Python中不同数据对象的空值校验的方法小结

x = None
if x is None:
    print("x is None")
else:
    print("x is not None")

s = ''
if not s:
    print("s is empty")
else:
    print("s is not empty")

empty_list = []
if not empty_list:
    print("empty_list is empty")
else:
    print("empty_list is not empty")

empty_dict = {}
if not empty_dict:
    print("empty_dict is empty")
else:
    print("empty_dict is not empty")

import os

filename = 'empty_file.txt'
if os.path.getsize(filename) == 0:
    print(f"{filename} is empty")
else:
    print(f"{filename} is not empty")

import pandas as pd

df = pd.DataFrame({'A': [1, None, 3], 'B': ['x', '', 'z']})
print(df.isnull().any())  # Check if any column has null values

import pandas as pd

# 创建包含空值的DataFrame
data = {'Name': ['Alice', 'Bob', None, 'David', 'Eve'],
        'Age': [25, None, 30, 35, 20]}
df = pd.DataFrame(data)

# 查看原始数据
print("原始数据:")
print(df)

# 检查空值并填充
df['Name'].fillna('Unknown', inplace=True)
df['Age'].fillna(df['Age'].mean(), inplace=True)

# 查看处理后的数据
print("\n处理后的数据:")
print(df)

import pandas as pd

# 创建包含空值的DataFrame
data = {'Name': ['Alice', 'Bob', 'Cathy', 'David', 'Eve'],
        'Sales': [100, None, 200, 150, None]}
df = pd.DataFrame(data)

# 查看原始数据
print("原始数据:")
print(df)

# 检查空值并删除
df.dropna(subset=['Sales'], inplace=True)

# 查看处理后的数据
print("\n处理后的数据:")
print(df)