diff --git a/Lec 44 - Aggregation.ipynb b/Lec 44 - Aggregation.ipynb
index f5b80d8..4a235f2 100644
--- a/Lec 44 - Aggregation.ipynb	
+++ b/Lec 44 - Aggregation.ipynb	
@@ -1,1963 +1,3925 @@
-{

- "metadata": {

-  "name": "",

-  "signature": "sha256:e15f796c810b6782ee8033e188d97395fb0602eeee010c7ad5f94bec363fe48c"

- },

- "nbformat": 3,

- "nbformat_minor": 0,

- "worksheets": [

-  {

-   "cells": [

-    {

-     "cell_type": "code",

-     "collapsed": false,

-     "input": [

-      "import numpy as np\n",

-      "import pandas as pd\n",

-      "from pandas import Series,DataFrame"

-     ],

-     "language": "python",

-     "metadata": {},

-     "outputs": [],

-     "prompt_number": 1

-    },

-    {

-     "cell_type": "code",

-     "collapsed": false,

-     "input": [

-      "# Data Agrregation consists of operations that result in a scalar (e.g. mean(),sum(),count(), etc)\n",

-      "\n",

-      "#Let's get a csv data set to play with\n",

-      "url = 'http://archive.ics.uci.edu/ml/machine-learning-databases/wine-quality/'\n",

-      "\n",

-      "\n",

-      "# Save thewinquality.csv file in the same folder as your ipython notebooks, note the delimiter used ;\n",

-      "dframe_wine = pd.read_csv('winequality_red.csv',sep=';')"

-     ],

-     "language": "python",

-     "metadata": {},

-     "outputs": [],

-     "prompt_number": 6

-    },

-    {

-     "cell_type": "code",

-     "collapsed": false,

-     "input": [

-      "# Let's get a preview\n",

-      "dframe_wine.head()"

-     ],

-     "language": "python",

-     "metadata": {},

-     "outputs": [

-      {

-       "html": [

-        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",

-        "<table border=\"1\" class=\"dataframe\">\n",

-        "  <thead>\n",

-        "    <tr style=\"text-align: right;\">\n",

-        "      <th></th>\n",

-        "      <th>fixed acidity</th>\n",

-        "      <th>volatile acidity</th>\n",

-        "      <th>citric acid</th>\n",

-        "      <th>residual sugar</th>\n",

-        "      <th>chlorides</th>\n",

-        "      <th>free sulfur dioxide</th>\n",

-        "      <th>total sulfur dioxide</th>\n",

-        "      <th>density</th>\n",

-        "      <th>pH</th>\n",

-        "      <th>sulphates</th>\n",

-        "      <th>alcohol</th>\n",

-        "      <th>quality</th>\n",

-        "    </tr>\n",

-        "  </thead>\n",

-        "  <tbody>\n",

-        "    <tr>\n",

-        "      <th>0</th>\n",

-        "      <td>  7.4</td>\n",

-        "      <td> 0.70</td>\n",

-        "      <td> 0.00</td>\n",

-        "      <td> 1.9</td>\n",

-        "      <td> 0.076</td>\n",

-        "      <td> 11</td>\n",

-        "      <td> 34</td>\n",

-        "      <td> 0.9978</td>\n",

-        "      <td> 3.51</td>\n",

-        "      <td> 0.56</td>\n",

-        "      <td> 9.4</td>\n",

-        "      <td> 5</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>1</th>\n",

-        "      <td>  7.8</td>\n",

-        "      <td> 0.88</td>\n",

-        "      <td> 0.00</td>\n",

-        "      <td> 2.6</td>\n",

-        "      <td> 0.098</td>\n",

-        "      <td> 25</td>\n",

-        "      <td> 67</td>\n",

-        "      <td> 0.9968</td>\n",

-        "      <td> 3.20</td>\n",

-        "      <td> 0.68</td>\n",

-        "      <td> 9.8</td>\n",

-        "      <td> 5</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>2</th>\n",

-        "      <td>  7.8</td>\n",

-        "      <td> 0.76</td>\n",

-        "      <td> 0.04</td>\n",

-        "      <td> 2.3</td>\n",

-        "      <td> 0.092</td>\n",

-        "      <td> 15</td>\n",

-        "      <td> 54</td>\n",

-        "      <td> 0.9970</td>\n",

-        "      <td> 3.26</td>\n",

-        "      <td> 0.65</td>\n",

-        "      <td> 9.8</td>\n",

-        "      <td> 5</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>3</th>\n",

-        "      <td> 11.2</td>\n",

-        "      <td> 0.28</td>\n",

-        "      <td> 0.56</td>\n",

-        "      <td> 1.9</td>\n",

-        "      <td> 0.075</td>\n",

-        "      <td> 17</td>\n",

-        "      <td> 60</td>\n",

-        "      <td> 0.9980</td>\n",

-        "      <td> 3.16</td>\n",

-        "      <td> 0.58</td>\n",

-        "      <td> 9.8</td>\n",

-        "      <td> 6</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>4</th>\n",

-        "      <td>  7.4</td>\n",

-        "      <td> 0.70</td>\n",

-        "      <td> 0.00</td>\n",

-        "      <td> 1.9</td>\n",

-        "      <td> 0.076</td>\n",

-        "      <td> 11</td>\n",

-        "      <td> 34</td>\n",

-        "      <td> 0.9978</td>\n",

-        "      <td> 3.51</td>\n",

-        "      <td> 0.56</td>\n",

-        "      <td> 9.4</td>\n",

-        "      <td> 5</td>\n",

-        "    </tr>\n",

-        "  </tbody>\n",

-        "</table>\n",

-        "</div>"

-       ],

-       "metadata": {},

-       "output_type": "pyout",

-       "prompt_number": 7,

-       "text": [

-        "   fixed acidity  volatile acidity  citric acid  residual sugar  chlorides  \\\n",

-        "0            7.4              0.70         0.00             1.9      0.076   \n",

-        "1            7.8              0.88         0.00             2.6      0.098   \n",

-        "2            7.8              0.76         0.04             2.3      0.092   \n",

-        "3           11.2              0.28         0.56             1.9      0.075   \n",

-        "4            7.4              0.70         0.00             1.9      0.076   \n",

-        "\n",

-        "   free sulfur dioxide  total sulfur dioxide  density    pH  sulphates  \\\n",

-        "0                   11                    34   0.9978  3.51       0.56   \n",

-        "1                   25                    67   0.9968  3.20       0.68   \n",

-        "2                   15                    54   0.9970  3.26       0.65   \n",

-        "3                   17                    60   0.9980  3.16       0.58   \n",

-        "4                   11                    34   0.9978  3.51       0.56   \n",

-        "\n",

-        "   alcohol  quality  \n",

-        "0      9.4        5  \n",

-        "1      9.8        5  \n",

-        "2      9.8        5  \n",

-        "3      9.8        6  \n",

-        "4      9.4        5  "

-       ]

-      }

-     ],

-     "prompt_number": 7

-    },

-    {

-     "cell_type": "code",

-     "collapsed": false,

-     "input": [

-      "# How about we find out the average alcohol content for the wine\n",

-      "dframe_wine['alcohol'].mean()"

-     ],

-     "language": "python",

-     "metadata": {},

-     "outputs": [

-      {

-       "metadata": {},

-       "output_type": "pyout",

-       "prompt_number": 8,

-       "text": [

-        "10.422983114446529"

-       ]

-      }

-     ],

-     "prompt_number": 8

-    },

-    {

-     "cell_type": "code",

-     "collapsed": false,

-     "input": [

-      "# That was an example of an aggregate, how about we make our own?\n",

-      "def max_to_min(arr):\n",

-      "    return arr.max() - arr.min()\n",

-      "\n",

-      "# Let's group the wines by \"quality\"\n",

-      "wino = dframe_wine.groupby('quality')\n",

-      "\n",

-      "# Show\n",

-      "wino.describe()"

-     ],

-     "language": "python",

-     "metadata": {},

-     "outputs": [

-      {

-       "html": [

-        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",

-        "<table border=\"1\" class=\"dataframe\">\n",

-        "  <thead>\n",

-        "    <tr style=\"text-align: right;\">\n",

-        "      <th></th>\n",

-        "      <th></th>\n",

-        "      <th>alcohol</th>\n",

-        "      <th>chlorides</th>\n",

-        "      <th>citric acid</th>\n",

-        "      <th>density</th>\n",

-        "      <th>fixed acidity</th>\n",

-        "      <th>free sulfur dioxide</th>\n",

-        "      <th>pH</th>\n",

-        "      <th>residual sugar</th>\n",

-        "      <th>sulphates</th>\n",

-        "      <th>total sulfur dioxide</th>\n",

-        "      <th>volatile acidity</th>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>quality</th>\n",

-        "      <th></th>\n",

-        "      <th></th>\n",

-        "      <th></th>\n",

-        "      <th></th>\n",

-        "      <th></th>\n",

-        "      <th></th>\n",

-        "      <th></th>\n",

-        "      <th></th>\n",

-        "      <th></th>\n",

-        "      <th></th>\n",

-        "      <th></th>\n",

-        "      <th></th>\n",

-        "    </tr>\n",

-        "  </thead>\n",

-        "  <tbody>\n",

-        "    <tr>\n",

-        "      <th rowspan=\"8\" valign=\"top\">3</th>\n",

-        "      <th>count</th>\n",

-        "      <td>  10.000000</td>\n",

-        "      <td>  10.000000</td>\n",

-        "      <td>  10.000000</td>\n",

-        "      <td>  10.000000</td>\n",

-        "      <td>  10.000000</td>\n",

-        "      <td>  10.000000</td>\n",

-        "      <td>  10.000000</td>\n",

-        "      <td>  10.000000</td>\n",

-        "      <td>  10.000000</td>\n",

-        "      <td>  10.000000</td>\n",

-        "      <td>  10.000000</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>mean</th>\n",

-        "      <td>   9.955000</td>\n",

-        "      <td>   0.122500</td>\n",

-        "      <td>   0.171000</td>\n",

-        "      <td>   0.997464</td>\n",

-        "      <td>   8.360000</td>\n",

-        "      <td>  11.000000</td>\n",

-        "      <td>   3.398000</td>\n",

-        "      <td>   2.635000</td>\n",

-        "      <td>   0.570000</td>\n",

-        "      <td>  24.900000</td>\n",

-        "      <td>   0.884500</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>std</th>\n",

-        "      <td>   0.818009</td>\n",

-        "      <td>   0.066241</td>\n",

-        "      <td>   0.250664</td>\n",

-        "      <td>   0.002002</td>\n",

-        "      <td>   1.770875</td>\n",

-        "      <td>   9.763879</td>\n",

-        "      <td>   0.144052</td>\n",

-        "      <td>   1.401596</td>\n",

-        "      <td>   0.122020</td>\n",

-        "      <td>  16.828877</td>\n",

-        "      <td>   0.331256</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>min</th>\n",

-        "      <td>   8.400000</td>\n",

-        "      <td>   0.061000</td>\n",

-        "      <td>   0.000000</td>\n",

-        "      <td>   0.994710</td>\n",

-        "      <td>   6.700000</td>\n",

-        "      <td>   3.000000</td>\n",

-        "      <td>   3.160000</td>\n",

-        "      <td>   1.200000</td>\n",

-        "      <td>   0.400000</td>\n",

-        "      <td>   9.000000</td>\n",

-        "      <td>   0.440000</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>25%</th>\n",

-        "      <td>   9.725000</td>\n",

-        "      <td>   0.079000</td>\n",

-        "      <td>   0.005000</td>\n",

-        "      <td>   0.996150</td>\n",

-        "      <td>   7.150000</td>\n",

-        "      <td>   5.000000</td>\n",

-        "      <td>   3.312500</td>\n",

-        "      <td>   1.875000</td>\n",

-        "      <td>   0.512500</td>\n",

-        "      <td>  12.500000</td>\n",

-        "      <td>   0.647500</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>50%</th>\n",

-        "      <td>   9.925000</td>\n",

-        "      <td>   0.090500</td>\n",

-        "      <td>   0.035000</td>\n",

-        "      <td>   0.997565</td>\n",

-        "      <td>   7.500000</td>\n",

-        "      <td>   6.000000</td>\n",

-        "      <td>   3.390000</td>\n",

-        "      <td>   2.100000</td>\n",

-        "      <td>   0.545000</td>\n",

-        "      <td>  15.000000</td>\n",

-        "      <td>   0.845000</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>75%</th>\n",

-        "      <td>  10.575000</td>\n",

-        "      <td>   0.143000</td>\n",

-        "      <td>   0.327500</td>\n",

-        "      <td>   0.998770</td>\n",

-        "      <td>   9.875000</td>\n",

-        "      <td>  14.500000</td>\n",

-        "      <td>   3.495000</td>\n",

-        "      <td>   3.100000</td>\n",

-        "      <td>   0.615000</td>\n",

-        "      <td>  42.500000</td>\n",

-        "      <td>   1.010000</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>max</th>\n",

-        "      <td>  11.000000</td>\n",

-        "      <td>   0.267000</td>\n",

-        "      <td>   0.660000</td>\n",

-        "      <td>   1.000800</td>\n",

-        "      <td>  11.600000</td>\n",

-        "      <td>  34.000000</td>\n",

-        "      <td>   3.630000</td>\n",

-        "      <td>   5.700000</td>\n",

-        "      <td>   0.860000</td>\n",

-        "      <td>  49.000000</td>\n",

-        "      <td>   1.580000</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th rowspan=\"8\" valign=\"top\">4</th>\n",

-        "      <th>count</th>\n",

-        "      <td>  53.000000</td>\n",

-        "      <td>  53.000000</td>\n",

-        "      <td>  53.000000</td>\n",

-        "      <td>  53.000000</td>\n",

-        "      <td>  53.000000</td>\n",

-        "      <td>  53.000000</td>\n",

-        "      <td>  53.000000</td>\n",

-        "      <td>  53.000000</td>\n",

-        "      <td>  53.000000</td>\n",

-        "      <td>  53.000000</td>\n",

-        "      <td>  53.000000</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>mean</th>\n",

-        "      <td>  10.265094</td>\n",

-        "      <td>   0.090679</td>\n",

-        "      <td>   0.174151</td>\n",

-        "      <td>   0.996542</td>\n",

-        "      <td>   7.779245</td>\n",

-        "      <td>  12.264151</td>\n",

-        "      <td>   3.381509</td>\n",

-        "      <td>   2.694340</td>\n",

-        "      <td>   0.596415</td>\n",

-        "      <td>  36.245283</td>\n",

-        "      <td>   0.693962</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>std</th>\n",

-        "      <td>   0.934776</td>\n",

-        "      <td>   0.076192</td>\n",

-        "      <td>   0.201030</td>\n",

-        "      <td>   0.001575</td>\n",

-        "      <td>   1.626624</td>\n",

-        "      <td>   9.025926</td>\n",

-        "      <td>   0.181441</td>\n",

-        "      <td>   1.789436</td>\n",

-        "      <td>   0.239391</td>\n",

-        "      <td>  27.583374</td>\n",

-        "      <td>   0.220110</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>min</th>\n",

-        "      <td>   9.000000</td>\n",

-        "      <td>   0.045000</td>\n",

-        "      <td>   0.000000</td>\n",

-        "      <td>   0.993400</td>\n",

-        "      <td>   4.600000</td>\n",

-        "      <td>   3.000000</td>\n",

-        "      <td>   2.740000</td>\n",

-        "      <td>   1.300000</td>\n",

-        "      <td>   0.330000</td>\n",

-        "      <td>   7.000000</td>\n",

-        "      <td>   0.230000</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>25%</th>\n",

-        "      <td>   9.600000</td>\n",

-        "      <td>   0.067000</td>\n",

-        "      <td>   0.030000</td>\n",

-        "      <td>   0.995650</td>\n",

-        "      <td>   6.800000</td>\n",

-        "      <td>   6.000000</td>\n",

-        "      <td>   3.300000</td>\n",

-        "      <td>   1.900000</td>\n",

-        "      <td>   0.490000</td>\n",

-        "      <td>  14.000000</td>\n",

-        "      <td>   0.530000</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>50%</th>\n",

-        "      <td>  10.000000</td>\n",

-        "      <td>   0.080000</td>\n",

-        "      <td>   0.090000</td>\n",

-        "      <td>   0.996500</td>\n",

-        "      <td>   7.500000</td>\n",

-        "      <td>  11.000000</td>\n",

-        "      <td>   3.370000</td>\n",

-        "      <td>   2.100000</td>\n",

-        "      <td>   0.560000</td>\n",

-        "      <td>  26.000000</td>\n",

-        "      <td>   0.670000</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>75%</th>\n",

-        "      <td>  11.000000</td>\n",

-        "      <td>   0.089000</td>\n",

-        "      <td>   0.270000</td>\n",

-        "      <td>   0.997450</td>\n",

-        "      <td>   8.400000</td>\n",

-        "      <td>  15.000000</td>\n",

-        "      <td>   3.500000</td>\n",

-        "      <td>   2.800000</td>\n",

-        "      <td>   0.600000</td>\n",

-        "      <td>  49.000000</td>\n",

-        "      <td>   0.870000</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>max</th>\n",

-        "      <td>  13.100000</td>\n",

-        "      <td>   0.610000</td>\n",

-        "      <td>   1.000000</td>\n",

-        "      <td>   1.001000</td>\n",

-        "      <td>  12.500000</td>\n",

-        "      <td>  41.000000</td>\n",

-        "      <td>   3.900000</td>\n",

-        "      <td>  12.900000</td>\n",

-        "      <td>   2.000000</td>\n",

-        "      <td> 119.000000</td>\n",

-        "      <td>   1.130000</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th rowspan=\"8\" valign=\"top\">5</th>\n",

-        "      <th>count</th>\n",

-        "      <td> 681.000000</td>\n",

-        "      <td> 681.000000</td>\n",

-        "      <td> 681.000000</td>\n",

-        "      <td> 681.000000</td>\n",

-        "      <td> 681.000000</td>\n",

-        "      <td> 681.000000</td>\n",

-        "      <td> 681.000000</td>\n",

-        "      <td> 681.000000</td>\n",

-        "      <td> 681.000000</td>\n",

-        "      <td> 681.000000</td>\n",

-        "      <td> 681.000000</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>mean</th>\n",

-        "      <td>   9.899706</td>\n",

-        "      <td>   0.092736</td>\n",

-        "      <td>   0.243686</td>\n",

-        "      <td>   0.997104</td>\n",

-        "      <td>   8.167254</td>\n",

-        "      <td>  16.983847</td>\n",

-        "      <td>   3.304949</td>\n",

-        "      <td>   2.528855</td>\n",

-        "      <td>   0.620969</td>\n",

-        "      <td>  56.513950</td>\n",

-        "      <td>   0.577041</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>std</th>\n",

-        "      <td>   0.736521</td>\n",

-        "      <td>   0.053707</td>\n",

-        "      <td>   0.180003</td>\n",

-        "      <td>   0.001589</td>\n",

-        "      <td>   1.563988</td>\n",

-        "      <td>  10.955446</td>\n",

-        "      <td>   0.150618</td>\n",

-        "      <td>   1.359753</td>\n",

-        "      <td>   0.171062</td>\n",

-        "      <td>  36.993116</td>\n",

-        "      <td>   0.164801</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>min</th>\n",

-        "      <td>   8.500000</td>\n",

-        "      <td>   0.039000</td>\n",

-        "      <td>   0.000000</td>\n",

-        "      <td>   0.992560</td>\n",

-        "      <td>   5.000000</td>\n",

-        "      <td>   3.000000</td>\n",

-        "      <td>   2.880000</td>\n",

-        "      <td>   1.200000</td>\n",

-        "      <td>   0.370000</td>\n",

-        "      <td>   6.000000</td>\n",

-        "      <td>   0.180000</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>25%</th>\n",

-        "      <td>   9.400000</td>\n",

-        "      <td>   0.074000</td>\n",

-        "      <td>   0.090000</td>\n",

-        "      <td>   0.996200</td>\n",

-        "      <td>   7.100000</td>\n",

-        "      <td>   9.000000</td>\n",

-        "      <td>   3.200000</td>\n",

-        "      <td>   1.900000</td>\n",

-        "      <td>   0.530000</td>\n",

-        "      <td>  26.000000</td>\n",

-        "      <td>   0.460000</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>50%</th>\n",

