I am trying to replace the first occurance based on the ID. My dataset looks like this:

df=

Index     ID             Status  
0     1895001            review   
1     1895001            review      
2     1895001            review      
3     2104264            review        
4     2102404            review        
5     2102404            review         
6     1809905            review
7     1809905            review       
8     1809905            review      
9     1811700            review

I tried this df.values[df.index, np.argmax(df.values=="review",1)] = "first review", but it replaces all of them 🙁

This is what I am expecting:

df=

Index   ID                   Status
0    1895001             first review         
1    1895001             review      
2    1895001             review       
3    2104264             first review        
4    2102404             first review        
5    2102404             review         
6    1809905             first review
7    1809905             review       
8    1809905             review       
9    1811700             first review

>Solution :

Use boolean indexing with the boolean inverse (~) of duplicated:

df.loc[~df['ID'].duplicated(), 'Status'] = 'first review'

Output:

   Index       ID        Status
0      0  1895001  first review
1      1  1895001        review
2      2  1895001        review
3      3  2104264  first review
4      4  2102404  first review
5      5  2102404        review
6      6  1809905  first review
7      7  1809905        review
8      8  1809905        review
9      9  1811700  first review