project002_winequality/winequality_analysis.ipynb

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   "source": [
    "# 观察数据集并提出问题\n",
    "\n",
    "数据集是两个 csv 文件，winequality-red.csv and winequality-white.csv"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 数据集包含下列字段\n",
    "\n",
    "- fixed acidity：固定酸度\n",
    "- volatile acidity：挥发性酸度\n",
    "- citric acid：柠檬酸\n",
    "- residual sugar：残糖\n",
    "- chlorides：氯化物\n",
    "- free sulfur dioxide：游离二氧化硫\t\n",
    "- total sulfur dioxide：总二氧化硫\n",
    "- density：密度\n",
    "- pH：PH 值\n",
    "- sulphates：硫酸盐\t\n",
    "- alcohol：酒精度\n",
    "- quality：质量，0 到 10 之间的得分（葡萄酒专家至少 3 次评估的中值）"
   ]
  },
  {
   "cell_type": "markdown",
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   "source": [
    "## 提出想了解的问题\n",
    "\n",
    "1. 两种类型的葡萄酒，哪种质量更高？\n",
    "2. 酒精度含量高的，是否质量也更高？\n",
    "3. PH 值和质量之间有什么变化趋势？\n",
    "4. 残糖含量越高，质量是否越高？\n",
    "5. 哪些化学性质与葡萄酒的质量相关程度更高？\n",
    "6. ..."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 查看数据基本特征"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 红葡萄酒数据集特征\n",
    "\n",
    "- 样本总数：1599\n",
    "- 列数：12\n",
    "- 是否有重复行：240行重复\n",
    "- 是否缺少值：没有缺失值\n",
    "- 质量等级唯一值的数量：df['quality'].value_counts()\n",
    "- 平均密度：0.9967"
   ]
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       "      <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",
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       "      <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",
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       "      <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",
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       "    <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",
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       "    <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",
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       "      <th>4</th>\n",
       "      <td>7.4</td>\n",
       "      <td>0.70</td>\n",
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       "      <td>0.9978</td>\n",
       "      <td>3.51</td>\n",
       "      <td>0.56</td>\n",
       "      <td>9.4</td>\n",
       "      <td>5</td>\n",
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       "   fixed acidity  volatile acidity  citric acid  ...  sulphates  alcohol  quality\n",
       "0            7.4              0.70         0.00  ...       0.56      9.4        5\n",
       "1            7.8              0.88         0.00  ...       0.68      9.8        5\n",
       "2            7.8              0.76         0.04  ...       0.65      9.8        5\n",
       "3           11.2              0.28         0.56  ...       0.58      9.8        6\n",
       "4            7.4              0.70         0.00  ...       0.56      9.4        5\n",
       "\n",
       "[5 rows x 12 columns]"
      ]
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   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "df = pd.read_csv('winequality-red.csv',sep=';')\n",
    "df.head()"
   ]
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       "      <th>fixed acidity</th>\n",
       "      <th>volatile acidity</th>\n",
       "      <th>citric acid</th>\n",
       "      <th>residual sugar</th>\n",
       "      <th>chlorides</th>\n",
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       "      <th>quality</th>\n",
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       "    <tr>\n",
       "      <th>1594</th>\n",
       "      <td>6.2</td>\n",
       "      <td>0.600</td>\n",
       "      <td>0.08</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.090</td>\n",
       "      <td>32.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>0.99490</td>\n",
       "      <td>3.45</td>\n",
       "      <td>0.58</td>\n",
       "      <td>10.5</td>\n",
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       "    <tr>\n",
       "      <th>1595</th>\n",
       "      <td>5.9</td>\n",
       "      <td>0.550</td>\n",
       "      <td>0.10</td>\n",
       "      <td>2.2</td>\n",
       "      <td>0.062</td>\n",
       "      <td>39.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>0.99512</td>\n",
       "      <td>3.52</td>\n",
       "      <td>0.76</td>\n",
       "      <td>11.2</td>\n",
       "      <td>6</td>\n",
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       "    <tr>\n",
       "      <th>1596</th>\n",
       "      <td>6.3</td>\n",
       "      <td>0.510</td>\n",
       "      <td>0.13</td>\n",
       "      <td>2.3</td>\n",
       "      <td>0.076</td>\n",
       "      <td>29.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>0.99574</td>\n",
       "      <td>3.42</td>\n",
       "      <td>0.75</td>\n",
       "      <td>11.0</td>\n",
       "      <td>6</td>\n",
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       "    <tr>\n",
       "      <th>1597</th>\n",
       "      <td>5.9</td>\n",
       "      <td>0.645</td>\n",
       "      <td>0.12</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.075</td>\n",
       "      <td>32.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>0.99547</td>\n",
       "      <td>3.57</td>\n",
       "      <td>0.71</td>\n",
       "      <td>10.2</td>\n",
       "      <td>5</td>\n",
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       "    <tr>\n",
       "      <th>1598</th>\n",
       "      <td>6.0</td>\n",
       "      <td>0.310</td>\n",
       "      <td>0.47</td>\n",
       "      <td>3.6</td>\n",
       "      <td>0.067</td>\n",
       "      <td>18.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>0.99549</td>\n",
       "      <td>3.39</td>\n",
       "      <td>0.66</td>\n",
       "      <td>11.0</td>\n",
       "      <td>6</td>\n",
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       "      fixed acidity  volatile acidity  citric acid  ...  sulphates  alcohol  quality\n",
       "1594            6.2             0.600         0.08  ...       0.58     10.5        5\n",
       "1595            5.9             0.550         0.10  ...       0.76     11.2        6\n",
       "1596            6.3             0.510         0.13  ...       0.75     11.0        6\n",
       "1597            5.9             0.645         0.12  ...       0.71     10.2        5\n",