-        "      <td>   9.700000</td>\n",

-        "      <td>   0.081000</td>\n",

-        "      <td>   0.230000</td>\n",

-        "      <td>   0.997000</td>\n",

-        "      <td>   7.800000</td>\n",

-        "      <td>  15.000000</td>\n",

-        "      <td>   3.300000</td>\n",

-        "      <td>   2.200000</td>\n",

-        "      <td>   0.580000</td>\n",

-        "      <td>  47.000000</td>\n",

-        "      <td>   0.580000</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>75%</th>\n",

-        "      <td>  10.200000</td>\n",

-        "      <td>   0.094000</td>\n",

-        "      <td>   0.360000</td>\n",

-        "      <td>   0.997900</td>\n",

-        "      <td>   8.900000</td>\n",

-        "      <td>  23.000000</td>\n",

-        "      <td>   3.400000</td>\n",

-        "      <td>   2.600000</td>\n",

-        "      <td>   0.660000</td>\n",

-        "      <td>  84.000000</td>\n",

-        "      <td>   0.670000</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>max</th>\n",

-        "      <td>  14.900000</td>\n",

-        "      <td>   0.611000</td>\n",

-        "      <td>   0.790000</td>\n",

-        "      <td>   1.003150</td>\n",

-        "      <td>  15.900000</td>\n",

-        "      <td>  68.000000</td>\n",

-        "      <td>   3.740000</td>\n",

-        "      <td>  15.500000</td>\n",

-        "      <td>   1.980000</td>\n",

-        "      <td> 155.000000</td>\n",

-        "      <td>   1.330000</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th rowspan=\"8\" valign=\"top\">6</th>\n",

-        "      <th>count</th>\n",

-        "      <td> 638.000000</td>\n",

-        "      <td> 638.000000</td>\n",

-        "      <td> 638.000000</td>\n",

-        "      <td> 638.000000</td>\n",

-        "      <td> 638.000000</td>\n",

-        "      <td> 638.000000</td>\n",

-        "      <td> 638.000000</td>\n",

-        "      <td> 638.000000</td>\n",

-        "      <td> 638.000000</td>\n",

-        "      <td> 638.000000</td>\n",

-        "      <td> 638.000000</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>mean</th>\n",

-        "      <td>  10.629519</td>\n",

-        "      <td>   0.084956</td>\n",

-        "      <td>   0.273824</td>\n",

-        "      <td>   0.996615</td>\n",

-        "      <td>   8.347179</td>\n",

-        "      <td>  15.711599</td>\n",

-        "      <td>   3.318072</td>\n",

-        "      <td>   2.477194</td>\n",

-        "      <td>   0.675329</td>\n",

-        "      <td>  40.869906</td>\n",

-        "      <td>   0.497484</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>std</th>\n",

-        "      <td>   1.049639</td>\n",

-        "      <td>   0.039563</td>\n",

-        "      <td>   0.195108</td>\n",

-        "      <td>   0.002000</td>\n",

-        "      <td>   1.797849</td>\n",

-        "      <td>   9.940911</td>\n",

-        "      <td>   0.153995</td>\n",

-        "      <td>   1.441576</td>\n",

-        "      <td>   0.158650</td>\n",

-        "      <td>  25.038250</td>\n",

-        "      <td>   0.160962</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>min</th>\n",

-        "      <td>   8.400000</td>\n",

-        "      <td>   0.034000</td>\n",

-        "      <td>   0.000000</td>\n",

-        "      <td>   0.990070</td>\n",

-        "      <td>   4.700000</td>\n",

-        "      <td>   1.000000</td>\n",

-        "      <td>   2.860000</td>\n",

-        "      <td>   0.900000</td>\n",

-        "      <td>   0.400000</td>\n",

-        "      <td>   6.000000</td>\n",

-        "      <td>   0.160000</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>25%</th>\n",

-        "      <td>   9.800000</td>\n",

-        "      <td>   0.068250</td>\n",

-        "      <td>   0.090000</td>\n",

-        "      <td>   0.995402</td>\n",

-        "      <td>   7.000000</td>\n",

-        "      <td>   8.000000</td>\n",

-        "      <td>   3.220000</td>\n",

-        "      <td>   1.900000</td>\n",

-        "      <td>   0.580000</td>\n",

-        "      <td>  23.000000</td>\n",

-        "      <td>   0.380000</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>50%</th>\n",

-        "      <td>  10.500000</td>\n",

-        "      <td>   0.078000</td>\n",

-        "      <td>   0.260000</td>\n",

-        "      <td>   0.996560</td>\n",

-        "      <td>   7.900000</td>\n",

-        "      <td>  14.000000</td>\n",

-        "      <td>   3.320000</td>\n",

-        "      <td>   2.200000</td>\n",

-        "      <td>   0.640000</td>\n",

-        "      <td>  35.000000</td>\n",

-        "      <td>   0.490000</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>75%</th>\n",

-        "      <td>  11.300000</td>\n",

-        "      <td>   0.088000</td>\n",

-        "      <td>   0.430000</td>\n",

-        "      <td>   0.997893</td>\n",

-        "      <td>   9.400000</td>\n",

-        "      <td>  21.000000</td>\n",

-        "      <td>   3.410000</td>\n",

-        "      <td>   2.500000</td>\n",

-        "      <td>   0.750000</td>\n",

-        "      <td>  54.000000</td>\n",

-        "      <td>   0.600000</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>max</th>\n",

-        "      <td>  14.000000</td>\n",

-        "      <td>   0.415000</td>\n",

-        "      <td>   0.780000</td>\n",

-        "      <td>   1.003690</td>\n",

-        "      <td>  14.300000</td>\n",

-        "      <td>  72.000000</td>\n",

-        "      <td>   4.010000</td>\n",

-        "      <td>  15.400000</td>\n",

-        "      <td>   1.950000</td>\n",

-        "      <td> 165.000000</td>\n",

-        "      <td>   1.040000</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th rowspan=\"8\" valign=\"top\">7</th>\n",

-        "      <th>count</th>\n",

-        "      <td> 199.000000</td>\n",

-        "      <td> 199.000000</td>\n",

-        "      <td> 199.000000</td>\n",

-        "      <td> 199.000000</td>\n",

-        "      <td> 199.000000</td>\n",

-        "      <td> 199.000000</td>\n",

-        "      <td> 199.000000</td>\n",

-        "      <td> 199.000000</td>\n",

-        "      <td> 199.000000</td>\n",

-        "      <td> 199.000000</td>\n",

-        "      <td> 199.000000</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>mean</th>\n",

-        "      <td>  11.465913</td>\n",

-        "      <td>   0.076588</td>\n",

-        "      <td>   0.375176</td>\n",

-        "      <td>   0.996104</td>\n",

-        "      <td>   8.872362</td>\n",

-        "      <td>  14.045226</td>\n",

-        "      <td>   3.290754</td>\n",

-        "      <td>   2.720603</td>\n",

-        "      <td>   0.741256</td>\n",

-        "      <td>  35.020101</td>\n",

-        "      <td>   0.403920</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>std</th>\n",

-        "      <td>   0.961933</td>\n",

-        "      <td>   0.029456</td>\n",

-        "      <td>   0.194432</td>\n",

-        "      <td>   0.002176</td>\n",

-        "      <td>   1.992483</td>\n",

-        "      <td>  10.175255</td>\n",

-        "      <td>   0.150101</td>\n",

-        "      <td>   1.371509</td>\n",

-        "      <td>   0.135639</td>\n",

-        "      <td>  33.191206</td>\n",

-        "      <td>   0.145224</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>min</th>\n",

-        "      <td>   9.200000</td>\n",

-        "      <td>   0.012000</td>\n",

-        "      <td>   0.000000</td>\n",

-        "      <td>   0.990640</td>\n",

-        "      <td>   4.900000</td>\n",

-        "      <td>   3.000000</td>\n",

-        "      <td>   2.920000</td>\n",

-        "      <td>   1.200000</td>\n",

-        "      <td>   0.390000</td>\n",

-        "      <td>   7.000000</td>\n",

-        "      <td>   0.120000</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>25%</th>\n",

-        "      <td>  10.800000</td>\n",

-        "      <td>   0.062000</td>\n",

-        "      <td>   0.305000</td>\n",

-        "      <td>   0.994765</td>\n",

-        "      <td>   7.400000</td>\n",

-        "      <td>   6.000000</td>\n",

-        "      <td>   3.200000</td>\n",

-        "      <td>   2.000000</td>\n",

-        "      <td>   0.650000</td>\n",

-        "      <td>  17.500000</td>\n",

-        "      <td>   0.300000</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>50%</th>\n",

-        "      <td>  11.500000</td>\n",

-        "      <td>   0.073000</td>\n",

-        "      <td>   0.400000</td>\n",

-        "      <td>   0.995770</td>\n",

-        "      <td>   8.800000</td>\n",

-        "      <td>  11.000000</td>\n",

-        "      <td>   3.280000</td>\n",

-        "      <td>   2.300000</td>\n",

-        "      <td>   0.740000</td>\n",

-        "      <td>  27.000000</td>\n",

-        "      <td>   0.370000</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>75%</th>\n",

-        "      <td>  12.100000</td>\n",

-        "      <td>   0.087000</td>\n",

-        "      <td>   0.490000</td>\n",

-        "      <td>   0.997360</td>\n",

-        "      <td>  10.100000</td>\n",

-        "      <td>  18.000000</td>\n",

-        "      <td>   3.380000</td>\n",

-        "      <td>   2.750000</td>\n",

-        "      <td>   0.830000</td>\n",

-        "      <td>  43.000000</td>\n",

-        "      <td>   0.485000</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>max</th>\n",

-        "      <td>  14.000000</td>\n",

-        "      <td>   0.358000</td>\n",

-        "      <td>   0.760000</td>\n",

-        "      <td>   1.003200</td>\n",

-        "      <td>  15.600000</td>\n",

-        "      <td>  54.000000</td>\n",

-        "      <td>   3.780000</td>\n",

-        "      <td>   8.900000</td>\n",

-        "      <td>   1.360000</td>\n",

-        "      <td> 289.000000</td>\n",

-        "      <td>   0.915000</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th rowspan=\"8\" valign=\"top\">8</th>\n",

-        "      <th>count</th>\n",

-        "      <td>  18.000000</td>\n",

-        "      <td>  18.000000</td>\n",

-        "      <td>  18.000000</td>\n",

-        "      <td>  18.000000</td>\n",

-        "      <td>  18.000000</td>\n",

-        "      <td>  18.000000</td>\n",

-        "      <td>  18.000000</td>\n",

-        "      <td>  18.000000</td>\n",

-        "      <td>  18.000000</td>\n",

-        "      <td>  18.000000</td>\n",

-        "      <td>  18.000000</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>mean</th>\n",

-        "      <td>  12.094444</td>\n",

-        "      <td>   0.068444</td>\n",

-        "      <td>   0.391111</td>\n",

-        "      <td>   0.995212</td>\n",

-        "      <td>   8.566667</td>\n",

-        "      <td>  13.277778</td>\n",

-        "      <td>   3.267222</td>\n",

-        "      <td>   2.577778</td>\n",

-        "      <td>   0.767778</td>\n",

-        "      <td>  33.444444</td>\n",

-        "      <td>   0.423333</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>std</th>\n",

-        "      <td>   1.224011</td>\n",

-        "      <td>   0.011678</td>\n",

-        "      <td>   0.199526</td>\n",

-        "      <td>   0.002378</td>\n",

-        "      <td>   2.119656</td>\n",

-        "      <td>  11.155613</td>\n",

-        "      <td>   0.200640</td>\n",

-        "      <td>   1.295038</td>\n",

-        "      <td>   0.115379</td>\n",

-        "      <td>  25.433240</td>\n",

-        "      <td>   0.144914</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>min</th>\n",

-        "      <td>   9.800000</td>\n",

-        "      <td>   0.044000</td>\n",

-        "      <td>   0.030000</td>\n",

-        "      <td>   0.990800</td>\n",

-        "      <td>   5.000000</td>\n",

-        "      <td>   3.000000</td>\n",

-        "      <td>   2.880000</td>\n",

-        "      <td>   1.400000</td>\n",

-        "      <td>   0.630000</td>\n",

-        "      <td>  12.000000</td>\n",

-        "      <td>   0.260000</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>25%</th>\n",

-        "      <td>  11.325000</td>\n",

-        "      <td>   0.062000</td>\n",

-        "      <td>   0.302500</td>\n",

-        "      <td>   0.994175</td>\n",

-        "      <td>   7.250000</td>\n",

-        "      <td>   6.000000</td>\n",

-        "      <td>   3.162500</td>\n",

-        "      <td>   1.800000</td>\n",

-        "      <td>   0.690000</td>\n",

-        "      <td>  16.000000</td>\n",

-        "      <td>   0.335000</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>50%</th>\n",

-        "      <td>  12.150000</td>\n",

-        "      <td>   0.070500</td>\n",

-        "      <td>   0.420000</td>\n",

-        "      <td>   0.994940</td>\n",

-        "      <td>   8.250000</td>\n",

-        "      <td>   7.500000</td>\n",

-        "      <td>   3.230000</td>\n",

-        "      <td>   2.100000</td>\n",

-        "      <td>   0.740000</td>\n",

-        "      <td>  21.500000</td>\n",

-        "      <td>   0.370000</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>75%</th>\n",

-        "      <td>  12.875000</td>\n",

-        "      <td>   0.075500</td>\n",

-        "      <td>   0.530000</td>\n",

-        "      <td>   0.997200</td>\n",

-        "      <td>  10.225000</td>\n",

-        "      <td>  16.500000</td>\n",

-        "      <td>   3.350000</td>\n",

-        "      <td>   2.600000</td>\n",

-        "      <td>   0.820000</td>\n",

-        "      <td>  43.000000</td>\n",

-        "      <td>   0.472500</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>max</th>\n",

-        "      <td>  14.000000</td>\n",

-        "      <td>   0.086000</td>\n",

-        "      <td>   0.720000</td>\n",

-        "      <td>   0.998800</td>\n",

-        "      <td>  12.600000</td>\n",

-        "      <td>  42.000000</td>\n",

-        "      <td>   3.720000</td>\n",

-        "      <td>   6.400000</td>\n",

-        "      <td>   1.100000</td>\n",

-        "      <td>  88.000000</td>\n",

-        "      <td>   0.850000</td>\n",

-        "    </tr>\n",

-        "  </tbody>\n",

-        "</table>\n",

-        "</div>"

-       ],

-       "metadata": {},

-       "output_type": "pyout",

-       "prompt_number": 25,

-       "text": [

-        "                  alcohol   chlorides  citric acid     density  fixed acidity  \\\n",

-        "quality                                                                         \n",

-        "3       count   10.000000   10.000000    10.000000   10.000000      10.000000   \n",

-        "        mean     9.955000    0.122500     0.171000    0.997464       8.360000   \n",

-        "        std      0.818009    0.066241     0.250664    0.002002       1.770875   \n",

-        "        min      8.400000    0.061000     0.000000    0.994710       6.700000   \n",

-        "        25%      9.725000    0.079000     0.005000    0.996150       7.150000   \n",

-        "        50%      9.925000    0.090500     0.035000    0.997565       7.500000   \n",

-        "        75%     10.575000    0.143000     0.327500    0.998770       9.875000   \n",

-        "        max     11.000000    0.267000     0.660000    1.000800      11.600000   \n",

-        "4       count   53.000000   53.000000    53.000000   53.000000      53.000000   \n",

-        "        mean    10.265094    0.090679     0.174151    0.996542       7.779245   \n",

-        "        std      0.934776    0.076192     0.201030    0.001575       1.626624   \n",

-        "        min      9.000000    0.045000     0.000000    0.993400       4.600000   \n",

-        "        25%      9.600000    0.067000     0.030000    0.995650       6.800000   \n",

-        "        50%     10.000000    0.080000     0.090000    0.996500       7.500000   \n",

-        "        75%     11.000000    0.089000     0.270000    0.997450       8.400000   \n",

-        "        max     13.100000    0.610000     1.000000    1.001000      12.500000   \n",

-        "5       count  681.000000  681.000000   681.000000  681.000000     681.000000   \n",

-        "        mean     9.899706    0.092736     0.243686    0.997104       8.167254   \n",

-        "        std      0.736521    0.053707     0.180003    0.001589       1.563988   \n",

-        "        min      8.500000    0.039000     0.000000    0.992560       5.000000   \n",

-        "        25%      9.400000    0.074000     0.090000    0.996200       7.100000   \n",

-        "        50%      9.700000    0.081000     0.230000    0.997000       7.800000   \n",

-        "        75%     10.200000    0.094000     0.360000    0.997900       8.900000   \n",

-        "        max     14.900000    0.611000     0.790000    1.003150      15.900000   \n",

-        "6       count  638.000000  638.000000   638.000000  638.000000     638.000000   \n",

-        "        mean    10.629519    0.084956     0.273824    0.996615       8.347179   \n",

-        "        std      1.049639    0.039563     0.195108    0.002000       1.797849   \n",

-        "        min      8.400000    0.034000     0.000000    0.990070       4.700000   \n",

-        "        25%      9.800000    0.068250     0.090000    0.995402       7.000000   \n",

-        "        50%     10.500000    0.078000     0.260000    0.996560       7.900000   \n",

-        "        75%     11.300000    0.088000     0.430000    0.997893       9.400000   \n",

-        "        max     14.000000    0.415000     0.780000    1.003690      14.300000   \n",

-        "7       count  199.000000  199.000000   199.000000  199.000000     199.000000   \n",

-        "        mean    11.465913    0.076588     0.375176    0.996104       8.872362   \n",

-        "        std      0.961933    0.029456     0.194432    0.002176       1.992483   \n",

-        "        min      9.200000    0.012000     0.000000    0.990640       4.900000   \n",

-        "        25%     10.800000    0.062000     0.305000    0.994765       7.400000   \n",

-        "        50%     11.500000    0.073000     0.400000    0.995770       8.800000   \n",

-        "        75%     12.100000    0.087000     0.490000    0.997360      10.100000   \n",

-        "        max     14.000000    0.358000     0.760000    1.003200      15.600000   \n",

-        "8       count   18.000000   18.000000    18.000000   18.000000      18.000000   \n",

-        "        mean    12.094444    0.068444     0.391111    0.995212       8.566667   \n",

-        "        std      1.224011    0.011678     0.199526    0.002378       2.119656   \n",

-        "        min      9.800000    0.044000     0.030000    0.990800       5.000000   \n",

-        "        25%     11.325000    0.062000     0.302500    0.994175       7.250000   \n",

-        "        50%     12.150000    0.070500     0.420000    0.994940       8.250000   \n",

-        "        75%     12.875000    0.075500     0.530000    0.997200      10.225000   \n",

-        "        max     14.000000    0.086000     0.720000    0.998800      12.600000   \n",

-        "\n",

-        "               free sulfur dioxide          pH  residual sugar   sulphates  \\\n",

-        "quality                                                                      \n",

-        "3       count            10.000000   10.000000       10.000000   10.000000   \n",

-        "        mean             11.000000    3.398000        2.635000    0.570000   \n",

-        "        std               9.763879    0.144052        1.401596    0.122020   \n",

-        "        min               3.000000    3.160000        1.200000    0.400000   \n",

-        "        25%               5.000000    3.312500        1.875000    0.512500   \n",

-        "        50%               6.000000    3.390000        2.100000    0.545000   \n",

-        "        75%              14.500000    3.495000        3.100000    0.615000   \n",

-        "        max              34.000000    3.630000        5.700000    0.860000   \n",

-        "4       count            53.000000   53.000000       53.000000   53.000000   \n",

-        "        mean             12.264151    3.381509        2.694340    0.596415   \n",

-        "        std               9.025926    0.181441        1.789436    0.239391   \n",

-        "        min               3.000000    2.740000        1.300000    0.330000   \n",

-        "        25%               6.000000    3.300000        1.900000    0.490000   \n",

-        "        50%              11.000000    3.370000        2.100000    0.560000   \n",

-        "        75%              15.000000    3.500000        2.800000    0.600000   \n",

-        "        max              41.000000    3.900000       12.900000    2.000000   \n",

-        "5       count           681.000000  681.000000      681.000000  681.000000   \n",

-        "        mean             16.983847    3.304949        2.528855    0.620969   \n",

-        "        std              10.955446    0.150618        1.359753    0.171062   \n",

-        "        min               3.000000    2.880000        1.200000    0.370000   \n",

-        "        25%               9.000000    3.200000        1.900000    0.530000   \n",

-        "        50%              15.000000    3.300000        2.200000    0.580000   \n",

-        "        75%              23.000000    3.400000        2.600000    0.660000   \n",

