Reputation: 33
df = pd.DataFrame({'site':[1,1,1,1,1,1,1,1,1,1], 'parm':[8,8,8,8,8,9,9,9,9,9],
'date':[1,2,3,4,5,1,2,3,4,5], 'obs':[1,1,2,3,3,3,5,5,6,6]})
Output
site parm date obs
0 1 8 1 1
1 1 8 2 1
2 1 8 3 2
3 1 8 4 3
4 1 8 5 3
5 1 9 1 3
6 1 9 2 5
7 1 9 3 5
8 1 9 4 6
9 1 9 5 6
I want to count repeating, sequential "obs" values within a "site" and "parm". I have this code which is close:
df['consecutive'] = df.parm.groupby((df.obs != df.obs.shift()).cumsum()).transform('size')
Output
site parm date obs consecutive
0 1 8 1 1 2
1 1 8 2 1 2
2 1 8 3 2 1
3 1 8 4 3 3
4 1 8 5 3 3
5 1 9 1 3 3
6 1 9 2 5 2
7 1 9 3 5 2
8 1 9 4 6 2
9 1 9 5 6 2
It creates the new column with the count. The gap is when the parm changes from 8 to 9 it includes the parm 9 in the parm 8 count. The expected output is:
site parm date obs consecutive
0 1 8 1 1 2
1 1 8 2 1 2
2 1 8 3 2 1
3 1 8 4 3 2
4 1 8 5 3 2
5 1 9 1 3 1
6 1 9 2 5 2
7 1 9 3 5 2
8 1 9 4 6 2
9 1 9 5 6 2
Upvotes: 3
Views: 143
Reputation: 150735
You need to throw site, parm
as indicated in the question into groupby
:
df['consecutive'] = (df.groupby([df.obs.ne(df.obs.shift()).cumsum(),
'site', 'parm']
)
['obs'].transform('size')
)
Output:
site parm date obs consecutive
0 1 8 1 1 2
1 1 8 2 1 2
2 1 8 3 2 1
3 1 8 4 3 2
4 1 8 5 3 2
5 1 9 1 3 1
6 1 9 2 5 2
7 1 9 3 5 2
8 1 9 4 6 2
9 1 9 5 6 2
Upvotes: 4