057-Lippert.ipynb

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   "source": [
    "# Jupyter in Education Talk\n",
    "## How to become financially independent with interactive widgets"
   ]
  },
  {
   "cell_type": "code",
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   "metadata": {
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   "outputs": [],
   "source": [
    "# Execute this cell to load the notebook's style sheet, then ignore it\n",
    "from IPython.core.display import HTML\n",
    "css_file = '../style/custom.css'\n",
    "HTML(open(css_file, \"r\").read())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import ipywidgets as widgets\n",
    "import matplotlib.ticker as mtick\n",
    "from IPython.display import YouTubeVideo, display"
   ]
  },
  {
   "cell_type": "code",
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   "source": [
    "#future self functions\n",
    "savings = .0000001\n",
    "money_market = .01\n",
    "cd = .01\n",
    "stocks = .07\n",
    "\n",
    "def calc_simple_compound_interest(i, r, t, one_time):\n",
    "    if one_time is True:\n",
    "        return i*(1+r)**t\n",
    "    else:\n",
    "        return i * (1+r) ** t + i * (1+r) * ((1+r) ** t - 1) / r\n",
    "    \n",
    "def get_compound_simple_df(i, one_time):\n",
    "    start_age = 20\n",
    "    stop_age = 60\n",
    "    yi = i*365\n",
    "    \n",
    "    df = pd.DataFrame({'Age': pd.Series(range(start_age,stop_age))})\n",
    "    \n",
    "    df['Mattress 0%'] = df.apply(lambda x: calc_simple_compound_interest(yi, savings, x['Age']-start_age, one_time), axis=1)\n",
    "    df['Money Market'] = df.apply(lambda x: calc_simple_compound_interest(yi, money_market, x['Age']-start_age, one_time), axis=1)\n",
    "    df['Bank/CD 1%'] = df.apply(lambda x: calc_simple_compound_interest(yi, cd, x['Age']-start_age, one_time), axis=1)\n",
    "    df['Stocks 7%'] = df.apply(lambda x: calc_simple_compound_interest(yi, stocks, x['Age']-start_age, one_time), axis=1)\n",
    "    \n",
    "    return df\n",
    "\n",
    "style = {'description_width': 'initial'}\n",
    "\n",
    "fs_rn_investment = widgets.IntSlider(\n",
    "    value=1,\n",
    "    min=1,\n",
    "    max=20,\n",
    "    step=1,\n",
    "    description='Daily amount you save & invest: $',\n",
    "    disabled=False,\n",
    "    continuous_update=False,\n",
    "    orientation='horizontal',\n",
    "    layout=widgets.Layout(width='100%'),\n",
    "    style=style,\n",
    "    readout=True,\n",
    "    readout_format='d'\n",
    ")\n",
    "\n",
    "fs_rn_play = widgets.Play(\n",
    "    value=1,\n",
    "    min=1,\n",
    "    max=20,\n",
    "    step=1,\n",
    "    description=\"Press play\",\n",
    "    interval=500,\n",
    "    #speed=0,\n",
    "    disabled=False\n",
    ")\n",
    "\n",
    "def fs_rn_output(i):\n",
    "    #create and display dataframe\n",
    "    df_plot = get_compound_simple_df(i, False)\n",
    "    ax = df_plot.plot.line(x='Age', y=['Mattress 0%', 'Bank/CD 1%', 'Stocks 7%'], figsize=(12,10), linewidth=3, grid=True, ylim=(0,1000000))\n",
    "    fmt = '${x:,.0f}'\n",
    "    tick = mtick.StrMethodFormatter(fmt)\n",
    "    ax.yaxis.set_major_formatter(tick)\n",
    "\n",
    "    #display(df_plot)\n",
    "    return(\"compare rate returns example\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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   "outputs": [],
   "source": [
    "#retirement functions\n",
    "\n",
    "def calc_stash_compound_interest(w, i, r, t):\n",
    "    return w + (i * (1+r) ** t + i * (1+r) * ((1+r) ** t - 1) / r)\n",
    "\n",
    "def calc_principal(w, i, t):\n",
    "    return w + (i * t)\n",
    "\n",
    "def get_retirement_df(rate, age, max_age, salary, spending, net_worth):\n",
    "    \n",
    "    df = pd.DataFrame({'Age': pd.Series(range(age, max_age))})\n",
    "\n",
