I have a dataframe of nested lists, with each list having a number of 2-element-lists nested within, looks like follows:
l1 = [[[1,0]],[[1,2],[6,9]],[[0,4]],[[0,4]], [[0,4]]]
l2 = [[[1,0]],[[1,2],[6,9]],[[0,4]],[[0.5]], [[0,6]]]
df_test= pd.DataFrame({'lst1Title': l1,
'lst2Title': l2})
df_test
What I am trying to do is to get the repeated entities under 1st1Title found and the corresponding outputs rows in column lst2Title grouped, and power list (possible permutations wihtout repetition) of 2 element lists generated, and repeated for each - as reproduced and shown bellow:
l1 = [[[1,0]],[[1,2],[6,9]],[[0,4]],[[0,4]], [[0,4]]]
l2 = [[[1,0]],[[1,2],[6,9]],[[0,4]],[[0.5]], [[0,6]]]
l3 = [[[1,0]],[[1,2],[6,9]],[[0,4],[0,5],[0,6],[4,5],[4,6],[5,6]],[[0,4],[0,5],[0,6],[4,5],[4,6],[5,6]], [[0,4],[0,5],[0,6],[4,5],[4,6],[5,6]]]
df_test= pd.DataFrame({'lst1Title': l1,
'lst2Title': l2, 'output': l3})
Ive tried variations of pd.groupby, which was consistently faced with 'list not hashable' error, as well as itertools.groupby, so far no luck.
pd.DataFrame([list(g) for k, g in itertools.groupby(df_test['1stTitle'])])
The number of elements in each column may change (i.e. row 1 in df)test has 2 lists, each with 2 elements) however each core element will always have 2 elements only, or be []. The core lists also dont have repeated numbers, i.e. [4,4] cannot exist.
