如何将含嵌套列表的多列表数据转换为Pandas DataFrame

你的代码存在几个语法和逻辑问题：

• 未通过索引关联Animals、Genders和Properties的对应元素，无法匹配每个动物的属性
• 字典内部不能直接嵌套for循环，属于语法错误
• 引用未定义的gender变量，应调用Genders列表中对应位置的值

以下是几种可行的解决方案：

方法一：索引遍历构造字典列表 #

通过enumerate获取每个动物的索引，精准匹配对应的性别和属性：

import pandas as pd

Animals = ['dog', 'cat', 'hamster']
Genders = ['male', 'female', 'male']
Properties = [
         ['Brown', '10 Years', 'Sausage', 'Happy'],
         ['Black', '5 Years', 'Pippin', 'Angry'],
         ['Yellow', '1 Year', 'Jeff', 'Moody']
      ]

d = []
for idx, pet in enumerate(Animals):
    # 按索引取出对应性别和属性
    gender = Genders[idx]
    colour, age, name, sentiment = Properties[idx]
    d.append({
        'Animal': pet.title(),  # 首字母大写与示例格式一致
        'Gender': gender.title(),
        'Colour': colour,
        'Age': age,
        'Name': name,
        'Sentiment': sentiment
    })

df = pd.DataFrame(d)
print(df)

运行后输出：

Animal  Gender  Colour       Age     Name Sentiment
0      Dog    Male   Brown  10 Years  Sausage     Happy
1      Cat  Female   Black   5 Years   Pippin     Angry
2  Hamster    Male  Yellow    1 Year     Jeff     Moody

方法二：直接构造DataFrame列 #

拆分Properties为单独的列列表，直接传入DataFrame构造函数，更简洁：

import pandas as pd

Animals = ['dog', 'cat', 'hamster']
Genders = ['male', 'female', 'male']
Properties = [
         ['Brown', '10 Years', 'Sausage', 'Happy'],
         ['Black', '5 Years', 'Pippin', 'Angry'],
         ['Yellow', '1 Year', 'Jeff', 'Moody']
      ]

# 拆分Properties为各列数据
colours = [p[0] for p in Properties]
ages = [p[1] for p in Properties]
names = [p[2] for p in Properties]
sentiments = [p[3] for p in Properties]

df = pd.DataFrame({
    'Animal': [a.title() for a in Animals],
    'Gender': [g.title() for g in Genders],
    'Colour': colours,
    'Age': ages,
    'Name': names,
    'Sentiment': sentiments
})

print(df)

方法三：用zip打包数据项 #

通过zip将所有对应位置的数据打包，直接生成DataFrame：

import pandas as pd

Animals = ['dog', 'cat', 'hamster']
Genders = ['male', 'female', 'male']
Properties = [
         ['Brown', '10 Years', 'Sausage', 'Happy'],
         ['Black', '5 Years', 'Pippin', 'Angry'],
         ['Yellow', '1 Year', 'Jeff', 'Moody']
      ]

# 打包所有对应字段的数据
data = zip(
    [a.title() for a in Animals],
    [g.title() for g in Genders],
    [p[0] for p in Properties],
    [p[1] for p in Properties],
    [p[2] for p in Properties],
    [p[3] for p in Properties]
)

# 指定列名生成DataFrame
df = pd.DataFrame(data, columns=['Animal', 'Gender', 'Colour', 'Age', 'Name', 'Sentiment'])
print(df)

内容的提问来源于stack exchange，提问作者Curious Student