4_Cs.ipynb

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   "source": [
    "### Diamonds are a Data Scientist's Best Friend"
   ]
  },
  {
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   "execution_count": 8,
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>carat</th>\n",
       "      <th>cut</th>\n",
       "      <th>color</th>\n",
       "      <th>clarity</th>\n",
       "      <th>depth</th>\n",
       "      <th>table</th>\n",
       "      <th>price</th>\n",
       "      <th>x</th>\n",
       "      <th>y</th>\n",
       "      <th>z</th>\n",
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       "      <th>27749</th>\n",
       "      <td>2.29</td>\n",
       "      <td>Premium</td>\n",
       "      <td>I</td>\n",
       "      <td>VS2</td>\n",
       "      <td>60.8</td>\n",
       "      <td>60.0</td>\n",
       "      <td>18823</td>\n",
       "      <td>8.50</td>\n",
       "      <td>8.47</td>\n",
       "      <td>5.16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27748</th>\n",
       "      <td>2.00</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>G</td>\n",
       "      <td>SI1</td>\n",
       "      <td>63.5</td>\n",
       "      <td>56.0</td>\n",
       "      <td>18818</td>\n",
       "      <td>7.90</td>\n",
       "      <td>7.97</td>\n",
       "      <td>5.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27747</th>\n",
       "      <td>1.51</td>\n",
       "      <td>Ideal</td>\n",
       "      <td>G</td>\n",
       "      <td>IF</td>\n",
       "      <td>61.7</td>\n",
       "      <td>55.0</td>\n",
       "      <td>18806</td>\n",
       "      <td>7.37</td>\n",
       "      <td>7.41</td>\n",
       "      <td>4.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27746</th>\n",
       "      <td>2.07</td>\n",
       "      <td>Ideal</td>\n",
       "      <td>G</td>\n",
       "      <td>SI2</td>\n",
       "      <td>62.5</td>\n",
       "      <td>55.0</td>\n",
       "      <td>18804</td>\n",
       "      <td>8.20</td>\n",
       "      <td>8.13</td>\n",
       "      <td>5.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27745</th>\n",
       "      <td>2.00</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>H</td>\n",
       "      <td>SI1</td>\n",
       "      <td>62.8</td>\n",
       "      <td>57.0</td>\n",
       "      <td>18803</td>\n",
       "      <td>7.95</td>\n",
       "      <td>8.00</td>\n",
       "      <td>5.01</td>\n",
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      "text/plain": [
       "       carat        cut color clarity  depth  table  price     x     y     z\n",
       "27749   2.29    Premium     I     VS2   60.8   60.0  18823  8.50  8.47  5.16\n",
       "27748   2.00  Very Good     G     SI1   63.5   56.0  18818  7.90  7.97  5.04\n",
       "27747   1.51      Ideal     G      IF   61.7   55.0  18806  7.37  7.41  4.56\n",
       "27746   2.07      Ideal     G     SI2   62.5   55.0  18804  8.20  8.13  5.11\n",
       "27745   2.00  Very Good     H     SI1   62.8   57.0  18803  7.95  8.00  5.01"
      ]
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     "execution_count": 8,
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   "source": [
    "## Load libraries \n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "\n",
    "## Load diamond dataset\n",
    "df = pd.read_csv(\"data/diamonds.csv\")\n",
    "df.drop(\"Unnamed: 0\", axis=1, inplace=True)\n",
    "## x = Length in mm\n",
    "## y = Width in mm\n",
    "## z = Depth in mm\n",
    "df = df.sort_values(by=\"price\", ascending=False)\n",
    "df.head()"
   ]
  },
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   "cell_type": "markdown",
   "metadata": {
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   },
   "source": [
    "### Levels of 3 C's\n",
    "The levels representing the 3 C's: Color, Cut, and Clarity are defined in the index. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
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       "      <th></th>\n",
       "      <th>carat</th>\n",
