Searching matches columns in 2 df in pandas

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I have 2 df, and I want change value in df1, if it has two matching values in df2

campaign_name adgroup_name status
apple_campaign apple_1 paused
apple_campaign apple_2 paused
apple_campaign apple_3 paused
pear_campaign pear_1 paused
pear_campaign pear_2 paused
pear_campaign pear_3 paused
pear_campaign pear_4 paused
peach_campaign peach_1 paused
peach_campaign peach_2 paused
campaign_name adgroup_name headline others
apple_campaign apple_1 apple chips etc
apple_campaign apple_1 apple cake etc
apple_campaign apple_3 apple juice etc
pear_campaign pear_1 pear chips etc
pear_campaign pear_2 pear cake etc
pear_campaign pear_4 pear juice etc
pear_campaign pear_4 pear pumpkin etc

So, I want to set "Status"->enabled, if df2 has the same "campaign_name", and "adgroup_name"

pandas python
1 Answers

You could merge with indicator and identify the merged rows:

df1.loc[(df1
 .merge(df2, on=['campaign_name', 'adgroup_name'], how='left', indicator=True)
 ['_merge'].eq('both')
), 'status'] = 'enabled'

output:

    campaign_name adgroup_name   status
0  apple_campaign      apple_1  enabled
1  apple_campaign      apple_2  enabled
2  apple_campaign      apple_3   paused
3   pear_campaign       pear_1  enabled
4   pear_campaign       pear_2  enabled
5   pear_campaign       pear_3  enabled
6   pear_campaign       pear_4   paused
7  peach_campaign      peach_1  enabled
8  peach_campaign      peach_2  enabled
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