       "1598            6.0             0.310         0.47  ...       0.66     11.0        6\n",
       "\n",
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   "source": [
    "df.tail()"
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       "      <th>fixed acidity</th>\n",
       "      <th>volatile acidity</th>\n",
       "      <th>citric acid</th>\n",
       "      <th>residual sugar</th>\n",
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       "      <th>4</th>\n",
       "      <td>7.4</td>\n",
       "      <td>0.700</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.90</td>\n",
       "      <td>0.076</td>\n",
       "      <td>11.0</td>\n",
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       "      <th>11</th>\n",
       "      <td>7.5</td>\n",
       "      <td>0.500</td>\n",
       "      <td>0.36</td>\n",
       "      <td>6.10</td>\n",
       "      <td>0.071</td>\n",
       "      <td>17.0</td>\n",
       "      <td>102.0</td>\n",
       "      <td>0.99780</td>\n",
       "      <td>3.35</td>\n",
       "      <td>0.80</td>\n",
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       "      <th>27</th>\n",
       "      <td>7.9</td>\n",
       "      <td>0.430</td>\n",
       "      <td>0.21</td>\n",
       "      <td>1.60</td>\n",
       "      <td>0.106</td>\n",
       "      <td>10.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>0.99660</td>\n",
       "      <td>3.17</td>\n",
       "      <td>0.91</td>\n",
       "      <td>9.5</td>\n",
       "      <td>5</td>\n",
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       "      <th>40</th>\n",
       "      <td>7.3</td>\n",
       "      <td>0.450</td>\n",
       "      <td>0.36</td>\n",
       "      <td>5.90</td>\n",
       "      <td>0.074</td>\n",
       "      <td>12.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>0.99780</td>\n",
       "      <td>3.33</td>\n",
       "      <td>0.83</td>\n",
       "      <td>10.5</td>\n",
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       "      <th>65</th>\n",
       "      <td>7.2</td>\n",
       "      <td>0.725</td>\n",
       "      <td>0.05</td>\n",
       "      <td>4.65</td>\n",
       "      <td>0.086</td>\n",
       "      <td>4.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>0.99620</td>\n",
       "      <td>3.41</td>\n",
       "      <td>0.39</td>\n",
       "      <td>10.9</td>\n",
       "      <td>5</td>\n",
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       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>8.8</td>\n",
       "      <td>0.410</td>\n",
       "      <td>0.64</td>\n",
       "      <td>2.20</td>\n",
       "      <td>0.093</td>\n",
       "      <td>9.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>0.99860</td>\n",
       "      <td>3.54</td>\n",
       "      <td>0.66</td>\n",
       "      <td>10.5</td>\n",
       "      <td>5</td>\n",
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       "    <tr>\n",
       "      <th>91</th>\n",
       "      <td>8.6</td>\n",
       "      <td>0.490</td>\n",
       "      <td>0.28</td>\n",
       "      <td>1.90</td>\n",
       "      <td>0.110</td>\n",
       "      <td>20.0</td>\n",
       "      <td>136.0</td>\n",
       "      <td>0.99720</td>\n",
       "      <td>2.93</td>\n",
       "      <td>1.95</td>\n",
       "      <td>9.9</td>\n",
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       "      <th>93</th>\n",
       "      <td>7.7</td>\n",
       "      <td>0.490</td>\n",
       "      <td>0.26</td>\n",
       "      <td>1.90</td>\n",
       "      <td>0.062</td>\n",
       "      <td>9.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>0.99660</td>\n",
       "      <td>3.39</td>\n",
       "      <td>0.64</td>\n",
       "      <td>9.6</td>\n",
       "      <td>5</td>\n",
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       "      <th>102</th>\n",
       "      <td>8.1</td>\n",
       "      <td>0.545</td>\n",
       "      <td>0.18</td>\n",
       "      <td>1.90</td>\n",
       "      <td>0.080</td>\n",
       "      <td>13.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0.99720</td>\n",
       "      <td>3.30</td>\n",
       "      <td>0.59</td>\n",
       "      <td>9.0</td>\n",
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       "      <th>105</th>\n",
       "      <td>8.1</td>\n",
       "      <td>0.575</td>\n",
       "      <td>0.22</td>\n",
       "      <td>2.10</td>\n",
       "      <td>0.077</td>\n",
       "      <td>12.0</td>\n",
       "      <td>65.0</td>\n",
       "      <td>0.99670</td>\n",
       "      <td>3.29</td>\n",
       "      <td>0.51</td>\n",
       "      <td>9.2</td>\n",
       "      <td>5</td>\n",
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       "    <tr>\n",
       "      <th>114</th>\n",
       "      <td>7.8</td>\n",
       "      <td>0.560</td>\n",
       "      <td>0.19</td>\n",
       "      <td>1.80</td>\n",
       "      <td>0.104</td>\n",
       "      <td>12.0</td>\n",
       "      <td>47.0</td>\n",
       "      <td>0.99640</td>\n",
       "      <td>3.19</td>\n",
       "      <td>0.93</td>\n",
       "      <td>9.5</td>\n",
       "      <td>5</td>\n",
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       "    <tr>\n",
       "      <th>121</th>\n",
       "      <td>8.8</td>\n",
       "      <td>0.550</td>\n",
       "      <td>0.04</td>\n",
       "      <td>2.20</td>\n",
       "      <td>0.119</td>\n",
       "      <td>14.0</td>\n",
       "      <td>56.0</td>\n",
       "      <td>0.99620</td>\n",
       "      <td>3.21</td>\n",
       "      <td>0.60</td>\n",
       "      <td>10.9</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132</th>\n",
       "      <td>5.6</td>\n",
       "      <td>0.500</td>\n",
       "      <td>0.09</td>\n",
       "      <td>2.30</td>\n",
       "      <td>0.049</td>\n",
       "      <td>17.0</td>\n",
       "      <td>99.0</td>\n",
       "      <td>0.99370</td>\n",
       "      <td>3.63</td>\n",
       "      <td>0.63</td>\n",
       "      <td>13.0</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>140</th>\n",
       "      <td>8.4</td>\n",
       "      <td>0.745</td>\n",
       "      <td>0.11</td>\n",
       "      <td>1.90</td>\n",
       "      <td>0.090</td>\n",
       "      <td>16.0</td>\n",
       "      <td>63.0</td>\n",
       "      <td>0.99650</td>\n",
       "      <td>3.19</td>\n",
