conclusions_groupby.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Drawing Conclusions Using Groupby"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#Import packages\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "from matplotlib import pyplot as plt\n",
    "import matplotlib\n",
    "% matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 6497 entries, 0 to 6496\n",
      "Data columns (total 13 columns):\n",
      "fixed_acidity           6497 non-null float64\n",
      "volatile_acidity        6497 non-null float64\n",
      "citric_acid             6497 non-null float64\n",
      "residual_sugar          6497 non-null float64\n",
      "chlorides               6497 non-null float64\n",
      "free_sulfur_dioxide     6497 non-null float64\n",
      "total_sulfur_dioxide    6497 non-null float64\n",
      "density                 6497 non-null float64\n",
      "pH                      6497 non-null float64\n",
      "sulphates               6497 non-null float64\n",
      "alcohol                 6497 non-null float64\n",
      "quality                 6497 non-null int64\n",
      "color                   6497 non-null object\n",
      "dtypes: float64(11), int64(1), object(1)\n",
      "memory usage: 659.9+ KB\n"
     ]
    }
   ],
   "source": [
    "# Load `winequality_edited.csv`\n",
    "wine_df = pd.read_csv('winequality_edited.csv')\n",
    "wine_df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "### Is a certain type of wine associated with higher quality?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "color\n",
       "red      5.636023\n",
       "white    5.877909\n",
       "Name: quality, dtype: float64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Find the mean quality of each wine type (red and white) with groupby\n",
    "wine_df.groupby('color')['quality'].mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### What level of acidity receives the highest average rating?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<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>count</th>\n",
       "      <td>6497.000000</td>\n",
       "      <td>6497.000000</td>\n",
       "      <td>6497.000000</td>\n",
       "      <td>6497.000000</td>\n",
       "      <td>6497.000000</td>\n",
       "      <td>6497.000000</td>\n",
       "      <td>6497.000000</td>\n",
       "      <td>6497.000000</td>\n",
       "      <td>6497.000000</td>\n",
       "      <td>6497.000000</td>\n",
       "      <td>6497.000000</td>\n",
       "      <td>6497.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>7.215307</td>\n",
       "      <td>0.339666</td>\n",
       "      <td>0.318633</td>\n",
       "      <td>5.443235</td>\n",
       "      <td>0.056034</td>\n",
       "      <td>30.525319</td>\n",
       "      <td>115.744574</td>\n",
       "      <td>0.994697</td>\n",
       "      <td>3.218501</td>\n",
       "      <td>0.531268</td>\n",
       "      <td>10.491801</td>\n",
       "      <td>5.818378</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.296434</td>\n",
       "      <td>0.164636</td>\n",
       "      <td>0.145318</td>\n",
       "      <td>4.757804</td>\n",
       "      <td>0.035034</td>\n",
       "      <td>17.749400</td>\n",
       "      <td>56.521855</td>\n",
       "      <td>0.002999</td>\n",
       "      <td>0.160787</td>\n",
       "      <td>0.148806</td>\n",
       "      <td>1.192712</td>\n",
       "      <td>0.873255</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>3.800000</td>\n",
       "      <td>0.080000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.600000</td>\n",
       "      <td>0.009000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>0.987110</td>\n",
       "      <td>2.720000</td>\n",
       "      <td>0.220000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>3.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>6.400000</td>\n",
       "      <td>0.230000</td>\n",
       "      <td>0.250000</td>\n",
       "      <td>1.800000</td>\n",
       "      <td>0.038000</td>\n",
       "      <td>17.000000</td>\n",
       "      <td>77.000000</td>\n",
       "      <td>0.992340</td>\n",
       "      <td>3.110000</td>\n",
       "      <td>0.430000</td>\n",
       "      <td>9.500000</td>\n",
       "      <td>5.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>7.000000</td>\n",
       "      <td>0.290000</td>\n",
       "      <td>0.310000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0.047000</td>\n",
       "      <td>29.000000</td>\n",
       "      <td>118.000000</td>\n",
       "      <td>0.994890</td>\n",
       "      <td>3.210000</td>\n",
       "      <td>0.510000</td>\n",
       "      <td>10.300000</td>\n",
       "      <td>6.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>7.700000</td>\n",
       "      <td>0.400000</td>\n",
       "      <td>0.390000</td>\n",
       "      <td>8.100000</td>\n",
       "      <td>0.065000</td>\n",
       "      <td>41.000000</td>\n",
       "      <td>156.000000</td>\n",
       "      <td>0.996990</td>\n",
       "      <td>3.320000</td>\n",
       "      <td>0.600000</td>\n",
       "      <td>11.300000</td>\n",
