{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Load Packages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "printyellow (generic function with 1 method)"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "using Printf, Dates, Statistics, CSV, DataFrames\n",
    "include(\"jlFiles/printmat.jl\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Loading Some Data with CSV.jl"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The first 4 lines of Data/Options_prices_US_Canada.csv:\n",
      "\n",
      "symbol,exchange,date,adjusted close,option symbol,expiration,strike,call/put,style,ask,bid,volume,open interest,unadjusted\n",
      "SPX,CBOE,03/30/17,2368.06,SPXW  170331C00300000,03/31/17,300,C,E,2073.9,2062.9,0,0,2368.927\n",
      "SPX,CBOE,03/30/17,2368.06,SPXW  170331P00300000,03/31/17,300,P,E,0.1,0,0,0,2368.927\n",
      "SPX,CBOE,03/30/17,2368.06,SPXW  170331C00400000,03/31/17,400,C,E,1974.1,1962.7,0,0,2368.927\n",
      "\n"
     ]
    }
   ],
   "source": [
    "DataFile = \"Data/Options_prices_US_Canada.csv\"\n",
    "\n",
    "println(\"The first 4 lines of $(DataFile):\\n\")\n",
    "txt = readlines(DataFile)\n",
    "printmat(txt[1:4])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Use `normalizenames` to get names that can be used in Julia as variables names and specify the `dateformat` used in the csv file (to convert to proper Julia dates). The dates in the file are given as `03/30/17` which CSV/DataFrames interpret as 30 March year 17 (AD). We add `Dates.Year(2000)` to get year 2017."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m13952×10 DataFrame\u001b[0m\n",
      "\u001b[1m   Row \u001b[0m│\u001b[1m symbol  \u001b[0m\u001b[1m date       \u001b[0m\u001b[1m close   \u001b[0m\u001b[1m expiration \u001b[0m\u001b[1m strike  \u001b[0m\u001b[1m call_put \u001b[0m\u001b[1m ask     \u001b[0m\u001b[1m\u001b[0m ⋯\n",
      "\u001b[1m       \u001b[0m│\u001b[90m String3 \u001b[0m\u001b[90m Date       \u001b[0m\u001b[90m Float64 \u001b[0m\u001b[90m Date       \u001b[0m\u001b[90m Float64 \u001b[0m\u001b[90m String1  \u001b[0m\u001b[90m Float64 \u001b[0m\u001b[90m\u001b[0m ⋯\n",
      "───────┼────────────────────────────────────────────────────────────────────────\n",
      "     1 │ SPX      2017-03-30  2368.06  2017-03-31    300.0  C         2073.9   ⋯\n",
      "     2 │ SPX      2017-03-30  2368.06  2017-03-31    300.0  P            0.1\n",
      "     3 │ SPX      2017-03-30  2368.06  2017-03-31    400.0  C         1974.1\n",
      "     4 │ SPX      2017-03-30  2368.06  2017-03-31    400.0  P            0.05\n",
      "     5 │ SPX      2017-03-30  2368.06  2017-03-31    500.0  C         1874.1   ⋯\n",
      "     6 │ SPX      2017-03-30  2368.06  2017-03-31    500.0  P            0.05\n",
      "     7 │ SPX      2017-03-30  2368.06  2017-03-31    600.0  C         1774.1\n",
      "     8 │ SPX      2017-03-30  2368.06  2017-03-31    600.0  P            0.05\n",
      "     9 │ SPX      2017-03-30  2368.06  2017-03-31    700.0  C         1673.9   ⋯\n",
      "    10 │ SPX      2017-03-30  2368.06  2017-03-31    700.0  P            0.05\n",
      "    11 │ SPX      2017-03-30  2368.06  2017-03-31    750.0  C         1624.1\n",
      "   ⋮   │    ⋮         ⋮          ⋮         ⋮          ⋮        ⋮         ⋮     ⋱\n",
      " 13943 │ XIU      2017-03-30    23.06  2019-03-15     21.0  C            3.21\n",
      " 13944 │ XIU      2017-03-30    23.06  2019-03-15     21.0  P            1.71  ⋯\n",
      " 13945 │ XIU      2017-03-30    23.06  2019-03-15     22.0  C            2.53\n",
      " 13946 │ XIU      2017-03-30    23.06  2019-03-15     22.0  P            2.03\n",
      " 13947 │ XIU      2017-03-30    23.06  2019-03-15     23.0  C            1.97\n",
      " 13948 │ XIU      2017-03-30    23.06  2019-03-15     23.0  P            2.51  ⋯\n",
      " 13949 │ XIU      2017-03-30    23.06  2019-03-15     24.0  C            1.5\n",
      " 13950 │ XIU      2017-03-30    23.06  2019-03-15     24.0  P            3.12\n",
      " 13951 │ XIU      2017-03-30    23.06  2019-03-15     25.0  C            1.13\n",
      " 13952 │ XIU      2017-03-30    23.06  2019-03-15     25.0  P            3.64  ⋯\n",
      "\u001b[36m                                                3 columns and 13931 rows omitted\u001b[0m"
     ]
    }
   ],
   "source": [
    "df1 = CSV.read(DataFile,DataFrame,normalizenames=true,dateformat=\"mm/dd/yy\")\n",
    "\n",
    "df1.date       .+= Dates.Year(2000)     #03/30/17 to 03/30/2017\n",
    "df1.expiration .+= Dates.Year(2000)\n",
    "\n",
    "select!(df1,Not([:exchange,:option_symbol,:style,:unadjusted]))  #deleting some columns\n",
    "rename!(df1,:adjusted_close => :close)          #renaming a column\n",
    "\n",
    "show(df1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Task 1\n",
    "\n",
    "Create a new DataFrame that contains only the data for SPX and those option contracts that were traded (volume > 0). Hint: `df1[vv, :]` picks out the rows of the data frame for which `vv` is `true`. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Task 2\n",
    "\n",
    "Create a *group* for each expiration date. These groups can be referred to as `dataG2[key]`.\n",
    "\n",
    "Hints: `groupby()`"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Task 3\n",
    "\n",
    "Print the number of contracts (`nrow`) and the sum of the open interest `:open_interest=>sum` for each of the expiration dates.\n",
    "\n",
    "Hint: `combine()`"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Task 4 \n",
    "Creating two new DataFrames: for expiration date 2017-04-21 and another for 2017-06-16.\n",
    "\n",
    "Hint: `dataG2[(expiration = Date(\"2017-04-21\"),)]`"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Task 5\n",
    "\n",
    "For the expiration date 2017-04-21, calculate the mid price as the average of the `.ask` and `.bid`. \n",
    "\n",
    "Plot the mid price as a function of the strike price `.strike` for put options. Add a curve another curve for the call options."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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