以下是针对问题的代码填空和答案： （1）创建数据框 `df` 的代码如下： ```python df = pd.DataFrame(data, index=index) ``` （2）查看存在缺失值的字段，完善以下代码： ```python print(df.isnull().any()) ``` 填空1：`isnull` （3）查看 `city` 存在缺失值的记录，完善以下代码： ```python y2 = df[df['city'].isnull()] print(y2) ``` 填空2：`df` （4）使用赋值操作和数据框对象的 `fillna()` 方法填充缺失值，完善以下代码： ```python adict = {'age': 22, 'city': 'tian jin', 'income': 36, 'sex': 'female', 'birth': '1986-6-5'} df.fillna(value=adict, inplace=True) ``` 填空3：`adict` 完整代码如下： ```python import numpy as np import pandas as pd index = pd.Index(data=["Tom", "Bob", "Mary", "James", "Andy", "Alice"], name="name") data = { "age": [18, 30, np.nan, 40, np.nan, 30], "city": ["Bei Jing ", "Shang Hai ", "Guang Zhou", "Shen Zhen", np.nan, " "], "income": [None, 11, 22, 33, np.nan, 55], "sex": [None, "male", "female", "male", np.nan, "male"], "birth": ["2000-02-10", "1988-10-17", None, "1978-08-08", np.nan, "1988-10-17"] } # (1) 创建数据框 df = pd.DataFrame(data, index=index) # (2) 查看存在缺失值的字段 print(df.isnull().any()) # (3) 查看 city 存在缺失值的记录 y2 = df[df['city'].isnull()] print(y2) # (4) 使用 fillna() 填充缺失值 adict = {'age': 22, 'city': 'tian jin', 'income': 36, 'sex': 'female', 'birth': '1986-6-5'} df.fillna(value=adict, inplace=True) ``` [2025-04-14 18:30:52 | AI问答 | 563点数解答]