Pandas Dataframe数据帧的迭代之iterrows(),itertuples(),items()详解

import pandas as pd  

df = pd.DataFrame({  
    'A': [1, 2, 3],  
    'B': [4, 5, 6],  
    'C': [7, 8, 9]  
})  

for index, row in df.iterrows():  
    print(f"Index: {index}")  
    print(row)  

import pandas as pd  

df = pd.DataFrame({  
    'A': [10, 20, 30],  
    'B': [40, 50, 60],  
    'C': ['p', 'q', 'r']  
})  
  
for row in df.itertuples():  
    print(row)

'''
Pandas(Index=0, A=10, B=40, C='p')  
Pandas(Index=1, A=20, B=50, C='q')  
Pandas(Index=2, A=30, B=60, C='r')'''

import pandas as pd  
  
# 创建一个DataFrame  
df = pd.DataFrame({  
    'A': [1, 2, 3],  
    'B': [4, 5, 6],  
    'C': [7, 8, 9]  
})  
  
# 方法1: 迭代列名  
for column in df.columns:  
    print(f"Column Name: {column}")  
    # 通过列名访问列数据  
    print(df[column])   
  
# 方法2: 直接迭代DataFrame对象（默认迭代列名）  
for column in df:  
    print(f"Column Name: {column}")  
    print(df[column])  
  
# 方法3: 使用df.items()同时迭代列名和数据  
for column, data in df.items():  
    print(f"Column Name: {column}")  
    # data变量直接包含列数据，无需通过df[column]访问  
    print(data)