-        "        max              68.000000    3.740000       15.500000    1.980000   \n",

-        "6       count           638.000000  638.000000      638.000000  638.000000   \n",

-        "        mean             15.711599    3.318072        2.477194    0.675329   \n",

-        "        std               9.940911    0.153995        1.441576    0.158650   \n",

-        "        min               1.000000    2.860000        0.900000    0.400000   \n",

-        "        25%               8.000000    3.220000        1.900000    0.580000   \n",

-        "        50%              14.000000    3.320000        2.200000    0.640000   \n",

-        "        75%              21.000000    3.410000        2.500000    0.750000   \n",

-        "        max              72.000000    4.010000       15.400000    1.950000   \n",

-        "7       count           199.000000  199.000000      199.000000  199.000000   \n",

-        "        mean             14.045226    3.290754        2.720603    0.741256   \n",

-        "        std              10.175255    0.150101        1.371509    0.135639   \n",

-        "        min               3.000000    2.920000        1.200000    0.390000   \n",

-        "        25%               6.000000    3.200000        2.000000    0.650000   \n",

-        "        50%              11.000000    3.280000        2.300000    0.740000   \n",

-        "        75%              18.000000    3.380000        2.750000    0.830000   \n",

-        "        max              54.000000    3.780000        8.900000    1.360000   \n",

-        "8       count            18.000000   18.000000       18.000000   18.000000   \n",

-        "        mean             13.277778    3.267222        2.577778    0.767778   \n",

-        "        std              11.155613    0.200640        1.295038    0.115379   \n",

-        "        min               3.000000    2.880000        1.400000    0.630000   \n",

-        "        25%               6.000000    3.162500        1.800000    0.690000   \n",

-        "        50%               7.500000    3.230000        2.100000    0.740000   \n",

-        "        75%              16.500000    3.350000        2.600000    0.820000   \n",

-        "        max              42.000000    3.720000        6.400000    1.100000   \n",

-        "\n",

-        "               total sulfur dioxide  volatile acidity  \n",

-        "quality                                                \n",

-        "3       count             10.000000         10.000000  \n",

-        "        mean              24.900000          0.884500  \n",

-        "        std               16.828877          0.331256  \n",

-        "        min                9.000000          0.440000  \n",

-        "        25%               12.500000          0.647500  \n",

-        "        50%               15.000000          0.845000  \n",

-        "        75%               42.500000          1.010000  \n",

-        "        max               49.000000          1.580000  \n",

-        "4       count             53.000000         53.000000  \n",

-        "        mean              36.245283          0.693962  \n",

-        "        std               27.583374          0.220110  \n",

-        "        min                7.000000          0.230000  \n",

-        "        25%               14.000000          0.530000  \n",

-        "        50%               26.000000          0.670000  \n",

-        "        75%               49.000000          0.870000  \n",

-        "        max              119.000000          1.130000  \n",

-        "5       count            681.000000        681.000000  \n",

-        "        mean              56.513950          0.577041  \n",

-        "        std               36.993116          0.164801  \n",

-        "        min                6.000000          0.180000  \n",

-        "        25%               26.000000          0.460000  \n",

-        "        50%               47.000000          0.580000  \n",

-        "        75%               84.000000          0.670000  \n",

-        "        max              155.000000          1.330000  \n",

-        "6       count            638.000000        638.000000  \n",

-        "        mean              40.869906          0.497484  \n",

-        "        std               25.038250          0.160962  \n",

-        "        min                6.000000          0.160000  \n",

-        "        25%               23.000000          0.380000  \n",

-        "        50%               35.000000          0.490000  \n",

-        "        75%               54.000000          0.600000  \n",

-        "        max              165.000000          1.040000  \n",

-        "7       count            199.000000        199.000000  \n",

-        "        mean              35.020101          0.403920  \n",

-        "        std               33.191206          0.145224  \n",

-        "        min                7.000000          0.120000  \n",

-        "        25%               17.500000          0.300000  \n",

-        "        50%               27.000000          0.370000  \n",

-        "        75%               43.000000          0.485000  \n",

-        "        max              289.000000          0.915000  \n",

-        "8       count             18.000000         18.000000  \n",

-        "        mean              33.444444          0.423333  \n",

-        "        std               25.433240          0.144914  \n",

-        "        min               12.000000          0.260000  \n",

-        "        25%               16.000000          0.335000  \n",

-        "        50%               21.500000          0.370000  \n",

-        "        75%               43.000000          0.472500  \n",

-        "        max               88.000000          0.850000  "

-       ]

-      }

-     ],

-     "prompt_number": 25

-    },

-    {

-     "cell_type": "code",

-     "collapsed": false,

-     "input": [

-      "# We can now apply our own aggregate function, this function takes the max value of the col and subtracts the min value of the col\n",

-      "wino.agg(max_to_min)"

-     ],

-     "language": "python",

-     "metadata": {},

-     "outputs": [

-      {

-       "html": [

-        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",

-        "<table border=\"1\" class=\"dataframe\">\n",

-        "  <thead>\n",

-        "    <tr style=\"text-align: right;\">\n",

-        "      <th></th>\n",

-        "      <th>fixed acidity</th>\n",

-        "      <th>volatile acidity</th>\n",

-        "      <th>citric acid</th>\n",

-        "      <th>residual sugar</th>\n",

-        "      <th>chlorides</th>\n",

-        "      <th>free sulfur dioxide</th>\n",

-        "      <th>total sulfur dioxide</th>\n",

-        "      <th>density</th>\n",

-        "      <th>pH</th>\n",

-        "      <th>sulphates</th>\n",

-        "      <th>alcohol</th>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>quality</th>\n",

-        "      <th></th>\n",

-        "      <th></th>\n",

-        "      <th></th>\n",

-        "      <th></th>\n",

-        "      <th></th>\n",

-        "      <th></th>\n",

-        "      <th></th>\n",

-        "      <th></th>\n",

-        "      <th></th>\n",

-        "      <th></th>\n",

-        "      <th></th>\n",

-        "    </tr>\n",

-        "  </thead>\n",

-        "  <tbody>\n",

-        "    <tr>\n",

-        "      <th>3</th>\n",

-        "      <td>  4.9</td>\n",

-        "      <td> 1.140</td>\n",

-        "      <td> 0.66</td>\n",

-        "      <td>  4.5</td>\n",

-        "      <td> 0.206</td>\n",

-        "      <td> 31</td>\n",

-        "      <td>  40</td>\n",

-        "      <td> 0.00609</td>\n",

-        "      <td> 0.47</td>\n",

-        "      <td> 0.46</td>\n",

-        "      <td> 2.6</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>4</th>\n",

-        "      <td>  7.9</td>\n",

-        "      <td> 0.900</td>\n",

-        "      <td> 1.00</td>\n",

-        "      <td> 11.6</td>\n",

-        "      <td> 0.565</td>\n",

-        "      <td> 38</td>\n",

-        "      <td> 112</td>\n",

-        "      <td> 0.00760</td>\n",

-        "      <td> 1.16</td>\n",

-        "      <td> 1.67</td>\n",

-        "      <td> 4.1</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>5</th>\n",

-        "      <td> 10.9</td>\n",

-        "      <td> 1.150</td>\n",

-        "      <td> 0.79</td>\n",

-        "      <td> 14.3</td>\n",

-        "      <td> 0.572</td>\n",

-        "      <td> 65</td>\n",

-        "      <td> 149</td>\n",

-        "      <td> 0.01059</td>\n",

-        "      <td> 0.86</td>\n",

-        "      <td> 1.61</td>\n",

-        "      <td> 6.4</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>6</th>\n",

-        "      <td>  9.6</td>\n",

-        "      <td> 0.880</td>\n",

-        "      <td> 0.78</td>\n",

-        "      <td> 14.5</td>\n",

-        "      <td> 0.381</td>\n",

-        "      <td> 71</td>\n",

-        "      <td> 159</td>\n",

-        "      <td> 0.01362</td>\n",

-        "      <td> 1.15</td>\n",

-        "      <td> 1.55</td>\n",

-        "      <td> 5.6</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>7</th>\n",

-        "      <td> 10.7</td>\n",

-        "      <td> 0.795</td>\n",

-        "      <td> 0.76</td>\n",

-        "      <td>  7.7</td>\n",

-        "      <td> 0.346</td>\n",

-        "      <td> 51</td>\n",

-        "      <td> 282</td>\n",

-        "      <td> 0.01256</td>\n",

-        "      <td> 0.86</td>\n",

-        "      <td> 0.97</td>\n",

-        "      <td> 4.8</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>8</th>\n",

-        "      <td>  7.6</td>\n",

-        "      <td> 0.590</td>\n",

-        "      <td> 0.69</td>\n",

-        "      <td>  5.0</td>\n",

-        "      <td> 0.042</td>\n",

-        "      <td> 39</td>\n",

-        "      <td>  76</td>\n",

-        "      <td> 0.00800</td>\n",

-        "      <td> 0.84</td>\n",

-        "      <td> 0.47</td>\n",

-        "      <td> 4.2</td>\n",

-        "    </tr>\n",

-        "  </tbody>\n",

-        "</table>\n",

-        "</div>"

-       ],

-       "metadata": {},

-       "output_type": "pyout",

-       "prompt_number": 22,

-       "text": [

-        "         fixed acidity  volatile acidity  citric acid  residual sugar  \\\n",

-        "quality                                                                 \n",

-        "3                  4.9             1.140         0.66             4.5   \n",

-        "4                  7.9             0.900         1.00            11.6   \n",

-        "5                 10.9             1.150         0.79            14.3   \n",

-        "6                  9.6             0.880         0.78            14.5   \n",

-        "7                 10.7             0.795         0.76             7.7   \n",

-        "8                  7.6             0.590         0.69             5.0   \n",

-        "\n",

-        "         chlorides  free sulfur dioxide  total sulfur dioxide  density    pH  \\\n",

-        "quality                                                                        \n",

-        "3            0.206                   31                    40  0.00609  0.47   \n",

-        "4            0.565                   38                   112  0.00760  1.16   \n",

-        "5            0.572                   65                   149  0.01059  0.86   \n",

-        "6            0.381                   71                   159  0.01362  1.15   \n",

-        "7            0.346                   51                   282  0.01256  0.86   \n",

-        "8            0.042                   39                    76  0.00800  0.84   \n",

-        "\n",

-        "         sulphates  alcohol  \n",

-        "quality                      \n",

-        "3             0.46      2.6  \n",

-        "4             1.67      4.1  \n",

-        "5             1.61      6.4  \n",

-        "6             1.55      5.6  \n",

-        "7             0.97      4.8  \n",

-        "8             0.47      4.2  "

-       ]

-      }

-     ],

-     "prompt_number": 22

-    },

-    {

-     "cell_type": "code",

-     "collapsed": false,

-     "input": [

-      "# We can also pass string methods through aggregate\n",

-      "wino.agg('mean')"

-     ],

-     "language": "python",

-     "metadata": {},

-     "outputs": [

-      {

-       "html": [

-        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",

-        "<table border=\"1\" class=\"dataframe\">\n",

-        "  <thead>\n",

-        "    <tr style=\"text-align: right;\">\n",

-        "      <th></th>\n",

-        "      <th>fixed acidity</th>\n",

-        "      <th>volatile acidity</th>\n",

-        "      <th>citric acid</th>\n",

-        "      <th>residual sugar</th>\n",

-        "      <th>chlorides</th>\n",

-        "      <th>free sulfur dioxide</th>\n",

-        "      <th>total sulfur dioxide</th>\n",

-        "      <th>density</th>\n",

-        "      <th>pH</th>\n",

-        "      <th>sulphates</th>\n",

-        "      <th>alcohol</th>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>quality</th>\n",

-        "      <th></th>\n",

-        "      <th></th>\n",

-        "      <th></th>\n",

-        "      <th></th>\n",

-        "      <th></th>\n",

-        "      <th></th>\n",

-        "      <th></th>\n",

-        "      <th></th>\n",

-        "      <th></th>\n",

-        "      <th></th>\n",

-        "      <th></th>\n",

-        "    </tr>\n",

-        "  </thead>\n",

-        "  <tbody>\n",

-        "    <tr>\n",

-        "      <th>3</th>\n",

-        "      <td> 8.360000</td>\n",

-        "      <td> 0.884500</td>\n",

-        "      <td> 0.171000</td>\n",

-        "      <td> 2.635000</td>\n",

-        "      <td> 0.122500</td>\n",

-        "      <td> 11.000000</td>\n",

-        "      <td> 24.900000</td>\n",

-        "      <td> 0.997464</td>\n",

-        "      <td> 3.398000</td>\n",

-        "      <td> 0.570000</td>\n",

-        "      <td>  9.955000</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>4</th>\n",

-        "      <td> 7.779245</td>\n",

-        "      <td> 0.693962</td>\n",

-        "      <td> 0.174151</td>\n",

-        "      <td> 2.694340</td>\n",

-        "      <td> 0.090679</td>\n",

-        "      <td> 12.264151</td>\n",

-        "      <td> 36.245283</td>\n",

-        "      <td> 0.996542</td>\n",

-        "      <td> 3.381509</td>\n",

-        "      <td> 0.596415</td>\n",

-        "      <td> 10.265094</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>5</th>\n",

-        "      <td> 8.167254</td>\n",

-        "      <td> 0.577041</td>\n",

-        "      <td> 0.243686</td>\n",

-        "      <td> 2.528855</td>\n",

-        "      <td> 0.092736</td>\n",

-        "      <td> 16.983847</td>\n",

-        "      <td> 56.513950</td>\n",

-        "      <td> 0.997104</td>\n",

-        "      <td> 3.304949</td>\n",

-        "      <td> 0.620969</td>\n",

-        "      <td>  9.899706</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>6</th>\n",

-        "      <td> 8.347179</td>\n",

-        "      <td> 0.497484</td>\n",

-        "      <td> 0.273824</td>\n",

-        "      <td> 2.477194</td>\n",

-        "      <td> 0.084956</td>\n",

-        "      <td> 15.711599</td>\n",

-        "      <td> 40.869906</td>\n",

-        "      <td> 0.996615</td>\n",

-        "      <td> 3.318072</td>\n",

-        "      <td> 0.675329</td>\n",

-        "      <td> 10.629519</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>7</th>\n",

-        "      <td> 8.872362</td>\n",

-        "      <td> 0.403920</td>\n",

-        "      <td> 0.375176</td>\n",

-        "      <td> 2.720603</td>\n",

-        "      <td> 0.076588</td>\n",

-        "      <td> 14.045226</td>\n",

-        "      <td> 35.020101</td>\n",

-        "      <td> 0.996104</td>\n",

-        "      <td> 3.290754</td>\n",

-        "      <td> 0.741256</td>\n",

-        "      <td> 11.465913</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>8</th>\n",

-        "      <td> 8.566667</td>\n",

-        "      <td> 0.423333</td>\n",

-        "      <td> 0.391111</td>\n",

-        "      <td> 2.577778</td>\n",

-        "      <td> 0.068444</td>\n",

-        "      <td> 13.277778</td>\n",

-        "      <td> 33.444444</td>\n",

-        "      <td> 0.995212</td>\n",

-        "      <td> 3.267222</td>\n",

-        "      <td> 0.767778</td>\n",

-        "      <td> 12.094444</td>\n",

-        "    </tr>\n",

-        "  </tbody>\n",

-        "</table>\n",

-        "</div>"

-       ],

-       "metadata": {},

-       "output_type": "pyout",

-       "prompt_number": 26,

-       "text": [

-        "         fixed acidity  volatile acidity  citric acid  residual sugar  \\\n",

-        "quality                                                                 \n",

-        "3             8.360000          0.884500     0.171000        2.635000   \n",

-        "4             7.779245          0.693962     0.174151        2.694340   \n",

-        "5             8.167254          0.577041     0.243686        2.528855   \n",

-        "6             8.347179          0.497484     0.273824        2.477194   \n",

-        "7             8.872362          0.403920     0.375176        2.720603   \n",

-        "8             8.566667          0.423333     0.391111        2.577778   \n",

-        "\n",

-        "         chlorides  free sulfur dioxide  total sulfur dioxide   density  \\\n",

-        "quality                                                                   \n",

-        "3         0.122500            11.000000             24.900000  0.997464   \n",

-        "4         0.090679            12.264151             36.245283  0.996542   \n",

-        "5         0.092736            16.983847             56.513950  0.997104   \n",

-        "6         0.084956            15.711599             40.869906  0.996615   \n",

-        "7         0.076588            14.045226             35.020101  0.996104   \n",

-        "8         0.068444            13.277778             33.444444  0.995212   \n",

-        "\n",

-        "               pH  sulphates    alcohol  \n",

-        "quality                                  \n",

-        "3        3.398000   0.570000   9.955000  \n",

-        "4        3.381509   0.596415  10.265094  \n",

-        "5        3.304949   0.620969   9.899706  \n",

-        "6        3.318072   0.675329  10.629519  \n",

-        "7        3.290754   0.741256  11.465913  \n",

-        "8        3.267222   0.767778  12.094444  "

-       ]

-      }

-     ],

-     "prompt_number": 26

-    },

-    {

-     "cell_type": "code",

-     "collapsed": false,

-     "input": [

-      "# Let's go back to the original dframe\n",

-      "dframe_wine.head()"

-     ],

-     "language": "python",

-     "metadata": {},

-     "outputs": [

-      {

-       "html": [

-        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",

-        "<table border=\"1\" class=\"dataframe\">\n",

-        "  <thead>\n",

-        "    <tr style=\"text-align: right;\">\n",

-        "      <th></th>\n",

-        "      <th>fixed acidity</th>\n",

-        "      <th>volatile acidity</th>\n",

-        "      <th>citric acid</th>\n",

-        "      <th>residual sugar</th>\n",

-        "      <th>chlorides</th>\n",

-        "      <th>free sulfur dioxide</th>\n",

-        "      <th>total sulfur dioxide</th>\n",

-        "      <th>density</th>\n",

-        "      <th>pH</th>\n",

-        "      <th>sulphates</th>\n",

-        "      <th>alcohol</th>\n",

-        "      <th>quality</th>\n",

-        "    </tr>\n",

-        "  </thead>\n",

-        "  <tbody>\n",

-        "    <tr>\n",

-        "      <th>0</th>\n",

-        "      <td>  7.4</td>\n",

-        "      <td> 0.70</td>\n",

-        "      <td> 0.00</td>\n",

-        "      <td> 1.9</td>\n",

-        "      <td> 0.076</td>\n",

-        "      <td> 11</td>\n",

-        "      <td> 34</td>\n",

-        "      <td> 0.9978</td>\n",

-        "      <td> 3.51</td>\n",

-        "      <td> 0.56</td>\n",

-        "      <td> 9.4</td>\n",

-        "      <td> 5</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>1</th>\n",

-        "      <td>  7.8</td>\n",

-        "      <td> 0.88</td>\n",

-        "      <td> 0.00</td>\n",

-        "      <td> 2.6</td>\n",

-        "      <td> 0.098</td>\n",

-        "      <td> 25</td>\n",

-        "      <td> 67</td>\n",

-        "      <td> 0.9968</td>\n",

-        "      <td> 3.20</td>\n",

-        "      <td> 0.68</td>\n",

-        "      <td> 9.8</td>\n",

-        "      <td> 5</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>2</th>\n",

-        "      <td>  7.8</td>\n",

-        "      <td> 0.76</td>\n",

-        "      <td> 0.04</td>\n",

-        "      <td> 2.3</td>\n",

-        "      <td> 0.092</td>\n",

-        "      <td> 15</td>\n",

-        "      <td> 54</td>\n",

-        "      <td> 0.9970</td>\n",

-        "      <td> 3.26</td>\n",

-        "      <td> 0.65</td>\n",

-        "      <td> 9.8</td>\n",

-        "      <td> 5</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>3</th>\n",

-        "      <td> 11.2</td>\n",

-        "      <td> 0.28</td>\n",

-        "      <td> 0.56</td>\n",

-        "      <td> 1.9</td>\n",

-        "      <td> 0.075</td>\n",

-        "      <td> 17</td>\n",

-        "      <td> 60</td>\n",

-        "      <td> 0.9980</td>\n",

-        "      <td> 3.16</td>\n",

-        "      <td> 0.58</td>\n",

-        "      <td> 9.8</td>\n",

-        "      <td> 6</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>4</th>\n",

