mariakmurphy55/titanicdata

---
language:
- en
pretty_name: titanic data
size_categories:
- 1K<n<10K
---
# Dataset Card for Titanic Data

Training and testing data for Titanic passengers' survival.

## Dataset Details

### Dataset Description

Train:
- Dimensions --> 891x12
- Column names --> "PassengerId", "Survived", "Pclass", "Name", "Sex", "Age", "SibSp", "Parch", "Ticket", "Fare", "Cabin", and "Embarked"

Test:
- Dimensions --> 418x11
- Column names --> "PassengerId", "Pclass", "Name", "Sex", "Age", "SibSp", "Parch", "Ticket", "Fare", "Cabin", and "Embarked"

### Dataset Sources

Kaggle Titanic dataset
https://www.kaggle.com/competitions/titanic

## Uses

Raw datasets being used in introduction to DVC and Amazon's S3 buckets.

## Dataset Structure

# Column definitions:
- "PassengerId" --> key for each passenger (int64)
- "Survived" --> binary variable indicating survival (int64)
- "Pclass" --> first, second, or third class (int64)
- "Name" --> passenger name; maiden name in parentheses for married women (object)
- "Sex" --> male or female (object)
- "Age" --> passenger age (float64)
- "SibSp" --> unknown meaning (int64)
- "Parch" --> unknown meaning (int64)
- "Ticket" --> ticket identifier (object)
- "Fare" --> float variable (float64)
- "Cabin" --> cabin identifier (object)
- "Embarked" --> C, Q, or S (object)

Categorical columns: "Name", "Sex", "Ticket", "Cabin", "Embarked"

Continuous columns: "PassengerId", "Pclass", "SibSp", "Parch", "Age", "Fare"

# Quick Facts:
Train:
- PassengerID, Survived, Pclass, Name, Sex, SibSp, Parch, Ticket, and Fare have no NA values
- Age not documented for 177 passengers (19.8653% NA)
- Cabin not documented for 687 passengers (77.1044% NA)
- Embarked not documented for 2 passengers (0.2245% NA)

Test:
- PassengerID, Pclass, Name, Sex, SibSp, Parch, Ticket, and Embarked have no NA values
- Age not documented for 86 passengers (20.5742% NA)
- Fare not documented for 1 passenger (0.2392% NA)
- Cabin not documented for 387 passengers (78.2297% NA)

# Summary Statistics:
Train:

Test:

## Dataset Card Author

Maria Murphy

原始信息汇总

数据集卡片：Titanic数据

数据集详情

数据集描述

训练集：

• 维度：891x12
• 列名："PassengerId", "Survived", "Pclass", "Name", "Sex", "Age", "SibSp", "Parch", "Ticket", "Fare", "Cabin", "Embarked"

测试集：

• 维度：418x11
• 列名："PassengerId", "Pclass", "Name", "Sex", "Age", "SibSp", "Parch", "Ticket", "Fare", "Cabin", "Embarked"

数据集来源

Kaggle Titanic数据集 Kaggle Titanic竞赛

数据集结构

列定义：

• "PassengerId"：每个乘客的唯一标识（int64）
• "Survived"：生存状态（int64）
• "Pclass"：舱位等级（int64）
• "Name"：乘客姓名，已婚女性括号内为娘家姓（object）
• "Sex"：性别（object）
• "Age"：年龄（float64）
• "SibSp"：未知含义（int64）
• "Parch"：未知含义（int64）
• "Ticket"：票号（object）
• "Fare"：票价（float64）
• "Cabin"：舱位号（object）
• "Embarked"：登船港口（object）

分类列："Name", "Sex", "Ticket", "Cabin", "Embarked"

连续列："PassengerId", "Pclass", "SibSp", "Parch", "Age", "Fare"

快速事实

训练集：

• PassengerID, Survived, Pclass, Name, Sex, SibSp, Parch, Ticket, Fare 无缺失值
• Age 缺失177条记录（19.8653% NA）
• Cabin 缺失687条记录（77.1044% NA）
• Embarked 缺失2条记录（0.2245% NA）

测试集：

• PassengerID, Pclass, Name, Sex, SibSp, Parch, Ticket, Embarked 无缺失值
• Age 缺失86条记录（20.5742% NA）
• Fare 缺失1条记录（0.2392% NA）
• Cabin 缺失387条记录（78.2297% NA）

摘要统计

训练集和测试集的摘要统计图表链接如下：

• 训练集：训练集摘要统计图表
• 测试集：测试集摘要统计图表