[英]How to update pandas dataframe columns based on another dataframe faster?
[英]How to Update Dataframe based on Results of Another Dataframe Using Pandas
我有两个名为channels和videos的数据框。
我需要一种方法来更新视频 > 网站列实例,基于频道 > 网站列实例中存储和匹配的信息。
使用的 ID 是:
Channel ID Website
========= ===== =======
Company A A0001 a.com
Company B A0002 b.com
Company C A0003 c.com
Company D A0004 d.com
Category Channel_id Channel_name website
======== ========== ============ =======
Comedy A0003 AAA
Action A0004 BBB
Horror A0008 CCC
Comedy A0001 DDD
Comedy A0044 EEE
Comedy A0002 FFF
Category Channel_id Channel_name website
Comedy A0003 AAA c.com
Action A0004 BBB d.com
Horror A0008 CCC
Comedy A0001 DDD a.com
Comedy A0044 EEE
Comedy A0002 FFF b.com
先感谢您。
你能试试这个吗?
result = pd.merge(videos, channels[['ID', 'Website']], how='left', left_on='Channel_id', right_on='ID').drop(columns='ID').fillna('')
输出
Category Channel_id Channel_name Website
0 Comedy A0003 AAA c.com
1 Action A0004 BBB d.com
2 Horror A0008 CCC
3 Comedy A0001 DDD a.com
4 Comedy A0044 EEE
5 Comedy A0002 FFF b.com
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