       "      <td>0.82</td>\n",
       "      <td>9.6</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>141</th>\n",
       "      <td>8.3</td>\n",
       "      <td>0.715</td>\n",
       "      <td>0.15</td>\n",
       "      <td>1.80</td>\n",
       "      <td>0.089</td>\n",
       "      <td>10.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>0.99680</td>\n",
       "      <td>3.23</td>\n",
       "      <td>0.77</td>\n",
       "      <td>9.5</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>144</th>\n",
       "      <td>5.2</td>\n",
       "      <td>0.340</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.80</td>\n",
       "      <td>0.050</td>\n",
       "      <td>27.0</td>\n",
       "      <td>63.0</td>\n",
       "      <td>0.99160</td>\n",
       "      <td>3.68</td>\n",
       "      <td>0.79</td>\n",
       "      <td>14.0</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>153</th>\n",
       "      <td>7.5</td>\n",
       "      <td>0.600</td>\n",
       "      <td>0.03</td>\n",
       "      <td>1.80</td>\n",
       "      <td>0.095</td>\n",
       "      <td>25.0</td>\n",
       "      <td>99.0</td>\n",
       "      <td>0.99500</td>\n",
       "      <td>3.35</td>\n",
       "      <td>0.54</td>\n",
       "      <td>10.1</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>156</th>\n",
       "      <td>7.1</td>\n",
       "      <td>0.430</td>\n",
       "      <td>0.42</td>\n",
       "      <td>5.50</td>\n",
       "      <td>0.070</td>\n",
       "      <td>29.0</td>\n",
       "      <td>129.0</td>\n",
       "      <td>0.99730</td>\n",
       "      <td>3.42</td>\n",
       "      <td>0.72</td>\n",
       "      <td>10.5</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>157</th>\n",
       "      <td>7.1</td>\n",
       "      <td>0.430</td>\n",
       "      <td>0.42</td>\n",
       "      <td>5.50</td>\n",
       "      <td>0.071</td>\n",
       "      <td>28.0</td>\n",
       "      <td>128.0</td>\n",
       "      <td>0.99730</td>\n",
       "      <td>3.42</td>\n",
       "      <td>0.71</td>\n",
       "      <td>10.5</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>8.0</td>\n",
       "      <td>0.420</td>\n",
       "      <td>0.17</td>\n",
       "      <td>2.00</td>\n",
       "      <td>0.073</td>\n",
       "      <td>6.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>0.99720</td>\n",
       "      <td>3.29</td>\n",
       "      <td>0.61</td>\n",
       "      <td>9.2</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>176</th>\n",
       "      <td>7.3</td>\n",
       "      <td>0.380</td>\n",
       "      <td>0.21</td>\n",
       "      <td>2.00</td>\n",
       "      <td>0.080</td>\n",
       "      <td>7.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0.99610</td>\n",
       "      <td>3.33</td>\n",
       "      <td>0.47</td>\n",
       "      <td>9.5</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180</th>\n",
       "      <td>8.8</td>\n",
       "      <td>0.610</td>\n",
       "      <td>0.14</td>\n",
       "      <td>2.40</td>\n",
       "      <td>0.067</td>\n",
       "      <td>10.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>0.99690</td>\n",
       "      <td>3.19</td>\n",
       "      <td>0.59</td>\n",
       "      <td>9.5</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>194</th>\n",
       "      <td>7.6</td>\n",
       "      <td>0.550</td>\n",
       "      <td>0.21</td>\n",
       "      <td>2.20</td>\n",
       "      <td>0.071</td>\n",
       "      <td>7.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>0.99640</td>\n",
       "      <td>3.28</td>\n",
       "      <td>0.55</td>\n",
       "      <td>9.7</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>206</th>\n",
       "      <td>12.8</td>\n",
       "      <td>0.300</td>\n",
       "      <td>0.74</td>\n",
       "      <td>2.60</td>\n",
       "      <td>0.095</td>\n",
       "      <td>9.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>0.99940</td>\n",
       "      <td>3.20</td>\n",
       "      <td>0.77</td>\n",
       "      <td>10.8</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>228</th>\n",
       "      <td>7.7</td>\n",
       "      <td>0.430</td>\n",
       "      <td>0.25</td>\n",
       "      <td>2.60</td>\n",
       "      <td>0.073</td>\n",
       "      <td>29.0</td>\n",
       "      <td>63.0</td>\n",
       "      <td>0.99615</td>\n",
       "      <td>3.37</td>\n",
       "      <td>0.58</td>\n",
       "      <td>10.5</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>233</th>\n",
       "      <td>6.9</td>\n",
       "      <td>0.520</td>\n",
       "      <td>0.25</td>\n",
       "      <td>2.60</td>\n",
       "      <td>0.081</td>\n",
       "      <td>10.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>0.99685</td>\n",
       "      <td>3.46</td>\n",
       "      <td>0.50</td>\n",
       "      <td>11.0</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>236</th>\n",
       "      <td>7.2</td>\n",
       "      <td>0.630</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.90</td>\n",
       "      <td>0.097</td>\n",
       "      <td>14.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>0.99675</td>\n",
       "      <td>3.37</td>\n",
       "      <td>0.58</td>\n",
       "      <td>9.0</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>238</th>\n",
       "      <td>7.2</td>\n",
       "      <td>0.630</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.90</td>\n",
       "      <td>0.097</td>\n",
       "      <td>14.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>0.99675</td>\n",
       "      <td>3.37</td>\n",
       "      <td>0.58</td>\n",
       "      <td>9.0</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>239</th>\n",
       "      <td>8.2</td>\n",
       "      <td>1.000</td>\n",
       "      <td>0.09</td>\n",
       "      <td>2.30</td>\n",
       "      <td>0.065</td>\n",
       "      <td>7.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>0.99685</td>\n",
       "      <td>3.32</td>\n",
       "      <td>0.55</td>\n",
       "      <td>9.0</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>244</th>\n",
       "      <td>15.0</td>\n",
       "      <td>0.210</td>\n",
       "      <td>0.44</td>\n",
       "      <td>2.20</td>\n",
       "      <td>0.075</td>\n",
