写一段代码让四个类别变量 “Vehicle Class” “Vehicle Size”“EmploymentStatus”“Location Code”的值转换为整数，原数据为字符串形式。再写一段代码让离散型变量“Income”的数据类型变成float

为了将四个类别变量（如 "Vehicle Class", "Vehicle Size", "EmploymentStatus", 和 "Location Code") 转换为整数，并将离散型变量"Income"从字符串转为浮点数，我们可以分别创建映射字典并使用类似的方法。下面是一段示例代码：

# 定义类别到整数的映射字典
category_mappings = {
    "Vehicle Class": {"Small": 1, "Medium": 2, "Large": 3},
    "Vehicle Size": {"Compact": 1, "Midsize": 2, "SUV": 3},
    "EmploymentStatus": {"Full-time": 1, "Part-time": 2, "Unemployed": 3},
    "Location Code": {"City": 1, "Suburb": 2, "Rural": 3},
}

# 对每个变量的数据进行转换
def categorical_to_integer(data, category_dict):
    return {key: int(category_dict[key].get(value, 0)) for key, value in data.items()}

income_data = ["$50,000", "$75,000", "$100,000"]
# 将"Income"转换为浮点数
def string_to_float(income_list):
    return [float(i.replace("$", "").replace(",", "")) for i in income_list]

transformed_data = categorical_to_integer({"Vehicle Class": "Small", "Vehicle Size": "Midsize", "EmploymentStatus": "Full-time", "Location Code": "City"}, category_mappings)
incomes_as_float = string_to_float(income_data)

print(transformed_data)
print(incomes_as_float)

这段代码首先定义了四个类别到整数的映射字典，然后定义了两个函数：`categorical_to_integer`用于转换类别变量为整数，`string_to_float`用于转换收入为浮点数。这两个函数随后应用于给定的数据。