PricescopeDiamondCostPrediction.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Benjamin Chodroff, benjamin.chodroff@gmail.com\n",
    "# With lots of love from my wife, Zheng Gao\n",
    "# 2013\n",
    "# Built using Python 2.7\n",
    "import os\n",
    "import requests\n",
    "import collections\n",
    "import json"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Convert diamond qualities into numbers using a dictionary\n",
    "colorsDict = {\"D\":1,\"E\":2,\"F\":3,\"G\":4,\"H\":5,\"I\":6,\"J\":7,\"K\":8,\"L\":9,\"M\":10,\"N\":11,\"O\":12,\"P\":13,\"Q\":14,\"R\":14,\"S\":15,\"T\":16,\"U\":17,\"V\":18,\"W\":19,\"X\":20,\"Y\":21,\"Z\":22}\n",
    "clarityDict = {\"FL\":1,\"IF\":2,\"VVS1\":3,\"VVS2\":4,\"VS1\":5,\"VS2\":6,\"SI1\":7,\"SI2\":8,\"SI3\":9,\"I1\":10,\"I2\":11,\"I3\":12}\n",
    "giacutDict = {\"Excellent\":1, \"Very Good\": 2, \"Good\":3,\"Fair\":4,\"Poor\":5,\"n/a\":6}\n",
    "dshapes = {\"round\":1,\"princess\":8,\"emerald\":4,\"oval\":6,\"marquise\":5,\"pear\":3,\"asscher\":15,\"cushion\":14,\"radiant\":7,\"heart\":10,\"european\":11,\"trilliant\":9,\"oldminer\":12,\"flanders\":13}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Compare your diamond to the internet\n",
    "# How many carats is your diamond?\n",
    "ycar = 1.8\n",
    "\n",
    "# What shape is your diamond? (See dshapes above)\n",
    "yshape = \"round\"\n",
    "\n",
    "# What color? (See colorsDict)\n",
    "ycol = \"G\"\n",
    "\n",
    "# What clarity? (see clarityDict)\n",
    "ycla = \"VS2\"\n",
    "\n",
    "# What quality cut? (see giacutDict)\n",
    "ycut = \"Excellent\"\n",
    "\n",
    "# What is the price in USD?\n",
    "ypri = 20491\n",
    "\n",
    "# Minimum and maximum specs to compare against on pricescope.com\n",
    "# Recommend +- 0.2 carat size based on your diamond size\n",
    "# let me know your cluster analysis! \n",
    "minCar = 1.6\n",
    "maxCar = 2.0\n",
    "minCol = \"K\"\n",
    "maxCol = \"D\"\n",
    "minCla = \"I3\"\n",
    "maxCla = \"FL\"\n",
    "minCut = \"Fair\"\n",
    "maxCut = \"Excellent\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# An array of all the diamonds (dictionaries) we find\n",
    "diamonds = []"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Finding diamonds:\n",
      "\tShape= round\n",
      "\tCarats= 1.6 - 2.0\n",
      "\tColor= K - D\n",
      "\tClarity= I3 - FL\n",
      "\tCut= Fair - Excellent\n"
     ]
    }
   ],
   "source": [
    "print \"Finding diamonds:\"\n",
    "print \"\\tShape=\",yshape\n",
    "print \"\\tCarats=\",str(minCar),\"-\", str(maxCar)\n",
    "print \"\\tColor=\",str(minCol),\"-\",str(maxCol)\n",
    "print \"\\tClarity=\",str(minCla),\"-\",str(maxCla)\n",
    "print \"\\tCut=\",str(minCut),\"-\",str(maxCut)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Finding round shaped diamonds with carat sizes from 1.6 to 2.0\n",
      "\tDownloading page 1 :\n",
      "\t\tFound 100 diamonds. 6149 diamonds to go\n",
      "\tDownloading page 2 :\n",
      "\t\tFound 100 diamonds. 6049 diamonds to go\n",
      "\tDownloading page 3 :\n",
      "\t\tFound 100 diamonds. 5949 diamonds to go\n",
      "\tDownloading page 4 :\n",
      "\t\tFound 100 diamonds. 5849 diamonds to go\n",
      "\tDownloading page 5 :\n",
      "\t\tFound 100 diamonds. 5749 diamonds to go\n",
      "\tDownloading page 6 :\n",
      "\t\tFound 100 diamonds. 5649 diamonds to go\n",
      "\tDownloading page 7 :\n",
      "\t\tFound 100 diamonds. 5549 diamonds to go\n",