       "      <td>6.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>15.900000</td>\n",
       "      <td>1.580000</td>\n",
       "      <td>1.660000</td>\n",
       "      <td>65.800000</td>\n",
       "      <td>0.611000</td>\n",
       "      <td>289.000000</td>\n",
       "      <td>440.000000</td>\n",
       "      <td>1.038980</td>\n",
       "      <td>4.010000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>14.900000</td>\n",
       "      <td>9.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       fixed_acidity  volatile_acidity  citric_acid  residual_sugar  \\\n",
       "count    6497.000000       6497.000000  6497.000000     6497.000000   \n",
       "mean        7.215307          0.339666     0.318633        5.443235   \n",
       "std         1.296434          0.164636     0.145318        4.757804   \n",
       "min         3.800000          0.080000     0.000000        0.600000   \n",
       "25%         6.400000          0.230000     0.250000        1.800000   \n",
       "50%         7.000000          0.290000     0.310000        3.000000   \n",
       "75%         7.700000          0.400000     0.390000        8.100000   \n",
       "max        15.900000          1.580000     1.660000       65.800000   \n",
       "\n",
       "         chlorides  free_sulfur_dioxide  total_sulfur_dioxide      density  \\\n",
       "count  6497.000000          6497.000000           6497.000000  6497.000000   \n",
       "mean      0.056034            30.525319            115.744574     0.994697   \n",
       "std       0.035034            17.749400             56.521855     0.002999   \n",
       "min       0.009000             1.000000              6.000000     0.987110   \n",
       "25%       0.038000            17.000000             77.000000     0.992340   \n",
       "50%       0.047000            29.000000            118.000000     0.994890   \n",
       "75%       0.065000            41.000000            156.000000     0.996990   \n",
       "max       0.611000           289.000000            440.000000     1.038980   \n",
       "\n",
       "                pH    sulphates      alcohol      quality  \n",
       "count  6497.000000  6497.000000  6497.000000  6497.000000  \n",
       "mean      3.218501     0.531268    10.491801     5.818378  \n",
       "std       0.160787     0.148806     1.192712     0.873255  \n",
       "min       2.720000     0.220000     8.000000     3.000000  \n",
       "25%       3.110000     0.430000     9.500000     5.000000  \n",
       "50%       3.210000     0.510000    10.300000     6.000000  \n",
       "75%       3.320000     0.600000    11.300000     6.000000  \n",
       "max       4.010000     2.000000    14.900000     9.000000  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# View the min, 25%, 50%, 75%, max pH values with Pandas describe\n",
    "# High: Lowest 25% of pH values\n",
    "# Moderately High: 25% - 50% of pH values\n",
    "# Medium: 50% - 75% of pH values\n",
    "# Low: 75% - max pH value\n",
    "wine_df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Bin edges that will be used to \"cut\" the data into groups\n",
    "bin_edges = [ 2.72, 3.11,3.21 , 3.32,4.01 ] # Fill in this list with five values you just found"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Labels for the four acidity level groups\n",
    "bin_names = [ 'High','Moderately High' ,'Meduim' ,'Low' ] # Name each acidity level category"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <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>color</th>\n",
       "      <th>acidity_levels</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>11.0</td>\n",
       "      <td>34.0</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>red</td>\n",
       "      <td>Low</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>25.0</td>\n",
       "      <td>67.0</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>red</td>\n",
       "      <td>Moderately High</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>15.0</td>\n",
       "      <td>54.0</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>red</td>\n",
       "      <td>Meduim</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>17.0</td>\n",
       "      <td>60.0</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>red</td>\n",
       "      <td>Moderately High</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>11.0</td>\n",
       "      <td>34.0</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>red</td>\n",
       "      <td>Low</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   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                 11.0                  34.0   0.9978  3.51       0.56   \n",
       "1                 25.0                  67.0   0.9968  3.20       0.68   \n",
       "2                 15.0                  54.0   0.9970  3.26       0.65   \n",
       "3                 17.0                  60.0   0.9980  3.16       0.58   \n",
       "4                 11.0                  34.0   0.9978  3.51       0.56   \n",
       "\n",
       "   alcohol  quality color   acidity_levels  \n",
       "0      9.4        5   red              Low  \n",
