Pandas：在选定的列上加入数据框
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Pandas: Join dataframes on selected columns
提问by Manu Sharma
I have two data frames as following
我有两个数据框如下
Data Set A
ID type msg
1 High Lets do
2 Low whats it
3 Medium thats it
Data Set B
ID Accounttype
2 Facebook
3 Linkedin
How can I get an updated table with help of join in pandas, it should look like an
如何在加入Pandas的帮助下获得更新的表格，它应该看起来像
Updated DatasetA
ID Account type msg
1 High Lets do
2 Facebook Low whats it
3 Linkedin Medium thats it
I can easily do it in SQL with Update and inner join, how to perform it in pandas, I tried to do it, but most of the operations for append/ merge. Any help will be appreciated
我可以使用更新和内部联接在 SQL 中轻松完成，如何在 Pandas 中执行它，我尝试这样做，但大多数附加/合并操作。任何帮助将不胜感激
回答by Merlin
Try this:
尝试这个：
df4
# ID type msg
# 0 1 High Letsdo
# 1 2 Low whatsit
# 2 3 Medium thatsit
df3:
# ID Accounttype xxx
# 0 2 Facebook 24
# 1 3 Linkedin 44
df4.merge(df3[['ID','Accounttype']],how='left').fillna("")
# ID type msg Accounttype
# 0 1 High Letsdo
# 1 2 Low whatsit Facebook
# 2 3 Medium thatsit Linkedin
回答by Manu Sharma
Seems there is no direct way to do it, so following is suggested
似乎没有直接的方法来做到这一点，所以建议以下
a=b.merge(account,how='left',on='ID')
create a list of columns you want in final data set
在最终数据集中创建您想要的列列表
list=['ID','Account','type','msg']
final=a[[col for col in list if col in b.columns]]
It will give you only desired columns after the left join
左连接后它只会给你想要的列