    "    df['Yearly Income'] = df.apply(lambda x: salary, axis=1)\n",
    "    df['Yearly Spending'] = df.apply(lambda x: spending, axis=1)\n",
    "    df['Yearly Savings'] = df.apply(lambda x: salary-spending, axis=1)\n",
    "    df['Total Stash'] = df.apply(lambda x: calc_stash_compound_interest(net_worth, salary-spending, rate*.01, x['Age']-age), axis=1)\n",
    "    df['Principal'] = df.apply(lambda x: calc_principal(net_worth, salary-spending, x['Age']-age), axis=1)\n",
    "    df['Total Stash'] = df['Total Stash'].astype('int64')\n",
    "    df['Principal'] = df['Principal'].astype('int64')\n",
    "    return df\n",
    "\n",
    "style = {'description_width': 'initial'}\n",
    "\n",
    "ma = 80\n",
    "age = widgets.IntText(\n",
    "    value=20,\n",
    "    placeholder=20,\n",
    "    description='Age you begin investing:',\n",
    "    readout_format='d',\n",
    "    style=style,\n",
    "    disabled=False\n",
    ")\n",
    "\n",
    "rate = widgets.IntText(\n",
    "    value=4,\n",
    "    placeholder=4,\n",
    "    description='Rate of return on investments:',\n",
    "    readout_format='d',\n",
    "    style=style,\n",
    "    disabled=False\n",
    ")\n",
    "\n",
    "salary = widgets.IntText(\n",
    "    value=80000,\n",
    "    placeholder=80000,\n",
    "    description='Yearly Salary: $',\n",
    "    readout_format='d',\n",
    "    style=style,\n",
    "    disabled=False\n",
    ")\n",
    "\n",
    "spending = widgets.IntText(\n",
    "    value=60000,\n",
    "    placeholder=60000,\n",
    "    description='Yearly Spending: $',\n",
    "    readout_format='d',\n",
    "    style=style,\n",
    "    disabled=False\n",
    ")\n",
    "\n",
    "net_worth = widgets.IntText(\n",
    "    value=20000,\n",
    "    placeholder=20000,\n",
    "    description='Current amount of assets or debt: $',\n",
    "    readout_format='d',\n",
    "    style=style,\n",
    "    disabled=False\n",
    ")\n",
    "\n",
    "def r_output(r, a, sal, sp, w):\n",
    "    #create and display dataframe\n",
    "    \n",
    "    def get_ret_age(df, ret_tgt):\n",
    "        try:\n",
    "            return df['Age'][df['Total Stash'] >= ret_tgt].iloc[0]\n",
    "        except:\n",
    "            return None\n",
    " \n",
    "    def get_ret_num(df, ret_age):\n",
    "        try:\n",
    "            return df['Total Stash'][df['Age'] >= ret_age].iloc[0]\n",
    "        except:\n",
    "            return df['Total Stash'].max()\n",
    "        \n",
    "    def func(stash, retire_number):\n",
    "        if stash > retire_number:\n",
    "            return retire_number\n",
    "        else:\n",
    "            return stash\n",
    "\n",
    "    df_plot = get_retirement_df(r, a, ma, sal, sp, w)\n",
    "    ret_target = 25*sp\n",
    "    ret_age = get_ret_age(df_plot, ret_target)\n",
    "    ret_number = get_ret_num(df_plot, ret_age)\n",
    "    df_plot['Retired Stash'] = df_plot.apply(lambda x: func(x['Total Stash'], ret_number), axis=1)\n",
    "\n",
    "    if ret_age is None:\n",
    "        print(\"Try reducing your spending or you won't have enough money to retire.\")\n",
    "    else:\n",
    "        ax = df_plot.plot.line(x='Age', y=['Principal', 'Total Stash', 'Retired Stash'], figsize=(12,10), linewidth=3, grid=True)\n",
    "        fmt = '${x:,.0f}'\n",
    "        tick = mtick.StrMethodFormatter(fmt)\n",
    "        ax.yaxis.set_major_formatter(tick)\n",
    "        ymin, ymax = ax.get_ylim()\n",
    "        xmin, xmax = ax.get_xlim()\n",
    "        ax.scatter(ret_age, ret_number, s=700, color='yellow', zorder=10)\n",
    "        ax.text(ret_age, ret_number+(ymax/100), s='   You may be able to retire at age ' + str(ret_age), fontsize='xx-large', fontweight='bold', color = 'purple', zorder=11)\n",
    "\n",
    "    #display(df_plot)\n",
    " \n",
