Python itertools groupby with aggregate

Question

I am trying to group on a column based on the sequence it appears (timestamp) and simultaneously finding aggregate (mean) on the other variables within the small group. I can successfully group it but unable to aggregate

Here is my sample input:

Date        T/F X1
12/02/19    T   10
12/02/19    T   20
12/02/19    F   15
12/02/19    T   12
12/03/19    F   10
12/03/19    F   20
12/03/19    T   30
12/04/19    T   40

Expected O/P

Date        T/F X1  Count
12/02/19    T   15  2
12/02/19    F   15  1
12/02/19    T   12  1
12/03/19    F   15  2
12/03/19    T   35  2

Here is the code I am using, which groups and give me the count for each group, how do I get the avg of X1 as well, within that group

import itertools 
for (key,group) in itertools.groupby(df['T/F']): 
    print (key, len(list(group))) 

Thanks for the help!

Answer 1

You can use the function groupby :

df1 = df.assign(Count=np.nan).\
groupby(df['T/F'].ne(df['T/F'].shift()).cumsum(), as_index=False).\
agg({'Date': 'first', 'T/F': 'first', 'X1': 'mean', 'Count': 'size'})

print(df1)

Output:

       Date T/F  X1  Count
0  12/02/19   T  15      2
1  12/02/19   F  15      1
2  12/02/19   T  12      1
3  12/03/19   F  15      2
4  12/03/19   T  35      2