       "      <td>10.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>1.00005</td>\n",
       "      <td>3.07</td>\n",
       "      <td>0.84</td>\n",
       "      <td>9.2</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1383</th>\n",
       "      <td>8.0</td>\n",
       "      <td>0.600</td>\n",
       "      <td>0.22</td>\n",
       "      <td>2.10</td>\n",
       "      <td>0.080</td>\n",
       "      <td>25.0</td>\n",
       "      <td>105.0</td>\n",
       "      <td>0.99613</td>\n",
       "      <td>3.30</td>\n",
       "      <td>0.49</td>\n",
       "      <td>9.9</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1387</th>\n",
       "      <td>7.4</td>\n",
       "      <td>0.640</td>\n",
       "      <td>0.07</td>\n",
       "      <td>1.80</td>\n",
       "      <td>0.100</td>\n",
       "      <td>8.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>0.99610</td>\n",
       "      <td>3.30</td>\n",
       "      <td>0.58</td>\n",
       "      <td>9.6</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1401</th>\n",
       "      <td>7.9</td>\n",
       "      <td>0.690</td>\n",
       "      <td>0.21</td>\n",
       "      <td>2.10</td>\n",
       "      <td>0.080</td>\n",
       "      <td>33.0</td>\n",
       "      <td>141.0</td>\n",
       "      <td>0.99620</td>\n",
       "      <td>3.25</td>\n",
       "      <td>0.51</td>\n",
       "      <td>9.9</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1409</th>\n",
       "      <td>6.0</td>\n",
       "      <td>0.510</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2.10</td>\n",
       "      <td>0.064</td>\n",
       "      <td>40.0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>0.99500</td>\n",
       "      <td>3.54</td>\n",
       "      <td>0.93</td>\n",
       "      <td>10.7</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1412</th>\n",
       "      <td>8.2</td>\n",
       "      <td>0.240</td>\n",
       "      <td>0.34</td>\n",
       "      <td>5.10</td>\n",
       "      <td>0.062</td>\n",
       "      <td>8.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>0.99740</td>\n",
       "      <td>3.22</td>\n",
       "      <td>0.94</td>\n",
       "      <td>10.9</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1416</th>\n",
       "      <td>10.0</td>\n",
       "      <td>0.320</td>\n",
       "      <td>0.59</td>\n",
       "      <td>2.20</td>\n",
       "      <td>0.077</td>\n",
       "      <td>3.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>0.99940</td>\n",
       "      <td>3.20</td>\n",
       "      <td>0.78</td>\n",
       "      <td>9.6</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1420</th>\n",
       "      <td>7.8</td>\n",
       "      <td>0.530</td>\n",
       "      <td>0.01</td>\n",
       "      <td>1.60</td>\n",
       "      <td>0.077</td>\n",
       "      <td>3.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>0.99500</td>\n",
       "      <td>3.16</td>\n",
       "      <td>0.46</td>\n",
       "      <td>9.8</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1425</th>\n",
       "      <td>8.3</td>\n",
       "      <td>0.260</td>\n",
       "      <td>0.37</td>\n",
       "      <td>1.40</td>\n",
       "      <td>0.076</td>\n",
       "      <td>8.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>0.99740</td>\n",
       "      <td>3.26</td>\n",
       "      <td>0.70</td>\n",
       "      <td>9.6</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1435</th>\n",
       "      <td>10.2</td>\n",
       "      <td>0.540</td>\n",
       "      <td>0.37</td>\n",
       "      <td>15.40</td>\n",
       "      <td>0.214</td>\n",
       "      <td>55.0</td>\n",
       "      <td>95.0</td>\n",
       "      <td>1.00369</td>\n",
       "      <td>3.18</td>\n",
       "      <td>0.77</td>\n",
       "      <td>9.0</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1446</th>\n",
       "      <td>6.9</td>\n",
       "      <td>0.630</td>\n",
       "      <td>0.02</td>\n",
       "      <td>1.90</td>\n",
       "      <td>0.078</td>\n",
       "      <td>18.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>0.99712</td>\n",
       "      <td>3.40</td>\n",
       "      <td>0.75</td>\n",
       "      <td>9.8</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1450</th>\n",
       "      <td>7.2</td>\n",
       "      <td>0.370</td>\n",
       "      <td>0.32</td>\n",
       "      <td>2.00</td>\n",
       "      <td>0.062</td>\n",
       "      <td>15.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>0.99470</td>\n",
       "      <td>3.23</td>\n",
       "      <td>0.73</td>\n",
       "      <td>11.3</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1457</th>\n",
       "      <td>7.6</td>\n",
       "      <td>0.490</td>\n",
       "      <td>0.33</td>\n",
       "      <td>1.90</td>\n",
       "      <td>0.074</td>\n",
       "      <td>27.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>0.99706</td>\n",
       "      <td>3.41</td>\n",
       "      <td>0.58</td>\n",
       "      <td>9.0</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1465</th>\n",
       "      <td>6.8</td>\n",
       "      <td>0.590</td>\n",
       "      <td>0.10</td>\n",
       "      <td>1.70</td>\n",
       "      <td>0.063</td>\n",
       "      <td>34.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>0.99580</td>\n",
       "      <td>3.41</td>\n",
       "      <td>0.67</td>\n",
       "      <td>9.7</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1468</th>\n",
       "      <td>7.3</td>\n",
       "      <td>0.480</td>\n",
       "      <td>0.32</td>\n",
       "      <td>2.10</td>\n",
       "      <td>0.062</td>\n",
       "      <td>31.0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>0.99728</td>\n",
       "      <td>3.30</td>\n",
       "      <td>0.65</td>\n",
       "      <td>10.0</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1476</th>\n",
       "      <td>9.9</td>\n",
       "      <td>0.500</td>\n",
       "      <td>0.50</td>\n",
       "      <td>13.80</td>\n",
       "      <td>0.205</td>\n",
       "      <td>48.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>1.00242</td>\n",
       "      <td>3.16</td>\n",
       "      <td>0.75</td>\n",
       "      <td>8.8</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1481</th>\n",
       "      <td>8.2</td>\n",
