🏠 Mortgage Calculator

# Libraries
import datetime
import pytz
from dateutil import parser
from datetime import timezone
from dateutil.relativedelta import relativedelta
## String manipulation
import string
import re #regex
## Data Generation
import random
## Data Manipulation
import pandas as pd
import numpy as np
## Vector Math
from numpy.linalg import norm
## Math
import math
import matplotlib as mpl

class mortgage:
    def __init__ (self,cost,down,sdate,yr_length,intr,prop_tax,pts,cc_pct,hoa,util,ins,fha):
        # load from class
        self.cost = cost
        self.down = down
        self.yrs = yr_length
        self.length = yr_length * 12
        self.fha = fha
        self.sdate = pd.to_datetime(sdate)
        self.intr_curr = intr
        self.pts = pts
        self.cc_pct = cc_pct
        self.hoa = hoa
        self.util = util
        self.ins = ins
        self.proptax = prop_tax
        
        # general functions
        self.mortgage = self.cost - self.down
        self.ltv = self.down/self.mortgage
        self.months = list(range(self.length+1))
        self.intr_12mon = intr/12
        self.savings = self.cost * 0.02
        
        # property tax
        self.ann_proptax = self.cost * self.proptax
        self.mon_proptax = self.ann_proptax / 12
        
        # closing
        self.c_costs = self.mortgage * self.cc_pct
        
        # points
        self.pts_cost = self.mortgage * 0.01 * self.pts
        self.intr = self.intr_curr - (0.0025*self.pts)
        self.mon_intr = self.intr/12
        self.mon_intr_curr = self.intr_curr/12
        
        # pmi
        if self.ltv < 0.2:
            self.ann_pmi =  self.mortgage * 0.01
            self.mon_pmi = self.ann_pmi/12
        else:
            self.ann_pmi = 0
            self.mon_pmi = 0
            self.payoff_pmi = 0
        
        # fha
        if self.fha != 0:
            self.fha_pct = 0.0175
            self.ann_fha = self.mortgage * self.fha_pct
            self.mon_fha = self.ann_fha / 12
        else: 
            self.ann_fha = 0
            self.mon_fha = 0
    
        # end stats
        self.money_on_hand = self.down + self.c_costs + self.pts_cost
        self.mon_mortgage = self.mortgage*((self.mon_intr)*(1+self.mon_intr)**(self.length))/((1+self.mon_intr)**(self.length)-1)
        self.tot_mortgage = self.mon_mortgage * self.length
        self.tot_interest = self.tot_mortgage - self.mortgage
        self.tot_mon_cost = self.mon_mortgage + self.hoa + self.mon_proptax + self.mon_pmi + self.mon_fha + self.ins
        self.tot_upfront_cost = self.down + self.c_costs
        
        if self.ltv < 0.2:
            self.payoff_pmi = round(math.log((((self.cost*0.2)-self.down)*(self.mon_intr))/((self.mon_mortgage-(self.mon_intr*self.mortgage)))+1)/math.log(1+(self.mon_intr))/12,2)
        else: self.payoff_pmi = 0
        
        if self.pts > 0:
            self.self.mon_mortgage = self.mortgage*((self.mon_intr_curr)*(1+self.mon_intr_curr)**(self.length))/((1+self.mon_intr_curr)**(self.length)-1)
            self.mon_mortgage_p_diff = self.self.mon_mortgage - self.mon_mortgage
            self.payoff_pts = round(self.pts_cost/(self.mon_mortgage_p_diff*12),2)
        else: 
            self.mon_mortgage_nop = self.mon_mortgage
            self.mon_mortgage_p_diff = 0
            self.payoff_pts = 0
        
        self.tot_mortgage_cost = self.tot_mortgage + (self.ann_fha * 11) + (self.ann_pmi * self.payoff_pmi)
        self.tot_cost = self.tot_mortgage_cost + self.tot_upfront_cost
        
#         math.log((((self.cost*0.2)-self.down)*(self.mon_intr))/((self.mon_mortgage-(self.mon_intr*self.mortgage))+1))
#         /math.log(1+(self.mon_intr))/12
        
        # data frame
        self.df = pd.DataFrame({'month':self.months})
        
        months = list(range(self.length+1))
        months_real = []
        months_princ = []
        months_intr = []
        for n in months:
            date_real = pd.to_datetime(sdate) + relativedelta(months=n)
            months_real.append(date_real.date().strftime('%m-%d-%Y'))
        self.df['real_date'] = months_real
        
        for n in months:
            princ = (self.mon_mortgage-(self.mon_intr*self.mortgage))*((1+self.mon_intr)**(n)-1)/(self.mon_intr)
            intr = (self.mon_mortgage*n)-princ
            months_princ.append(princ)
            months_intr.append(round(intr,2))
        self.df['principal_paid'] = months_princ
        self.df['interest_paid'] = months_intr
        self.df['short_date'] = self.df['real_date'].apply(lambda x: pd.to_datetime(x).strftime('%B-%Y'))
        