       "1      9.8        5   red  Moderately High  \n",
       "2      9.8        5   red           Meduim  \n",
       "3      9.8        6   red  Moderately High  \n",
       "4      9.4        5   red              Low  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Creates acidity_levels column\n",
    "wine_df['acidity_levels'] = pd.cut(wine_df['pH'], bin_edges, labels=bin_names)\n",
    "\n",
    "# Checks for successful creation of this column\n",
    "wine_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
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       "    <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",
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       "      <th>quality</th>\n",
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       "      <th>acidity_levels</th>\n",
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       "    <tr>\n",
       "      <th>High</th>\n",
       "      <td>7.543914</td>\n",
       "      <td>0.294683</td>\n",
       "      <td>0.370792</td>\n",
       "      <td>7.088876</td>\n",
       "      <td>0.055131</td>\n",
       "      <td>33.179965</td>\n",
       "      <td>129.897496</td>\n",
       "      <td>0.994708</td>\n",
       "      <td>3.029062</td>\n",
       "      <td>0.503937</td>\n",
       "      <td>10.330208</td>\n",
       "      <td>5.783343</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Moderately High</th>\n",
       "      <td>7.365064</td>\n",
       "      <td>0.318551</td>\n",
       "      <td>0.340548</td>\n",
       "      <td>5.931984</td>\n",
       "      <td>0.054666</td>\n",
       "      <td>33.229154</td>\n",
       "      <td>126.815886</td>\n",
       "      <td>0.994697</td>\n",
       "      <td>3.164833</td>\n",
       "      <td>0.509300</td>\n",
       "      <td>10.391073</td>\n",
       "      <td>5.784540</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Meduim</th>\n",
       "      <td>7.143566</td>\n",
       "      <td>0.346751</td>\n",
       "      <td>0.313585</td>\n",
       "      <td>4.721159</td>\n",
       "      <td>0.055715</td>\n",
       "      <td>28.983995</td>\n",
       "      <td>111.182138</td>\n",
       "      <td>0.994476</td>\n",
       "      <td>3.267010</td>\n",
       "      <td>0.541287</td>\n",
       "      <td>10.610369</td>\n",
       "      <td>5.850832</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Low</th>\n",
       "      <td>6.769949</td>\n",
       "      <td>0.403815</td>\n",
       "      <td>0.243901</td>\n",
       "      <td>3.848983</td>\n",
       "      <td>0.058777</td>\n",
       "      <td>26.327510</td>\n",
       "      <td>93.244917</td>\n",
       "      <td>0.994899</td>\n",
       "      <td>3.433348</td>\n",
       "      <td>0.574136</td>\n",
       "      <td>10.656057</td>\n",
       "      <td>5.859593</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 fixed_acidity  volatile_acidity  citric_acid  residual_sugar  \\\n",
       "acidity_levels                                                                  \n",
       "High                  7.543914          0.294683     0.370792        7.088876   \n",
       "Moderately High       7.365064          0.318551     0.340548        5.931984   \n",
       "Meduim                7.143566          0.346751     0.313585        4.721159   \n",
       "Low                   6.769949          0.403815     0.243901        3.848983   \n",
       "\n",
       "                 chlorides  free_sulfur_dioxide  total_sulfur_dioxide  \\\n",
       "acidity_levels                                                          \n",
       "High              0.055131            33.179965            129.897496   \n",
       "Moderately High   0.054666            33.229154            126.815886   \n",
       "Meduim            0.055715            28.983995            111.182138   \n",
       "Low               0.058777            26.327510             93.244917   \n",
       "\n",
       "                  density        pH  sulphates    alcohol   quality  \n",
       "acidity_levels                                                       \n",
       "High             0.994708  3.029062   0.503937  10.330208  5.783343  \n",
       "Moderately High  0.994697  3.164833   0.509300  10.391073  5.784540  \n",
       "Meduim           0.994476  3.267010   0.541287  10.610369  5.850832  \n",
       "Low              0.994899  3.433348   0.574136  10.656057  5.859593  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Find the mean quality of each acidity level with groupby\n",
    "wine_df.groupby('acidity_levels').mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Save changes for the next section\n",
    "wine_df.to_csv('winequality_edited.csv', index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## QUIZ Q&A"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Is the mean quality of red wine greater than, less than, or equal to that of white wine?\n",
    "Less"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### What level of acidity receives the highest average rating?\n",
    "Low acidity "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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