ValueError: cannot insert ID, already exists

Question

I have this data:

ID   TIME 1    2 1    4 1    2 2    3 

I want to group the data by ID and calculate the mean time and the size of each group.

ID   MEAN_TIME COUNT 1    2.67      3 2    3.00      1 

If I run this code, then I get an error "ValueError: cannot insert ID, already exists":

result = df.groupby(['ID']).agg({'TIME': 'mean', 'ID': 'count'}).reset_index() 

Answer 1

Use parameter drop=True which not create new column with index but remove it:

result = df.groupby(['ID']).agg({'TIME': 'mean', 'ID': 'count'}).reset_index(drop=True) print (result)    ID      TIME 0   3  2.666667 1   1  3.000000 

But if need new column from index need rename old column names first:

result = df.groupby(['ID']).agg({'TIME': 'mean', 'ID': 'count'})            .rename(columns={'ID':'COUNT','TIME':'MEAN_TIME'})            .reset_index() print (result)    ID  COUNT  MEAN_TIME 0   1      3   2.666667 1   2      1   3.000000 

Solution if need aggreagate by multiple columns:

result = df.groupby(['ID']).agg({'TIME':{'MEAN_TIME': 'mean'}, 'ID': {'COUNT': 'count'}}) result.columns = result.columns.droplevel(0) print (result.reset_index())    ID  COUNT  MEAN_TIME 0   1      3   2.666667 1   2      1   3.000000