    def mortgage_sentence(self):
        numb = [self.cost, self.down, self.mon_mortgage, self.tot_mortgage, self.tot_interest, self.mon_pmi, self.mon_fha,
                (self.ann_fha*11), self.hoa, self.mon_proptax, self.util, self.tot_mon_cost, self.pts_cost, self.c_costs,
                self.savings, self.tot_upfront_cost, self.ins]
        numb_list = []
        for z in numb:
            z = ('{:,.2f}'.format(round(z,2)))
            numb_list.append('$'+z)
        string = 'For a %s year mortgage on a %s with a %s down payment and a %.2f interest rate, your monthly mortgage payment will be %s. ' %(self.yrs, numb_list[0], numb_list[1], self.intr, numb_list[2])
        string2 = 'The total mortgage cost over %s years is %s, of which %s is interest. ' %(self.yrs, numb_list[3],numb_list[4])
        if self.ltv < 0.2 and self.fha == 0:
            string3 = 'Because your Loan-to-value (LTV) ratio is %.2f, which is lower than 0.2 (20%% downpayment), an additional Premium Mortgage Insurance (PMI) monthly payment of %s is needed. The additional PMI payment will end when the LTV  reaches 0.2. This will happen after %.2f years, assuming no re-financing and on-time payments. ' \
            %(float(self.ltv),numb_list[5], float(self.payoff_pmi))
        elif self.fha == 1:
            string3 = 'Because you have chosen an FHA loan, you will be paying an additional monthly Mortgage Insurance Premium (MIP) of %s for 11 years of the loan. This will add an additional %s to the total cost. ' \
            %(numb_list[6], numb_list[7])
        else: string3 = ''
        if self.hoa > 0:
            string4_1 = 'a monthly HOA payment of %s' %(numb_list[8])
        else: string4_1 = ''
        if self.mon_proptax > 0:
            string4_2 = 'the expected property tax of %s' %(numb_list[9])
        else: string4_2 = ''
        if self.util > 0:
            string4_3 = 'the expected monthly utility bill of %s' %( numb_list[10])
        else: string4_3 = ''
        if self.ins > 0:
            string4_4 = 'the expected monthly insurance of %s' %(numb_list[16])
        else: string4_4 = ''
        if (string4_1 == '' and string4_2 == '' and string4_3 == '' and string4_4 == ''):
            string4 = 'The total monthly payment is %s' %(numb_list[11])
        else:
            string4 = 'Additionally,'
            for x in [string4_1,string4_2,string4_3,string4_4]:
                if x != '':
                    string4 = string4 + ' ' + x + ', and'
            string4 = string4[:-4] + ' will make the monthly payment %s. ' %(numb_list[11])
        if self.pts > 0:
            string5 = 'In opting to buy %s Interest Point(s) for %s (-0.025 interest point per point) to bring down the current interest rate of %.2f to %.2f, it will take %.2f years of monthly mortgage payments to make up the upfront cost. ' %(self.pts, numb_list[12], self.intr_curr, self.intr, self.payoff_pts)
        else: string5 = ''
        string6 = 'You will pay %s upfront, %s of which are closing costs, and should have around %s of savings. ' \
        %(numb_list[15], numb_list[13], numb_list[14])
        return string + string2 + string3 + string4 + string5 + string6
    
    def mortgage_short(self):
        numb = [self.tot_mon_cost,
                self.tot_upfront_cost]
        numb_list = []
        for z in numb:
            z = ('{:,.2f}'.format(round(z,2)))
            numb_list.append('$'+z)
        string = 'Your monthly payment will be %s. Your total upfront costs will be around %s' %(numb_list[0], numb_list[1])
        return string
    
    def mortgage_list(self):
        list_df = pd.DataFrame(columns=['metric', 'value'])
        metric = ['Loan Cost', 'Downpayment', 'Monthly Mortgage', 'Total Mortgage Cost', 'Total Interest', 'Monthly PMI', \
                'Monthly FHA', 'Annual FHA', 'HOA', 'Monthly Property Tax', 'Utilities', 'Insurance', 'Total Monthly Cost', \
                'Points Upfront Cost', 'Closing Costs', 'Savings', 'Total Upfront Costs']
        numb = [self.cost, self.down, self.mon_mortgage, self.tot_mortgage, self.tot_interest, self.mon_pmi, \
                self.mon_fha, (self.ann_fha*11), self.hoa, self.mon_proptax, self.util, self.ins, self.tot_mon_cost, \
                self.pts_cost, self.c_costs, self.savings, self.tot_upfront_cost]
        numb_list = []
        for z in numb:
            z = ('{:,.2f}'.format(round(z,2)))
            numb_list.append('$'+z)
        list_df = pd.DataFrame({'metric':metric, 'value':numb_list})
        return list_df
        

    def mortgage_year(self,yr):
        dte = self.sdate + relativedelta(years=yr)
#         closest_mon = 
#         string = 
        return dte

# (cost,down,sdate,length,intr,prop_tax,pts,cc_pct,hoa,util,fha)
import plotly.express as px
import plotly.graph_objects as go

test = mortgage(450000,50000,'2023-05-01',30,0.04,0.054,0,0.04,0,0,200,0)
test.df

test = mortgage(450000,50000,'2023-05-01',30,0.04,0.054,0,0.04,0,0,200,0)

fig = go.Figure(layout=go.Layout(
        title=go.layout.Title(text="Principal and Interst Over Time")))
fig.add_trace(go.Scatter(x=test.df['short_date'], y=test.df['principal_paid'],
                    mode='lines',
                    name='Principal',
                    stackgroup='one'))
fig.add_trace(go.Scatter(x=test.df['short_date'], y=test.df['interest_paid'],
                    mode='lines',
                    name='Interest',
                    stackgroup='one'))
fig = fig.update_xaxes(showgrid=False, nticks=8)
fig = fig.update_layout(yaxis_tickprefix = '$', yaxis_tickformat = ',')
fig.show()

test = mortgage(450000,50000,'2023-05-01',30,0.04,0.054,0,0.04,0,0,200,0)
test.mortgage_list()

# (cost,down,sdate,length,intr,prop_tax,pts,cc_pct,hoa,util,fha)
mortgage(450000,50000,'2023-05-01',30,0.04,0.054,0,0.04,0,0,200,0).mortgage_sentence()

mortgage(450000,50000,'2023-05-01',30,0.04,0.054,0,0.04,0,0,200,0).mortgage_short()