggle-titanic-csv-bb03/bfd4e31c/?iid=000-143&v=presentation
    Explore at:
    Dataset updated
    Nov 16, 2021
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Analysis of ā€˜Titanic csv’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/fossouodonald/titaniccsv on 13 November 2021.

    --- Dataset description provided by original source is as follows ---

    this dataset is the result of titanic csv

    --- Original source retains full ownership of the source dataset ---

  16. RMS Titanic Complete Passenger and Crew Dataset

    • encyclopedia-titanica.org
    Updated Aug 24, 2008
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    Encyclopedia Titanica (2008). RMS Titanic Complete Passenger and Crew Dataset [Dataset]. https://www.encyclopedia-titanica.org/titanic-victims/
    Explore at:
    Dataset updated
    Aug 24, 2008
    Dataset authored and provided by
    Encyclopedia Titanicahttp://www.encyclopedia-titanica.org/
    License

    https://www.encyclopedia-titanica.org/copyright-and-permissions.htmlhttps://www.encyclopedia-titanica.org/copyright-and-permissions.html

    Description

    The complete list of RMS Titanic passengers and crew, including detailed records of survivors and victims.

  17. titanic

    • zenodo.org
    • huggingface.co
    csv
    Updated Feb 7, 2022
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    Miguel Arbea Gomez; Miguel Arbea Gomez (2022). titanic [Dataset]. http://doi.org/10.5281/zenodo.5987761
    Explore at:
    csvAvailable download formats
    Dataset updated
    Feb 7, 2022
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Miguel Arbea Gomez; Miguel Arbea Gomez
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    titanic dataset

  18. A

    ā€˜Titanic Solution for Beginner's Guide’ analyzed by Analyst-2

    • analyst-2.ai
    Updated Sep 30, 2021
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2021). ā€˜Titanic Solution for Beginner's Guide’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/kaggle-titanic-solution-for-beginner-s-guide-78b3/db683166/?iid=041-447&v=presentation
    Explore at:
    Dataset updated
    Sep 30, 2021
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Analysis of ā€˜Titanic Solution for Beginner's Guide’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/harunshimanto/titanic-solution-for-beginners-guide on 30 September 2021.

    --- Dataset description provided by original source is as follows ---

    Overview

    The data has been split into two groups:

    training set (train.csv)
    test set (test.csv)
    

    The training set should be used to build your machine learning models. For the training set, we provide the outcome (also known as the ā€œground truthā€) for each passenger. Your model will be based on ā€œfeaturesā€ like passengers’ gender and class. You can also use feature engineering to create new features.

    The test set should be used to see how well your model performs on unseen data. For the test set, we do not provide the ground truth for each passenger. It is your job to predict these outcomes. For each passenger in the test set, use the model you trained to predict whether or not they survived the sinking of the Titanic.

    We also include gender_submission.csv, a set of predictions that assume all and only female passengers survive, as an example of what a submission file should look like.

    Data Dictionary

    Variable Definition Key survival Survival 0 = No, 1 = Yes pclass Ticket class 1 = 1st, 2 = 2nd, 3 = 3rd sex Sex
    Age Age in years
    sibsp # of siblings / spouses aboard the Titanic
    parch # of parents / children aboard the Titanic
    ticket Ticket number
    fare Passenger fare
    cabin Cabin number
    embarked Port of Embarkation C = Cherbourg, Q = Queenstown, S = Southampton

    Variable Notes

    pclass: A proxy for socio-economic status (SES) 1st = Upper 2nd = Middle 3rd = Lower

    age: Age is fractional if less than 1. If the age is estimated, is it in the form of xx.5

    sibsp: The dataset defines family relations in this way... Sibling = brother, sister, stepbrother, stepsister Spouse = husband, wife (mistresses and fiancƩs were ignored)

    parch: The dataset defines family relations in this way... Parent = mother, father Child = daughter, son, stepdaughter, stepson Some children travelled only with a nanny, therefore parch=0 for them.

    --- Original source retains full ownership of the source dataset ---

  19. c

    Titanic-Passengers

    • csvbase.com
    application/parquet +3
    Updated Mar 1, 2025
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    csvbase (2025). Titanic-Passengers [Dataset]. https://csvbase.com/mdfarragher/Titanic-Passengers
    Explore at:
    csv(58617), application/parquet(37129), application/x-jsonlines(165135), xlsx(57101)Available download formats
    Dataset updated
    Mar 1, 2025
    Dataset provided by
    csvbase
    Description

    A partial passenger manifest for the fateful last trip of the Titanic

  20. Titanic-Dataset

    • kaggle.com
    Updated Dec 3, 2024
    + more versions
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    fehu.zone (2024). Titanic-Dataset [Dataset]. https://www.kaggle.com/datasets/fehu94/titanic-dataset/data
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Dec 3, 2024
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    fehu.zone
    Description

    Dataset

    This dataset was created by fehu.zone

    Contents

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Sakshi Satre (2024). Titanic Dataset [Dataset]. https://www.kaggle.com/datasets/sakshisatre/titanic-dataset
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Titanic Dataset

"Tragedy at Sea : The Titanic Disaster !!"

Explore at:
CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
Dataset updated
Apr 30, 2024
Dataset provided by
Kagglehttp://kaggle.com/
Authors
Sakshi Satre
License

Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
License information was derived automatically

Description

The dataset containing information about passengers aboard the Titanic is one of the most famous datasets used in data science and machine learning. It was created to analyze and understand the factors that influenced survival rates among passengers during the tragic sinking of the RMS Titanic on April 15, 1912.

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F19517213%2Fd4016c159f1ad17cb30d8905192fe9d7%2Ftitanic-ship_1027017-11.avif?generation=1711562371875068&alt=media" alt="">

Data Description :-

The dataset is often used for predictive modeling and statistical analysis to determine which factors (such as socio-economic status, age, gender, etc.) were associated with a higher likelihood of survival. It contains 1309 rows and 14 columns.

Columns : -

  • Pclass: Ticket class indicating the socio-economic status of the passenger. It is categorized into three classes: 1 = Upper, 2 = Middle, 3 = Lower.

  • Survived: A binary indicator that shows whether the passenger survived (1) or not (0) during the Titanic disaster. This is the target variable for analysis.

  • Name: The full name of the passenger, including title (e.g., Mr., Mrs., etc.).

  • Sex: The gender of the passenger, denoted as either male or female.

  • Age: The age of the passenger in years.

  • SibSp: The number of siblings or spouses aboard the Titanic for the respective passenger.

  • Parch: The number of parents or children aboard the Titanic for the respective passenger.

  • Ticket: The ticket number assigned to the passenger.

  • Fare: The fare paid by the passenger for the ticket.

  • Cabin: The cabin number assigned to the passenger, if available.

  • Embarked: The port of embarkation for the passenger. It can take one of three values: C = Cherbourg, Q = Queenstown, S = Southampton.

  • Boat: If the passenger survived, this column contains the identifier of the lifeboat they were rescued in.

  • Body: If the passenger did not survive, this column contains the identification number of their recovered body, if applicable.

  • Home.dest: The destination or place of residence of the passenger.

These descriptions provide a detailed understanding of each column in the Titanic dataset subset, offering insights into the demographic, travel, and survival-related information recorded for each passenger.

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