Python学习笔记9：pandas.DataFrame.iterrows()方法

更多内容参考：pandas官方文档

Pandas的基础结构可以分为两种：数据框和序列。数据框是拥有轴标签的二维链表，换言之数据框是拥有标签的行和列组成的矩阵 - 列标签位列名，行标签为索引。Pandas中的行和列是Pandas序列 - 拥有轴标签的一维链表。

iterrows()是在数据框中的行进行迭代的一个生成器，它返回每行的索引及一个包含行本身的对象。

示例：

import pandas as pd
import numpy as np
df = pd.DataFrame(np.random.randn(10, 4), columns=list('ABCD'))
df

	A	B	C	D
0	-0.961305	-0.236265	0.232204	-0.707088
1	-0.898214	0.514331	0.290273	0.224386
2	-0.290242	-1.134433	-1.891123	1.121723
3	-0.654990	0.208918	1.443723	-0.357779
4	-1.264342	-0.555124	-1.236119	0.791272
5	-0.579388	0.607004	-0.231509	1.061788
6	-2.189155	-0.375116	-1.213247	-0.127200
7	0.018989	0.152848	0.586678	-0.629936
8	0.843229	1.489267	0.353259	-1.073245
9	0.648877	2.103916	0.053645	1.940579

for i,r in df.iterrows():
    print(i,r)

0 A   -0.961305
B   -0.236265
C    0.232204
D   -0.707088
Name: 0, dtype: float64
1 A   -0.898214
B    0.514331
C    0.290273
D    0.224386
Name: 1, dtype: float64
2 A   -0.290242
B   -1.134433
C   -1.891123
D    1.121723
Name: 2, dtype: float64
3 A   -0.654990
B    0.208918
C    1.443723
D   -0.357779
Name: 3, dtype: float64
4 A   -1.264342
B   -0.555124
C   -1.236119
D    0.791272
Name: 4, dtype: float64
5 A   -0.579388
B    0.607004
C   -0.231509
D    1.061788
Name: 5, dtype: float64
6 A   -2.189155
B   -0.375116
C   -1.213247
D   -0.127200
Name: 6, dtype: float64
7 A    0.018989
B    0.152848
C    0.586678
D   -0.629936
Name: 7, dtype: float64
8 A    0.843229
B    1.489267
C    0.353259
D   -1.073245
Name: 8, dtype: float64
9 A    0.648877
B    2.103916
C    0.053645
D    1.940579
Name: 9, dtype: float64

其他链接：https://python.freelycode.com/contribution/detail/1083

https://stackoverflow.com/questions/44506473/pandas-df-iterrows-method-to-access-a-set-number-of-rows