      "\tDownloading page 8 :\n",
      "\t\tFound 100 diamonds. 5449 diamonds to go\n",
      "\tDownloading page 9 :\n",
      "\t\tFound 100 diamonds. 5349 diamonds to go\n",
      "\tDownloading page 10 :\n",
      "\t\tFound 100 diamonds. 5249 diamonds to go\n",
      "\tDownloading page 11 :\n",
      "\t\tFound 100 diamonds. 5149 diamonds to go\n",
      "\tDownloading page 12 :\n",
      "\t\tFound 100 diamonds. 5049 diamonds to go\n",
      "\tDownloading page 13 :\n",
      "\t\tFound 100 diamonds. 4949 diamonds to go\n",
      "\tDownloading page 14 :\n",
      "\t\tFound 100 diamonds. 4849 diamonds to go\n",
      "\tDownloading page 15 :\n",
      "\t\tFound 100 diamonds. 4749 diamonds to go\n",
      "\tDownloading page 16 :\n",
      "\t\tFound 100 diamonds. 4649 diamonds to go\n",
      "\tDownloading page 17 :\n",
      "\t\tFound 100 diamonds. 4549 diamonds to go\n",
      "\tDownloading page 18 :\n",
      "\t\tFound 100 diamonds. 4449 diamonds to go\n",
      "\tDownloading page 19 :\n",
      "\t\tFound 100 diamonds. 4349 diamonds to go\n",
      "\tDownloading page 20 :\n",
      "\t\tFound 100 diamonds. 4249 diamonds to go\n",
      "\tDownloading page 21 :\n",
      "\t\tFound 100 diamonds. 4149 diamonds to go\n",
      "\tDownloading page 22 :\n",
      "\t\tFound 100 diamonds. 4049 diamonds to go\n",
      "\tDownloading page 23 :\n",
      "\t\tFound 100 diamonds. 3949 diamonds to go\n",
      "\tDownloading page 24 :\n",
      "\t\tFound 100 diamonds. 3849 diamonds to go\n",
      "\tDownloading page 25 :\n",
      "\t\tFound 100 diamonds. 3749 diamonds to go\n",
      "\tDownloading page 26 :\n",
      "\t\tFound 100 diamonds. 3649 diamonds to go\n",
      "\tDownloading page 27 :\n",
      "\t\tFound 100 diamonds. 3549 diamonds to go\n",
      "\tDownloading page 28 :\n",
      "\t\tFound 100 diamonds. 3449 diamonds to go\n",
      "\tDownloading page 29 :\n",
      "\t\tFound 100 diamonds. 3349 diamonds to go\n",
      "\tDownloading page 30 :\n",
      "\t\tFound 100 diamonds. 3249 diamonds to go\n",
      "\tDownloading page 31 :\n",
      "\t\tFound 100 diamonds. 3149 diamonds to go\n",
      "\tDownloading page 32 :\n",
      "\t\tFound 100 diamonds. 3049 diamonds to go\n",
      "\tDownloading page 33 :\n",
      "\t\tFound 100 diamonds. 2949 diamonds to go\n",
      "\tDownloading page 34 :\n",
      "\t\tFound 100 diamonds. 2849 diamonds to go\n",
      "\tDownloading page 35 :\n",
      "\t\tFound 100 diamonds. 2749 diamonds to go\n",
      "\tDownloading page 36 :\n",
      "\t\tFound 100 diamonds. 2649 diamonds to go\n",
      "\tDownloading page 37 :\n",
      "\t\tFound 100 diamonds. 2549 diamonds to go\n",
      "\tDownloading page 38 :\n",
      "\t\tFound 100 diamonds. 2449 diamonds to go\n",
      "\tDownloading page 39 :\n",
      "\t\tFound 100 diamonds. 2349 diamonds to go\n",
      "\tDownloading page 40 :\n",
      "\t\tFound 100 diamonds. 2249 diamonds to go\n",
      "\tDownloading page 41 :\n",
      "\t\tFound 100 diamonds. 2149 diamonds to go\n",
      "\tDownloading page 42 :\n",
      "\t\tFound 100 diamonds. 2049 diamonds to go\n",
      "\tDownloading page 43 :\n",
      "\t\tFound 100 diamonds. 1949 diamonds to go\n",
      "\tDownloading page 44 :\n",
      "\t\tFound 100 diamonds. 1849 diamonds to go\n",
      "\tDownloading page 45 :\n",
      "\t\tFound 100 diamonds. 1749 diamonds to go\n",
      "\tDownloading page 46 :\n",