       "      <th>cut</th>\n",
       "      <th>clarity</th>\n",
       "      <th>depth</th>\n",
       "      <th>table</th>\n",
       "      <th>price</th>\n",
       "      <th>x</th>\n",
       "      <th>y</th>\n",
       "      <th>z</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>color</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>D</th>\n",
       "      <td>6775</td>\n",
       "      <td>6775</td>\n",
       "      <td>6775</td>\n",
       "      <td>6775</td>\n",
       "      <td>6775</td>\n",
       "      <td>6775</td>\n",
       "      <td>6775</td>\n",
       "      <td>6775</td>\n",
       "      <td>6775</td>\n",
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       "    <tr>\n",
       "      <th>E</th>\n",
       "      <td>9797</td>\n",
       "      <td>9797</td>\n",
       "      <td>9797</td>\n",
       "      <td>9797</td>\n",
       "      <td>9797</td>\n",
       "      <td>9797</td>\n",
       "      <td>9797</td>\n",
       "      <td>9797</td>\n",
       "      <td>9797</td>\n",
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       "    <tr>\n",
       "      <th>F</th>\n",
       "      <td>9542</td>\n",
       "      <td>9542</td>\n",
       "      <td>9542</td>\n",
       "      <td>9542</td>\n",
       "      <td>9542</td>\n",
       "      <td>9542</td>\n",
       "      <td>9542</td>\n",
       "      <td>9542</td>\n",
       "      <td>9542</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>G</th>\n",
       "      <td>11292</td>\n",
       "      <td>11292</td>\n",
       "      <td>11292</td>\n",
       "      <td>11292</td>\n",
       "      <td>11292</td>\n",
       "      <td>11292</td>\n",
       "      <td>11292</td>\n",
       "      <td>11292</td>\n",
       "      <td>11292</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>H</th>\n",
       "      <td>8304</td>\n",
       "      <td>8304</td>\n",
       "      <td>8304</td>\n",
       "      <td>8304</td>\n",
       "      <td>8304</td>\n",
       "      <td>8304</td>\n",
       "      <td>8304</td>\n",
       "      <td>8304</td>\n",
       "      <td>8304</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>I</th>\n",
       "      <td>5422</td>\n",
       "      <td>5422</td>\n",
       "      <td>5422</td>\n",
       "      <td>5422</td>\n",
       "      <td>5422</td>\n",
       "      <td>5422</td>\n",
       "      <td>5422</td>\n",
       "      <td>5422</td>\n",
       "      <td>5422</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>J</th>\n",
       "      <td>2808</td>\n",
       "      <td>2808</td>\n",
       "      <td>2808</td>\n",
       "      <td>2808</td>\n",
       "      <td>2808</td>\n",
       "      <td>2808</td>\n",
       "      <td>2808</td>\n",
       "      <td>2808</td>\n",
       "      <td>2808</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      "text/plain": [
       "       carat    cut  clarity  depth  table  price      x      y      z\n",
       "color                                                                 \n",
       "D       6775   6775     6775   6775   6775   6775   6775   6775   6775\n",
       "E       9797   9797     9797   9797   9797   9797   9797   9797   9797\n",
       "F       9542   9542     9542   9542   9542   9542   9542   9542   9542\n",
       "G      11292  11292    11292  11292  11292  11292  11292  11292  11292\n",
       "H       8304   8304     8304   8304   8304   8304   8304   8304   8304\n",
       "I       5422   5422     5422   5422   5422   5422   5422   5422   5422\n",
       "J       2808   2808     2808   2808   2808   2808   2808   2808   2808"
      ]
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   "source": [
    "df.groupby('color').count()"
   ]
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       "      <th>carat</th>\n",
       "      <th>color</th>\n",
       "      <th>clarity</th>\n",
       "      <th>depth</th>\n",
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       "      <th>cut</th>\n",
