{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import os\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def federal_taxes(gross, status=\"single\", ira=None):\n",
    "    if gross > 113700:\n",
    "        fica = (113700*0.124)/2.\n",
    "\n",
    "    elif gross <= 113700:\n",
    "        fica = (gross*0.124)/2.\n",
    "\n",
    "    if status == \"single\":\n",
    "        if gross > 200000:\n",
    "            medicare = (gross*0.038)/2.\n",
    "\n",
    "        elif gross <= 200000:\n",
    "            medicare = (gross*0.029)/2.\n",
    "            \n",
    "    elif status == \"married\":\n",
    "        if gross > 250000:\n",
    "            medicare = (gross*0.038)/2.\n",
    "\n",
    "        elif gross <= 250000:\n",
    "            medicare = (gross*0.029)/2.\n",
    "\n",
    "   \n",
    "    if type(ira) != type(None):\n",
    "        if ira == \"calc\":\n",
    "            if status == \"single\":\n",
    "                if 0.1*gross <= 5500:\n",
    "                    ira = 0.1*gross\n",
    "                else:\n",
    "                    ira = 5500.\n",
    "                \n",
    "            elif status == \"married\":\n",
    "                if 0.1*gross <= 11000:\n",
    "                    ira = 0.1*gross\n",
    "                else:\n",
    "                    ira = 11000.            \n",
    "        gross = gross - ira\n",
    "        \n",
    "    if status.lower() == \"single\":\n",
    "        std_deduct = 6200\n",
    "        exemption = 3950\n",
    "        gross = gross - std_deduct - exemption \n",
    "\n",
    "        if gross <= 9075:\n",
    "            return 0.1 * gross + fica + medicare\n",
    "\n",
    "        elif (gross > 9075) & (gross <= 36900):\n",
    "            return 907.5 + 0.15 * (gross - 9075) + fica + medicare\n",
    "\n",
    "        elif (gross > 36900) & (gross <= 89350):\n",
    "            return 5081.25 + 0.25 * (gross - 36900) + fica + medicare\n",
    "\n",
    "        elif (gross > 89350) & (gross <= 186350):\n",
    "            return 18193.75 + 0.28 * (gross - 89350) + fica + medicare\n",
    "\n",
    "        elif (gross > 186350) & (gross <= 405100):\n",
    "            return 45353.75 + 0.33 * (gross - 186350) + fica + medicare\n",
    "\n",
    "        elif (gross > 405100) & (gross <= 406750):\n",
    "            return 117541.25 + 0.35 * (gross - 405100) + fica + medicare\n",
    "\n",
    "        elif gross > 406750:\n",
    "            return 118118.75 + 0.369 * (gross - 406750) + fica + medicare\n",
    "\n",
    "    elif status.lower() == \"married\":\n",
    "        std_deduct = 12400\n",
    "        exemption = 7900\n",
    "        gross = gross - std_deduct - exemption\n",
    "\n",
    "        if gross <= 18150:\n",
    "            return 0.1 * gross + fica + medicare\n",
    "\n",
    "        elif (gross > 18150) & (gross <= 73800):\n",
    "            return 1815 + 0.15 * (gross - 18150) + fica + medicare\n",
    "\n",
    "        elif (gross > 73800) & (gross <= 148850):\n",
    "            return 10162.50 + 0.25 * (gross - 73800) + fica + medicare\n",
    "\n",
    "        elif (gross > 148850) & (gross <= 226850):\n",
    "            return 28925 + 0.28 * (gross - 148850) + fica + medicare\n",
    "\n",
    "        elif (gross > 226850) & (gross <= 405100):\n",
    "            return 50765 + 0.33 * (gross - 226850) + fica + medicare\n",
