Insert into sublist if sublist is not having same no of records.

[michalmonday]

I added pandas way too, trying to make it a little more concise, it would be cool if some pandas wizard would post an optimal solution just to check how good it can possibly look like

def Decimal(x):
    return x

results = [
    (Decimal('28000.0000'), 2010, 272), (Decimal('308000.0000'), 2011, 272),
    (Decimal('582000.0000'), 2012, 272), (Decimal('387000.0000'), 2013, 272),
    (Decimal('367000.0000'), 2010, 281), (Decimal('3037000.0000'), 2011, 281),
    (Decimal('4822000.0000'), 2012, 281), (Decimal('2936000.0000'), 2013, 281),
    (Decimal('637000.0000'), 2010, 282), (Decimal('3440000.0000'), 2011, 282),
    (Decimal('478000.0000'), 2010, 296), (Decimal('1209000.0000'), 2012, 296)
]
 
#Desired output


years = sorted(set([x[1] for x in results]))
employees = sorted(set([x[2] for x in results]))

sales = []
for emp in employees:
    
    # get all the results for that particular employee
    emp_results = [x for x in results if x[2] == emp]

    # init/fill emp_sales with as many 0's as there are years
    emp_sales = [0] * len(years)
    
    for year_index, year in enumerate(years):
        for result_year, result_sales_amount in [(x[1], x[0]) for x in emp_results]:
            if year == result_year:
                emp_sales[year_index] = result_sales_amount
                
    sales.append(emp_sales)
    
print('years:\n', years, '\n')
print('employees:\n', employees, '\n')
print('sales:\n', sales, '\n')

Output:
years:
 [2010, 2011, 2012, 2013] 

employees:
 [272, 281, 282, 296] 

sales:
 [['28000.0000', '308000.0000', '582000.0000', '387000.0000'], ['367000.0000', '3037000.0000', '4822000.0000', '2936000.0000'], ['637000.0000', '3440000.0000', 0, 0], ['478000.0000', 0, '1209000.0000', 0]] 

import pandas as pd

def Decimal(x):
    return x

results = [
    (Decimal('28000.0000'), 2010, 272), (Decimal('308000.0000'), 2011, 272),
    (Decimal('582000.0000'), 2012, 272), (Decimal('387000.0000'), 2013, 272),
    (Decimal('367000.0000'), 2010, 281), (Decimal('3037000.0000'), 2011, 281),
    (Decimal('4822000.0000'), 2012, 281), (Decimal('2936000.0000'), 2013, 281),
    (Decimal('637000.0000'), 2010, 282), (Decimal('3440000.0000'), 2011, 282),
    (Decimal('478000.0000'), 2010, 296), (Decimal('1209000.0000'), 2012, 296)
]

pd.set_option('display.float_format', '{:.2f}'.format)

df = pd.DataFrame(results, columns = ['sales' , 'year', 'employee'])

years = df['year'].unique()
employees = df['employee'].unique()

new_df = pd.DataFrame(index = employees, columns = years)

for emp in employees:
    emp_df = df.loc[df['employee'] == emp]

    new_df.loc[emp, : ] = [float(emp_df.loc[emp_df['year']==year]['sales']) if year in list(emp_df['year']) else 0 for year in years]

print(new_df)

Output:
         2010       2011       2012       2013
272  28000.00  308000.00  582000.00  387000.00
281 367000.00 3037000.00 4822000.00 2936000.00
282 637000.00 3440000.00          0          0
296 478000.00          0 1209000.00          0