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       "      <th>Fair</th>\n",
       "      <td>1610</td>\n",
       "      <td>1610</td>\n",
       "      <td>1610</td>\n",
       "      <td>1610</td>\n",
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       "      <th>Good</th>\n",
       "      <td>4906</td>\n",
       "      <td>4906</td>\n",
       "      <td>4906</td>\n",
       "      <td>4906</td>\n",
       "      <td>4906</td>\n",
       "      <td>4906</td>\n",
       "      <td>4906</td>\n",
       "      <td>4906</td>\n",
       "      <td>4906</td>\n",
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       "      <th>Ideal</th>\n",
       "      <td>21551</td>\n",
       "      <td>21551</td>\n",
       "      <td>21551</td>\n",
       "      <td>21551</td>\n",
       "      <td>21551</td>\n",
       "      <td>21551</td>\n",
       "      <td>21551</td>\n",
       "      <td>21551</td>\n",
       "      <td>21551</td>\n",
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       "    <tr>\n",
       "      <th>Premium</th>\n",
       "      <td>13791</td>\n",
       "      <td>13791</td>\n",
       "      <td>13791</td>\n",
       "      <td>13791</td>\n",
       "      <td>13791</td>\n",
       "      <td>13791</td>\n",
       "      <td>13791</td>\n",
       "      <td>13791</td>\n",
       "      <td>13791</td>\n",
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       "    <tr>\n",
       "      <th>Very Good</th>\n",
       "      <td>12082</td>\n",
       "      <td>12082</td>\n",
       "      <td>12082</td>\n",
       "      <td>12082</td>\n",
       "      <td>12082</td>\n",
       "      <td>12082</td>\n",
       "      <td>12082</td>\n",
       "      <td>12082</td>\n",
       "      <td>12082</td>\n",
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      "text/plain": [
       "           carat  color  clarity  depth  table  price      x      y      z\n",
       "cut                                                                       \n",
       "Fair        1610   1610     1610   1610   1610   1610   1610   1610   1610\n",
       "Good        4906   4906     4906   4906   4906   4906   4906   4906   4906\n",
       "Ideal      21551  21551    21551  21551  21551  21551  21551  21551  21551\n",
       "Premium    13791  13791    13791  13791  13791  13791  13791  13791  13791\n",
       "Very Good  12082  12082    12082  12082  12082  12082  12082  12082  12082"
      ]
     },
     "execution_count": 10,
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   ],
   "source": [
    "df.groupby('cut').count()"
   ]
  },
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       "      <th></th>\n",
       "      <th>carat</th>\n",
       "      <th>cut</th>\n",
       "      <th>color</th>\n",
       "      <th>depth</th>\n",
       "      <th>table</th>\n",
       "      <th>price</th>\n",
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       "    <tr>\n",
       "      <th>clarity</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th>I1</th>\n",
       "      <td>741</td>\n",
       "      <td>741</td>\n",
       "      <td>741</td>\n",
       "      <td>741</td>\n",
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       "      <th>IF</th>\n",
       "      <td>1790</td>\n",
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       "      <td>1790</td>\n",
       "      <td>1790</td>\n",
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       "      <td>1790</td>\n",
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       "    <tr>\n",
       "      <th>SI1</th>\n",
       "      <td>13065</td>\n",
       "      <td>13065</td>\n",
       "      <td>13065</td>\n",
       "      <td>13065</td>\n",
       "      <td>13065</td>\n",
       "      <td>13065</td>\n",
       "      <td>13065</td>\n",
       "      <td>13065</td>\n",
       "      <td>13065</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SI2</th>\n",
       "      <td>9194</td>\n",
       "      <td>9194</td>\n",
       "      <td>9194</td>\n",
       "      <td>9194</td>\n",
