As the title goes this is very similar to: Split a Pandas column of lists into multiple columns
However, in my df I don't know a priori the length of the longest list and I find not efficient assigning columns manually.
For now I convert the lists to strings and then I use:
df = pd.DataFrame(d1['l'].astype(str).str.replace("[\[\],\']","",regex=True).str.split().values.tolist())
input:
d1 = {'teams': [['SF', 'NYG', 'aks', 'tls', 'slp', 'raa', 'gla'],['SF', 'NYG'],['SF', 'NYG'],
['SF', 'NYG'],['SF', 'NYG'],['SF', 'NYG'],['SF', 'NYG']]}
d1 = pd.DataFrame(d1)
print (df2)
teams
0 [SF, NYG, aks, tls, slp, raa, gla]
1 [SF, NYG]
2 [SF, NYG]
3 [SF, NYG]
4 [SF, NYG]
5 [SF, NYG]
6 [SF, NYG]
Out:
team1 team2 teamn
0 SF NYG .... gla
1 SF NYG
2 SF NYG None
3 SF NYG None
4 SF NYG
5 SF NYG
6 SF NYG
Any quicker alternative?