      "\t\tFound 100 diamonds. 1649 diamonds to go\n",
      "\tDownloading page 47 :\n",
      "\t\tFound 100 diamonds. 1549 diamonds to go\n",
      "\tDownloading page 48 :\n",
      "\t\tFound 100 diamonds. 1449 diamonds to go\n",
      "\tDownloading page 49 :\n",
      "\t\tFound 100 diamonds. 1349 diamonds to go\n",
      "\tDownloading page 50 :\n",
      "\t\tFound 100 diamonds. 1249 diamonds to go\n",
      "\tDownloading page 51 :\n",
      "\t\tFound 100 diamonds. 1149 diamonds to go\n",
      "\tDownloading page 52 :\n",
      "\t\tFound 100 diamonds. 1049 diamonds to go\n",
      "\tDownloading page 53 :\n",
      "\t\tFound 100 diamonds. 949 diamonds to go\n",
      "\tDownloading page 54 :\n",
      "\t\tFound 100 diamonds. 849 diamonds to go\n",
      "\tDownloading page 55 :\n",
      "\t\tFound 100 diamonds. 749 diamonds to go\n",
      "\tDownloading page 56 :\n",
      "\t\tFound 100 diamonds. 649 diamonds to go\n",
      "\tDownloading page 57 :\n",
      "\t\tFound 100 diamonds. 549 diamonds to go\n",
      "\tDownloading page 58 :\n",
      "\t\tFound 100 diamonds. 449 diamonds to go\n",
      "\tDownloading page 59 :\n",
      "\t\tFound 100 diamonds. 349 diamonds to go\n",
      "\tDownloading page 60 :\n",
      "\t\tFound 100 diamonds. 249 diamonds to go\n",
      "\tDownloading page 61 :\n",
      "\t\tFound 100 diamonds. 149 diamonds to go\n",
      "\tDownloading page 62 :\n",
      "\t\tFound 100 diamonds. 49 diamonds to go\n",
      "\tDownloading page 63 :\n",
      "\t\tFound 49 diamonds. 0 diamonds to go\n",
      "\tDownloading page 64 :\n",
      "\t\tNo more diamonds found.\n",
      "Finished searching for all diamond shapes!\n"
     ]
    }
   ],
   "source": [
    "# There is a lack of good error checking throughout this process, my apologies\n",
    "shape=dshapes[yshape]\n",
    "print \"Finding\", yshape,\"shaped diamonds with carat sizes from\", str(minCar), \"to\", str(maxCar)\n",
    "#download up to 1000 pages of results before giving up\n",
    "for i in range(1,1001):\n",
    "        print \"\\tDownloading page\",str(i),\":\"\n",
    "        # The URL we found while using Google Developer Tools for XHR requests\n",
    "        url='https://www.pricescope.com/diamonds/api/ps_dl/d_s'\n",
    "        # This ensures we identify ourselves as a valid browser and that we expect json responses\n",
    "        headers = { 'user-agent' : 'Mozilla/5.0', 'content-type' : 'text/json' }\n",
    "        # The payload is the question we wish to ask, but we modify it to iteratively \n",
    "        # loop through the shapes and pages. Note - some of the mins/maxes are reversed!\n",
    "        payload = '{\"df\":{\"vendor\":-1,\"inhouse\":-1,\"shape\":'+str(shape)+',\"fancy_shape\":1,\"minprice\":1,\"maxprice\":1600000,\"minfancy_price\":0,\"maxfancy_price\":1600000,\"mincarat\":'+str(minCar)+',\"maxcarat\":'+str(maxCar)+',\"minfancy_carat\":0.23,\"maxfancy_carat\":21.7,\"mindepth\":0,\"maxdepth\":100,\"mintable\":0,\"maxtable\":100,\"mincut\":'+str(giacutDict[maxCut])+',\"maxcut\":'+str(giacutDict[minCut])+',\"mincolor\":'+str(colorsDict[maxCol])+',\"maxcolor\":'+str(colorsDict[minCol])+',\"fancy_color\":1,\"minfancy_intensity\":1,\"maxfancy_intensity\":9,\"minfancy_overtone\":1,\"maxfancy_overtone\":9,\"minclarity\":'+str(clarityDict[maxCla])+',\"maxclarity\":'+str(clarityDict[minCla])+',\"minsymmetry\":1,\"maxsymmetry\":8,\"minpolish\":1,\"maxpolish\":8,\"minflourescence\":1,\"maxflourescence\":6,\"checkbox_panel1\":\"04\",\"checkbox_panel2\":\"\",\"fancy_checkbox_panel2\":\"\",\"sort\":\"\",\"fancy_sort\":\"\",\"page\":'+str(i)+',\"pageview\":\"96\",\"adv\":false,\"fancy_adv\":false},\"dp\":0}'\n",