    "\n",
    "        elif (gross > 405100) & (gross <= 457600):\n",
    "            return 109587.50 + 0.35 * (gross - 405100) + fica + medicare\n",
    "\n",
    "        elif gross > 457600:\n",
    "            return 127962.50 + 0.369 * (gross - 457600) + fica + medicare\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def nystate_taxes(gross, status=\"single\", ira=None):\n",
    "    if type(ira) != type(None):\n",
    "        if ira == \"calc\":\n",
    "            if status == \"single\":\n",
    "                if 0.1*gross <= 5500:\n",
    "                    ira = 0.1*gross\n",
    "                else:\n",
    "                    ira = 5500.\n",
    "                \n",
    "            elif status == \"married\":\n",
    "                if 0.1*gross <= 11000:\n",
    "                    ira = 0.1*gross\n",
    "                else:\n",
    "                    ira = 11000.            \n",
    "        gross = gross - ira\n",
    "    \n",
    "    if status.lower() == \"single\":\n",
    "        std_deduct = 7800\n",
    "        gross = gross - std_deduct        \n",
    "\n",
    "        if gross < 8300:\n",
    "            return 0.04*gross\n",
    "\n",
    "        elif (gross >= 8300) & (gross < 11450):\n",
    "            return 0.04*8300 + 0.045*(gross - 8300)\n",
    "\n",
    "        elif (gross >= 11450) & (gross < 13550):\n",
    "            return 0.04*8300 + 0.045*(11450 - 8300) + 0.0525*(gross - 11450)\n",
    "\n",
    "        elif (gross >= 13550) & (gross < 20850):\n",
    "            return 0.04*8300 + 0.045*(11450 - 8300) + 0.0525*(13550 - 11450) + 0.059*(gross - 13550)\n",
    "\n",
    "        elif (gross >= 20850) & (gross < 78400):\n",
    "            return 0.04*8300 + 0.045*(11450 - 8300) + 0.0525*(13550 - 11450) + 0.059*(20850 - 13550) + 0.0645*(gross - 20850)\n",
    "\n",
    "        elif (gross >= 78400) & (gross < 209250):\n",
    "            return 0.04*8300 + 0.045*(11450 - 8300) + 0.0525*(13550 - 11450) + 0.059*(20850 - 13550) + 0.0645*(78400 - 20850) + 0.0665*(gross - 78400)\n",
    "\n",
    "        elif (gross >= 209250) & (gross < 1046350):\n",
    "            return 0.04*8300 + 0.045*(11450 - 8300) + 0.0525*(13550 - 11450) + 0.059*(20850 - 13550) + 0.0645*(78400 - 20850) + 0.0665*(209250 - 78400) + 0.0685*(gross - 209250)\n",
    "\n",
    "        elif gross >= 1046350:\n",
    "            return 0.04*8300 + 0.045*(11450 - 8300) + 0.0525*(13550 - 11450) + 0.059*(20850 - 13550) + 0.0645*(78400 - 20850) + 0.0665*(209250 - 78400) + 0.0685*(1046350 - 209250) + 0.0882*(gross - 1046350)\n",
    "\n",
    "\n",
    "    elif status.lower() == \"married\":\n",
    "        std_deduct = 15650\n",
    "        gross = gross - std_deduct\n",
    "\n",
    "        if gross < 16700:\n",
    "            return 0.04*gross\n",
    "\n",
    "        elif (gross >= 16700) & (gross < 22950):\n",
    "            return 0.04*16700 + 0.045*(gross - 16700)\n",
    "\n",
    "        elif (gross >= 22950) & (gross < 27150):\n",
    "            return 0.04*16700 + 0.045*(22950 - 16700) + 0.0525*(gross - 22950)\n",
    "\n",
    "        elif (gross >= 27150) & (gross < 41800):\n",
    "            return 0.04*16700 + 0.045*(22950 - 16700) + 0.0525*(27150 - 22950) + 0.059*(gross - 27150)\n",
    "\n",
    "        elif (gross >= 41800) & (gross < 156900):\n",