       "      <td>9194</td>\n",
       "      <td>9194</td>\n",
       "      <td>9194</td>\n",
       "      <td>9194</td>\n",
       "      <td>9194</td>\n",
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       "    <tr>\n",
       "      <th>VS1</th>\n",
       "      <td>8171</td>\n",
       "      <td>8171</td>\n",
       "      <td>8171</td>\n",
       "      <td>8171</td>\n",
       "      <td>8171</td>\n",
       "      <td>8171</td>\n",
       "      <td>8171</td>\n",
       "      <td>8171</td>\n",
       "      <td>8171</td>\n",
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       "    <tr>\n",
       "      <th>VS2</th>\n",
       "      <td>12258</td>\n",
       "      <td>12258</td>\n",
       "      <td>12258</td>\n",
       "      <td>12258</td>\n",
       "      <td>12258</td>\n",
       "      <td>12258</td>\n",
       "      <td>12258</td>\n",
       "      <td>12258</td>\n",
       "      <td>12258</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VVS1</th>\n",
       "      <td>3655</td>\n",
       "      <td>3655</td>\n",
       "      <td>3655</td>\n",
       "      <td>3655</td>\n",
       "      <td>3655</td>\n",
       "      <td>3655</td>\n",
       "      <td>3655</td>\n",
       "      <td>3655</td>\n",
       "      <td>3655</td>\n",
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       "    <tr>\n",
       "      <th>VVS2</th>\n",
       "      <td>5066</td>\n",
       "      <td>5066</td>\n",
       "      <td>5066</td>\n",
       "      <td>5066</td>\n",
       "      <td>5066</td>\n",
       "      <td>5066</td>\n",
       "      <td>5066</td>\n",
       "      <td>5066</td>\n",
       "      <td>5066</td>\n",
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      "text/plain": [
       "         carat    cut  color  depth  table  price      x      y      z\n",
       "clarity                                                               \n",
       "I1         741    741    741    741    741    741    741    741    741\n",
       "IF        1790   1790   1790   1790   1790   1790   1790   1790   1790\n",
       "SI1      13065  13065  13065  13065  13065  13065  13065  13065  13065\n",
       "SI2       9194   9194   9194   9194   9194   9194   9194   9194   9194\n",
       "VS1       8171   8171   8171   8171   8171   8171   8171   8171   8171\n",
       "VS2      12258  12258  12258  12258  12258  12258  12258  12258  12258\n",
       "VVS1      3655   3655   3655   3655   3655   3655   3655   3655   3655\n",
       "VVS2      5066   5066   5066   5066   5066   5066   5066   5066   5066"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby('clarity').count()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "heading_collapsed": true
   },
   "source": [
    "### Cutting and Polishing Data for Display"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "hidden": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Cut</th>\n",
       "      <th>Color</th>\n",
       "      <th>Clarity</th>\n",
       "      <th>Carat</th>\n",
       "      <th>Price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>27749</th>\n",
       "      <td>75</td>\n",
       "      <td>16</td>\n",
       "      <td>42</td>\n",
       "      <td>54.855643</td>\n",
       "      <td>100.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27748</th>\n",
       "      <td>50</td>\n",
       "      <td>50</td>\n",
       "      <td>28</td>\n",
       "      <td>47.244094</td>\n",
       "      <td>99.972969</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27747</th>\n",
       "      <td>100</td>\n",
       "      <td>50</td>\n",
       "      <td>100</td>\n",
       "      <td>34.383202</td>\n",
       "      <td>99.908093</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27746</th>\n",
       "      <td>100</td>\n",
       "      <td>50</td>\n",
       "      <td>14</td>\n",
       "      <td>49.081365</td>\n",
       "      <td>99.897281</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27745</th>\n",
       "      <td>50</td>\n",