       "      <td>0.280</td>\n",
       "      <td>0.60</td>\n",
       "      <td>3.00</td>\n",
       "      <td>0.104</td>\n",
       "      <td>10.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>0.99828</td>\n",
       "      <td>3.39</td>\n",
       "      <td>0.68</td>\n",
       "      <td>10.6</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1491</th>\n",
       "      <td>5.6</td>\n",
       "      <td>0.540</td>\n",
       "      <td>0.04</td>\n",
       "      <td>1.70</td>\n",
       "      <td>0.049</td>\n",
       "      <td>5.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>0.99420</td>\n",
       "      <td>3.72</td>\n",
       "      <td>0.58</td>\n",
       "      <td>11.4</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1496</th>\n",
       "      <td>7.7</td>\n",
       "      <td>0.540</td>\n",
       "      <td>0.26</td>\n",
       "      <td>1.90</td>\n",
       "      <td>0.089</td>\n",
       "      <td>23.0</td>\n",
       "      <td>147.0</td>\n",
       "      <td>0.99636</td>\n",
       "      <td>3.26</td>\n",
       "      <td>0.59</td>\n",
       "      <td>9.7</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1499</th>\n",
       "      <td>6.9</td>\n",
       "      <td>0.740</td>\n",
       "      <td>0.03</td>\n",
       "      <td>2.30</td>\n",
       "      <td>0.054</td>\n",
       "      <td>7.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0.99508</td>\n",
       "      <td>3.45</td>\n",
       "      <td>0.63</td>\n",
       "      <td>11.5</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1507</th>\n",
       "      <td>7.5</td>\n",
       "      <td>0.380</td>\n",
       "      <td>0.57</td>\n",
       "      <td>2.30</td>\n",
       "      <td>0.106</td>\n",
       "      <td>5.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.99605</td>\n",
       "      <td>3.36</td>\n",
       "      <td>0.55</td>\n",
       "      <td>11.4</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1520</th>\n",
       "      <td>6.5</td>\n",
       "      <td>0.530</td>\n",
       "      <td>0.06</td>\n",
       "      <td>2.00</td>\n",
       "      <td>0.063</td>\n",
       "      <td>29.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>0.99489</td>\n",
       "      <td>3.38</td>\n",
       "      <td>0.83</td>\n",
       "      <td>10.3</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1522</th>\n",
       "      <td>6.1</td>\n",
       "      <td>0.320</td>\n",
       "      <td>0.25</td>\n",
       "      <td>2.30</td>\n",
       "      <td>0.071</td>\n",
       "      <td>23.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>0.99633</td>\n",
       "      <td>3.42</td>\n",
       "      <td>0.97</td>\n",
       "      <td>10.6</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1557</th>\n",
       "      <td>6.6</td>\n",
       "      <td>0.855</td>\n",
       "      <td>0.02</td>\n",
       "      <td>2.40</td>\n",
       "      <td>0.062</td>\n",
       "      <td>15.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>0.99627</td>\n",
       "      <td>3.54</td>\n",
       "      <td>0.60</td>\n",
       "      <td>11.0</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1560</th>\n",
       "      <td>7.8</td>\n",
       "      <td>0.600</td>\n",
       "      <td>0.26</td>\n",
       "      <td>2.00</td>\n",
       "      <td>0.080</td>\n",
       "      <td>31.0</td>\n",
       "      <td>131.0</td>\n",
       "      <td>0.99622</td>\n",
       "      <td>3.21</td>\n",
       "      <td>0.52</td>\n",
       "      <td>9.9</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1561</th>\n",
       "      <td>7.8</td>\n",
       "      <td>0.600</td>\n",
       "      <td>0.26</td>\n",
       "      <td>2.00</td>\n",
       "      <td>0.080</td>\n",
       "      <td>31.0</td>\n",
       "      <td>131.0</td>\n",
       "      <td>0.99622</td>\n",
       "      <td>3.21</td>\n",
       "      <td>0.52</td>\n",
       "      <td>9.9</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1563</th>\n",
       "      <td>7.2</td>\n",
       "      <td>0.695</td>\n",
       "      <td>0.13</td>\n",
       "      <td>2.00</td>\n",
       "      <td>0.076</td>\n",
       "      <td>12.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>0.99546</td>\n",
       "      <td>3.29</td>\n",
       "      <td>0.54</td>\n",
       "      <td>10.1</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1564</th>\n",
       "      <td>7.2</td>\n",
       "      <td>0.695</td>\n",
       "      <td>0.13</td>\n",
       "      <td>2.00</td>\n",
       "      <td>0.076</td>\n",
       "      <td>12.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>0.99546</td>\n",
       "      <td>3.29</td>\n",
       "      <td>0.54</td>\n",
       "      <td>10.1</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1567</th>\n",
       "      <td>7.2</td>\n",
       "      <td>0.695</td>\n",
       "      <td>0.13</td>\n",
       "      <td>2.00</td>\n",
       "      <td>0.076</td>\n",
       "      <td>12.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>0.99546</td>\n",
       "      <td>3.29</td>\n",
       "      <td>0.54</td>\n",
       "      <td>10.1</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1581</th>\n",
       "      <td>6.2</td>\n",
       "      <td>0.560</td>\n",
       "      <td>0.09</td>\n",
       "      <td>1.70</td>\n",
       "      <td>0.053</td>\n",
       "      <td>24.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>0.99402</td>\n",
       "      <td>3.54</td>\n",
       "      <td>0.60</td>\n",
       "      <td>11.3</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1596</th>\n",
       "      <td>6.3</td>\n",
       "      <td>0.510</td>\n",
       "      <td>0.13</td>\n",
       "      <td>2.30</td>\n",
       "      <td>0.076</td>\n",
       "      <td>29.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>0.99574</td>\n",
       "      <td>3.42</td>\n",
       "      <td>0.75</td>\n",
       "      <td>11.0</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>240 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      fixed acidity  volatile acidity  citric acid  ...  sulphates  alcohol  quality\n",
       "4               7.4             0.700         0.00  ...       0.56      9.4        5\n",
