I have a Pandas DataFrame that includes a column with in each row a Numpy array of fixed length (say 30) with integers. However, I cannot find a way to split the np array and for each integer in the array, create a new DataFrame column 0 ... 29.
For example (C consists of np.ndarrays):
A B C
1 0 0 [0,3,4,...]
2 1 1 [0,1,2,...]
3 2 2 [3,4,5,...]
4 3 3 [5,6,7,...]
Should be:
A B 0 1 2 ... 29
1 0 0 0 3 4 ...
2 1 1 0 1 2 ...
3 2 2 3 4 5 ...
4 3 3 5 6 7 ...
I can do it for one array s by doing pd.DataFrame(s).T, but not for every row at once (by using something like apply()).
Is there a general solution, if a column would consist of lists instead of np array?