       "      <td>33</td>\n",
       "      <td>28</td>\n",
       "      <td>47.244094</td>\n",
       "      <td>99.891874</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Cut  Color  Clarity      Carat       Price\n",
       "27749   75     16       42  54.855643  100.000000\n",
       "27748   50     50       28  47.244094   99.972969\n",
       "27747  100     50      100  34.383202   99.908093\n",
       "27746  100     50       14  49.081365   99.897281\n",
       "27745   50     33       28  47.244094   99.891874"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## Cut diamonds that skew carat range\n",
    "indicies_to_remove = [27415, 27630, 27130]\n",
    "df = df.drop(indicies_to_remove)\n",
    "\n",
    "## Convert Column Classes to Rankings\n",
    "clarity={\n",
    "'IF':7,\n",
    "'VVS1':6,\n",
    "'VVS2':5,\n",
    "'VS1':4,\n",
    "'VS2':3,\n",
    "'SI1':2,\n",
    "'SI2': 1,\n",
    "'I1':0\n",
    "}\n",
    "\n",
    "cut={\n",
    "'Ideal':4,\n",
    "'Premium':3,\n",
    "'Very Good':2,\n",
    "'Good': 1,\n",
    "'Fair':0\n",
    "}\n",
    "\n",
    "color={\n",
    "'D':6,\n",
    "'E':5,\n",
    "'F':4,\n",
    "'G':3,\n",
    "'H':2,\n",
    "'I': 1,\n",
    "'J':0\n",
    "}\n",
    "\n",
    "## Map dictionary values to new columns\n",
    "df['Clarity'] = df['clarity'].map(clarity)\n",
    "df['Cut'] = df['cut'].map(cut)\n",
    "df['Color'] = df['color'].map(color)\n",
    "df['price'] = df['price'].astype(float)\n",
    "\n",
    "\n",
    "## Convert all rankings and contiguous data to scale between 0-100\n",
    "factors = ['Cut', 'Color', \"Clarity\", \"carat\", \"price\"]\n",
    "\n",
    "new_max = 100\n",
    "new_min = 0\n",
    "new_range = new_max - new_min\n",
    "\n",
    "for factor in factors:\n",
    "    max_val = df[factor].max()\n",
    "    min_val = df[factor].min()\n",
    "    val_range = max_val - min_val\n",
    "    df[factor + '_Adj'] = df[factor].apply(lambda x: (((x - min_val) * new_range) / val_range) + new_min)\n",
    "\n",
    "## Subset scaled columns \n",
    "df2 = df[['Cut_Adj', \"Color_Adj\", \"Clarity_Adj\", \"carat_Adj\", \"price_Adj\"]]\n",
    "df2.columns = ['Cut', \"Color\", \"Clarity\", \"Carat\", \"Price\"]\n",
    "df2.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "hidden": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "       Cut  Color  Clarity      Carat  Price\n",
      "27749   75     16       42  54.855643  100.0\n",
      "   Cut  Color  Clarity     Carat  Price\n",
      "1   75     83       28  0.262467    0.0\n",
      "0  100     83       14  0.787402    0.0\n"
     ]
    }
   ],
   "source": [
    "df2 = df2.sort_values(by=\"Price\", ascending=False)\n",
    "## Most Expensive Diamonds\n",
    "print(df2.head(1))\n",
    "## Least Expensive Diamonds\n",
    "print(df2.tail(2))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### The Star of the Show"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "## Points in this star\n",
    "labels = ['Cut', \"Color\", \"Clarity\", \"Carat\", \"Price\"]\n",
    "points = len(labels)\n",
    "\n",
    "angles = np.linspace(0, 2 * np.pi, points, endpoint=False).tolist()\n",
    "angles += angles[:1]\n",
    "\n",
    "def add_to_star(diamond, color, label=None):\n",
    "    values = df2.loc[diamond].tolist()\n",
    "    values += values[:1]\n",
    "    if label != None:\n",
    "        ax.plot(angles, values, color=color, linewidth=1, label=label)\n",
    "    else:\n",
    "        ax.plot(angles, values, color=color, linewidth=1, label=diamond)\n",
    "    ax.fill(angles, values, color=color, alpha=0.25)\n",
    "    \n",
    "## Create plot object   \n",
    "fig, ax = plt.subplots(figsize=(6, 6), subplot_kw=dict(polar=True))  \n",
    "\n",
    "## Plot a new diamond with the add_to_star function\n",
    "add_to_star(27749, '#1aaf6c', \"Most Expensive Diamond\")\n",
    "add_to_star(0, '#429bf4', \"Least Expensive A\")\n",
    "add_to_star(1, '#d42cea', \"Least Expensive B\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "## Points in this star\n",
