Python3.x 通过最接近的匹配合并两个不同长度的列上的两个数据框

我想合并这些示例数据帧:

1. 如何在新的df中获得最接近的匹配？

df1:

name           age      department
DJ Griffin     27       FD
Harris Smith   33       RD


df2:

name               age      department
D.J. Griffin III   27       FD
Harris Smith       33       RD
Miles Jones        58       RD

结果应该如下所示:

df3:

name         age      department   name_y
DJ Griffin     27       FD         D.J. Griffin III
Harris Smith   33       RD         Harris Smith

使用了Difflib，但出现错误，原因是dfs的长度不同.

import pandas as pd
import difflib

df1 = pd.DataFrame([["DJ Griffin", 27, "FD"], ["Harris Smith", 33, "RD"]], columns=["name", "age", "department"])
df2 = pd.DataFrame([["D.J. Griffin III", 27, "FD"], ["Harris Smith", 33, "RD"], ["Miles Jones", 58, "RD"]], columns=["name", "age", "department"])

df2['name_y'] = df2['name']

df2['name'] = df2['name'].apply(lambda x: difflib.get_close_matches(x, df1['name'])[0])

结果:

IndexError: list index out of range

2. 如果还有一个45岁的哈里斯·史密斯，如何通过两列找到最接近的匹配？

For the duplicate Harris Smith case

df1:

name           age      department
DJ Griffin     27       FD
Harris Smith   33       RD
Harris Smith   45       BA

df2:

name               age      department
D.J. Griffin III   27       FD
Harris Smith       33       RD
Harris Smith       45       BA
Miles Jones        58       RD

结果应该如下所示:

df3:

name         age      department   name_y
DJ Griffin     27       FD         D.J. Griffin III
Harris Smith   33       RD         Harris Smith
Harris Smith   45       BA         Harris Smith

import pandas as pd
import difflib

df1 = pd.DataFrame([["DJ Griffin", 27, "FD"], ["Harris Smith", 33, "RD"], ["Harris Smith", 45, "BA"]], columns=["name", "age", "department"])
df2 = pd.DataFrame([["D.J. Griffin III", 27, "FD"], ["Harris Smith", 33, "RD"], ["Harris Smith", 45, "BA"], ["Miles Jones", 58, "RD"]], columns=["name", "age", "department"])

df2['name_y'] = df2['name']

谢谢你的帮助.