    "        # Submits a POST request to the URL using our payload and headers\n",
    "        r = requests.post(url, data=payload, headers=headers)\n",
    "        # Basic check to see if the response code is valid\n",
    "        if not r.ok:\n",
    "            print \"\\t\\tUnexpected error encountered while downloading page, skipping\"\n",
    "            break     \n",
    "        # Open up the page results into a json object\n",
    "        diamondpage = json.loads(r.text)\n",
    "        # See how many diamonds were found\n",
    "        foundnumdiamonds = len(diamondpage['d'])\n",
    "        foundtotaldiamonds = diamondpage['s']\n",
    "        \n",
    "\n",
    "        if(foundnumdiamonds>0):\n",
    "            diamonds+= diamondpage['d']\n",
    "            diamondstogo = foundtotaldiamonds - len(diamonds) \n",
    "            print \"\\t\\tFound\",str(foundnumdiamonds),\"diamonds.\",str(diamondstogo),\"diamonds to go\"\n",
    "            # Append the diamonds it found in this page to our diamonds array\n",
    "            \n",
    "        else:\n",
    "            print \"\\t\\tNo more diamonds found.\"\n",
    "            # If this page has no diamonds on it, we are done with this page\n",
    "            break\n",
    "print \"Finished searching for all diamond shapes!\"\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Found a total of 6249 unique diamonds\n"
     ]
    }
   ],
   "source": [
    "print \"Found a total of\",str(len(diamonds)),\"unique diamonds\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Save the results into diamond.txt (overwrite) in case you want to use it later\n",
    "f = open('diamonds.txt', 'w')\n",
    "for i in diamonds:\n",
    "    f.write(str(i))\n",
    "f.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# R Libraries\n",
    "import rpy2\n",
    "from rpy2.robjects.packages import importr\n",
    "import rpy2.robjects as ro\n",
    "\n",
    "# See the plot in jupyter notebook\n",
    "from IPython.core.display import Image"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "r_base = importr('base')\n",
    "stats = importr('stats')\n",
    "graphics = importr('graphics')\n",
    "labels = \"carat,color,clarity,cut,price\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "carat = []\n",
    "color = []\n",
    "clarity = []\n",
    "giacut = []\n",
    "price = []"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "for diamond in diamonds:\n",
    "    carat.append(diamond['Size'])\n",
    "    color.append(colorsDict[diamond['Color']])\n",
    "    clarity.append(clarityDict[diamond['Clarity']])\n",
    "    giacut.append(giacutDict[diamond['GIACutGrade']])\n",
    "    price.append(diamond['Price'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "carat = ro.FloatVector(carat)\n",
    "color = ro.IntVector(color)\n",
    "clarity = ro.IntVector(clarity)\n",
    "giacut = ro.IntVector(giacut)\n",
    "price = ro.FloatVector(price)\n",
    "ro.globalenv[\"carat\"] = carat\n",
    "ro.globalenv[\"color\"] = color\n",
    "ro.globalenv[\"clarity\"] = clarity\n",
    "ro.globalenv[\"giacut\"] = giacut\n",
    "ro.globalenv[\"price\"] = price"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Building Model\n",
      "Building Prediction\n",