    "labels = ['Cut', \"Color\", \"Clarity\", \"Carat\", \"Price\"]\n",
    "points = len(labels)\n",
    "\n",
    "angles = np.linspace(0, 2 * np.pi, points, endpoint=False).tolist()\n",
    "angles += angles[:1]\n",
    "\n",
    "def add_to_star(diamond, color, label=None):\n",
    "    values = df2.loc[diamond].tolist()\n",
    "    values += values[:1]\n",
    "    if label != None:\n",
    "        ax.plot(angles, values, color=color, linewidth=1, label=label)\n",
    "    else:\n",
    "        ax.plot(angles, values, color=color, linewidth=1, label=diamond)\n",
    "    ax.fill(angles, values, color=color, alpha=0.25)\n",
    "    \n",
    "## Create plot object   \n",
    "fig, ax = plt.subplots(figsize=(6, 6), subplot_kw=dict(polar=True))  \n",
    "\n",
    "## Plot a new diamond with the add_to_star function\n",
    "add_to_star(27749, '#1aaf6c', \"Most Expensive Diamond\")\n",
    "add_to_star(0, '#429bf4', \"Least Expensive A\")\n",
    "add_to_star(1, '#d42cea', \"Least Expensive B\")\n",
    "\n",
    "## Fix axis to star from top\n",
    "ax.set_theta_offset(np.pi / 2)\n",
    "ax.set_theta_direction(-1)\n",
    "\n",
    "## Edit x axis lables\n",
    "for label, angle in zip(ax.get_xticklabels(), angles):\n",
    "    if angle in (0, np.pi):\n",
    "        label.set_horizontalalignment('center')\n",
    "    elif 0 < angle < np.pi:\n",
    "        label.set_horizontalalignment('left')\n",
    "    else:\n",
    "        label.set_horizontalalignment('right')\n",
    "\n",
    "        \n",
    "## Customize your graphic\n",
    "\n",
    "# Change the location of the gridlines or remove them\n",
    "ax.set_rgrids([20, 40, 60 ,80])\n",
    "#ax.set_rgrids([]) # This removes grid lines\n",
    "\n",
    "# Change the color of the ticks\n",
    "ax.tick_params(colors='#222222')\n",
    "# Make the y-axis labels larger, smaller, or remove by setting fontsize\n",
    "ax.tick_params(axis='y', labelsize=0)\n",
    "# Make the x-axis labels larger or smaller.\n",
    "ax.tick_params(axis='x', labelsize=13)\n",
    "\n",
    "# Change the color of the circular gridlines.\n",
    "ax.grid(color='#AAAAAA')\n",
    "# Change the color of the outer circle\n",
    "ax.spines['polar'].set_color('#222222')\n",
    "# Change the circle background color\n",
    "ax.set_facecolor('#FAFAFA')\n",
    "\n",
    "# Add title and legend\n",
    "ax.set_title('Comparing Diamonds Across Dimensions', y=1.08)\n",
    "ax.legend(loc='upper right', bbox_to_anchor=(1.3, 1.1))\n",
    "\n",
    "# Draw axis lines for each angle and label.\n",
    "ax.set_thetagrids(np.degrees(angles), labels)\n",
    "\n",
    "plt.savefig('images/foo.png', bbox_inches='tight', dpi=300)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Best Bling for Your Buck"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>carat</th>\n",
       "      <th>cut</th>\n",
       "      <th>color</th>\n",
       "      <th>clarity</th>\n",
       "      <th>depth</th>\n",
       "      <th>table</th>\n",
       "      <th>price</th>\n",
       "      <th>x</th>\n",
       "      <th>y</th>\n",
       "      <th>z</th>\n",
       "      <th>Clarity</th>\n",
       "      <th>Cut</th>\n",
       "      <th>Color</th>\n",
       "      <th>Cut_Adj</th>\n",
       "      <th>Color_Adj</th>\n",
       "      <th>Clarity_Adj</th>\n",
       "      <th>carat_Adj</th>\n",
       "      <th>price_Adj</th>\n",
       "      <th>Total</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>26965</th>\n",
       "      <td>1.07</td>\n",
       "      <td>Ideal</td>\n",
       "      <td>D</td>\n",
       "      <td>IF</td>\n",
       "      <td>60.9</td>\n",
       "      <td>54.0</td>\n",
       "      <td>17042.0</td>\n",
       "      <td>6.66</td>\n",
       "      <td>6.73</td>\n",
       "      <td>4.08</td>\n",
       "      <td>7</td>\n",
       "      <td>4</td>\n",
       "      <td>6</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>22.834646</td>\n",
       "      <td>90.371412</td>\n",
