Python代码实现泰坦尼克号数据清洗

以下是Python代码实现泰坦尼克号数据清洗的示例：

import pandas as pd

# 读取数据文件
titanic = pd.read_csv('titanic.csv')

# 删除无用列
titanic = titanic.drop(['PassengerId', 'Name', 'Ticket', 'Cabin'], axis=1)

# 处理缺失值
titanic['Age'] = titanic['Age'].fillna(titanic['Age'].median())
titanic['Embarked'] = titanic['Embarked'].fillna(titanic['Embarked'].mode()[0])

# 将分类变量转换为数字变量
titanic['Sex'] = titanic['Sex'].map({'female': 0, 'male': 1}).astype(int)
embarked_mapping = {'S': 0, 'C': 1, 'Q': 2}
titanic['Embarked'] = titanic['Embarked'].map(embarked_mapping).astype(int)

# 查看数据清洗后的结果
print(titanic.head())

代码的执行结果为：

   Survived  Pclass  Sex   Age  SibSp  Parch     Fare  Embarked
0         0       3    1  22.0      1      0   7.2500         0
1         1       1    0  38.0      1      0  71.2833         1
2         1       3    0  26.0      0      0   7.9250         0
3         1       1    0  35.0      1      0  53.1000         0
4         0       3    1  35.0      0      0   8.0500         0