How to split a DataFrame on each different value in a column?

Question

Below is an example DataFrame.

      0      1     2     3          4
0   0.0  13.00  4.50  30.0   0.0,13.0
1   0.0  13.00  4.75  30.0   0.0,13.0
2   0.0  13.00           


        

Answer 1

Looks like you want to groupby the first colum. You could create a dictionary from the groupby object, and have the groupby keys be the dictionary keys:

out = dict(tuple(df.groupby(0)))

Or we could also build a list from the groupby object. This becomes more useful when we only want positional indexing rather than based on the grouping key:

out = [sub_df for _, sub_df in df.groupby(0)]

We could then index the dict based on the grouping key, or the list based on the group's position:

print(out[0])

    0     1     2     3         4
0  0.0  13.0  4.50  30.0  0.0,13.0
1  0.0  13.0  4.75  30.0  0.0,13.0
2  0.0  13.0  5.00  30.0  0.0,13.0
3  0.0  13.0  5.25  30.0  0.0,13.0
4  0.0  13.0  5.50  30.0  0.0,13.0
5  0.0  13.0  5.75   0.0  0.0,13.0
6  0.0  13.0  6.00  30.0  0.0,13.0