       "11              7.5             0.500         0.36  ...       0.80     10.5        5\n",
       "27              7.9             0.430         0.21  ...       0.91      9.5        5\n",
       "40              7.3             0.450         0.36  ...       0.83     10.5        5\n",
       "65              7.2             0.725         0.05  ...       0.39     10.9        5\n",
       "76              8.8             0.410         0.64  ...       0.66     10.5        5\n",
       "91              8.6             0.490         0.28  ...       1.95      9.9        6\n",
       "93              7.7             0.490         0.26  ...       0.64      9.6        5\n",
       "102             8.1             0.545         0.18  ...       0.59      9.0        6\n",
       "105             8.1             0.575         0.22  ...       0.51      9.2        5\n",
       "114             7.8             0.560         0.19  ...       0.93      9.5        5\n",
       "121             8.8             0.550         0.04  ...       0.60     10.9        6\n",
       "132             5.6             0.500         0.09  ...       0.63     13.0        5\n",
       "140             8.4             0.745         0.11  ...       0.82      9.6        5\n",
       "141             8.3             0.715         0.15  ...       0.77      9.5        5\n",
       "144             5.2             0.340         0.00  ...       0.79     14.0        6\n",
       "153             7.5             0.600         0.03  ...       0.54     10.1        5\n",
       "156             7.1             0.430         0.42  ...       0.72     10.5        5\n",
       "157             7.1             0.430         0.42  ...       0.71     10.5        5\n",
       "172             8.0             0.420         0.17  ...       0.61      9.2        6\n",
       "176             7.3             0.380         0.21  ...       0.47      9.5        5\n",
       "180             8.8             0.610         0.14  ...       0.59      9.5        5\n",
       "194             7.6             0.550         0.21  ...       0.55      9.7        5\n",
       "206            12.8             0.300         0.74  ...       0.77     10.8        7\n",
       "228             7.7             0.430         0.25  ...       0.58     10.5        6\n",
       "233             6.9             0.520         0.25  ...       0.50     11.0        5\n",
       "236             7.2             0.630         0.00  ...       0.58      9.0        6\n",
       "238             7.2             0.630         0.00  ...       0.58      9.0        6\n",
       "239             8.2             1.000         0.09  ...       0.55      9.0        6\n",
       "244            15.0             0.210         0.44  ...       0.84      9.2        7\n",
       "...             ...               ...          ...  ...        ...      ...      ...\n",
       "1383            8.0             0.600         0.22  ...       0.49      9.9        5\n",
       "1387            7.4             0.640         0.07  ...       0.58      9.6        5\n",
       "1401            7.9             0.690         0.21  ...       0.51      9.9        5\n",
       "1409            6.0             0.510         0.00  ...       0.93     10.7        6\n",
       "1412            8.2             0.240         0.34  ...       0.94     10.9        6\n",
       "1416           10.0             0.320         0.59  ...       0.78      9.6        5\n",
       "1420            7.8             0.530         0.01  ...       0.46      9.8        5\n",
       "1425            8.3             0.260         0.37  ...       0.70      9.6        6\n",
       "1435           10.2             0.540         0.37  ...       0.77      9.0        6\n",
       "1446            6.9             0.630         0.02  ...       0.75      9.8        5\n",
       "1450            7.2             0.370         0.32  ...       0.73     11.3        7\n",
       "1457            7.6             0.490         0.33  ...       0.58      9.0        5\n",
       "1465            6.8             0.590         0.10  ...       0.67      9.7        5\n",
       "1468            7.3             0.480         0.32  ...       0.65     10.0        7\n",
       "1476            9.9             0.500         0.50  ...       0.75      8.8        5\n",
       "1481            8.2             0.280         0.60  ...       0.68     10.6        5\n",
       "1491            5.6             0.540         0.04  ...       0.58     11.4        5\n",
       "1496            7.7             0.540         0.26  ...       0.59      9.7        5\n",
       "1499            6.9             0.740         0.03  ...       0.63     11.5        6\n",
       "1507            7.5             0.380         0.57  ...       0.55     11.4        6\n",
       "1520            6.5             0.530         0.06  ...       0.83     10.3        6\n",
       "1522            6.1             0.320         0.25  ...       0.97     10.6        5\n",
       "1557            6.6             0.855         0.02  ...       0.60     11.0        6\n",
       "1560            7.8             0.600         0.26  ...       0.52      9.9        5\n",
       "1561            7.8             0.600         0.26  ...       0.52      9.9        5\n",
       "1563            7.2             0.695         0.13  ...       0.54     10.1        5\n",
       "1564            7.2             0.695         0.13  ...       0.54     10.1        5\n",
       "1567            7.2             0.695         0.13  ...       0.54     10.1        5\n",
       "1581            6.2             0.560         0.09  ...       0.60     11.3        5\n",
       "1596            6.3             0.510         0.13  ...       0.75     11.0        6\n",
       "\n",
       "[240 rows x 12 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.duplicated() == True]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-16T03:36:33.135710Z",
     "start_time": "2020-01-16T03:36:33.122109Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "fixed acidity           0\n",
       "volatile acidity        0\n",
       "citric acid             0\n",
       "residual sugar          0\n",
       "chlorides               0\n",
       "free sulfur dioxide     0\n",
       "total sulfur dioxide    0\n",
       "density                 0\n",
       "pH                      0\n",
