Python pandas 遍历DataFrame中的行数据的方法及示例代码

1、使用DataFrame.iterrows遍历

相关文档：DataFrame.iterrows

import pandas as pd
df = pd.DataFrame({'c1': [10, 11, 12], 'c2': [100, 110, 120]})
for index, row in df.iterrows():
    print(row['c1'], row['c2'])

输出：

10 100
11 110
12 120

2、使用iloc[]实现

import pandas as pd
df = pd.DataFrame({'A':[1, 2, 3], 'B':[4, 5, 6], 'C':[7, 8, 9]})
print(df)
for i in range(df.shape[0]):
    print(df.iloc[i, 1])
    print(df.iloc[i, [0, 2]])

3、使用DataFrame.itertuples()遍历

相关文档：DataFrame.itertuples()

import pandas as pd
df = pd.DataFrame({'A':[1, 2, 3], 'B':[4, 5, 6], 'C':[7, 8, 9]})
print(df)
for row in df.itertuples(index=True, name='Pandas'):
    print(row.c1, row.c2)

4、使用DataFrame.apply()遍历

相关文档：DataFrame.apply()

import pandas as pd
def print_row(row):
   print row['c1'], row['c2']
df.apply(lambda row: print_row(row), axis=1)