       "      <td>322.834646</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26311</th>\n",
       "      <td>1.06</td>\n",
       "      <td>Ideal</td>\n",
       "      <td>D</td>\n",
       "      <td>IF</td>\n",
       "      <td>61.2</td>\n",
       "      <td>57.0</td>\n",
       "      <td>15813.0</td>\n",
       "      <td>6.57</td>\n",
       "      <td>6.61</td>\n",
       "      <td>4.03</td>\n",
       "      <td>7</td>\n",
       "      <td>4</td>\n",
       "      <td>6</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>22.572178</td>\n",
       "      <td>83.727091</td>\n",
       "      <td>322.572178</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25718</th>\n",
       "      <td>1.04</td>\n",
       "      <td>Ideal</td>\n",
       "      <td>D</td>\n",
       "      <td>IF</td>\n",
       "      <td>61.8</td>\n",
       "      <td>57.0</td>\n",
       "      <td>14626.0</td>\n",
       "      <td>6.52</td>\n",
       "      <td>6.49</td>\n",
       "      <td>4.02</td>\n",
       "      <td>7</td>\n",
       "      <td>4</td>\n",
       "      <td>6</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>22.047244</td>\n",
       "      <td>77.309834</td>\n",
       "      <td>322.047244</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25622</th>\n",
       "      <td>1.04</td>\n",
       "      <td>Ideal</td>\n",
       "      <td>D</td>\n",
       "      <td>IF</td>\n",
       "      <td>61.8</td>\n",
       "      <td>57.0</td>\n",
       "      <td>14494.0</td>\n",
       "      <td>6.49</td>\n",
       "      <td>6.52</td>\n",
       "      <td>4.02</td>\n",
       "      <td>7</td>\n",
       "      <td>4</td>\n",
       "      <td>6</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>22.047244</td>\n",
       "      <td>76.596205</td>\n",
       "      <td>322.047244</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27226</th>\n",
       "      <td>1.03</td>\n",
       "      <td>Ideal</td>\n",
       "      <td>D</td>\n",
       "      <td>IF</td>\n",
       "      <td>62.0</td>\n",
       "      <td>56.0</td>\n",
       "      <td>17590.0</td>\n",
       "      <td>6.55</td>\n",
       "      <td>6.44</td>\n",
       "      <td>4.03</td>\n",
       "      <td>7</td>\n",
       "      <td>4</td>\n",
       "      <td>6</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>21.784777</td>\n",
       "      <td>93.334054</td>\n",
       "      <td>321.784777</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       carat    cut color clarity  depth  table    price     x     y     z  \\\n",
       "26965   1.07  Ideal     D      IF   60.9   54.0  17042.0  6.66  6.73  4.08   \n",
       "26311   1.06  Ideal     D      IF   61.2   57.0  15813.0  6.57  6.61  4.03   \n",
       "25718   1.04  Ideal     D      IF   61.8   57.0  14626.0  6.52  6.49  4.02   \n",
       "25622   1.04  Ideal     D      IF   61.8   57.0  14494.0  6.49  6.52  4.02   \n",
       "27226   1.03  Ideal     D      IF   62.0   56.0  17590.0  6.55  6.44  4.03   \n",
       "\n",
       "       Clarity  Cut  Color  Cut_Adj  Color_Adj  Clarity_Adj  carat_Adj  \\\n",
       "26965        7    4      6      100        100          100  22.834646   \n",
       "26311        7    4      6      100        100          100  22.572178   \n",
       "25718        7    4      6      100        100          100  22.047244   \n",
       "25622        7    4      6      100        100          100  22.047244   \n",
       "27226        7    4      6      100        100          100  21.784777   \n",
       "\n",
       "       price_Adj       Total  \n",
       "26965  90.371412  322.834646  \n",
       "26311  83.727091  322.572178  \n",
       "25718  77.309834  322.047244  \n",
       "25622  76.596205  322.047244  \n",
       "27226  93.334054  321.784777  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## Get total value of 4 C's\n",
    "df['Total'] = df['Cut_Adj'] + df['Color_Adj'] + df['Clarity_Adj'] + df['carat_Adj']\n",
