简体   繁体   English

合并两个数据框并保留第一个 df 中的额外行

[英]Merging two data frames and keeping the extra rows from first df

I have 2 data frames df1 and df2我有 2 个数据框 df1 和 df2

df1 df1

        A  B 
id0     a  3      
id1     b  4      
id2     c  0 

df2 df2

       A   B 
id2   aa  80      
id3   d   44      
id4   r   100 

I want to join concat df1 and df2 in such a way that all rows of df1 are retained and if there are rows with the same index in df2( id2 ; in this case );我想以这样的方式连接 concat df1 和 df2,即保留 df1 的所有行,并且如果 df2( id2 ;在这种情况下) 中存在具有相同索引的行; its dropped from df2.它从 df2 下降。

Final df should look like最终 df 应该看起来像

        A  B 
id0     a  3      
id1     b  4      
id2     c  0
id3     d   44      
id4     r   100

How can it be done in pandas python?如何在 Pandas python 中完成?

Regards问候

You can use combine_first , it is specifically designed for this operation:您可以使用combine_first ,它是专门为此操作设计的:

df1.combine_first(df2)

output:输出:

     A    B
id0  a    3
id1  b    4
id2  c    0
id3  d   44
id4  r  100

Use concat with filter first duplicates by Index.duplicated :使用concat和按Index.duplicated过滤第一个重复Index.duplicated

df = pd.concat([df1, df2])
df = df[~df.index.duplicated()]
print (df)
     A    B
id0  a    3
id1  b    4
id2  c    0
id3  d   44
id4  r  100

声明:本站的技术帖子网页,遵循CC BY-SA 4.0协议,如果您需要转载,请注明本站网址或者原文地址。任何问题请咨询:yoyou2525@163.com.

 
粤ICP备18138465号  © 2020-2024 STACKOOM.COM