Ufdjrw

I am relatively new to Python so pardon my question if it's relatively basic (have not been able to find anything helpful online).

I have a dataframe that has 3 columns, Fund | Investor | Quantity, and need to insert a new column into my dataframe that calculates each investors' pro-rata ownership.

I assume looping through the dataframe is the best way to do this but am having issues.

See this question.
Therefore you can group and apply:

In [1]: df = pd.DataFrame([
 ...: ['Fund 1','Investor A', 10],
 ...: ['Fund 1','Investor B', 20],
 ...: ['Fund 2','Investor A', 30],
 ...: ['Fund 2','Investor B', 40],
 ...: ['Fund 2','Investor C', 30],
 ...: ['Fund 3','Investor A', 50],
 ...: ['Fund 3','Investor B', 50],
 ...: ], columns=['Fund','Investor', 'Qty'])
 ...:

In [2]: df['wanted'] = df.groupby('Fund').Qty.apply(lambda x: x/x.sum())

In [3]: df
Out[3]:
 Fund Investor Qty wanted
0 Fund 1 Investor A 10 0.333333
1 Fund 1 Investor B 20 0.666667
2 Fund 2 Investor A 30 0.300000
3 Fund 2 Investor B 40 0.400000
4 Fund 2 Investor C 30 0.300000
5 Fund 3 Investor A 50 0.500000
6 Fund 3 Investor B 50 0.500000

The last step towards the percentages will be easy for you.

It would be very easy if you can post your code but for reference you can use like:

df['D'] = df['A'] + df['B'] + df['C']

try above way in your existing code. Let me know if it helps.

try:

df['percent'] = df['QTY'] / df.groupby('Fund')['QTY'].transform('sum') * 100