    "            return 0.04*16700 + 0.045*(22950 - 16700) + 0.0525*(27150 - 22950) + 0.059*(41800 - 27150) + 0.0645*(gross - 41800)\n",
    "\n",
    "        elif (gross >= 156900) & (gross < 313850):\n",
    "            return 0.04*16700 + 0.045*(22950 - 16700) + 0.0525*(27150 - 22950) + 0.059*(41800 - 27150) + 0.0645*(156900 - 41800) + 0.0665*(gross - 156900)\n",
    "\n",
    "        elif (gross >= 313850) & (gross < 2092800):\n",
    "            return 0.04*16700 + 0.045*(22950 - 16700) + 0.0525*(27150 - 22950) + 0.059*(41800 - 27150) + 0.0645*(156900 - 41800) + 0.0665*(313850 - 156900) + 0.0685*(gross - 313850)\n",
    "\n",
    "        elif gross >= 2092800:\n",
    "            return 0.04*16700 + 0.045*(22950 - 16700) + 0.0525*(27150 - 22950) + 0.059*(41800 - 27150) + 0.0645*(156900 - 41800) + 0.0665*(313850 - 156900) + 0.0685*(2092800 - 313850) + 0.0882*(gross - 2092800)\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def nycity_taxes(gross, status=\"single\", ira=None):\n",
    "    if type(ira) != type(None):\n",
    "        if ira == \"calc\":\n",
    "            if status == \"single\":\n",
    "                if 0.1*gross <= 5500:\n",
    "                    ira = 0.1*gross\n",
    "                else:\n",
    "                    ira = 5500.\n",
    "                \n",
    "            elif status == \"married\":\n",
    "                if 0.1*gross <= 11000:\n",
    "                    ira = 0.1*gross\n",
    "                else:\n",
    "                    ira = 11000.            \n",
    "        gross = gross - ira\n",
    "    \n",
    "    if status.lower() == \"single\":\n",
    "\n",
    "        if gross <= 12000:\n",
    "            return 0.02907*gross\n",
    "\n",
    "        elif (gross > 12000) & (gross <= 25000):\n",
    "            return 349 + 0.03534*(gross - 12000)\n",
    "\n",
    "        elif (gross > 25000) & (gross <= 50000):\n",
    "            return 808 + 0.03591*(gross - 25000)\n",
    "\n",
    "        elif (gross > 50000) & (gross <= 500000):\n",
    "            return 1706 + 0.03648*(gross - 50000)\n",
    "\n",
    "        elif gross > 500000:\n",
    "            return 18122 + 0.03876*(gross - 500000)\n",
    "\n",
    "\n",
    "    elif status.lower() == \"married\":\n",
    "\n",
    "        if gross <= 21600:\n",
    "            return 0.02907*gross\n",
    "\n",
    "        elif (gross > 21600) & (gross <= 45000):\n",
    "            return 628 + 0.03534*(gross - 21600)\n",
    "\n",
    "        elif (gross > 45000) & (gross <= 90000):\n",
    "            return 1455 + 0.03591*(gross - 45000)\n",
    "\n",
    "        elif (gross > 90000) & (gross <= 500000):\n",
    "            return 3071 + 0.03648*(gross - 90000)\n",
    "\n",
    "        elif gross > 500000:\n",
    "            return 18028 + 0.03876*(gross - 500000)\n",
    "      "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "minimum = 7.25 * 40 * 50 / 1E3\n",
    "\n",
    "salaries = np.linspace(minimum, 200., 10000)\n",
    "taxes_single = np.array([federal_taxes(s*1E3, status=\"single\") for s in salaries])/1E3\n",
    "taxes_single_ira = np.array([federal_taxes(s*1E3, status=\"single\", ira=\"calc\") for s in salaries])/1E3\n",
    "taxes_single_nys = np.array([federal_taxes(s*1E3, status=\"single\") + nystate_taxes(s*1E3, status=\"single\") for s in salaries])/1E3\n",
    "taxes_single_nyc = np.array([federal_taxes(s*1E3, status=\"single\") + nystate_taxes(s*1E3, status=\"single\") + nycity_taxes(s*1E3, status=\"single\") for s in salaries])/1E3\n",