    "    return(\"compare rate returns example\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# FIRE Overview"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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   },
   "outputs": [],
   "source": [
    "#a 5 minute overview of FIRE\n",
    "YouTubeVideo('8si7cqw9wm0')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Track your spending - budgeting\n",
    "\n",
    "## First steps to acheiving Financial Independence\n",
    "1. Understand how much you make and how much you spend\n",
    "2. Understand where you spend your money\n",
    "    - Everyone has different styles or preferences (more or less granularity)\n",
    "    - Here are my bins (housing, health, food, transportation, utilities, miscellaneous)\n",
    "\n",
    "**Tools**\n",
    "- YNAB & MINT\n",
    "- Excel\n",
    "- Quicken\n",
    "- Bank apps"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Steps to lower your spending\n",
    "### 1. Payoff debts\n",
    "### 2. Lower spending\n",
    "### 3. Build Emergency funds\n",
    "### 4. Invest"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## How to lower your spending without being miserable?\n",
    "### Why are you buying that?  (Greed or Fear)\n",
    "### Does that thing really make you happy?\n",
    "- The concept of badassity.\n",
    "- The challenge of consumerism"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Be nice to your future self\n",
    "### 1 coffee at \\\\$4 a day times 365 days in a year = \\\\$1460\n",
    "### minus 1 bag of coffee \\\\$8 each week at home = \\\\$416\n",
    "### total savings = \\\\$1044 per year"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Be really nice to your future self"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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   "outputs": [],
   "source": [
    "fs_rn_res = widgets.interactive(fs_rn_output, i=fs_rn_investment)\n",
    "widgets.jslink((fs_rn_play, 'value'), (fs_rn_investment, 'value'))\n",
    "widgets.VBox([fs_rn_play, fs_rn_res])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Investing\n",
    " ## Warning I am NOT an accredited financial advisor\n",
    " ### Investing versus saving\n",
    " ### Investment options\n",
    " - Savings\n",
    " - Money Market\n",
    " - Certificate of Deposit (CD)\n",
    " - Stocks\n",
    " - Company investments (401k, Employee Stock Purchase Plans, etc.) - read the fine print - matching, vesting\n",
    " - Home/property\n",
    " - Others (Lending Club, Peer Street)\n",
    " \n",
    "### Invest early and often (more compound interest magic)\n",
    "### Set it and forget it"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4% and 25 times rules"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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   },
   "outputs": [],
   "source": [
    "r_res = widgets.interactive(r_output, r=rate, a=age, sal=salary, sp=spending, w=net_worth)\n",
    "widgets.VBox([r_res])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Takeaway\n",
    " - Track your spending - budgeting\n",
    " - Payoff debts\n",
    " - Lower your spending\n",
    " - Build emergency fund\n",
    " - Invest for the future\n",
    "    - Be nice to your future self\n",
    "    - How soon can you retire?\n",
    "    - The 4% rule\n",
    "    - Invest early and often (more compound interest magic)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Links\n",
    "- FIRE Intro on Youtube - https://www.youtube.com/watch?v=8si7cqw9wm0\n",
    "- FIRE retirement calculator - https://playingwithfire.co/retirementcalculator/\n",
    "- Mr. Money Mustache & the 4% Rule - https://www.mrmoneymustache.com/2012/05/29/how-much-do-i-need-for-retirement/\n",
    "- compound interest - https://www.fool.com/how-to-invest/thirteen-steps/step-1-change-your-life-with-one-calculation.aspx"
   ]
  },
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