college_value.py

import csv
import sys
import json

import numpy as np


def money(n):
    try:
        return "${:,.2f}".format(n)
    except Exception as e:
        return n

def main():

    college_tuition = 300000
    number_years = 1
    total_college_cost = college_tuition * number_years 
    college_outflows = [-college_tuition for 
        x in range(number_years)]
    cost_of_capital = .075
    project_missing_earnings = False
    npvs = []

    with open('hamilton_project_data.csv', 'rb') as f:
        reader= csv.DictReader(f)
        highschool_str = 'High School Degree or GED'
        non_majors = [highschool_str, 'Year'] 
        majors = [field for field in reader.fieldnames 
            if field not in non_majors]
        rows = list(reader)
        years = len(rows)
        monthly_loan_payment = -np.pmt(cost_of_capital/12, 
            12*years, total_college_cost)

        for major in majors:
            earnings_inflows = []
            earnings_inflows_after_debt = []
            last_earnings_index = 0

            for i, row in enumerate(rows):
                high_school = float(row[highschool_str])
                major_earnings_raw = row.get(major)
                if not major_earnings_raw:
                    # incomplete data for some majors/years 
                    if last_earnings_index == 0: 
                        last_earnings_index = i - 1
                    if project_missing_earnings:
                        major_earnings_raw = rows[last_earnings_index].get(major) 
                    else:
                        major_earnings_raw = '0' 

                major_earnings = float(major_earnings_raw)
                earnings_difference = major_earnings - high_school
                earnings_inflows.append(earnings_difference)
                earnings_difference_after_debt = earnings_difference - (monthly_loan_payment * 12)
                earnings_inflows_after_debt.append(earnings_difference_after_debt)

            total_cashflows = college_outflows + earnings_inflows
            npv = np.npv(cost_of_capital, total_cashflows) 
            irr = np.irr(total_cashflows)

            result = {
                'major': major, 
                'npv': npv, 
                'earnings_differences': earnings_inflows,
                'earnings_differences_after_debt': earnings_inflows_after_debt,
            }

            npvs.append(result)

    npvs = sorted(npvs, key=lambda k: k['npv'])
    writer = csv.writer(sys.stdout)

    print 'All NPVs'
    print '==========================='
    writer.writerow(['Major', 'NPV'])
    for row in npvs:
        writer.writerow([row['major'][:30], money(row['npv'])])
    print '\n\n\n'
    print 'NPVs with No Worse Off'
    print '==========================='
    npvs_plus_plus = [x for x in npvs if not 
        any([y < 0 for y in x['earnings_differences_after_debt']]) 
        and x['npv'] > 0
    ]
    writer.writerow(['Major', 'NPV'])
    for row in npvs_plus_plus:
        writer.writerow([row['major'][:30], money(row['npv'])])


if __name__ == '__main__':
    main()