-        "      <td>  7.4</td>\n",

-        "      <td> 0.70</td>\n",

-        "      <td> 0.00</td>\n",

-        "      <td> 1.9</td>\n",

-        "      <td> 0.076</td>\n",

-        "      <td> 11</td>\n",

-        "      <td> 34</td>\n",

-        "      <td> 0.9978</td>\n",

-        "      <td> 3.51</td>\n",

-        "      <td> 0.56</td>\n",

-        "      <td> 9.4</td>\n",

-        "      <td> 5</td>\n",

-        "    </tr>\n",

-        "  </tbody>\n",

-        "</table>\n",

-        "</div>"

-       ],

-       "metadata": {},

-       "output_type": "pyout",

-       "prompt_number": 27,

-       "text": [

-        "   fixed acidity  volatile acidity  citric acid  residual sugar  chlorides  \\\n",

-        "0            7.4              0.70         0.00             1.9      0.076   \n",

-        "1            7.8              0.88         0.00             2.6      0.098   \n",

-        "2            7.8              0.76         0.04             2.3      0.092   \n",

-        "3           11.2              0.28         0.56             1.9      0.075   \n",

-        "4            7.4              0.70         0.00             1.9      0.076   \n",

-        "\n",

-        "   free sulfur dioxide  total sulfur dioxide  density    pH  sulphates  \\\n",

-        "0                   11                    34   0.9978  3.51       0.56   \n",

-        "1                   25                    67   0.9968  3.20       0.68   \n",

-        "2                   15                    54   0.9970  3.26       0.65   \n",

-        "3                   17                    60   0.9980  3.16       0.58   \n",

-        "4                   11                    34   0.9978  3.51       0.56   \n",

-        "\n",

-        "   alcohol  quality  \n",

-        "0      9.4        5  \n",

-        "1      9.8        5  \n",

-        "2      9.8        5  \n",

-        "3      9.8        6  \n",

-        "4      9.4        5  "

-       ]

-      }

-     ],

-     "prompt_number": 27

-    },

-    {

-     "cell_type": "code",

-     "collapsed": false,

-     "input": [

-      "# Let's adda  quality to alcohol content ratio\n",

-      "dframe_wine['qual/alc ratio'] = dframe_wine['quality']/dframe_wine['alcohol']"

-     ],

-     "language": "python",

-     "metadata": {},

-     "outputs": [],

-     "prompt_number": 28

-    },

-    {

-     "cell_type": "code",

-     "collapsed": false,

-     "input": [

-      "# Show\n",

-      "dframe_wine.head()"

-     ],

-     "language": "python",

-     "metadata": {},

-     "outputs": [

-      {

-       "html": [

-        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",

-        "<table border=\"1\" class=\"dataframe\">\n",

-        "  <thead>\n",

-        "    <tr style=\"text-align: right;\">\n",

-        "      <th></th>\n",

-        "      <th>fixed acidity</th>\n",

-        "      <th>volatile acidity</th>\n",

-        "      <th>citric acid</th>\n",

-        "      <th>residual sugar</th>\n",

-        "      <th>chlorides</th>\n",

-        "      <th>free sulfur dioxide</th>\n",

-        "      <th>total sulfur dioxide</th>\n",

-        "      <th>density</th>\n",

-        "      <th>pH</th>\n",

-        "      <th>sulphates</th>\n",

-        "      <th>alcohol</th>\n",

-        "      <th>quality</th>\n",

-        "      <th>qual/alc ratio</th>\n",

-        "    </tr>\n",

-        "  </thead>\n",

-        "  <tbody>\n",

-        "    <tr>\n",

-        "      <th>0</th>\n",

-        "      <td>  7.4</td>\n",

-        "      <td> 0.70</td>\n",

-        "      <td> 0.00</td>\n",

-        "      <td> 1.9</td>\n",

-        "      <td> 0.076</td>\n",

-        "      <td> 11</td>\n",

-        "      <td> 34</td>\n",

-        "      <td> 0.9978</td>\n",

-        "      <td> 3.51</td>\n",

-        "      <td> 0.56</td>\n",

-        "      <td> 9.4</td>\n",

-        "      <td> 5</td>\n",

-        "      <td> 0.531915</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>1</th>\n",

-        "      <td>  7.8</td>\n",

-        "      <td> 0.88</td>\n",

-        "      <td> 0.00</td>\n",

-        "      <td> 2.6</td>\n",

-        "      <td> 0.098</td>\n",

-        "      <td> 25</td>\n",

-        "      <td> 67</td>\n",

-        "      <td> 0.9968</td>\n",

-        "      <td> 3.20</td>\n",

-        "      <td> 0.68</td>\n",

-        "      <td> 9.8</td>\n",

-        "      <td> 5</td>\n",

-        "      <td> 0.510204</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>2</th>\n",

-        "      <td>  7.8</td>\n",

-        "      <td> 0.76</td>\n",

-        "      <td> 0.04</td>\n",

-        "      <td> 2.3</td>\n",

-        "      <td> 0.092</td>\n",

-        "      <td> 15</td>\n",

-        "      <td> 54</td>\n",

-        "      <td> 0.9970</td>\n",

-        "      <td> 3.26</td>\n",

-        "      <td> 0.65</td>\n",

-        "      <td> 9.8</td>\n",

-        "      <td> 5</td>\n",

-        "      <td> 0.510204</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>3</th>\n",

-        "      <td> 11.2</td>\n",

-        "      <td> 0.28</td>\n",

-        "      <td> 0.56</td>\n",

-        "      <td> 1.9</td>\n",

-        "      <td> 0.075</td>\n",

-        "      <td> 17</td>\n",

-        "      <td> 60</td>\n",

-        "      <td> 0.9980</td>\n",

-        "      <td> 3.16</td>\n",

-        "      <td> 0.58</td>\n",

-        "      <td> 9.8</td>\n",

-        "      <td> 6</td>\n",

-        "      <td> 0.612245</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>4</th>\n",

-        "      <td>  7.4</td>\n",

-        "      <td> 0.70</td>\n",

-        "      <td> 0.00</td>\n",

-        "      <td> 1.9</td>\n",

-        "      <td> 0.076</td>\n",

-        "      <td> 11</td>\n",

-        "      <td> 34</td>\n",

-        "      <td> 0.9978</td>\n",

-        "      <td> 3.51</td>\n",

-        "      <td> 0.56</td>\n",

-        "      <td> 9.4</td>\n",

-        "      <td> 5</td>\n",

-        "      <td> 0.531915</td>\n",

-        "    </tr>\n",

-        "  </tbody>\n",

-        "</table>\n",

-        "</div>"

-       ],

-       "metadata": {},

-       "output_type": "pyout",

-       "prompt_number": 29,

-       "text": [

-        "   fixed acidity  volatile acidity  citric acid  residual sugar  chlorides  \\\n",

-        "0            7.4              0.70         0.00             1.9      0.076   \n",

-        "1            7.8              0.88         0.00             2.6      0.098   \n",

-        "2            7.8              0.76         0.04             2.3      0.092   \n",

-        "3           11.2              0.28         0.56             1.9      0.075   \n",

-        "4            7.4              0.70         0.00             1.9      0.076   \n",

-        "\n",

-        "   free sulfur dioxide  total sulfur dioxide  density    pH  sulphates  \\\n",

-        "0                   11                    34   0.9978  3.51       0.56   \n",

-        "1                   25                    67   0.9968  3.20       0.68   \n",

-        "2                   15                    54   0.9970  3.26       0.65   \n",

-        "3                   17                    60   0.9980  3.16       0.58   \n",

-        "4                   11                    34   0.9978  3.51       0.56   \n",

-        "\n",

-        "   alcohol  quality  qual/alc ratio  \n",

-        "0      9.4        5        0.531915  \n",

-        "1      9.8        5        0.510204  \n",

-        "2      9.8        5        0.510204  \n",

-        "3      9.8        6        0.612245  \n",

-        "4      9.4        5        0.531915  "

-       ]

-      }

-     ],

-     "prompt_number": 29

-    },

-    {

-     "cell_type": "code",

-     "collapsed": false,

-     "input": [

-      "# WE can also use pivot tables instead of groupby\n",

-      "\n",

-      "# Pivot table of quality\n",

-      "dframe_wine.pivot_table(index=['quality'])"

-     ],

-     "language": "python",

-     "metadata": {},

-     "outputs": [

-      {

-       "html": [

-        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",

-        "<table border=\"1\" class=\"dataframe\">\n",

-        "  <thead>\n",

-        "    <tr style=\"text-align: right;\">\n",

-        "      <th></th>\n",

-        "      <th>alcohol</th>\n",

-        "      <th>chlorides</th>\n",

-        "      <th>citric acid</th>\n",

-        "      <th>density</th>\n",

-        "      <th>fixed acidity</th>\n",

-        "      <th>free sulfur dioxide</th>\n",

-        "      <th>pH</th>\n",

-        "      <th>qual/alc ratio</th>\n",

-        "      <th>residual sugar</th>\n",

-        "      <th>sulphates</th>\n",

-        "      <th>total sulfur dioxide</th>\n",

-        "      <th>volatile acidity</th>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>quality</th>\n",

-        "      <th></th>\n",

-        "      <th></th>\n",

-        "      <th></th>\n",

-        "      <th></th>\n",

-        "      <th></th>\n",

-        "      <th></th>\n",

-        "      <th></th>\n",

-        "      <th></th>\n",

-        "      <th></th>\n",

-        "      <th></th>\n",

-        "      <th></th>\n",

-        "      <th></th>\n",

-        "    </tr>\n",

-        "  </thead>\n",

-        "  <tbody>\n",

-        "    <tr>\n",

-        "      <th>3</th>\n",

-        "      <td>  9.955000</td>\n",

-        "      <td> 0.122500</td>\n",

-        "      <td> 0.171000</td>\n",

-        "      <td> 0.997464</td>\n",

-        "      <td> 8.360000</td>\n",

-        "      <td> 11.000000</td>\n",

-        "      <td> 3.398000</td>\n",

-        "      <td> 0.303286</td>\n",

-        "      <td> 2.635000</td>\n",

-        "      <td> 0.570000</td>\n",

-        "      <td> 24.900000</td>\n",

-        "      <td> 0.884500</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>4</th>\n",

-        "      <td> 10.265094</td>\n",

-        "      <td> 0.090679</td>\n",

-        "      <td> 0.174151</td>\n",

-        "      <td> 0.996542</td>\n",

-        "      <td> 7.779245</td>\n",

-        "      <td> 12.264151</td>\n",

-        "      <td> 3.381509</td>\n",

-        "      <td> 0.392724</td>\n",

-        "      <td> 2.694340</td>\n",

-        "      <td> 0.596415</td>\n",

-        "      <td> 36.245283</td>\n",

-        "      <td> 0.693962</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>5</th>\n",

-        "      <td>  9.899706</td>\n",

-        "      <td> 0.092736</td>\n",

-        "      <td> 0.243686</td>\n",

-        "      <td> 0.997104</td>\n",

-        "      <td> 8.167254</td>\n",

-        "      <td> 16.983847</td>\n",

-        "      <td> 3.304949</td>\n",

-        "      <td> 0.507573</td>\n",

-        "      <td> 2.528855</td>\n",

-        "      <td> 0.620969</td>\n",

-        "      <td> 56.513950</td>\n",

-        "      <td> 0.577041</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>6</th>\n",

-        "      <td> 10.629519</td>\n",

-        "      <td> 0.084956</td>\n",

-        "      <td> 0.273824</td>\n",

-        "      <td> 0.996615</td>\n",

-        "      <td> 8.347179</td>\n",

-        "      <td> 15.711599</td>\n",

-        "      <td> 3.318072</td>\n",

-        "      <td> 0.569801</td>\n",

-        "      <td> 2.477194</td>\n",

-        "      <td> 0.675329</td>\n",

-        "      <td> 40.869906</td>\n",

-        "      <td> 0.497484</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>7</th>\n",

-        "      <td> 11.465913</td>\n",

-        "      <td> 0.076588</td>\n",

-        "      <td> 0.375176</td>\n",

-        "      <td> 0.996104</td>\n",

-        "      <td> 8.872362</td>\n",

-        "      <td> 14.045226</td>\n",

-        "      <td> 3.290754</td>\n",

-        "      <td> 0.614855</td>\n",

-        "      <td> 2.720603</td>\n",

-        "      <td> 0.741256</td>\n",

-        "      <td> 35.020101</td>\n",

-        "      <td> 0.403920</td>\n",

-        "    </tr>\n",

-        "    <tr>\n",

-        "      <th>8</th>\n",

-        "      <td> 12.094444</td>\n",

-        "      <td> 0.068444</td>\n",

-        "      <td> 0.391111</td>\n",

-        "      <td> 0.995212</td>\n",

-        "      <td> 8.566667</td>\n",

-        "      <td> 13.277778</td>\n",

-        "      <td> 3.267222</td>\n",

-        "      <td> 0.668146</td>\n",

-        "      <td> 2.577778</td>\n",

-        "      <td> 0.767778</td>\n",

-        "      <td> 33.444444</td>\n",

-        "      <td> 0.423333</td>\n",

-        "    </tr>\n",

-        "  </tbody>\n",

-        "</table>\n",

-        "</div>"

-       ],

-       "metadata": {},

-       "output_type": "pyout",

-       "prompt_number": 32,

-       "text": [

-        "           alcohol  chlorides  citric acid   density  fixed acidity  \\\n",

-        "quality                                                               \n",

-        "3         9.955000   0.122500     0.171000  0.997464       8.360000   \n",

-        "4        10.265094   0.090679     0.174151  0.996542       7.779245   \n",

-        "5         9.899706   0.092736     0.243686  0.997104       8.167254   \n",

-        "6        10.629519   0.084956     0.273824  0.996615       8.347179   \n",

-        "7        11.465913   0.076588     0.375176  0.996104       8.872362   \n",

-        "8        12.094444   0.068444     0.391111  0.995212       8.566667   \n",

-        "\n",

-        "         free sulfur dioxide        pH  qual/alc ratio  residual sugar  \\\n",

-        "quality                                                                  \n",

-        "3                  11.000000  3.398000        0.303286        2.635000   \n",

-        "4                  12.264151  3.381509        0.392724        2.694340   \n",

-        "5                  16.983847  3.304949        0.507573        2.528855   \n",

-        "6                  15.711599  3.318072        0.569801        2.477194   \n",

-        "7                  14.045226  3.290754        0.614855        2.720603   \n",

-        "8                  13.277778  3.267222        0.668146        2.577778   \n",

-        "\n",

-        "         sulphates  total sulfur dioxide  volatile acidity  \n",

-        "quality                                                     \n",

-        "3         0.570000             24.900000          0.884500  \n",

-        "4         0.596415             36.245283          0.693962  \n",

-        "5         0.620969             56.513950          0.577041  \n",

-        "6         0.675329             40.869906          0.497484  \n",

-        "7         0.741256             35.020101          0.403920  \n",

-        "8         0.767778             33.444444          0.423333  "

-       ]

-      }

-     ],

-     "prompt_number": 32

-    },

-    {

-     "cell_type": "code",

-     "collapsed": false,

-     "input": [

-      "%matplotlib inline\n",

-      "dframe_wine.plot(kind='scatter',x='quality',y='alcohol')"

-     ],

-     "language": "python",

-     "metadata": {},

-     "outputs": [

-      {

-       "metadata": {},

-       "output_type": "pyout",

-       "prompt_number": 38,

-       "text": [

-        "<matplotlib.axes._subplots.AxesSubplot at 0xecb6470>"

-       ]

-      },

-      {

-       "metadata": {},

-       "output_type": "display_data",

-       "png": "iVBORw0KGgoAAAANSUhEUgAAAX0AAAEPCAYAAACukxSbAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\naohP+s45V0N80nfOuRry/wEBAmAaegSRYQAAAABJRU5ErkJggg==\n",

-       "text": [

-        "<matplotlib.figure.Figure at 0xabda588>"

-       ]

-      }

-     ],

-     "prompt_number": 38

-    },

-    {

-     "cell_type": "markdown",

-     "metadata": {},

-     "source": [

-      "We can see that the data is probably better fit for a box plot for a more concise view of the data\n",

-      "See if you can figure how to get a boxplot using the pandas documentation and what you have learned so far\n",

-      "\n",

-      "Don't worry if you can't quite figure it out just yet, the next section will cover all sorts of data visualizations!"

-     ]

-    },

-    {

-     "cell_type": "code",

-     "collapsed": false,

-     "input": [],

-     "language": "python",

-     "metadata": {},

-     "outputs": []

-    }

-   ],

-   "metadata": {}

-  }

- ]

