Select rows that come after a condition, under a condition in pandas

I have a dataframe that looks like this:

import pandas as pd
pd.DataFrame({'id': [1,1,1,1,2,2,2,2], 
             'time': [1,2,3,4,1,2,5,6],
             'is': [0,1,0,0,0,1,0,0]})

id  time    is
0   1   1   0
1   1   2   1
2   1   3   0
3   1   4   0
4   2   1   0
5   2   2   1
6   2   5   0
7   2   6   0

which is sorted by id and time

I want for each id, to select only the rows that satisfy at least one of the two conditions:

• is==1
• the rows after the rows where is==1 and time between these 2 rows, does not have gaps.

The resulting dataframe should look like this:

pd.DataFrame({'id': [1,1,2], 
             'time': [2,3,2],
             'is': [1,0,1]})

How could I do that ?

>Solution :

You can use groupby.shift:

# form groups
g = df.groupby('id')

# select rows with is==1 and the next ones (per group)
m1 = df['is'].eq(1) | g['is'].shift().eq(1)
# select rows with successive time
m2 = g['time'].diff().eq(1)

out = df[m1&m2]

Output:

   id  time  is
1   1     2   1
2   1     3   0
5   2     2   1