获取Python中的特定行

我有两个csv文件

一个是：

"CONS_NO","DATA_DATE","KWH_READING","KWH_READING1","KWH"
"1652714033","2015/1/12","4747.3800","4736.8000","10.5800"
"3332440062","2015/1/12","408.6800","407.8200","0.8600"
"7804314033","2015/1/12","1794.3500","1792.5000","1.8500"
"0114314033","2015/1/12","3525.2000","3519.4400","5.7600"
"1742440062","2015/1/12","3097.1900","3091.4100","5.7800"
"8230100023","2015/1/12","1035.0500","1026.8400","8.2100"

6360609057
8771218657
1338004100
2500009393
9184968250
9710581700
8833903141

总共大约六百万行

另一项是：

"CONS_NO","DATA_DATE","KWH_READING","KWH_READING1","KWH"
"1652714033","2015/1/12","4747.3800","4736.8000","10.5800"
"3332440062","2015/1/12","408.6800","407.8200","0.8600"
"7804314033","2015/1/12","1794.3500","1792.5000","1.8500"
"0114314033","2015/1/12","3525.2000","3519.4400","5.7600"
"1742440062","2015/1/12","3097.1900","3091.4100","5.7800"
"8230100023","2015/1/12","1035.0500","1026.8400","8.2100"

6360609057
8771218657
1338004100
2500009393
9184968250
9710581700
8833903141

总共大约一万行

---

第二个csv文件仅包含CONS_NO。我想找到第一个csv文件中与第二个csv文件中的编号对应的行；并删除Python中第一个csv文件中的其他行。

您可以使用

pandas

中的合并方法合并这两个

DataFrame

我将您的示例数据更改为以下内容：

test1.csv

是：

"CONS_NO","DATA_DATE","KWH_READING","KWH_READING1","KWH"
"1652714033","2015/1/12","4747.3800","4736.8000","10.5800"
"3332440062","2015/1/12","408.6800","407.8200","0.8600"
"7804314033","2015/1/12","1794.3500","1792.5000","1.8500"
"8833903141","2015/1/12","3525.2000","3519.4400","5.7600"
"1742440062","2015/1/12","3097.1900","3091.4100","5.7800"
"8833903141","2015/1/12","1035.0500","1026.8400","8.2100"

`test2.csv'是：

6360609057
8771218657
1338004100
2500009393
9184968250
9710581700
8833903141

现在可以使用以下代码合并它们：

import pandas as pd

df1 = pd.read_csv('test1.csv')
df2 = pd.read_csv('test2.csv', names=['CONS_NO'])

pd.merge(df1, df2, on='CONS_NO')

它给出以下输出：

    CONS_NO     DATA_DATE   KWH_READING KWH_READING1    KWH
0   8833903141  2015/1/12   3525.20     3519.44         5.76
1   8833903141  2015/1/12   1035.05     1026.84         8.21

---

到目前为止你尝试了什么？熊猫支持。试着自己解决这个问题，如果你卡住了，用一些代码编辑这个问题。谢谢，让我试试。