-}
\ No newline at end of file
+{
+
+ "metadata": {
+
+  "name": "",
+
+  "signature": "sha256:e15f796c810b6782ee8033e188d97395fb0602eeee010c7ad5f94bec363fe48c"
+
+ },
+
+ "nbformat": 3,
+
+ "nbformat_minor": 0,
+
+ "worksheets": [
+
+  {
+
+   "cells": [
+
+    {
+
+     "cell_type": "code",
+
+     "collapsed": false,
+
+     "input": [
+
+      "import numpy as np\n",
+
+      "import pandas as pd\n",
+
+      "from pandas import Series,DataFrame"
+
+     ],
+
+     "language": "python",
+
+     "metadata": {},
+
+     "outputs": [],
+
+     "prompt_number": 1
+
+    },
+
+    {
+
+     "cell_type": "code",
+
+     "collapsed": false,
+
+     "input": [
+
+      "# Data Agrregation consists of operations that result in a scalar (e.g. mean(),sum(),count(), etc)\n",
+
+      "\n",
+
+      "#Let's get a csv data set to play with\n",
+
+      "url = 'http://archive.ics.uci.edu/ml/machine-learning-databases/wine-quality/'\n",
+
+      "\n",
+
+      "\n",
+
+      "# Save thewinquality.csv file in the same folder as your ipython notebooks, note the delimiter used ;\n",
+
+      "dframe_wine = pd.read_csv('winequality_red.csv',sep=';')"
+
+     ],
+
+     "language": "python",
+
+     "metadata": {},
+
+     "outputs": [],
+
+     "prompt_number": 6
+
+    },
+
+    {
+
+     "cell_type": "code",
+
+     "collapsed": false,
+
+     "input": [
+
+      "# Let's get a preview\n",
+
+      "dframe_wine.head()"
+
+     ],
+
+     "language": "python",
+
+     "metadata": {},
+
+     "outputs": [
+
+      {
+
+       "html": [
+
+        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
+
+        "<table border=\"1\" class=\"dataframe\">\n",
+
+        "  <thead>\n",
+
+        "    <tr style=\"text-align: right;\">\n",
+
+        "      <th></th>\n",
+
+        "      <th>fixed acidity</th>\n",
+
+        "      <th>volatile acidity</th>\n",
+
+        "      <th>citric acid</th>\n",
+
+        "      <th>residual sugar</th>\n",
+
+        "      <th>chlorides</th>\n",
+
+        "      <th>free sulfur dioxide</th>\n",
+
+        "      <th>total sulfur dioxide</th>\n",
+
+        "      <th>density</th>\n",
+
+        "      <th>pH</th>\n",
+
+        "      <th>sulphates</th>\n",
+
+        "      <th>alcohol</th>\n",
+
+        "      <th>quality</th>\n",
+
+        "    </tr>\n",
+
+        "  </thead>\n",
+
+        "  <tbody>\n",
+
+        "    <tr>\n",
+
+        "      <th>0</th>\n",
+
+        "      <td>  7.4</td>\n",
+
+        "      <td> 0.70</td>\n",
+
+        "      <td> 0.00</td>\n",
+
+        "      <td> 1.9</td>\n",
+
+        "      <td> 0.076</td>\n",
+
+        "      <td> 11</td>\n",
+
+        "      <td> 34</td>\n",
+
+        "      <td> 0.9978</td>\n",
+
+        "      <td> 3.51</td>\n",
+
+        "      <td> 0.56</td>\n",
+
+        "      <td> 9.4</td>\n",
+
+        "      <td> 5</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>1</th>\n",
+
+        "      <td>  7.8</td>\n",
+
+        "      <td> 0.88</td>\n",
+
+        "      <td> 0.00</td>\n",
+
+        "      <td> 2.6</td>\n",
+
+        "      <td> 0.098</td>\n",
+
+        "      <td> 25</td>\n",
+
+        "      <td> 67</td>\n",
+
+        "      <td> 0.9968</td>\n",
+
+        "      <td> 3.20</td>\n",
+
+        "      <td> 0.68</td>\n",
+
+        "      <td> 9.8</td>\n",
+
+        "      <td> 5</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>2</th>\n",
+
+        "      <td>  7.8</td>\n",
+
+        "      <td> 0.76</td>\n",
+
+        "      <td> 0.04</td>\n",
+
+        "      <td> 2.3</td>\n",
+
+        "      <td> 0.092</td>\n",
+
+        "      <td> 15</td>\n",
+
+        "      <td> 54</td>\n",
+
+        "      <td> 0.9970</td>\n",
+
+        "      <td> 3.26</td>\n",
+
+        "      <td> 0.65</td>\n",
+
+        "      <td> 9.8</td>\n",
+
+        "      <td> 5</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>3</th>\n",
+
+        "      <td> 11.2</td>\n",
+
+        "      <td> 0.28</td>\n",
+
+        "      <td> 0.56</td>\n",
+
+        "      <td> 1.9</td>\n",
+
+        "      <td> 0.075</td>\n",
+
+        "      <td> 17</td>\n",
+
+        "      <td> 60</td>\n",
+
+        "      <td> 0.9980</td>\n",
+
+        "      <td> 3.16</td>\n",
+
+        "      <td> 0.58</td>\n",
+
+        "      <td> 9.8</td>\n",
+
+        "      <td> 6</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>4</th>\n",
+
+        "      <td>  7.4</td>\n",
+
+        "      <td> 0.70</td>\n",
+
+        "      <td> 0.00</td>\n",
+
+        "      <td> 1.9</td>\n",
+
+        "      <td> 0.076</td>\n",
+
+        "      <td> 11</td>\n",
+
+        "      <td> 34</td>\n",
+
+        "      <td> 0.9978</td>\n",
+
+        "      <td> 3.51</td>\n",
+
+        "      <td> 0.56</td>\n",
+
+        "      <td> 9.4</td>\n",
+
+        "      <td> 5</td>\n",
+
+        "    </tr>\n",
+
+        "  </tbody>\n",
+
+        "</table>\n",
+
+        "</div>"
+
+       ],
+
+       "metadata": {},
+
+       "output_type": "pyout",
+
+       "prompt_number": 7,
+
+       "text": [
+
+        "   fixed acidity  volatile acidity  citric acid  residual sugar  chlorides  \\\n",
+
+        "0            7.4              0.70         0.00             1.9      0.076   \n",
+
+        "1            7.8              0.88         0.00             2.6      0.098   \n",
+
+        "2            7.8              0.76         0.04             2.3      0.092   \n",
+
+        "3           11.2              0.28         0.56             1.9      0.075   \n",
+
+        "4            7.4              0.70         0.00             1.9      0.076   \n",
+
+        "\n",
+
+        "   free sulfur dioxide  total sulfur dioxide  density    pH  sulphates  \\\n",
+
+        "0                   11                    34   0.9978  3.51       0.56   \n",
+
+        "1                   25                    67   0.9968  3.20       0.68   \n",
+
+        "2                   15                    54   0.9970  3.26       0.65   \n",
+
+        "3                   17                    60   0.9980  3.16       0.58   \n",
+
+        "4                   11                    34   0.9978  3.51       0.56   \n",
+
+        "\n",
+
+        "   alcohol  quality  \n",
+
+        "0      9.4        5  \n",
+
+        "1      9.8        5  \n",
+
+        "2      9.8        5  \n",
+
+        "3      9.8        6  \n",
+
+        "4      9.4        5  "
+
+       ]
+
+      }
+
+     ],
+
+     "prompt_number": 7
+
+    },
+
+    {
+
+     "cell_type": "code",
+
+     "collapsed": false,
+
+     "input": [
+
+      "# How about we find out the average alcohol content for the wine\n",
+
+      "dframe_wine['alcohol'].mean()"
+
+     ],
+
+     "language": "python",
+
+     "metadata": {},
+
+     "outputs": [
+
+      {
+
+       "metadata": {},
+
+       "output_type": "pyout",
+
+       "prompt_number": 8,
+
+       "text": [
+
+        "10.422983114446529"
+
+       ]
+
+      }
+
+     ],
+
+     "prompt_number": 8
+
+    },
+
+    {
+
+     "cell_type": "code",
+
+     "collapsed": false,
+
+     "input": [
+
+      "# That was an example of an aggregate, how about we make our own?\n",
+
+      "def max_to_min(arr):\n",
+
+      "    return arr.max() - arr.min()\n",
+
+      "\n",
+
+      "# Let's group the wines by \"quality\"\n",
+
+      "wino = dframe_wine.groupby('quality')\n",
+
+      "\n",
+
+      "# Show\n",
+
+      "wino.describe()"
+
+     ],
+
+     "language": "python",
+
+     "metadata": {},
+
+     "outputs": [
+
+      {
+
+       "html": [
+
+        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
+
+        "<table border=\"1\" class=\"dataframe\">\n",
+
+        "  <thead>\n",
+
+        "    <tr style=\"text-align: right;\">\n",
+
+        "      <th></th>\n",
+
+        "      <th></th>\n",
+
+        "      <th>alcohol</th>\n",
+
+        "      <th>chlorides</th>\n",
+
+        "      <th>citric acid</th>\n",
+
+        "      <th>density</th>\n",
+
+        "      <th>fixed acidity</th>\n",
+
+        "      <th>free sulfur dioxide</th>\n",
+
+        "      <th>pH</th>\n",
+
+        "      <th>residual sugar</th>\n",
+
+        "      <th>sulphates</th>\n",
+
+        "      <th>total sulfur dioxide</th>\n",
+
+        "      <th>volatile acidity</th>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>quality</th>\n",
+
+        "      <th></th>\n",
+
+        "      <th></th>\n",
+
+        "      <th></th>\n",
+
+        "      <th></th>\n",
+
+        "      <th></th>\n",
+
+        "      <th></th>\n",
+
+        "      <th></th>\n",
+
+        "      <th></th>\n",
+
+        "      <th></th>\n",
+
+        "      <th></th>\n",
+
+        "      <th></th>\n",
+
+        "      <th></th>\n",
+
+        "    </tr>\n",
+
+        "  </thead>\n",
+
+        "  <tbody>\n",
+
+        "    <tr>\n",
+
+        "      <th rowspan=\"8\" valign=\"top\">3</th>\n",
+
+        "      <th>count</th>\n",
+
+        "      <td>  10.000000</td>\n",
+
+        "      <td>  10.000000</td>\n",
+
+        "      <td>  10.000000</td>\n",
+
+        "      <td>  10.000000</td>\n",
+
+        "      <td>  10.000000</td>\n",
+
+        "      <td>  10.000000</td>\n",
+
+        "      <td>  10.000000</td>\n",
+
+        "      <td>  10.000000</td>\n",
+
+        "      <td>  10.000000</td>\n",
+
+        "      <td>  10.000000</td>\n",
+
+        "      <td>  10.000000</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>mean</th>\n",
+
+        "      <td>   9.955000</td>\n",
+
+        "      <td>   0.122500</td>\n",
+
+        "      <td>   0.171000</td>\n",
+
+        "      <td>   0.997464</td>\n",
+
+        "      <td>   8.360000</td>\n",
+
+        "      <td>  11.000000</td>\n",
+
+        "      <td>   3.398000</td>\n",
+
+        "      <td>   2.635000</td>\n",
+
+        "      <td>   0.570000</td>\n",
+
+        "      <td>  24.900000</td>\n",
+
+        "      <td>   0.884500</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>std</th>\n",
+
+        "      <td>   0.818009</td>\n",
+
+        "      <td>   0.066241</td>\n",
+
+        "      <td>   0.250664</td>\n",
+
+        "      <td>   0.002002</td>\n",
+
+        "      <td>   1.770875</td>\n",
+
+        "      <td>   9.763879</td>\n",
+
+        "      <td>   0.144052</td>\n",
+
+        "      <td>   1.401596</td>\n",
+
+        "      <td>   0.122020</td>\n",
+
+        "      <td>  16.828877</td>\n",
+
+        "      <td>   0.331256</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>min</th>\n",
+
+        "      <td>   8.400000</td>\n",
+
+        "      <td>   0.061000</td>\n",
+
+        "      <td>   0.000000</td>\n",
+
+        "      <td>   0.994710</td>\n",
+
+        "      <td>   6.700000</td>\n",
+
+        "      <td>   3.000000</td>\n",
+
+        "      <td>   3.160000</td>\n",
+
+        "      <td>   1.200000</td>\n",
+
+        "      <td>   0.400000</td>\n",
+
+        "      <td>   9.000000</td>\n",
+
+        "      <td>   0.440000</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>25%</th>\n",
+
+        "      <td>   9.725000</td>\n",
+
+        "      <td>   0.079000</td>\n",
+
+        "      <td>   0.005000</td>\n",
+
+        "      <td>   0.996150</td>\n",
+
+        "      <td>   7.150000</td>\n",
+
+        "      <td>   5.000000</td>\n",
+
+        "      <td>   3.312500</td>\n",
+
+        "      <td>   1.875000</td>\n",
+
+        "      <td>   0.512500</td>\n",
+
+        "      <td>  12.500000</td>\n",
+
+        "      <td>   0.647500</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>50%</th>\n",
+
+        "      <td>   9.925000</td>\n",
+
+        "      <td>   0.090500</td>\n",
+
+        "      <td>   0.035000</td>\n",
+
+        "      <td>   0.997565</td>\n",
+
+        "      <td>   7.500000</td>\n",
+
+        "      <td>   6.000000</td>\n",
+
+        "      <td>   3.390000</td>\n",
+
+        "      <td>   2.100000</td>\n",
+
+        "      <td>   0.545000</td>\n",
+
+        "      <td>  15.000000</td>\n",
+
+        "      <td>   0.845000</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>75%</th>\n",
+
+        "      <td>  10.575000</td>\n",
+
+        "      <td>   0.143000</td>\n",
+
+        "      <td>   0.327500</td>\n",
+
+        "      <td>   0.998770</td>\n",
+
+        "      <td>   9.875000</td>\n",
+
+        "      <td>  14.500000</td>\n",
+
+        "      <td>   3.495000</td>\n",
+
+        "      <td>   3.100000</td>\n",
+
+        "      <td>   0.615000</td>\n",
+
+        "      <td>  42.500000</td>\n",
+
+        "      <td>   1.010000</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>max</th>\n",
+
+        "      <td>  11.000000</td>\n",
+
+        "      <td>   0.267000</td>\n",
+
+        "      <td>   0.660000</td>\n",
+
+        "      <td>   1.000800</td>\n",
+
+        "      <td>  11.600000</td>\n",
+
+        "      <td>  34.000000</td>\n",
+
+        "      <td>   3.630000</td>\n",
+
+        "      <td>   5.700000</td>\n",
+
+        "      <td>   0.860000</td>\n",
+
+        "      <td>  49.000000</td>\n",
+
+        "      <td>   1.580000</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th rowspan=\"8\" valign=\"top\">4</th>\n",
+
+        "      <th>count</th>\n",
+
+        "      <td>  53.000000</td>\n",
+
+        "      <td>  53.000000</td>\n",
+
+        "      <td>  53.000000</td>\n",
+
+        "      <td>  53.000000</td>\n",
+
+        "      <td>  53.000000</td>\n",
+
+        "      <td>  53.000000</td>\n",
+
+        "      <td>  53.000000</td>\n",
+
+        "      <td>  53.000000</td>\n",
+
+        "      <td>  53.000000</td>\n",
+
+        "      <td>  53.000000</td>\n",
+
+        "      <td>  53.000000</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>mean</th>\n",
+
+        "      <td>  10.265094</td>\n",
+
+        "      <td>   0.090679</td>\n",
+
+        "      <td>   0.174151</td>\n",
+
+        "      <td>   0.996542</td>\n",
+
+        "      <td>   7.779245</td>\n",
+
+        "      <td>  12.264151</td>\n",
+
+        "      <td>   3.381509</td>\n",
+
+        "      <td>   2.694340</td>\n",
+
+        "      <td>   0.596415</td>\n",
+
+        "      <td>  36.245283</td>\n",
+
+        "      <td>   0.693962</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>std</th>\n",
+
+        "      <td>   0.934776</td>\n",
+
+        "      <td>   0.076192</td>\n",
+
+        "      <td>   0.201030</td>\n",
+
+        "      <td>   0.001575</td>\n",
+
+        "      <td>   1.626624</td>\n",
+
+        "      <td>   9.025926</td>\n",
+
+        "      <td>   0.181441</td>\n",
+
+        "      <td>   1.789436</td>\n",
+
+        "      <td>   0.239391</td>\n",
+
+        "      <td>  27.583374</td>\n",
+
+        "      <td>   0.220110</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>min</th>\n",
+
+        "      <td>   9.000000</td>\n",
+
+        "      <td>   0.045000</td>\n",
+
+        "      <td>   0.000000</td>\n",
+
+        "      <td>   0.993400</td>\n",
+
+        "      <td>   4.600000</td>\n",
+
+        "      <td>   3.000000</td>\n",
+
+        "      <td>   2.740000</td>\n",
+
+        "      <td>   1.300000</td>\n",
+
+        "      <td>   0.330000</td>\n",
+
+        "      <td>   7.000000</td>\n",
+
+        "      <td>   0.230000</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>25%</th>\n",
+
+        "      <td>   9.600000</td>\n",
+
+        "      <td>   0.067000</td>\n",
+
+        "      <td>   0.030000</td>\n",
+
+        "      <td>   0.995650</td>\n",
+
+        "      <td>   6.800000</td>\n",
+
+        "      <td>   6.000000</td>\n",
+
+        "      <td>   3.300000</td>\n",
+
+        "      <td>   1.900000</td>\n",
+
+        "      <td>   0.490000</td>\n",
+
+        "      <td>  14.000000</td>\n",
+
+        "      <td>   0.530000</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>50%</th>\n",
+
+        "      <td>  10.000000</td>\n",
+
+        "      <td>   0.080000</td>\n",
+
+        "      <td>   0.090000</td>\n",
+
+        "      <td>   0.996500</td>\n",
+
+        "      <td>   7.500000</td>\n",
+
+        "      <td>  11.000000</td>\n",
+
+        "      <td>   3.370000</td>\n",
+
+        "      <td>   2.100000</td>\n",
+
+        "      <td>   0.560000</td>\n",
+
+        "      <td>  26.000000</td>\n",
+
+        "      <td>   0.670000</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>75%</th>\n",
+
+        "      <td>  11.000000</td>\n",
+
+        "      <td>   0.089000</td>\n",
+
+        "      <td>   0.270000</td>\n",
+
+        "      <td>   0.997450</td>\n",
+
+        "      <td>   8.400000</td>\n",
+
+        "      <td>  15.000000</td>\n",
+
+        "      <td>   3.500000</td>\n",
+
+        "      <td>   2.800000</td>\n",
+
+        "      <td>   0.600000</td>\n",
+
+        "      <td>  49.000000</td>\n",
+
+        "      <td>   0.870000</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>max</th>\n",
+
+        "      <td>  13.100000</td>\n",
+
+        "      <td>   0.610000</td>\n",
+
+        "      <td>   1.000000</td>\n",
+
+        "      <td>   1.001000</td>\n",
+
+        "      <td>  12.500000</td>\n",
+
+        "      <td>  41.000000</td>\n",
+
+        "      <td>   3.900000</td>\n",
+
+        "      <td>  12.900000</td>\n",
+
+        "      <td>   2.000000</td>\n",
+
+        "      <td> 119.000000</td>\n",
+
+        "      <td>   1.130000</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th rowspan=\"8\" valign=\"top\">5</th>\n",
+
+        "      <th>count</th>\n",
+
+        "      <td> 681.000000</td>\n",
+
+        "      <td> 681.000000</td>\n",
+
+        "      <td> 681.000000</td>\n",
+
+        "      <td> 681.000000</td>\n",
+
+        "      <td> 681.000000</td>\n",
+
+        "      <td> 681.000000</td>\n",
+
+        "      <td> 681.000000</td>\n",
+
+        "      <td> 681.000000</td>\n",
+
+        "      <td> 681.000000</td>\n",
+
+        "      <td> 681.000000</td>\n",
+
+        "      <td> 681.000000</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>mean</th>\n",
+
+        "      <td>   9.899706</td>\n",
+
+        "      <td>   0.092736</td>\n",
+
+        "      <td>   0.243686</td>\n",
+
+        "      <td>   0.997104</td>\n",
+
+        "      <td>   8.167254</td>\n",
+
+        "      <td>  16.983847</td>\n",
+
+        "      <td>   3.304949</td>\n",
+
+        "      <td>   2.528855</td>\n",
+
+        "      <td>   0.620969</td>\n",
+
+        "      <td>  56.513950</td>\n",
+
+        "      <td>   0.577041</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>std</th>\n",
+
+        "      <td>   0.736521</td>\n",
+
+        "      <td>   0.053707</td>\n",
+
+        "      <td>   0.180003</td>\n",
+
+        "      <td>   0.001589</td>\n",
+
+        "      <td>   1.563988</td>\n",
+
+        "      <td>  10.955446</td>\n",
+
+        "      <td>   0.150618</td>\n",
+
+        "      <td>   1.359753</td>\n",
+
+        "      <td>   0.171062</td>\n",
+
+        "      <td>  36.993116</td>\n",
+
+        "      <td>   0.164801</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>min</th>\n",
+
+        "      <td>   8.500000</td>\n",
+
+        "      <td>   0.039000</td>\n",
+
+        "      <td>   0.000000</td>\n",
+
+        "      <td>   0.992560</td>\n",
+
+        "      <td>   5.000000</td>\n",
+
+        "      <td>   3.000000</td>\n",
+
+        "      <td>   2.880000</td>\n",
+
+        "      <td>   1.200000</td>\n",
+
+        "      <td>   0.370000</td>\n",
+
+        "      <td>   6.000000</td>\n",
+
+        "      <td>   0.180000</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>25%</th>\n",
+
+        "      <td>   9.400000</td>\n",
+
+        "      <td>   0.074000</td>\n",
+
+        "      <td>   0.090000</td>\n",
+
+        "      <td>   0.996200</td>\n",
+
+        "      <td>   7.100000</td>\n",
+
+        "      <td>   9.000000</td>\n",
+
+        "      <td>   3.200000</td>\n",
+
+        "      <td>   1.900000</td>\n",
+
+        "      <td>   0.530000</td>\n",
+
+        "      <td>  26.000000</td>\n",
+
+        "      <td>   0.460000</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>50%</th>\n",
+
+        "      <td>   9.700000</td>\n",
+
+        "      <td>   0.081000</td>\n",
+
+        "      <td>   0.230000</td>\n",
+
+        "      <td>   0.997000</td>\n",
