custom groupby function pandas python

user_9379421 0
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I have a following dataframe:

enter image description here

I would like to group by id and add a flag column which contains Y if anytime Y has occurred against id, resultant DF would like following:

enter image description here

Here is my approach which is too time consuming and not sure of correctness:

temp=pd.DataFrame()
j='flag'
for i in df['id'].unique():
  test=df[df['id']==i]
  test[j]=np.where(np.any((test[j]=='Y')),'Y',test[j])
temp=temp.append(test)
pandas for-loop group-by python
2 Answers

Compare flag to Y, group by id, and use any:

new_df = (df['flag'] == 'Y').groupby(df['id']).any().map({True:'Y', False:'N'}).reset_index()

Output:

>>> new_df
   id flag
0   1    Y
1   2    Y
2   3    N
3   4    N
4   5    Y
Admin1

You can do groupby + max since Y > N:

df.groupby('id', as_index=False)['flag'].max()

   id flag
0   1    Y
1   2    Y
2   3    N
3   4    N
4   5    Y
user_128331660
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