    "\n",
    "taxes_married = np.array([federal_taxes(s*1E3, status=\"married\") for s in salaries])/1E3\n",
    "taxes_married_ira = np.array([federal_taxes(s*1E3, status=\"married\", ira=\"calc\") for s in salaries])/1E3\n",
    "taxes_married_nys = np.array([federal_taxes(s*1E3, status=\"married\") + nystate_taxes(s*1E3, status=\"married\") for s in salaries])/1E3\n",
    "taxes_married_nyc = np.array([federal_taxes(s*1E3, status=\"married\") + nystate_taxes(s*1E3, status=\"married\") + nycity_taxes(s*1E3, status=\"married\") for s in salaries])/1E3\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "14541.25"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "salary = 65000.\n",
    "federal_taxes(salary, status=\"single\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
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       "AElFTkSuQmCC\n"
      ],
      "text/plain": [
       "<matplotlib.figure.Figure at 0x106280750>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(12,4))\n",
    "fig.subplots_adjust(top=0.97, right=0.97, left=0.05, bottom=0.1, wspace=0)\n",
    "ax = plt.subplot(133)\n",
    "ax.plot(salaries, taxes_single_nyc, color=\"b\", linestyle=\":\", linewidth=2)\n",
    "ax.plot(salaries, taxes_married_nyc, color=\"r\", linestyle=\":\", linewidth=2)\n",
    "ax.set_ylim(1,79)\n",
    "ax.set_xticks(np.arange(20,220,20))\n",
    "ax.set_xlim(15)\n",
    "ax.minorticks_on()\n",
    "ax.grid()\n",
    "\n",
    "ax = plt.subplot(132)\n",
    "ax.plot(salaries, taxes_single_nys, color=\"b\", linestyle=\"--\")\n",
    "ax.plot(salaries, taxes_married_nys, color=\"r\", linestyle=\"--\")\n",
    "ax.set_xlabel(\"Total Gross Salary (x $1000)\")\n",
    "ax.set_ylim(1,79)\n",
    "ax.set_xticks(np.arange(20,220,20))\n",
    "ax.set_xlim(15, 195)\n",
    "ax.minorticks_on()\n",
    "ax.grid()\n",
    "\n",
    "ax = plt.subplot(131)\n",
    "ax.plot(salaries, taxes_single, color=\"b\", linewidth=\"2\")\n",
    "ax.plot(salaries, taxes_married, color=\"r\", linewidth=\"2\")\n",
    "ax.text(0.03,0.9,\"Taxes in WA state compared to NY\",transform=ax.transAxes, fontsize=14)\n",
    "ax.set_ylabel(\"Total Taxes (x $1000)\")\n",
    "ax.set_ylim(1,79)\n",
    "ax.set_xlim(salaries[0], salaries[-1])\n",
    "ax.set_xticks(np.arange(20,220,20))\n",
    "ax.set_xlim(15, 195)\n",
    "ax.minorticks_on()\n",
    "ax.grid()\n",
    "\n",
    "# ax.legend((\"Single in WA\",\"Single in NY\",\"Single in NYC\",\"Married in WA\",\"Married in NY\",\"Married in NYC\"), loc=4)\n",
    "plt.savefig(\"taxes_WANY.jpg\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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       "A/r/izU+ZMDc4ncAAAAASUVORK5CYII=\n"
      ],
      "text/plain": [
       "<matplotlib.figure.Figure at 0x106280110>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "## Taxes as fraction of salary\n",
    "fig = plt.figure(figsize=(12,4))\n",
    "fig.subplots_adjust(top=0.97, right=0.97, left=0.05, bottom=0.1, wspace=0)\n",
    "ax = plt.subplot(133)\n",
    "ax.plot(salaries, taxes_single_nyc/salaries * 100, color=\"b\", linestyle=\":\")\n",
    "ax.plot(salaries, taxes_married_nyc/salaries * 100, color=\"r\", linestyle=\":\")\n",
    "ax.set_xticks(np.arange(20,220,20))\n",
    "ax.set_xlim(15, salaries[-1])\n",
    "ax.set_ylim(1,39)\n",
    "ax.minorticks_on()\n",
    "ax.grid()\n",
    "\n",