+
+        "      <td>   7.800000</td>\n",
+
+        "      <td>  15.000000</td>\n",
+
+        "      <td>   3.300000</td>\n",
+
+        "      <td>   2.200000</td>\n",
+
+        "      <td>   0.580000</td>\n",
+
+        "      <td>  47.000000</td>\n",
+
+        "      <td>   0.580000</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>75%</th>\n",
+
+        "      <td>  10.200000</td>\n",
+
+        "      <td>   0.094000</td>\n",
+
+        "      <td>   0.360000</td>\n",
+
+        "      <td>   0.997900</td>\n",
+
+        "      <td>   8.900000</td>\n",
+
+        "      <td>  23.000000</td>\n",
+
+        "      <td>   3.400000</td>\n",
+
+        "      <td>   2.600000</td>\n",
+
+        "      <td>   0.660000</td>\n",
+
+        "      <td>  84.000000</td>\n",
+
+        "      <td>   0.670000</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>max</th>\n",
+
+        "      <td>  14.900000</td>\n",
+
+        "      <td>   0.611000</td>\n",
+
+        "      <td>   0.790000</td>\n",
+
+        "      <td>   1.003150</td>\n",
+
+        "      <td>  15.900000</td>\n",
+
+        "      <td>  68.000000</td>\n",
+
+        "      <td>   3.740000</td>\n",
+
+        "      <td>  15.500000</td>\n",
+
+        "      <td>   1.980000</td>\n",
+
+        "      <td> 155.000000</td>\n",
+
+        "      <td>   1.330000</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th rowspan=\"8\" valign=\"top\">6</th>\n",
+
+        "      <th>count</th>\n",
+
+        "      <td> 638.000000</td>\n",
+
+        "      <td> 638.000000</td>\n",
+
+        "      <td> 638.000000</td>\n",
+
+        "      <td> 638.000000</td>\n",
+
+        "      <td> 638.000000</td>\n",
+
+        "      <td> 638.000000</td>\n",
+
+        "      <td> 638.000000</td>\n",
+
+        "      <td> 638.000000</td>\n",
+
+        "      <td> 638.000000</td>\n",
+
+        "      <td> 638.000000</td>\n",
+
+        "      <td> 638.000000</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>mean</th>\n",
+
+        "      <td>  10.629519</td>\n",
+
+        "      <td>   0.084956</td>\n",
+
+        "      <td>   0.273824</td>\n",
+
+        "      <td>   0.996615</td>\n",
+
+        "      <td>   8.347179</td>\n",
+
+        "      <td>  15.711599</td>\n",
+
+        "      <td>   3.318072</td>\n",
+
+        "      <td>   2.477194</td>\n",
+
+        "      <td>   0.675329</td>\n",
+
+        "      <td>  40.869906</td>\n",
+
+        "      <td>   0.497484</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>std</th>\n",
+
+        "      <td>   1.049639</td>\n",
+
+        "      <td>   0.039563</td>\n",
+
+        "      <td>   0.195108</td>\n",
+
+        "      <td>   0.002000</td>\n",
+
+        "      <td>   1.797849</td>\n",
+
+        "      <td>   9.940911</td>\n",
+
+        "      <td>   0.153995</td>\n",
+
+        "      <td>   1.441576</td>\n",
+
+        "      <td>   0.158650</td>\n",
+
+        "      <td>  25.038250</td>\n",
+
+        "      <td>   0.160962</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>min</th>\n",
+
+        "      <td>   8.400000</td>\n",
+
+        "      <td>   0.034000</td>\n",
+
+        "      <td>   0.000000</td>\n",
+
+        "      <td>   0.990070</td>\n",
+
+        "      <td>   4.700000</td>\n",
+
+        "      <td>   1.000000</td>\n",
+
+        "      <td>   2.860000</td>\n",
+
+        "      <td>   0.900000</td>\n",
+
+        "      <td>   0.400000</td>\n",
+
+        "      <td>   6.000000</td>\n",
+
+        "      <td>   0.160000</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>25%</th>\n",
+
+        "      <td>   9.800000</td>\n",
+
+        "      <td>   0.068250</td>\n",
+
+        "      <td>   0.090000</td>\n",
+
+        "      <td>   0.995402</td>\n",
+
+        "      <td>   7.000000</td>\n",
+
+        "      <td>   8.000000</td>\n",
+
+        "      <td>   3.220000</td>\n",
+
+        "      <td>   1.900000</td>\n",
+
+        "      <td>   0.580000</td>\n",
+
+        "      <td>  23.000000</td>\n",
+
+        "      <td>   0.380000</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>50%</th>\n",
+
+        "      <td>  10.500000</td>\n",
+
+        "      <td>   0.078000</td>\n",
+
+        "      <td>   0.260000</td>\n",
+
+        "      <td>   0.996560</td>\n",
+
+        "      <td>   7.900000</td>\n",
+
+        "      <td>  14.000000</td>\n",
+
+        "      <td>   3.320000</td>\n",
+
+        "      <td>   2.200000</td>\n",
+
+        "      <td>   0.640000</td>\n",
+
+        "      <td>  35.000000</td>\n",
+
+        "      <td>   0.490000</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>75%</th>\n",
+
+        "      <td>  11.300000</td>\n",
+
+        "      <td>   0.088000</td>\n",
+
+        "      <td>   0.430000</td>\n",
+
+        "      <td>   0.997893</td>\n",
+
+        "      <td>   9.400000</td>\n",
+
+        "      <td>  21.000000</td>\n",
+
+        "      <td>   3.410000</td>\n",
+
+        "      <td>   2.500000</td>\n",
+
+        "      <td>   0.750000</td>\n",
+
+        "      <td>  54.000000</td>\n",
+
+        "      <td>   0.600000</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>max</th>\n",
+
+        "      <td>  14.000000</td>\n",
+
+        "      <td>   0.415000</td>\n",
+
+        "      <td>   0.780000</td>\n",
+
+        "      <td>   1.003690</td>\n",
+
+        "      <td>  14.300000</td>\n",
+
+        "      <td>  72.000000</td>\n",
+
+        "      <td>   4.010000</td>\n",
+
+        "      <td>  15.400000</td>\n",
+
+        "      <td>   1.950000</td>\n",
+
+        "      <td> 165.000000</td>\n",
+
+        "      <td>   1.040000</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th rowspan=\"8\" valign=\"top\">7</th>\n",
+
+        "      <th>count</th>\n",
+
+        "      <td> 199.000000</td>\n",
+
+        "      <td> 199.000000</td>\n",
+
+        "      <td> 199.000000</td>\n",
+
+        "      <td> 199.000000</td>\n",
+
+        "      <td> 199.000000</td>\n",
+
+        "      <td> 199.000000</td>\n",
+
+        "      <td> 199.000000</td>\n",
+
+        "      <td> 199.000000</td>\n",
+
+        "      <td> 199.000000</td>\n",
+
+        "      <td> 199.000000</td>\n",
+
+        "      <td> 199.000000</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>mean</th>\n",
+
+        "      <td>  11.465913</td>\n",
+
+        "      <td>   0.076588</td>\n",
+
+        "      <td>   0.375176</td>\n",
+
+        "      <td>   0.996104</td>\n",
+
+        "      <td>   8.872362</td>\n",
+
+        "      <td>  14.045226</td>\n",
+
+        "      <td>   3.290754</td>\n",
+
+        "      <td>   2.720603</td>\n",
+
+        "      <td>   0.741256</td>\n",
+
+        "      <td>  35.020101</td>\n",
+
+        "      <td>   0.403920</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>std</th>\n",
+
+        "      <td>   0.961933</td>\n",
+
+        "      <td>   0.029456</td>\n",
+
+        "      <td>   0.194432</td>\n",
+
+        "      <td>   0.002176</td>\n",
+
+        "      <td>   1.992483</td>\n",
+
+        "      <td>  10.175255</td>\n",
+
+        "      <td>   0.150101</td>\n",
+
+        "      <td>   1.371509</td>\n",
+
+        "      <td>   0.135639</td>\n",
+
+        "      <td>  33.191206</td>\n",
+
+        "      <td>   0.145224</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>min</th>\n",
+
+        "      <td>   9.200000</td>\n",
+
+        "      <td>   0.012000</td>\n",
+
+        "      <td>   0.000000</td>\n",
+
+        "      <td>   0.990640</td>\n",
+
+        "      <td>   4.900000</td>\n",
+
+        "      <td>   3.000000</td>\n",
+
+        "      <td>   2.920000</td>\n",
+
+        "      <td>   1.200000</td>\n",
+
+        "      <td>   0.390000</td>\n",
+
+        "      <td>   7.000000</td>\n",
+
+        "      <td>   0.120000</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>25%</th>\n",
+
+        "      <td>  10.800000</td>\n",
+
+        "      <td>   0.062000</td>\n",
+
+        "      <td>   0.305000</td>\n",
+
+        "      <td>   0.994765</td>\n",
+
+        "      <td>   7.400000</td>\n",
+
+        "      <td>   6.000000</td>\n",
+
+        "      <td>   3.200000</td>\n",
+
+        "      <td>   2.000000</td>\n",
+
+        "      <td>   0.650000</td>\n",
+
+        "      <td>  17.500000</td>\n",
+
+        "      <td>   0.300000</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>50%</th>\n",
+
+        "      <td>  11.500000</td>\n",
+
+        "      <td>   0.073000</td>\n",
+
+        "      <td>   0.400000</td>\n",
+
+        "      <td>   0.995770</td>\n",
+
+        "      <td>   8.800000</td>\n",
+
+        "      <td>  11.000000</td>\n",
+
+        "      <td>   3.280000</td>\n",
+
+        "      <td>   2.300000</td>\n",
+
+        "      <td>   0.740000</td>\n",
+
+        "      <td>  27.000000</td>\n",
+
+        "      <td>   0.370000</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>75%</th>\n",
+
+        "      <td>  12.100000</td>\n",
+
+        "      <td>   0.087000</td>\n",
+
+        "      <td>   0.490000</td>\n",
+
+        "      <td>   0.997360</td>\n",
+
+        "      <td>  10.100000</td>\n",
+
+        "      <td>  18.000000</td>\n",
+
+        "      <td>   3.380000</td>\n",
+
+        "      <td>   2.750000</td>\n",
+
+        "      <td>   0.830000</td>\n",
+
+        "      <td>  43.000000</td>\n",
+
+        "      <td>   0.485000</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>max</th>\n",
+
+        "      <td>  14.000000</td>\n",
+
+        "      <td>   0.358000</td>\n",
+
+        "      <td>   0.760000</td>\n",
+
+        "      <td>   1.003200</td>\n",
+
+        "      <td>  15.600000</td>\n",
+
+        "      <td>  54.000000</td>\n",
+
+        "      <td>   3.780000</td>\n",
+
+        "      <td>   8.900000</td>\n",
+
+        "      <td>   1.360000</td>\n",
+
+        "      <td> 289.000000</td>\n",
+
+        "      <td>   0.915000</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th rowspan=\"8\" valign=\"top\">8</th>\n",
+
+        "      <th>count</th>\n",
+
+        "      <td>  18.000000</td>\n",
+
+        "      <td>  18.000000</td>\n",
+
+        "      <td>  18.000000</td>\n",
+
+        "      <td>  18.000000</td>\n",
+
+        "      <td>  18.000000</td>\n",
+
+        "      <td>  18.000000</td>\n",
+
+        "      <td>  18.000000</td>\n",
+
+        "      <td>  18.000000</td>\n",
+
+        "      <td>  18.000000</td>\n",
+
+        "      <td>  18.000000</td>\n",
+
+        "      <td>  18.000000</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>mean</th>\n",
+
+        "      <td>  12.094444</td>\n",
+
+        "      <td>   0.068444</td>\n",
+
+        "      <td>   0.391111</td>\n",
+
+        "      <td>   0.995212</td>\n",
+
+        "      <td>   8.566667</td>\n",
+
+        "      <td>  13.277778</td>\n",
+
+        "      <td>   3.267222</td>\n",
+
+        "      <td>   2.577778</td>\n",
+
+        "      <td>   0.767778</td>\n",
+
+        "      <td>  33.444444</td>\n",
+
+        "      <td>   0.423333</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>std</th>\n",
+
+        "      <td>   1.224011</td>\n",
+
+        "      <td>   0.011678</td>\n",
+
+        "      <td>   0.199526</td>\n",
+
+        "      <td>   0.002378</td>\n",
+
+        "      <td>   2.119656</td>\n",
+
+        "      <td>  11.155613</td>\n",
+
+        "      <td>   0.200640</td>\n",
+
+        "      <td>   1.295038</td>\n",
+
+        "      <td>   0.115379</td>\n",
+
+        "      <td>  25.433240</td>\n",
+
+        "      <td>   0.144914</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>min</th>\n",
+
+        "      <td>   9.800000</td>\n",
+
+        "      <td>   0.044000</td>\n",
+
+        "      <td>   0.030000</td>\n",
+
+        "      <td>   0.990800</td>\n",
+
+        "      <td>   5.000000</td>\n",
+
+        "      <td>   3.000000</td>\n",
+
+        "      <td>   2.880000</td>\n",
+
+        "      <td>   1.400000</td>\n",
+
+        "      <td>   0.630000</td>\n",
+
+        "      <td>  12.000000</td>\n",
+
+        "      <td>   0.260000</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>25%</th>\n",
+
+        "      <td>  11.325000</td>\n",
+
+        "      <td>   0.062000</td>\n",
+
+        "      <td>   0.302500</td>\n",
+
+        "      <td>   0.994175</td>\n",
+
+        "      <td>   7.250000</td>\n",
+
+        "      <td>   6.000000</td>\n",
+
+        "      <td>   3.162500</td>\n",
+
+        "      <td>   1.800000</td>\n",
+
+        "      <td>   0.690000</td>\n",
+
+        "      <td>  16.000000</td>\n",
+
+        "      <td>   0.335000</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>50%</th>\n",
+
+        "      <td>  12.150000</td>\n",
+
+        "      <td>   0.070500</td>\n",
+
+        "      <td>   0.420000</td>\n",
+
+        "      <td>   0.994940</td>\n",
+
+        "      <td>   8.250000</td>\n",
+
+        "      <td>   7.500000</td>\n",
+
+        "      <td>   3.230000</td>\n",
+
+        "      <td>   2.100000</td>\n",
+
+        "      <td>   0.740000</td>\n",
+
+        "      <td>  21.500000</td>\n",
+
+        "      <td>   0.370000</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>75%</th>\n",
+
+        "      <td>  12.875000</td>\n",
+
+        "      <td>   0.075500</td>\n",
+
+        "      <td>   0.530000</td>\n",
+
+        "      <td>   0.997200</td>\n",
+
+        "      <td>  10.225000</td>\n",
+
+        "      <td>  16.500000</td>\n",
+
+        "      <td>   3.350000</td>\n",
+
+        "      <td>   2.600000</td>\n",
+
+        "      <td>   0.820000</td>\n",
+
+        "      <td>  43.000000</td>\n",
+
+        "      <td>   0.472500</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>max</th>\n",
+
+        "      <td>  14.000000</td>\n",
+
+        "      <td>   0.086000</td>\n",
+
+        "      <td>   0.720000</td>\n",
+
+        "      <td>   0.998800</td>\n",
+
+        "      <td>  12.600000</td>\n",
+
+        "      <td>  42.000000</td>\n",
+
+        "      <td>   3.720000</td>\n",
+
+        "      <td>   6.400000</td>\n",
+
+        "      <td>   1.100000</td>\n",
+
+        "      <td>  88.000000</td>\n",
+
+        "      <td>   0.850000</td>\n",
+
+        "    </tr>\n",
+
+        "  </tbody>\n",
+
+        "</table>\n",
+
+        "</div>"
+
+       ],
+
+       "metadata": {},
+
+       "output_type": "pyout",
+
+       "prompt_number": 25,
+
+       "text": [
+
+        "                  alcohol   chlorides  citric acid     density  fixed acidity  \\\n",
+
+        "quality                                                                         \n",
+
+        "3       count   10.000000   10.000000    10.000000   10.000000      10.000000   \n",
+
+        "        mean     9.955000    0.122500     0.171000    0.997464       8.360000   \n",
+
+        "        std      0.818009    0.066241     0.250664    0.002002       1.770875   \n",
+
+        "        min      8.400000    0.061000     0.000000    0.994710       6.700000   \n",
+
+        "        25%      9.725000    0.079000     0.005000    0.996150       7.150000   \n",
+
+        "        50%      9.925000    0.090500     0.035000    0.997565       7.500000   \n",
+
+        "        75%     10.575000    0.143000     0.327500    0.998770       9.875000   \n",
+
+        "        max     11.000000    0.267000     0.660000    1.000800      11.600000   \n",
+
+        "4       count   53.000000   53.000000    53.000000   53.000000      53.000000   \n",
+
+        "        mean    10.265094    0.090679     0.174151    0.996542       7.779245   \n",
+
+        "        std      0.934776    0.076192     0.201030    0.001575       1.626624   \n",
+
+        "        min      9.000000    0.045000     0.000000    0.993400       4.600000   \n",
+
+        "        25%      9.600000    0.067000     0.030000    0.995650       6.800000   \n",
+
+        "        50%     10.000000    0.080000     0.090000    0.996500       7.500000   \n",
+
+        "        75%     11.000000    0.089000     0.270000    0.997450       8.400000   \n",
+
+        "        max     13.100000    0.610000     1.000000    1.001000      12.500000   \n",
+
+        "5       count  681.000000  681.000000   681.000000  681.000000     681.000000   \n",
+
+        "        mean     9.899706    0.092736     0.243686    0.997104       8.167254   \n",
+
+        "        std      0.736521    0.053707     0.180003    0.001589       1.563988   \n",
+
+        "        min      8.500000    0.039000     0.000000    0.992560       5.000000   \n",
+
+        "        25%      9.400000    0.074000     0.090000    0.996200       7.100000   \n",
+
+        "        50%      9.700000    0.081000     0.230000    0.997000       7.800000   \n",
+
+        "        75%     10.200000    0.094000     0.360000    0.997900       8.900000   \n",
+
+        "        max     14.900000    0.611000     0.790000    1.003150      15.900000   \n",
+
+        "6       count  638.000000  638.000000   638.000000  638.000000     638.000000   \n",
+
+        "        mean    10.629519    0.084956     0.273824    0.996615       8.347179   \n",
+
+        "        std      1.049639    0.039563     0.195108    0.002000       1.797849   \n",
+
+        "        min      8.400000    0.034000     0.000000    0.990070       4.700000   \n",
+
+        "        25%      9.800000    0.068250     0.090000    0.995402       7.000000   \n",
+
+        "        50%     10.500000    0.078000     0.260000    0.996560       7.900000   \n",
+
+        "        75%     11.300000    0.088000     0.430000    0.997893       9.400000   \n",
+
+        "        max     14.000000    0.415000     0.780000    1.003690      14.300000   \n",
+
+        "7       count  199.000000  199.000000   199.000000  199.000000     199.000000   \n",
+
+        "        mean    11.465913    0.076588     0.375176    0.996104       8.872362   \n",
+
+        "        std      0.961933    0.029456     0.194432    0.002176       1.992483   \n",
+
+        "        min      9.200000    0.012000     0.000000    0.990640       4.900000   \n",
+
+        "        25%     10.800000    0.062000     0.305000    0.994765       7.400000   \n",
+
+        "        50%     11.500000    0.073000     0.400000    0.995770       8.800000   \n",
+
+        "        75%     12.100000    0.087000     0.490000    0.997360      10.100000   \n",
+
+        "        max     14.000000    0.358000     0.760000    1.003200      15.600000   \n",
+
+        "8       count   18.000000   18.000000    18.000000   18.000000      18.000000   \n",
+
+        "        mean    12.094444    0.068444     0.391111    0.995212       8.566667   \n",
+
+        "        std      1.224011    0.011678     0.199526    0.002378       2.119656   \n",
+
+        "        min      9.800000    0.044000     0.030000    0.990800       5.000000   \n",
+
+        "        25%     11.325000    0.062000     0.302500    0.994175       7.250000   \n",
+
+        "        50%     12.150000    0.070500     0.420000    0.994940       8.250000   \n",
+
+        "        75%     12.875000    0.075500     0.530000    0.997200      10.225000   \n",
+
+        "        max     14.000000    0.086000     0.720000    0.998800      12.600000   \n",
+
+        "\n",
+
+        "               free sulfur dioxide          pH  residual sugar   sulphates  \\\n",
+
+        "quality                                                                      \n",
+
+        "3       count            10.000000   10.000000       10.000000   10.000000   \n",
+
+        "        mean             11.000000    3.398000        2.635000    0.570000   \n",
+
+        "        std               9.763879    0.144052        1.401596    0.122020   \n",
+
+        "        min               3.000000    3.160000        1.200000    0.400000   \n",
+
+        "        25%               5.000000    3.312500        1.875000    0.512500   \n",
+
+        "        50%               6.000000    3.390000        2.100000    0.545000   \n",
+
+        "        75%              14.500000    3.495000        3.100000    0.615000   \n",
+
+        "        max              34.000000    3.630000        5.700000    0.860000   \n",
+
+        "4       count            53.000000   53.000000       53.000000   53.000000   \n",
