How to groupby consecutive values in pandas DataFrame

Question

I have a column in a DataFrame with values:

[1, 1, -1, 1, -1, -1] 

How can I group them like this?

[1,1] [-1] [1] [-1, -1] 

Answer 1

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] 

Answer 2

Using groupby from itertools data from Jez

from itertools import groupby [ list(group) for key, group in groupby(df.a.values.tolist())] Out[361]: [[1, 1], [-1], [1], [-1, -1]]