    "ax = plt.subplot(132)\n",
    "ax.plot(salaries, taxes_single_nys/salaries * 100, color=\"b\", linestyle=\"--\")\n",
    "ax.plot(salaries, taxes_married_nys/salaries * 100, color=\"r\", linestyle=\"--\")\n",
    "ax.set_xticks(np.arange(20,220,20))\n",
    "ax.set_xlim(15, 195)\n",
    "ax.set_ylim(1,39)\n",
    "ax.set_xlabel(\"Total Gross Salary (x $1000)\")\n",
    "ax.minorticks_on()\n",
    "ax.grid()\n",
    "\n",
    "ax = plt.subplot(131)\n",
    "ax.plot(salaries, taxes_single/salaries * 100, color=\"b\", linewidth=\"2\")\n",
    "ax.plot(salaries, taxes_married/salaries * 100, color=\"r\", linewidth=\"2\")\n",
    "ax.set_ylabel(\"Total Percent of Salary (%)\")\n",
    "ax.set_xticks(np.arange(20,220,20))\n",
    "ax.set_xlim(15, 195)\n",
    "ax.set_ylim(1,39)\n",
    "ax.minorticks_on()\n",
    "ax.grid()\n",
    "\n",
    "# ax.legend((\"Single in WA\",\"Single in NY\",\"Single in NYC\",\"Married in WA\",\"Married in NY\",\"Married in NYC\"), loc=4)\n",
    "plt.savefig(\"taxes_WANY_prct.jpg\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "diff = taxes_single - taxes_married\n",
    "diff_prct = (taxes_single/salaries * 100) - (taxes_married/salaries * 100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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       "QmCC\n"
      ],
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1062a4b10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,6))\n",
    "plt.subplot(121)\n",
    "plt.plot(salaries, diff)\n",
    "\n",
    "plt.subplot(122)\n",
    "plt.plot(salaries, diff_prct)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 94.08745875])"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "salaries[np.where(diff_prct == max(diff_prct))]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3904.4148\n"
     ]
    }
   ],
   "source": [
    "print federal_taxes(1081.80*24)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "25963.199999999997"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "1081.80*24"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "56458.15"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "federal_taxes(200000, status=\"single\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "9643.75 2391.775 1705.75 13741.275\n"
     ]
    }
   ],
   "source": [
    "print federal_taxes(50000), nystate_taxes(50000), nycity_taxes(50000), federal_taxes(50000) + nystate_taxes(50000) + nycity_taxes(50000)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### The Financial Life of Mr. Johnny Averageface"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Salary: \\$50K\n",
    "\n",
    "Annual Expenses\n",
    "<ul>\n",
    "<li>Rent: \\$15,600 (\\$1,300 per month)</li>\n",
    "<li>Food: \\$7,500 (\\$150 per week)</li>\n",
    "<li>Credit Card Payment: \\$3,750 (\\$312.50 per month)</li>\n",
    "<li>Student Loan Payment: \\$4,143 (\\$345.24 per month)</li>\n",
    "<li>Funtimes: \\$3,600 (\\$300 per month)</li>\n",
    "</ul>\n",
    "\n",
    "Sources: \n",
    "<ul>\n",
    "<li>http://www.nerdwallet.com/blog/credit-card-data/average-credit-card-debt-household/</li>\n",
    "<li>http://www.finaid.org/calculators/loanpayments.phtml</li>\n",
    "</ul>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
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       "ZvW+lZLen46XpJ0r+xRmVksO9i8Wbd5nFdlTc/8d+Hqa2llMtprgN4F10nKy5wJHpH2D9m22bjsM\n",