       "sulphates               0\n",
       "alcohol                 0\n",
       "quality                 0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-16T03:57:05.033146Z",
     "start_time": "2020-01-16T03:57:05.025419Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5    681\n",
       "6    638\n",
       "7    199\n",
       "4     53\n",
       "8     18\n",
       "3     10\n",
       "Name: quality, dtype: int64"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['quality'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-16T03:38:30.860061Z",
     "start_time": "2020-01-16T03:38:30.846812Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.996746679174484"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['density'].mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 白葡萄酒数据集特征\n",
    "\n",
    "- 样本总数：4898\n",
    "- 列数：12\n",
    "- 是否有重复行：937行重复\n",
    "- 是否缺少值：没有缺失值\n",
    "- 质量等级唯一值的数量：df['quality'].value_counts()\n",
    "- 平均密度：0.9940"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-16T04:07:19.624761Z",
     "start_time": "2020-01-16T04:07:19.563205Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>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>7.0</td>\n",
       "      <td>0.27</td>\n",
       "      <td>0.36</td>\n",
       "      <td>20.7</td>\n",
       "      <td>0.045</td>\n",
       "      <td>45.0</td>\n",
       "      <td>170.0</td>\n",
       "      <td>1.0010</td>\n",
       "      <td>3.00</td>\n",
       "      <td>0.45</td>\n",
       "      <td>8.8</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>6.3</td>\n",
       "      <td>0.30</td>\n",
       "      <td>0.34</td>\n",
       "      <td>1.6</td>\n",
       "      <td>0.049</td>\n",
       "      <td>14.0</td>\n",
       "      <td>132.0</td>\n",
       "      <td>0.9940</td>\n",
       "      <td>3.30</td>\n",
       "      <td>0.49</td>\n",
       "      <td>9.5</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>8.1</td>\n",
       "      <td>0.28</td>\n",
       "      <td>0.40</td>\n",
       "      <td>6.9</td>\n",
       "      <td>0.050</td>\n",
       "      <td>30.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>0.9951</td>\n",
       "      <td>3.26</td>\n",
       "      <td>0.44</td>\n",
       "      <td>10.1</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>7.2</td>\n",
       "      <td>0.23</td>\n",
       "      <td>0.32</td>\n",
       "      <td>8.5</td>\n",
       "      <td>0.058</td>\n",
       "      <td>47.0</td>\n",
       "      <td>186.0</td>\n",
       "      <td>0.9956</td>\n",
       "      <td>3.19</td>\n",
       "      <td>0.40</td>\n",
       "      <td>9.9</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>7.2</td>\n",
       "      <td>0.23</td>\n",
       "      <td>0.32</td>\n",
       "      <td>8.5</td>\n",
       "      <td>0.058</td>\n",
       "      <td>47.0</td>\n",
       "      <td>186.0</td>\n",
       "      <td>0.9956</td>\n",
       "      <td>3.19</td>\n",
       "      <td>0.40</td>\n",
       "      <td>9.9</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   fixed acidity  volatile acidity  citric acid  ...  sulphates  alcohol  quality\n",
       "0            7.0              0.27         0.36  ...       0.45      8.8        6\n",
       "1            6.3              0.30         0.34  ...       0.49      9.5        6\n",
       "2            8.1              0.28         0.40  ...       0.44     10.1        6\n",
       "3            7.2              0.23         0.32  ...       0.40      9.9        6\n",
       "4            7.2              0.23         0.32  ...       0.40      9.9        6\n",
       "\n",
       "[5 rows x 12 columns]"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "df = pd.read_csv('winequality-white.csv',sep=';')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
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     "end_time": "2020-01-16T04:07:37.594626Z",
     "start_time": "2020-01-16T04:07:37.550338Z"
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       "  <thead>\n",
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       "      <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",
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       "      <th>density</th>\n",
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       "      <th>sulphates</th>\n",
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       "      <th>quality</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4893</th>\n",
       "      <td>6.2</td>\n",
       "      <td>0.21</td>\n",
       "      <td>0.29</td>\n",
       "      <td>1.6</td>\n",
       "      <td>0.039</td>\n",
       "      <td>24.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>0.99114</td>\n",
       "      <td>3.27</td>\n",
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       "      <th>4894</th>\n",
       "      <td>6.6</td>\n",
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       "      <td>0.36</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.047</td>\n",
       "      <td>57.0</td>\n",
       "      <td>168.0</td>\n",
       "      <td>0.99490</td>\n",
       "      <td>3.15</td>\n",
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       "      <th>4895</th>\n",
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       "      <td>0.24</td>\n",
       "      <td>0.19</td>\n",
       "      <td>1.2</td>\n",
       "      <td>0.041</td>\n",
       "      <td>30.0</td>\n",
       "      <td>111.0</td>\n",
       "      <td>0.99254</td>\n",
       "      <td>2.99</td>\n",
       "      <td>0.46</td>\n",
       "      <td>9.4</td>\n",
       "      <td>6</td>\n",
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       "    <tr>\n",
       "      <th>4896</th>\n",
       "      <td>5.5</td>\n",
       "      <td>0.29</td>\n",
       "      <td>0.30</td>\n",
       "      <td>1.1</td>\n",
       "      <td>0.022</td>\n",
       "      <td>20.0</td>\n",
       "      <td>110.0</td>\n",
       "      <td>0.98869</td>\n",
       "      <td>3.34</td>\n",
       "      <td>0.38</td>\n",
       "      <td>12.8</td>\n",
       "      <td>7</td>\n",
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       "    <tr>\n",
       "      <th>4897</th>\n",
       "      <td>6.0</td>\n",
       "      <td>0.21</td>\n",
