You can use groupby
by custom Series
:
df = pd.DataFrame({'a': [1, 1, -1, 1, -1, -1]})
print (df)
a
0 1
1 1
2 -1
3 1
4 -1
5 -1
print ((df.a != df.a.shift()).cumsum())
0 1
1 1
2 2
3 3
4 4
5 4
Name: a, dtype: int32
for i, g in df.groupby([(df.a != df.a.shift()).cumsum()]):
print (i)
print (g)
print (g.a.tolist())
a
0 1
1 1
[1, 1]
2
a
2 -1
[-1]
3
a
3 1
[1]
4
a
4 -1
5 -1
[-1, -1]
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