How can I split a list into a list of lists based on the difference between adjacent elements?

Question

E.g., if I've got

MAX_ALLOWED_DIFF = 3
nums=[1, 2, 4, 10, 13, 2, 5, 5, 5]

the output should be

groups = [[1, 2, 4], [10, 13], [2, 5, 5, 5]]

The context: I had a pandas.Series object nums and I used

nums = nums.diff().gt(DETECTION_MAX_DIFF_NS).cumsum()).apply(list).tolist()

to subsample in the same fashion but I noticed that there're a lot of duplicates in my Series nums and after I use .unique() method I don't have Series object anymore, I've got numpy.ndarray (1D) instead.

I believe I may use sth like pandas.Series(nums.unique) but I don't like this hack.

Answer 1

So we using drop_duplicates, keep nums stay in pd.Series

nums=nums.drop_duplicates()
nums.groupby(nums.diff().abs().gt(MAX_ALLOWED_DIFF).cumsum()).apply(list).tolist()
Out[447]: [[1, 2, 4], [10, 13], [5]]