      "Adjusted R Squared = 0.8\n",
      "Price = 927 + 18837*Carats + -2035*Color + -1749*Clarity + 546 *Cut\n"
     ]
    }
   ],
   "source": [
    "print \"Building Model\"\n",
    "res = stats.lm(\"price ~ carat + color + clarity + giacut \")\n",
    "print \"Building Prediction\"\n",
    "pred = stats.predict(res)\n",
    "summary = r_base.summary(res)\n",
    "ars = \"Adjusted R Squared = \" + str(round(summary[8][0],2))\n",
    "print ars\n",
    "coef = summary.rx2('coefficients')[0:6]\n",
    "formula = \"Price = \" + str(int(round(coef[0]))) + \" + \" + str(int(round(coef[1]))) + \"*Carats + \" + str(int(round(coef[2]))) + \"*Color + \" + str(int(round(coef[3]))) + \"*Clarity + \" + str(int(round(coef[4]))) + \" *Cut\" \n",
    "print formula"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Comparing Actual to Predicted Price Fit\n",
      "Writing plot to prediction.png\n"
     ]
    },
    {
     "data": {
      "image/png": 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KH5tttpnPYqCUMl68/6kEpTsS4uoRZhpoP5JWrVp5MnFk1NC/SJilKE3ggpBTEUmkKEff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\n3+sIzm3h1c+5ZqM5P9QQiHiQnFd481NfmtFHPWPfgf+gX+V4agZEDEHOy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xVUm+lW/nyU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      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print \"Comparing Actual to Predicted Price Fit\"\n",
    "ro.globalenv[\"pred\"] = pred\n",
    "comp = stats.lm(\"pred ~ price\")\n",
    "plotfile='prediction.png'\n",
    "print \"Writing plot to\",plotfile\n",
    "ro.r.png(plotfile, width=768, height=640)\n",
    "ro.r.plot([x for x in pred],[y for y in price], main=\"Actual vs Predicted Price\",xlab=\"Predicted Price\",ylab=\"Actual Price\", cex=0.5)\n",
    "\n",
    "ro.r.abline(comp,col=\"green\",lty=\"dotted\",lwd=3)\n",
    "\n",
    "ypred = coef[0] + coef[1]*ycar + coef[2]*colorsDict[ycol] + coef[3]*clarityDict[ycla] + coef[4]*giacutDict[ycut]\n",
    "Sdiam = \"Your Diamond: \" + yshape + \" Shape, \" + str(ycar) + \" Carats, \" + str(ycol) + \" Color, \" + str(ycla) + \" Clarity, \" + str(ycut) + \" Cut, $\" + str(ypri)\n",
    "Spred = \"Predicted Price = $\" + str(int(round(ypred)))\n",
    "Sdiff = \"Difference = $\" + str(int(ypred-ypri))\n",
    "savings = int(round(100*((ypred-ypri)/ypri)))\n",
    "Ssavings = \"Savings = \" + str(savings) + \"%\"\n",
    "ro.r.points(ypred,ypri,col=\"red\",pch='x',cex=2)\n",
    "ro.r.legend(\"bottomright\",legend=[Sdiam,Spred,Sdiff,Ssavings], bg = \"white\",cex=0.8)\n",
    "\n",
    "ro.r.legend(\"top\",legend=[formula,ars,\"Sample Size = \" + str(len(price))+\" Diamonds\"], bg = \"white\")\n",
    "ro.r('dev.off()')\n",
    "\n",
    "Image(filename='prediction.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Watch out! Your diamond is 18% more expensive than predicted online market rates\n"
     ]
    }
   ],
   "source": [
    "if (savings<0):\n",
    "    print \"Watch out! Your diamond is \"+str(abs(savings))+\"% more expensive than predicted online market rates\"\n",
    "else:\n",
    "    print \"Congratulations! Your diamond is \"+str(savings)+\"% less expensive than predicted online market rates\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# TODO: Figure out how to use ggplot2\n",
    "# TODO: Make the graph interactive so you can hover over different diamond details\n",
    "# TODO: Automated clustering analysis"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}