+
+        "        mean             12.264151    3.381509        2.694340    0.596415   \n",
+
+        "        std               9.025926    0.181441        1.789436    0.239391   \n",
+
+        "        min               3.000000    2.740000        1.300000    0.330000   \n",
+
+        "        25%               6.000000    3.300000        1.900000    0.490000   \n",
+
+        "        50%              11.000000    3.370000        2.100000    0.560000   \n",
+
+        "        75%              15.000000    3.500000        2.800000    0.600000   \n",
+
+        "        max              41.000000    3.900000       12.900000    2.000000   \n",
+
+        "5       count           681.000000  681.000000      681.000000  681.000000   \n",
+
+        "        mean             16.983847    3.304949        2.528855    0.620969   \n",
+
+        "        std              10.955446    0.150618        1.359753    0.171062   \n",
+
+        "        min               3.000000    2.880000        1.200000    0.370000   \n",
+
+        "        25%               9.000000    3.200000        1.900000    0.530000   \n",
+
+        "        50%              15.000000    3.300000        2.200000    0.580000   \n",
+
+        "        75%              23.000000    3.400000        2.600000    0.660000   \n",
+
+        "        max              68.000000    3.740000       15.500000    1.980000   \n",
+
+        "6       count           638.000000  638.000000      638.000000  638.000000   \n",
+
+        "        mean             15.711599    3.318072        2.477194    0.675329   \n",
+
+        "        std               9.940911    0.153995        1.441576    0.158650   \n",
+
+        "        min               1.000000    2.860000        0.900000    0.400000   \n",
+
+        "        25%               8.000000    3.220000        1.900000    0.580000   \n",
+
+        "        50%              14.000000    3.320000        2.200000    0.640000   \n",
+
+        "        75%              21.000000    3.410000        2.500000    0.750000   \n",
+
+        "        max              72.000000    4.010000       15.400000    1.950000   \n",
+
+        "7       count           199.000000  199.000000      199.000000  199.000000   \n",
+
+        "        mean             14.045226    3.290754        2.720603    0.741256   \n",
+
+        "        std              10.175255    0.150101        1.371509    0.135639   \n",
+
+        "        min               3.000000    2.920000        1.200000    0.390000   \n",
+
+        "        25%               6.000000    3.200000        2.000000    0.650000   \n",
+
+        "        50%              11.000000    3.280000        2.300000    0.740000   \n",
+
+        "        75%              18.000000    3.380000        2.750000    0.830000   \n",
+
+        "        max              54.000000    3.780000        8.900000    1.360000   \n",
+
+        "8       count            18.000000   18.000000       18.000000   18.000000   \n",
+
+        "        mean             13.277778    3.267222        2.577778    0.767778   \n",
+
+        "        std              11.155613    0.200640        1.295038    0.115379   \n",
+
+        "        min               3.000000    2.880000        1.400000    0.630000   \n",
+
+        "        25%               6.000000    3.162500        1.800000    0.690000   \n",
+
+        "        50%               7.500000    3.230000        2.100000    0.740000   \n",
+
+        "        75%              16.500000    3.350000        2.600000    0.820000   \n",
+
+        "        max              42.000000    3.720000        6.400000    1.100000   \n",
+
+        "\n",
+
+        "               total sulfur dioxide  volatile acidity  \n",
+
+        "quality                                                \n",
+
+        "3       count             10.000000         10.000000  \n",
+
+        "        mean              24.900000          0.884500  \n",
+
+        "        std               16.828877          0.331256  \n",
+
+        "        min                9.000000          0.440000  \n",
+
+        "        25%               12.500000          0.647500  \n",
+
+        "        50%               15.000000          0.845000  \n",
+
+        "        75%               42.500000          1.010000  \n",
+
+        "        max               49.000000          1.580000  \n",
+
+        "4       count             53.000000         53.000000  \n",
+
+        "        mean              36.245283          0.693962  \n",
+
+        "        std               27.583374          0.220110  \n",
+
+        "        min                7.000000          0.230000  \n",
+
+        "        25%               14.000000          0.530000  \n",
+
+        "        50%               26.000000          0.670000  \n",
+
+        "        75%               49.000000          0.870000  \n",
+
+        "        max              119.000000          1.130000  \n",
+
+        "5       count            681.000000        681.000000  \n",
+
+        "        mean              56.513950          0.577041  \n",
+
+        "        std               36.993116          0.164801  \n",
+
+        "        min                6.000000          0.180000  \n",
+
+        "        25%               26.000000          0.460000  \n",
+
+        "        50%               47.000000          0.580000  \n",
+
+        "        75%               84.000000          0.670000  \n",
+
+        "        max              155.000000          1.330000  \n",
+
+        "6       count            638.000000        638.000000  \n",
+
+        "        mean              40.869906          0.497484  \n",
+
+        "        std               25.038250          0.160962  \n",
+
+        "        min                6.000000          0.160000  \n",
+
+        "        25%               23.000000          0.380000  \n",
+
+        "        50%               35.000000          0.490000  \n",
+
+        "        75%               54.000000          0.600000  \n",
+
+        "        max              165.000000          1.040000  \n",
+
+        "7       count            199.000000        199.000000  \n",
+
+        "        mean              35.020101          0.403920  \n",
+
+        "        std               33.191206          0.145224  \n",
+
+        "        min                7.000000          0.120000  \n",
+
+        "        25%               17.500000          0.300000  \n",
+
+        "        50%               27.000000          0.370000  \n",
+
+        "        75%               43.000000          0.485000  \n",
+
+        "        max              289.000000          0.915000  \n",
+
+        "8       count             18.000000         18.000000  \n",
+
+        "        mean              33.444444          0.423333  \n",
+
+        "        std               25.433240          0.144914  \n",
+
+        "        min               12.000000          0.260000  \n",
+
+        "        25%               16.000000          0.335000  \n",
+
+        "        50%               21.500000          0.370000  \n",
+
+        "        75%               43.000000          0.472500  \n",
+
+        "        max               88.000000          0.850000  "
+
+       ]
+
+      }
+
+     ],
+
+     "prompt_number": 25
+
+    },
+
+    {
+
+     "cell_type": "code",
+
+     "collapsed": false,
+
+     "input": [
+
+      "# We can now apply our own aggregate function, this function takes the max value of the col and subtracts the min value of the col\n",
+
+      "wino.agg(max_to_min)"
+
+     ],
+
+     "language": "python",
+
+     "metadata": {},
+
+     "outputs": [
+
+      {
+
+       "html": [
+
+        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
+
+        "<table border=\"1\" class=\"dataframe\">\n",
+
+        "  <thead>\n",
+
+        "    <tr style=\"text-align: right;\">\n",
+
+        "      <th></th>\n",
+
+        "      <th>fixed acidity</th>\n",
+
+        "      <th>volatile acidity</th>\n",
+
+        "      <th>citric acid</th>\n",
+
+        "      <th>residual sugar</th>\n",
+
+        "      <th>chlorides</th>\n",
+
+        "      <th>free sulfur dioxide</th>\n",
+
+        "      <th>total sulfur dioxide</th>\n",
+
+        "      <th>density</th>\n",
+
+        "      <th>pH</th>\n",
+
+        "      <th>sulphates</th>\n",
+
+        "      <th>alcohol</th>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>quality</th>\n",
+
+        "      <th></th>\n",
+
+        "      <th></th>\n",
+
+        "      <th></th>\n",
+
+        "      <th></th>\n",
+
+        "      <th></th>\n",
+
+        "      <th></th>\n",
+
+        "      <th></th>\n",
+
+        "      <th></th>\n",
+
+        "      <th></th>\n",
+
+        "      <th></th>\n",
+
+        "      <th></th>\n",
+
+        "    </tr>\n",
+
+        "  </thead>\n",
+
+        "  <tbody>\n",
+
+        "    <tr>\n",
+
+        "      <th>3</th>\n",
+
+        "      <td>  4.9</td>\n",
+
+        "      <td> 1.140</td>\n",
+
+        "      <td> 0.66</td>\n",
+
+        "      <td>  4.5</td>\n",
+
+        "      <td> 0.206</td>\n",
+
+        "      <td> 31</td>\n",
+
+        "      <td>  40</td>\n",
+
+        "      <td> 0.00609</td>\n",
+
+        "      <td> 0.47</td>\n",
+
+        "      <td> 0.46</td>\n",
+
+        "      <td> 2.6</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>4</th>\n",
+
+        "      <td>  7.9</td>\n",
+
+        "      <td> 0.900</td>\n",
+
+        "      <td> 1.00</td>\n",
+
+        "      <td> 11.6</td>\n",
+
+        "      <td> 0.565</td>\n",
+
+        "      <td> 38</td>\n",
+
+        "      <td> 112</td>\n",
+
+        "      <td> 0.00760</td>\n",
+
+        "      <td> 1.16</td>\n",
+
+        "      <td> 1.67</td>\n",
+
+        "      <td> 4.1</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>5</th>\n",
+
+        "      <td> 10.9</td>\n",
+
+        "      <td> 1.150</td>\n",
+
+        "      <td> 0.79</td>\n",
+
+        "      <td> 14.3</td>\n",
+
+        "      <td> 0.572</td>\n",
+
+        "      <td> 65</td>\n",
+
+        "      <td> 149</td>\n",
+
+        "      <td> 0.01059</td>\n",
+
+        "      <td> 0.86</td>\n",
+
+        "      <td> 1.61</td>\n",
+
+        "      <td> 6.4</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>6</th>\n",
+
+        "      <td>  9.6</td>\n",
+
+        "      <td> 0.880</td>\n",
+
+        "      <td> 0.78</td>\n",
+
+        "      <td> 14.5</td>\n",
+
+        "      <td> 0.381</td>\n",
+
+        "      <td> 71</td>\n",
+
+        "      <td> 159</td>\n",
+
+        "      <td> 0.01362</td>\n",
+
+        "      <td> 1.15</td>\n",
+
+        "      <td> 1.55</td>\n",
+
+        "      <td> 5.6</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>7</th>\n",
+
+        "      <td> 10.7</td>\n",
+
+        "      <td> 0.795</td>\n",
+
+        "      <td> 0.76</td>\n",
+
+        "      <td>  7.7</td>\n",
+
+        "      <td> 0.346</td>\n",
+
+        "      <td> 51</td>\n",
+
+        "      <td> 282</td>\n",
+
+        "      <td> 0.01256</td>\n",
+
+        "      <td> 0.86</td>\n",
+
+        "      <td> 0.97</td>\n",
+
+        "      <td> 4.8</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>8</th>\n",
+
+        "      <td>  7.6</td>\n",
+
+        "      <td> 0.590</td>\n",
+
+        "      <td> 0.69</td>\n",
+
+        "      <td>  5.0</td>\n",
+
+        "      <td> 0.042</td>\n",
+
+        "      <td> 39</td>\n",
+
+        "      <td>  76</td>\n",
+
+        "      <td> 0.00800</td>\n",
+
+        "      <td> 0.84</td>\n",
+
+        "      <td> 0.47</td>\n",
+
+        "      <td> 4.2</td>\n",
+
+        "    </tr>\n",
+
+        "  </tbody>\n",
+
+        "</table>\n",
+
+        "</div>"
+
+       ],
+
+       "metadata": {},
+
+       "output_type": "pyout",
+
+       "prompt_number": 22,
+
+       "text": [
+
+        "         fixed acidity  volatile acidity  citric acid  residual sugar  \\\n",
+
+        "quality                                                                 \n",
+
+        "3                  4.9             1.140         0.66             4.5   \n",
+
+        "4                  7.9             0.900         1.00            11.6   \n",
+
+        "5                 10.9             1.150         0.79            14.3   \n",
+
+        "6                  9.6             0.880         0.78            14.5   \n",
+
+        "7                 10.7             0.795         0.76             7.7   \n",
+
+        "8                  7.6             0.590         0.69             5.0   \n",
+
+        "\n",
+
+        "         chlorides  free sulfur dioxide  total sulfur dioxide  density    pH  \\\n",
+
+        "quality                                                                        \n",
+
+        "3            0.206                   31                    40  0.00609  0.47   \n",
+
+        "4            0.565                   38                   112  0.00760  1.16   \n",
+
+        "5            0.572                   65                   149  0.01059  0.86   \n",
+
+        "6            0.381                   71                   159  0.01362  1.15   \n",
+
+        "7            0.346                   51                   282  0.01256  0.86   \n",
+
+        "8            0.042                   39                    76  0.00800  0.84   \n",
+
+        "\n",
+
+        "         sulphates  alcohol  \n",
+
+        "quality                      \n",
+
+        "3             0.46      2.6  \n",
+
+        "4             1.67      4.1  \n",
+
+        "5             1.61      6.4  \n",
+
+        "6             1.55      5.6  \n",
+
+        "7             0.97      4.8  \n",
+
+        "8             0.47      4.2  "
+
+       ]
+
+      }
+
+     ],
+
+     "prompt_number": 22
+
+    },
+
+    {
+
+     "cell_type": "code",
+
+     "collapsed": false,
+
+     "input": [
+
+      "# We can also pass string methods through aggregate\n",
+
+      "wino.agg('mean')"
+
+     ],
+
+     "language": "python",
+
+     "metadata": {},
+
+     "outputs": [
+
+      {
+
+       "html": [
+
+        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
+
+        "<table border=\"1\" class=\"dataframe\">\n",
+
+        "  <thead>\n",
+
+        "    <tr style=\"text-align: right;\">\n",
+
+        "      <th></th>\n",
+
+        "      <th>fixed acidity</th>\n",
+
+        "      <th>volatile acidity</th>\n",
+
+        "      <th>citric acid</th>\n",
+
+        "      <th>residual sugar</th>\n",
+
+        "      <th>chlorides</th>\n",
+
+        "      <th>free sulfur dioxide</th>\n",
+
+        "      <th>total sulfur dioxide</th>\n",
+
+        "      <th>density</th>\n",
+
+        "      <th>pH</th>\n",
+
+        "      <th>sulphates</th>\n",
+
+        "      <th>alcohol</th>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>quality</th>\n",
+
+        "      <th></th>\n",
+
+        "      <th></th>\n",
+
+        "      <th></th>\n",
+
+        "      <th></th>\n",
+
+        "      <th></th>\n",
+
+        "      <th></th>\n",
+
+        "      <th></th>\n",
+
+        "      <th></th>\n",
+
+        "      <th></th>\n",
+
+        "      <th></th>\n",
+
+        "      <th></th>\n",
+
+        "    </tr>\n",
+
+        "  </thead>\n",
+
+        "  <tbody>\n",
+
+        "    <tr>\n",
+
+        "      <th>3</th>\n",
+
+        "      <td> 8.360000</td>\n",
+
+        "      <td> 0.884500</td>\n",
+
+        "      <td> 0.171000</td>\n",
+
+        "      <td> 2.635000</td>\n",
+
+        "      <td> 0.122500</td>\n",
+
+        "      <td> 11.000000</td>\n",
+
+        "      <td> 24.900000</td>\n",
+
+        "      <td> 0.997464</td>\n",
+
+        "      <td> 3.398000</td>\n",
+
+        "      <td> 0.570000</td>\n",
+
+        "      <td>  9.955000</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>4</th>\n",
+
+        "      <td> 7.779245</td>\n",
+
+        "      <td> 0.693962</td>\n",
+
+        "      <td> 0.174151</td>\n",
+
+        "      <td> 2.694340</td>\n",
+
+        "      <td> 0.090679</td>\n",
+
+        "      <td> 12.264151</td>\n",
+
+        "      <td> 36.245283</td>\n",
+
+        "      <td> 0.996542</td>\n",
+
+        "      <td> 3.381509</td>\n",
+
+        "      <td> 0.596415</td>\n",
+
+        "      <td> 10.265094</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>5</th>\n",
+
+        "      <td> 8.167254</td>\n",
+
+        "      <td> 0.577041</td>\n",
+
+        "      <td> 0.243686</td>\n",
+
+        "      <td> 2.528855</td>\n",
+
+        "      <td> 0.092736</td>\n",
+
+        "      <td> 16.983847</td>\n",
+
+        "      <td> 56.513950</td>\n",
+
+        "      <td> 0.997104</td>\n",
+
+        "      <td> 3.304949</td>\n",
+
+        "      <td> 0.620969</td>\n",
+
+        "      <td>  9.899706</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>6</th>\n",
+
+        "      <td> 8.347179</td>\n",
+
+        "      <td> 0.497484</td>\n",
+
+        "      <td> 0.273824</td>\n",
+
+        "      <td> 2.477194</td>\n",
+
+        "      <td> 0.084956</td>\n",
+
+        "      <td> 15.711599</td>\n",
+
+        "      <td> 40.869906</td>\n",
+
+        "      <td> 0.996615</td>\n",
+
+        "      <td> 3.318072</td>\n",
+
+        "      <td> 0.675329</td>\n",
+
+        "      <td> 10.629519</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>7</th>\n",
+
+        "      <td> 8.872362</td>\n",
+
+        "      <td> 0.403920</td>\n",
+
+        "      <td> 0.375176</td>\n",
+
+        "      <td> 2.720603</td>\n",
+
+        "      <td> 0.076588</td>\n",
+
+        "      <td> 14.045226</td>\n",
+
+        "      <td> 35.020101</td>\n",
+
+        "      <td> 0.996104</td>\n",
+
+        "      <td> 3.290754</td>\n",
+
+        "      <td> 0.741256</td>\n",
+
+        "      <td> 11.465913</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>8</th>\n",
+
+        "      <td> 8.566667</td>\n",
+
+        "      <td> 0.423333</td>\n",
+
+        "      <td> 0.391111</td>\n",
+
+        "      <td> 2.577778</td>\n",
+
+        "      <td> 0.068444</td>\n",
+
+        "      <td> 13.277778</td>\n",
+
+        "      <td> 33.444444</td>\n",
+
+        "      <td> 0.995212</td>\n",
+
+        "      <td> 3.267222</td>\n",
+
+        "      <td> 0.767778</td>\n",
+
+        "      <td> 12.094444</td>\n",
+
+        "    </tr>\n",
+
+        "  </tbody>\n",
+
+        "</table>\n",
+
+        "</div>"
+
+       ],
+
+       "metadata": {},
+
+       "output_type": "pyout",
+
+       "prompt_number": 26,
+
+       "text": [
+
+        "         fixed acidity  volatile acidity  citric acid  residual sugar  \\\n",
+
+        "quality                                                                 \n",
+
+        "3             8.360000          0.884500     0.171000        2.635000   \n",
+
+        "4             7.779245          0.693962     0.174151        2.694340   \n",
+
+        "5             8.167254          0.577041     0.243686        2.528855   \n",
+
+        "6             8.347179          0.497484     0.273824        2.477194   \n",
+
+        "7             8.872362          0.403920     0.375176        2.720603   \n",
+
+        "8             8.566667          0.423333     0.391111        2.577778   \n",
+
+        "\n",
+
+        "         chlorides  free sulfur dioxide  total sulfur dioxide   density  \\\n",
+
+        "quality                                                                   \n",
+
+        "3         0.122500            11.000000             24.900000  0.997464   \n",
+
+        "4         0.090679            12.264151             36.245283  0.996542   \n",
+
+        "5         0.092736            16.983847             56.513950  0.997104   \n",
+
+        "6         0.084956            15.711599             40.869906  0.996615   \n",
+
+        "7         0.076588            14.045226             35.020101  0.996104   \n",
+
+        "8         0.068444            13.277778             33.444444  0.995212   \n",
+
+        "\n",
+
+        "               pH  sulphates    alcohol  \n",
+
+        "quality                                  \n",
+
+        "3        3.398000   0.570000   9.955000  \n",
+
+        "4        3.381509   0.596415  10.265094  \n",
+
