Pandas: fetch rows that continuously have a similar value - sql

Question

I have a dataframe like so..
id time status
-- ---- ------
a 1 T
a 2 F
b 1 T
b 2 T
a 3 T
a 4 T
b 3 F
b 4 T
b 5 T
I would like to fetch the ids that continuously have the status 'T' for a certain threshold number of times (say 2 in this case).
Thus the fetched rows would be...
id time status
-- ---- ------
b 1 T
b 2 T
a 3 T
a 4 T
b 4 T
b 5 T
I can think of an iterative solution. What I am looking for is something more pandas/sql like. I think an order by id and then time followed by a group by first by id and then status should work, but I'd like to be sure.

Answer 1

Compare values by Series.eq for T and count consecutive values with Series.shift and Series.cumsum, count by Series.value_counts and Series.map to original - get counts per consecutive groups. Then compare by Series.ge and last filter by boolean indexing chain both mask by bitwise AND:
N = 2
m1 = df['status'].eq('T')
g = df['status'].ne(df['status'].shift()).cumsum()
m2 = g.map(g.value_counts()).ge(N)
df = df[m1 & m2]
print (df)
id time status
2 b 1 T
3 b 2 T
4 a 3 T
5 a 4 T
7 b 4 T
8 b 5 T
Details:
print (df.assign(m1=m1, g=g, counts=g.map(g.value_counts()), m2=m2))
id time status m1 g counts m2
0 a 1 T True 1 1 False
1 a 2 F False 2 1 False
2 b 1 T True 3 4 True
3 b 2 T True 3 4 True
4 a 3 T True 3 4 True
5 a 4 T True 3 4 True
6 b 3 F False 4 1 False
7 b 4 T True 5 2 True
8 b 5 T True 5 2 True