    "df = df.sort_values(by=\"Total\", ascending=False)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "       carat   cut color clarity  depth  table    price     x     y     z  \\\n",
      "26320    2.4  Fair     J     SI2   65.4   56.0  15824.0  8.35  8.29  5.44   \n",
      "\n",
      "       Clarity  Cut  Color  Cut_Adj  Color_Adj  Clarity_Adj  carat_Adj  \\\n",
      "26320        1    0      0        0          0           14  57.742782   \n",
      "\n",
      "       price_Adj      Total  4C_by_Price  \n",
      "26320   83.78656  71.742782     0.004534  \n",
      "       carat    cut color clarity  depth  table  price     x     y     z  \\\n",
      "31597    0.2  Ideal     D     VS2   61.5   57.0  367.0  3.81  3.77  2.33   \n",
      "\n",
      "       Clarity  Cut  Color  Cut_Adj  Color_Adj  Clarity_Adj  carat_Adj  \\\n",
      "31597        3    4      6      100        100           42        0.0   \n",
      "\n",
      "       price_Adj  Total  4C_by_Price  \n",
      "31597   0.221658  242.0     0.659401  \n"
     ]
    }
   ],
   "source": [
    "## Divide Value total by Price\n",
    "df['4C_by_Price'] = df['Total']/df['price']\n",
    "df = df.sort_values(by=\"4C_by_Price\", ascending=False)\n",
    "print(df.tail(1))\n",
    "print(df.head(1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "## Points in this star\n",
    "labels = ['Cut', \"Color\", \"Clarity\", \"Carat\", \"Price\"]\n",
    "points = len(labels)\n",
    "\n",
    "angles = np.linspace(0, 2 * np.pi, points, endpoint=False).tolist()\n",
    "angles += angles[:1]\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(6, 6), subplot_kw=dict(polar=True))\n",
    "\n",
    "def add_to_star(diamond, color, label=None):\n",
    "    values = df2.loc[diamond].tolist()\n",
    "    values += values[:1]\n",
    "    if label != None:\n",
    "        ax.plot(angles, values, color=color, linewidth=1, label=label)\n",
    "    else:\n",
    "        ax.plot(angles, values, color=color, linewidth=1, label=diamond)\n",
    "    ax.fill(angles, values, color=color, alpha=0.25)\n",
    "\n",
    "## Plot a new diamond with the add_to_star function\n",
    "add_to_star(31597, '#1aaf6c', \"Best Bling for Your Buck\")\n",
    "add_to_star(26320, '#429bf4', \"Worst Bling for Your Buck\")\n",
    "\n",
    "## Fix axis to star from top\n",
    "ax.set_theta_offset(np.pi / 2)\n",
    "ax.set_theta_direction(-1)\n",
    "\n",
    "## Edit x axis lables\n",
    "for label, angle in zip(ax.get_xticklabels(), angles):\n",
    "    if angle in (0, np.pi):\n",
    "        label.set_horizontalalignment('center')\n",
    "    elif 0 < angle < np.pi:\n",
    "        label.set_horizontalalignment('left')\n",
    "    else:\n",
    "        label.set_horizontalalignment('right')\n",
    "\n",
    "        \n",
    "## Customize your graphic\n",
    "\n",
    "# Change the location of the gridlines or remove them\n",
    "ax.set_rgrids([20, 40, 60 ,80])\n",
    "#ax.set_rgrids([]) # This removes grid lines\n",
    "\n",
    "# Change the color of the ticks\n",
    "ax.tick_params(colors='#222222')\n",
    "# Make the y-axis labels larger, smaller, or remove by setting fontsize\n",
    "ax.tick_params(axis='y', labelsize=0)\n",
    "# Make the x-axis labels larger or smaller.\n",
    "ax.tick_params(axis='x', labelsize=13)\n",
    "\n",
    "# Change the color of the circular gridlines.\n",
    "ax.grid(color='#AAAAAA')\n",
    "# Change the color of the outer circle\n",
    "ax.spines['polar'].set_color('#222222')\n",
    "# Change the circle background color\n",
    "ax.set_facecolor('#FAFAFA')\n",
    "\n",
    "# Add title and legend\n",
    "ax.set_title('Comparing Diamonds Across Dimensions', y=1.08)\n",
    "ax.legend(loc='upper right', bbox_to_anchor=(1.3, 1.1))\n",
    "\n",
    "# Draw axis lines for each angle and label.\n",
    "ax.set_thetagrids(np.degrees(angles), labels)\n",
    "\n",
    "plt.savefig('images/bar.png', bbox_inches='tight', dpi=300)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "### End of Script"
   ]
  }
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