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       "wMHezKwG/j9wmDneVs/jyAAAAABJRU5ErkJggg==\n"
      ],
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1068c7710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "salary = 50.*1E3\n",
    "\n",
    "rent = 1300*12\n",
    "food = 150*50\n",
    "\n",
    "taxes = federal_taxes(salary)\n",
    "taxes_nys = federal_taxes(salary) + nystate_taxes(salary)\n",
    "taxes_nyc = federal_taxes(salary) + nystate_taxes(salary) + nycity_taxes(salary)\n",
    "\n",
    "expenses_1 = np.array([taxes, rent, food, 3750, 4143, 3600])/1.E3\n",
    "expenses_2 = np.array([taxes_nys, rent, food, 3750, 4143, 3600])/1.E3\n",
    "expenses_3 = np.array([taxes_nyc, rent, food, 3750, 4143, 3600])/1.E3\n",
    "\n",
    "w = 0.75\n",
    "inds = [1. + w/3]*len(expenses_1)\n",
    "\n",
    "plt.bar(w/3, salary/1E3, width=w, color=\"g\")\n",
    "\n",
    "plt.bar(inds[0], expenses_1[-1], width=w, color=\"b\")\n",
    "plt.bar(inds[0]+1, expenses_2[-1], width=w, color=\"b\")\n",
    "plt.bar(inds[0]+2, expenses_3[-1], width=w, color=\"b\")\n",
    "\n",
    "colors = [\"blue\",\"orange\",\"purple\",\"gray\",\"yellow\",\"r\"]\n",
    "\n",
    "for ii in range(1,len(inds)):\n",
    "    yind = -(ii+1)\n",
    "    plt.bar(inds[ii], expenses_1[yind], bottom=sum(expenses_1[yind+1:]), width=w, color=colors[ii])\n",
    "    plt.bar(inds[ii]+1, expenses_2[yind], bottom=sum(expenses_2[yind+1:]), width=w, color=colors[ii])\n",
    "    plt.bar(inds[ii]+2, expenses_3[yind], bottom=sum(expenses_3[yind+1:]), width=w, color=colors[ii])\n",
    "\n",
    "# plt.legend([\"A\", \"B\", \"C\", \"D\", \"E\", \"F\"])\n",
    "\n",
    "ylines = np.arange(0,100+10,10)\n",
    "for ii in range(10):\n",
    "    plt.plot([0,100],[ylines[ii],ylines[ii]],color='k',linestyle=\":\",alpha=0.5)\n",
    "\n",
    "plt.xlim(0,4.3)\n",
    "plt.ylim(0,salary/1E3 + 10)\n",
    "plt.minorticks_on()\n",
    "plt.ylabel(\"Total Amount (x $1000)\")\n",
    "\n",
    "plt.xticks([w/3+0.35, inds[0]+0.35, inds[0]+1+0.35, inds[0]+2+0.35],[\"Gross\\nIncome\", \"WA\", \"NY State\", \"NY City\"])\n",
    "plt.savefig(\"income_expenses_compare.png\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "13741.275\n"
     ]
    }
   ],
   "source": [
    "# print federal_taxes(80000, status=\"married\") + nystate_taxes(80000, status=\"married\") + nycity_taxes(80000, status=\"married\")\n",
    "print federal_taxes(50000, status=\"single\") + nystate_taxes(50000, status=\"single\") + nycity_taxes(50000, status=\"single\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "197.8166666666667"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "federal_taxes((1081*2 + 1600)*12)/12., 1081*2 + 1600"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1402.18"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "1600-197.82"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5570.0958"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "federal_taxes(30928.90 + (400.04*5 + 388.10), status=\"single\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4849.14585"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "federal_taxes(30928.90, status=\"single\", ira=1200)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": []
  }
 ],
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    "name": "ipython",
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   "file_extension": ".py",
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