+        "5        3.304949   0.620969   9.899706  \n",
+
+        "6        3.318072   0.675329  10.629519  \n",
+
+        "7        3.290754   0.741256  11.465913  \n",
+
+        "8        3.267222   0.767778  12.094444  "
+
+       ]
+
+      }
+
+     ],
+
+     "prompt_number": 26
+
+    },
+
+    {
+
+     "cell_type": "code",
+
+     "collapsed": false,
+
+     "input": [
+
+      "# Let's go back to the original dframe\n",
+
+      "dframe_wine.head()"
+
+     ],
+
+     "language": "python",
+
+     "metadata": {},
+
+     "outputs": [
+
+      {
+
+       "html": [
+
+        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
+
+        "<table border=\"1\" class=\"dataframe\">\n",
+
+        "  <thead>\n",
+
+        "    <tr style=\"text-align: right;\">\n",
+
+        "      <th></th>\n",
+
+        "      <th>fixed acidity</th>\n",
+
+        "      <th>volatile acidity</th>\n",
+
+        "      <th>citric acid</th>\n",
+
+        "      <th>residual sugar</th>\n",
+
+        "      <th>chlorides</th>\n",
+
+        "      <th>free sulfur dioxide</th>\n",
+
+        "      <th>total sulfur dioxide</th>\n",
+
+        "      <th>density</th>\n",
+
+        "      <th>pH</th>\n",
+
+        "      <th>sulphates</th>\n",
+
+        "      <th>alcohol</th>\n",
+
+        "      <th>quality</th>\n",
+
+        "    </tr>\n",
+
+        "  </thead>\n",
+
+        "  <tbody>\n",
+
+        "    <tr>\n",
+
+        "      <th>0</th>\n",
+
+        "      <td>  7.4</td>\n",
+
+        "      <td> 0.70</td>\n",
+
+        "      <td> 0.00</td>\n",
+
+        "      <td> 1.9</td>\n",
+
+        "      <td> 0.076</td>\n",
+
+        "      <td> 11</td>\n",
+
+        "      <td> 34</td>\n",
+
+        "      <td> 0.9978</td>\n",
+
+        "      <td> 3.51</td>\n",
+
+        "      <td> 0.56</td>\n",
+
+        "      <td> 9.4</td>\n",
+
+        "      <td> 5</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>1</th>\n",
+
+        "      <td>  7.8</td>\n",
+
+        "      <td> 0.88</td>\n",
+
+        "      <td> 0.00</td>\n",
+
+        "      <td> 2.6</td>\n",
+
+        "      <td> 0.098</td>\n",
+
+        "      <td> 25</td>\n",
+
+        "      <td> 67</td>\n",
+
+        "      <td> 0.9968</td>\n",
+
+        "      <td> 3.20</td>\n",
+
+        "      <td> 0.68</td>\n",
+
+        "      <td> 9.8</td>\n",
+
+        "      <td> 5</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>2</th>\n",
+
+        "      <td>  7.8</td>\n",
+
+        "      <td> 0.76</td>\n",
+
+        "      <td> 0.04</td>\n",
+
+        "      <td> 2.3</td>\n",
+
+        "      <td> 0.092</td>\n",
+
+        "      <td> 15</td>\n",
+
+        "      <td> 54</td>\n",
+
+        "      <td> 0.9970</td>\n",
+
+        "      <td> 3.26</td>\n",
+
+        "      <td> 0.65</td>\n",
+
+        "      <td> 9.8</td>\n",
+
+        "      <td> 5</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>3</th>\n",
+
+        "      <td> 11.2</td>\n",
+
+        "      <td> 0.28</td>\n",
+
+        "      <td> 0.56</td>\n",
+
+        "      <td> 1.9</td>\n",
+
+        "      <td> 0.075</td>\n",
+
+        "      <td> 17</td>\n",
+
+        "      <td> 60</td>\n",
+
+        "      <td> 0.9980</td>\n",
+
+        "      <td> 3.16</td>\n",
+
+        "      <td> 0.58</td>\n",
+
+        "      <td> 9.8</td>\n",
+
+        "      <td> 6</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>4</th>\n",
+
+        "      <td>  7.4</td>\n",
+
+        "      <td> 0.70</td>\n",
+
+        "      <td> 0.00</td>\n",
+
+        "      <td> 1.9</td>\n",
+
+        "      <td> 0.076</td>\n",
+
+        "      <td> 11</td>\n",
+
+        "      <td> 34</td>\n",
+
+        "      <td> 0.9978</td>\n",
+
+        "      <td> 3.51</td>\n",
+
+        "      <td> 0.56</td>\n",
+
+        "      <td> 9.4</td>\n",
+
+        "      <td> 5</td>\n",
+
+        "    </tr>\n",
+
+        "  </tbody>\n",
+
+        "</table>\n",
+
+        "</div>"
+
+       ],
+
+       "metadata": {},
+
+       "output_type": "pyout",
+
+       "prompt_number": 27,
+
+       "text": [
+
+        "   fixed acidity  volatile acidity  citric acid  residual sugar  chlorides  \\\n",
+
+        "0            7.4              0.70         0.00             1.9      0.076   \n",
+
+        "1            7.8              0.88         0.00             2.6      0.098   \n",
+
+        "2            7.8              0.76         0.04             2.3      0.092   \n",
+
+        "3           11.2              0.28         0.56             1.9      0.075   \n",
+
+        "4            7.4              0.70         0.00             1.9      0.076   \n",
+
+        "\n",
+
+        "   free sulfur dioxide  total sulfur dioxide  density    pH  sulphates  \\\n",
+
+        "0                   11                    34   0.9978  3.51       0.56   \n",
+
+        "1                   25                    67   0.9968  3.20       0.68   \n",
+
+        "2                   15                    54   0.9970  3.26       0.65   \n",
+
+        "3                   17                    60   0.9980  3.16       0.58   \n",
+
+        "4                   11                    34   0.9978  3.51       0.56   \n",
+
+        "\n",
+
+        "   alcohol  quality  \n",
+
+        "0      9.4        5  \n",
+
+        "1      9.8        5  \n",
+
+        "2      9.8        5  \n",
+
+        "3      9.8        6  \n",
+
+        "4      9.4        5  "
+
+       ]
+
+      }
+
+     ],
+
+     "prompt_number": 27
+
+    },
+
+    {
+
+     "cell_type": "code",
+
+     "collapsed": false,
+
+     "input": [
+
+      "# Let's add a  quality to alcohol content ratio\n",
+
+      "dframe_wine['qual/alc ratio'] = dframe_wine['quality']/dframe_wine['alcohol']"
+
+     ],
+
+     "language": "python",
+
+     "metadata": {},
+
+     "outputs": [],
+
+     "prompt_number": 28
+
+    },
+
+    {
+
+     "cell_type": "code",
+
+     "collapsed": false,
+
+     "input": [
+
+      "# Show\n",
+
+      "dframe_wine.head()"
+
+     ],
+
+     "language": "python",
+
+     "metadata": {},
+
+     "outputs": [
+
+      {
+
+       "html": [
+
+        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
+
+        "<table border=\"1\" class=\"dataframe\">\n",
+
+        "  <thead>\n",
+
+        "    <tr style=\"text-align: right;\">\n",
+
+        "      <th></th>\n",
+
+        "      <th>fixed acidity</th>\n",
+
+        "      <th>volatile acidity</th>\n",
+
+        "      <th>citric acid</th>\n",
+
+        "      <th>residual sugar</th>\n",
+
+        "      <th>chlorides</th>\n",
+
+        "      <th>free sulfur dioxide</th>\n",
+
+        "      <th>total sulfur dioxide</th>\n",
+
+        "      <th>density</th>\n",
+
+        "      <th>pH</th>\n",
+
+        "      <th>sulphates</th>\n",
+
+        "      <th>alcohol</th>\n",
+
+        "      <th>quality</th>\n",
+
+        "      <th>qual/alc ratio</th>\n",
+
+        "    </tr>\n",
+
+        "  </thead>\n",
+
+        "  <tbody>\n",
+
+        "    <tr>\n",
+
+        "      <th>0</th>\n",
+
+        "      <td>  7.4</td>\n",
+
+        "      <td> 0.70</td>\n",
+
+        "      <td> 0.00</td>\n",
+
+        "      <td> 1.9</td>\n",
+
+        "      <td> 0.076</td>\n",
+
+        "      <td> 11</td>\n",
+
+        "      <td> 34</td>\n",
+
+        "      <td> 0.9978</td>\n",
+
+        "      <td> 3.51</td>\n",
+
+        "      <td> 0.56</td>\n",
+
+        "      <td> 9.4</td>\n",
+
+        "      <td> 5</td>\n",
+
+        "      <td> 0.531915</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>1</th>\n",
+
+        "      <td>  7.8</td>\n",
+
+        "      <td> 0.88</td>\n",
+
+        "      <td> 0.00</td>\n",
+
+        "      <td> 2.6</td>\n",
+
+        "      <td> 0.098</td>\n",
+
+        "      <td> 25</td>\n",
+
+        "      <td> 67</td>\n",
+
+        "      <td> 0.9968</td>\n",
+
+        "      <td> 3.20</td>\n",
+
+        "      <td> 0.68</td>\n",
+
+        "      <td> 9.8</td>\n",
+
+        "      <td> 5</td>\n",
+
+        "      <td> 0.510204</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>2</th>\n",
+
+        "      <td>  7.8</td>\n",
+
+        "      <td> 0.76</td>\n",
+
+        "      <td> 0.04</td>\n",
+
+        "      <td> 2.3</td>\n",
+
+        "      <td> 0.092</td>\n",
+
+        "      <td> 15</td>\n",
+
+        "      <td> 54</td>\n",
+
+        "      <td> 0.9970</td>\n",
+
+        "      <td> 3.26</td>\n",
+
+        "      <td> 0.65</td>\n",
+
+        "      <td> 9.8</td>\n",
+
+        "      <td> 5</td>\n",
+
+        "      <td> 0.510204</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>3</th>\n",
+
+        "      <td> 11.2</td>\n",
+
+        "      <td> 0.28</td>\n",
+
+        "      <td> 0.56</td>\n",
+
+        "      <td> 1.9</td>\n",
+
+        "      <td> 0.075</td>\n",
+
+        "      <td> 17</td>\n",
+
+        "      <td> 60</td>\n",
+
+        "      <td> 0.9980</td>\n",
+
+        "      <td> 3.16</td>\n",
+
+        "      <td> 0.58</td>\n",
+
+        "      <td> 9.8</td>\n",
+
+        "      <td> 6</td>\n",
+
+        "      <td> 0.612245</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>4</th>\n",
+
+        "      <td>  7.4</td>\n",
+
+        "      <td> 0.70</td>\n",
+
+        "      <td> 0.00</td>\n",
+
+        "      <td> 1.9</td>\n",
+
+        "      <td> 0.076</td>\n",
+
+        "      <td> 11</td>\n",
+
+        "      <td> 34</td>\n",
+
+        "      <td> 0.9978</td>\n",
+
+        "      <td> 3.51</td>\n",
+
+        "      <td> 0.56</td>\n",
+
+        "      <td> 9.4</td>\n",
+
+        "      <td> 5</td>\n",
+
+        "      <td> 0.531915</td>\n",
+
+        "    </tr>\n",
+
+        "  </tbody>\n",
+
+        "</table>\n",
+
+        "</div>"
+
+       ],
+
+       "metadata": {},
+
+       "output_type": "pyout",
+
+       "prompt_number": 29,
+
+       "text": [
+
+        "   fixed acidity  volatile acidity  citric acid  residual sugar  chlorides  \\\n",
+
+        "0            7.4              0.70         0.00             1.9      0.076   \n",
+
+        "1            7.8              0.88         0.00             2.6      0.098   \n",
+
+        "2            7.8              0.76         0.04             2.3      0.092   \n",
+
+        "3           11.2              0.28         0.56             1.9      0.075   \n",
+
+        "4            7.4              0.70         0.00             1.9      0.076   \n",
+
+        "\n",
+
+        "   free sulfur dioxide  total sulfur dioxide  density    pH  sulphates  \\\n",
+
+        "0                   11                    34   0.9978  3.51       0.56   \n",
+
+        "1                   25                    67   0.9968  3.20       0.68   \n",
+
+        "2                   15                    54   0.9970  3.26       0.65   \n",
+
+        "3                   17                    60   0.9980  3.16       0.58   \n",
+
+        "4                   11                    34   0.9978  3.51       0.56   \n",
+
+        "\n",
+
+        "   alcohol  quality  qual/alc ratio  \n",
+
+        "0      9.4        5        0.531915  \n",
+
+        "1      9.8        5        0.510204  \n",
+
+        "2      9.8        5        0.510204  \n",
+
+        "3      9.8        6        0.612245  \n",
+
+        "4      9.4        5        0.531915  "
+
+       ]
+
+      }
+
+     ],
+
+     "prompt_number": 29
+
+    },
+
+    {
+
+     "cell_type": "code",
+
+     "collapsed": false,
+
+     "input": [
+
+      "# We can also use pivot tables instead of groupby\n",
+
+      "\n",
+
+      "# Pivot table of quality\n",
+
+      "dframe_wine.pivot_table(index=['quality'])"
+
+     ],
+
+     "language": "python",
+
+     "metadata": {},
+
+     "outputs": [
+
+      {
+
+       "html": [
+
+        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
+
+        "<table border=\"1\" class=\"dataframe\">\n",
+
+        "  <thead>\n",
+
+        "    <tr style=\"text-align: right;\">\n",
+
+        "      <th></th>\n",
+
+        "      <th>alcohol</th>\n",
+
+        "      <th>chlorides</th>\n",
+
+        "      <th>citric acid</th>\n",
+
+        "      <th>density</th>\n",
+
+        "      <th>fixed acidity</th>\n",
+
+        "      <th>free sulfur dioxide</th>\n",
+
+        "      <th>pH</th>\n",
+
+        "      <th>qual/alc ratio</th>\n",
+
+        "      <th>residual sugar</th>\n",
+
+        "      <th>sulphates</th>\n",
+
+        "      <th>total sulfur dioxide</th>\n",
+
+        "      <th>volatile acidity</th>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>quality</th>\n",
+
+        "      <th></th>\n",
+
+        "      <th></th>\n",
+
+        "      <th></th>\n",
+
+        "      <th></th>\n",
+
+        "      <th></th>\n",
+
+        "      <th></th>\n",
+
+        "      <th></th>\n",
+
+        "      <th></th>\n",
+
+        "      <th></th>\n",
+
+        "      <th></th>\n",
+
+        "      <th></th>\n",
+
+        "      <th></th>\n",
+
+        "    </tr>\n",
+
+        "  </thead>\n",
+
+        "  <tbody>\n",
+
+        "    <tr>\n",
+
+        "      <th>3</th>\n",
+
+        "      <td>  9.955000</td>\n",
+
+        "      <td> 0.122500</td>\n",
+
+        "      <td> 0.171000</td>\n",
+
+        "      <td> 0.997464</td>\n",
+
+        "      <td> 8.360000</td>\n",
+
+        "      <td> 11.000000</td>\n",
+
+        "      <td> 3.398000</td>\n",
+
+        "      <td> 0.303286</td>\n",
+
+        "      <td> 2.635000</td>\n",
+
+        "      <td> 0.570000</td>\n",
+
+        "      <td> 24.900000</td>\n",
+
+        "      <td> 0.884500</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>4</th>\n",
+
+        "      <td> 10.265094</td>\n",
+
+        "      <td> 0.090679</td>\n",
+
+        "      <td> 0.174151</td>\n",
+
+        "      <td> 0.996542</td>\n",
+
+        "      <td> 7.779245</td>\n",
+
+        "      <td> 12.264151</td>\n",
+
+        "      <td> 3.381509</td>\n",
+
+        "      <td> 0.392724</td>\n",
+
+        "      <td> 2.694340</td>\n",
+
+        "      <td> 0.596415</td>\n",
+
+        "      <td> 36.245283</td>\n",
+
+        "      <td> 0.693962</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>5</th>\n",
+
+        "      <td>  9.899706</td>\n",
+
+        "      <td> 0.092736</td>\n",
+
+        "      <td> 0.243686</td>\n",
+
+        "      <td> 0.997104</td>\n",
+
+        "      <td> 8.167254</td>\n",
+
+        "      <td> 16.983847</td>\n",
+
+        "      <td> 3.304949</td>\n",
+
+        "      <td> 0.507573</td>\n",
+
+        "      <td> 2.528855</td>\n",
+
+        "      <td> 0.620969</td>\n",
+
+        "      <td> 56.513950</td>\n",
+
+        "      <td> 0.577041</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>6</th>\n",
+
+        "      <td> 10.629519</td>\n",
+
+        "      <td> 0.084956</td>\n",
+
+        "      <td> 0.273824</td>\n",
+
+        "      <td> 0.996615</td>\n",
+
+        "      <td> 8.347179</td>\n",
+
+        "      <td> 15.711599</td>\n",
+
+        "      <td> 3.318072</td>\n",
+
+        "      <td> 0.569801</td>\n",
+
+        "      <td> 2.477194</td>\n",
+
+        "      <td> 0.675329</td>\n",
+
+        "      <td> 40.869906</td>\n",
+
+        "      <td> 0.497484</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>7</th>\n",
+
+        "      <td> 11.465913</td>\n",
+
+        "      <td> 0.076588</td>\n",
+
+        "      <td> 0.375176</td>\n",
+
+        "      <td> 0.996104</td>\n",
+
+        "      <td> 8.872362</td>\n",
+
+        "      <td> 14.045226</td>\n",
+
+        "      <td> 3.290754</td>\n",
+
+        "      <td> 0.614855</td>\n",
+
+        "      <td> 2.720603</td>\n",
+
+        "      <td> 0.741256</td>\n",
+
+        "      <td> 35.020101</td>\n",
+
+        "      <td> 0.403920</td>\n",
+
+        "    </tr>\n",
+
+        "    <tr>\n",
+
+        "      <th>8</th>\n",
+
+        "      <td> 12.094444</td>\n",
+
+        "      <td> 0.068444</td>\n",
+
+        "      <td> 0.391111</td>\n",
+
+        "      <td> 0.995212</td>\n",
+
+        "      <td> 8.566667</td>\n",
+
+        "      <td> 13.277778</td>\n",
+
+        "      <td> 3.267222</td>\n",
+
+        "      <td> 0.668146</td>\n",
+
+        "      <td> 2.577778</td>\n",
+
+        "      <td> 0.767778</td>\n",
+
+        "      <td> 33.444444</td>\n",
+
+        "      <td> 0.423333</td>\n",
+
+        "    </tr>\n",
+
+        "  </tbody>\n",
+
+        "</table>\n",
+
+        "</div>"
+
+       ],
+
+       "metadata": {},
+
+       "output_type": "pyout",
+
+       "prompt_number": 32,
+
+       "text": [
+
+        "           alcohol  chlorides  citric acid   density  fixed acidity  \\\n",
+
+        "quality                                                               \n",
+
+        "3         9.955000   0.122500     0.171000  0.997464       8.360000   \n",
+
+        "4        10.265094   0.090679     0.174151  0.996542       7.779245   \n",
+
+        "5         9.899706   0.092736     0.243686  0.997104       8.167254   \n",
+
+        "6        10.629519   0.084956     0.273824  0.996615       8.347179   \n",
+
+        "7        11.465913   0.076588     0.375176  0.996104       8.872362   \n",
+
+        "8        12.094444   0.068444     0.391111  0.995212       8.566667   \n",
+
+        "\n",
+
+        "         free sulfur dioxide        pH  qual/alc ratio  residual sugar  \\\n",
+
+        "quality                                                                  \n",
+
+        "3                  11.000000  3.398000        0.303286        2.635000   \n",
+
+        "4                  12.264151  3.381509        0.392724        2.694340   \n",
+
+        "5                  16.983847  3.304949        0.507573        2.528855   \n",
+
+        "6                  15.711599  3.318072        0.569801        2.477194   \n",
+
+        "7                  14.045226  3.290754        0.614855        2.720603   \n",
+
+        "8                  13.277778  3.267222        0.668146        2.577778   \n",
+
+        "\n",
+
+        "         sulphates  total sulfur dioxide  volatile acidity  \n",
+
+        "quality                                                     \n",
+
+        "3         0.570000             24.900000          0.884500  \n",
+
+        "4         0.596415             36.245283          0.693962  \n",
+
+        "5         0.620969             56.513950          0.577041  \n",
+
+        "6         0.675329             40.869906          0.497484  \n",
+
+        "7         0.741256             35.020101          0.403920  \n",
+
+        "8         0.767778             33.444444          0.423333  "
+
+       ]
+
+      }
+
+     ],
+
+     "prompt_number": 32
+
+    },
+
+    {
+
+     "cell_type": "code",
+
+     "collapsed": false,
+
+     "input": [
+
+      "%matplotlib inline\n",
+
+      "dframe_wine.plot(kind='scatter',x='quality',y='alcohol')"
+
+     ],
+
+     "language": "python",
+
+     "metadata": {},
+
+     "outputs": [
+
+      {
+
+       "metadata": {},
+
+       "output_type": "pyout",
+
+       "prompt_number": 38,
+
+       "text": [
+
+        "<matplotlib.axes._subplots.AxesSubplot at 0xecb6470>"
+
+       ]
+
+      },
+
+      {
+
+       "metadata": {},
+
+       "output_type": "display_data",
+
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAX0AAAEPCAYAAACukxSbAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\naohP+s45V0N80nfOuRry/wEBAmAaegSRYQAAAABJRU5ErkJggg==\n",
+
+       "text": [
+
+        "<matplotlib.figure.Figure at 0xabda588>"
+
+       ]
+
+      }
+
+     ],
+
+     "prompt_number": 38
+
+    },
+
+    {
+
+     "cell_type": "markdown",
+
+     "metadata": {},
+
+     "source": [
+
+      "We can see that the data is probably better fit for a box plot for a more concise view of the data\n",
+
+      "See if you can figure out how to get a boxplot using the pandas documentation and what you have learned so far\n",
+
+      "\n",
+
+      "Don't worry if you can't quite figure it out just yet, the next section will cover all sorts of data visualizations!"
+
+     ]
+
+    },
+
+    {
+
+     "cell_type": "code",
+
+     "collapsed": false,
+
+     "input": [],
+
+     "language": "python",
+
+     "metadata": {},
+
+     "outputs": []
+
+    }
+
+   ],
+
+   "metadata": {}
+
+  }
+
+ ]
+
+}