Convert List to DataFrame
Let's see. I modified the string a bit, so that it can be saves as a dictionary.

g = {(8758148.0, 'CI Alpine Growth Equity Fund'): 'D    0.000016 Name: 8758148.0, dtype: float64',
 (8758148.0, 'CI American Growth Fund'): 'D    0.0 Name: 8758148.0, dtype: float64',
 (8758148.0, 'CI American Small Companies Fund'): 'D    0.0 Name: 8758148.0, dtype: float64',
 (8758148.0, 'CI American Value Fund'): 'D    0.0 Name: 8758148.0, dtype: float64',
 (8758148.0, 'CI Canadian Equity Fund'): 'D    0.0 Name: 8758148.0, dtype: float64',
 (8758148.0, 'CI Canadian Investment Fund'): 'D    0.0 Name: 8758148.0, dtype: float64',
 (8758148.0, 'CI Canadian Small Cap Fund'): 'D    0.0 Name: 8758148.0, dtype: float64',
 (8758148.0, 'CI Canadian Small/Mid Cap Fund'): 'D    0.0 Name: 8758148.0, dtype: float64',
 (8758148.0, 'CI Global Bond RSP Fund'): 'D    0.0 Name: 8758148.0, dtype: float64',
 (8758148.0, 'CI Harbour Fund'): 'D    0.0 Name: 8758148.0, dtype: float64' }


Now here is the code:

df = pd.DataFrame([i[0] for i in g.keys()], columns=['id'])
df['Name'] = [i[1] for i in g.keys()]
df['Value'] = [i.split()[1] for i in g.values()]
df

    id          Name                            Value
0   8758148.0   CI Alpine Growth Equity Fund    0.000016
1   8758148.0   CI American Growth Fund 0.0
2   8758148.0   CI American Small Companies Fund    0.0
3   8758148.0   CI American Value Fund  0.0
4   8758148.0   CI Canadian Equity Fund 0.0
5   8758148.0   CI Canadian Investment Fund 0.0
6   8758148.0   CI Canadian Small Cap Fund  0.0
7   8758148.0   CI Canadian Small/Mid Cap Fund  0.0
8   8758148.0   CI Global Bond RSP Fund 0.0
9   8758148.0   CI Harbour Fund 0.0