       "      <td>0.38</td>\n",
       "      <td>0.8</td>\n",
       "      <td>0.020</td>\n",
       "      <td>22.0</td>\n",
       "      <td>98.0</td>\n",
       "      <td>0.98941</td>\n",
       "      <td>3.26</td>\n",
       "      <td>0.32</td>\n",
       "      <td>11.8</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      fixed acidity  volatile acidity  citric acid  ...  sulphates  alcohol  quality\n",
       "4893            6.2              0.21         0.29  ...       0.50     11.2        6\n",
       "4894            6.6              0.32         0.36  ...       0.46      9.6        5\n",
       "4895            6.5              0.24         0.19  ...       0.46      9.4        6\n",
       "4896            5.5              0.29         0.30  ...       0.38     12.8        7\n",
       "4897            6.0              0.21         0.38  ...       0.32     11.8        6\n",
       "\n",
       "[5 rows x 12 columns]"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "df.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-16T04:09:08.476891Z",
     "start_time": "2020-01-16T04:09:08.401876Z"
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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",
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       "      <th>alcohol</th>\n",
       "      <th>quality</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>7.2</td>\n",
       "      <td>0.230</td>\n",
       "      <td>0.32</td>\n",
       "      <td>8.50</td>\n",
       "      <td>0.058</td>\n",
       "      <td>47.0</td>\n",
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       "      <td>3.19</td>\n",
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       "      <th>5</th>\n",
       "      <td>8.1</td>\n",
       "      <td>0.280</td>\n",
       "      <td>0.40</td>\n",
       "      <td>6.90</td>\n",
       "      <td>0.050</td>\n",
       "      <td>30.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>0.99510</td>\n",
       "      <td>3.26</td>\n",
       "      <td>0.44</td>\n",
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       "      <th>7</th>\n",
       "      <td>7.0</td>\n",
       "      <td>0.270</td>\n",
       "      <td>0.36</td>\n",
       "      <td>20.70</td>\n",
       "      <td>0.045</td>\n",
       "      <td>45.0</td>\n",
       "      <td>170.0</td>\n",
       "      <td>1.00100</td>\n",
       "      <td>3.00</td>\n",
       "      <td>0.45</td>\n",
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       "      <th>8</th>\n",
       "      <td>6.3</td>\n",
       "      <td>0.300</td>\n",
       "      <td>0.34</td>\n",
       "      <td>1.60</td>\n",
       "      <td>0.049</td>\n",
       "      <td>14.0</td>\n",
       "      <td>132.0</td>\n",
       "      <td>0.99400</td>\n",
       "      <td>3.30</td>\n",
       "      <td>0.49</td>\n",
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       "      <td>6</td>\n",
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       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>6.2</td>\n",
       "      <td>0.660</td>\n",
       "      <td>0.48</td>\n",
       "      <td>1.20</td>\n",
       "      <td>0.029</td>\n",
       "      <td>29.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>0.98920</td>\n",
       "      <td>3.33</td>\n",
       "      <td>0.39</td>\n",
       "      <td>12.800000</td>\n",
       "      <td>8</td>\n",
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       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>7.3</td>\n",
       "      <td>0.240</td>\n",
       "      <td>0.39</td>\n",
       "      <td>17.95</td>\n",
       "      <td>0.057</td>\n",
       "      <td>45.0</td>\n",
       "      <td>149.0</td>\n",
       "      <td>0.99990</td>\n",
       "      <td>3.21</td>\n",
       "      <td>0.36</td>\n",
       "      <td>8.600000</td>\n",
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       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>7.0</td>\n",
       "      <td>0.310</td>\n",
       "      <td>0.26</td>\n",
       "      <td>7.40</td>\n",
       "      <td>0.069</td>\n",
       "      <td>28.0</td>\n",
       "      <td>160.0</td>\n",
       "      <td>0.99540</td>\n",
       "      <td>3.13</td>\n",
       "      <td>0.46</td>\n",
       "      <td>9.800000</td>\n",
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       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>6.0</td>\n",
       "      <td>0.190</td>\n",
       "      <td>0.26</td>\n",
       "      <td>12.40</td>\n",
       "      <td>0.048</td>\n",
       "      <td>50.0</td>\n",
       "      <td>147.0</td>\n",
       "      <td>0.99720</td>\n",
       "      <td>3.30</td>\n",
       "      <td>0.36</td>\n",
       "      <td>8.900000</td>\n",
       "      <td>6</td>\n",
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       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>6.6</td>\n",
       "      <td>0.380</td>\n",
       "      <td>0.15</td>\n",
       "      <td>4.60</td>\n",
       "      <td>0.044</td>\n",
       "      <td>25.0</td>\n",
       "      <td>78.0</td>\n",
       "      <td>0.99310</td>\n",
       "      <td>3.11</td>\n",
       "      <td>0.38</td>\n",
       "      <td>10.200000</td>\n",
       "      <td>6</td>\n",
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       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>6.7</td>\n",
       "      <td>0.230</td>\n",
       "      <td>0.31</td>\n",
       "      <td>2.10</td>\n",
       "      <td>0.046</td>\n",
       "      <td>30.0</td>\n",
       "      <td>96.0</td>\n",
       "      <td>0.99260</td>\n",
       "      <td>3.33</td>\n",
       "      <td>0.64</td>\n",
       "      <td>10.700000</td>\n",
       "      <td>8</td>\n",
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       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>7.4</td>\n",
       "      <td>0.240</td>\n",
       "      <td>0.29</td>\n",
       "      <td>10.10</td>\n",
       "      <td>0.050</td>\n",
       "      <td>21.0</td>\n",
       "      <td>105.0</td>\n",
       "      <td>0.99620</td>\n",
       "      <td>3.13</td>\n",
       "      <td>0.35</td>\n",
       "      <td>9.500000</td>\n",
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       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>7.1</td>\n",
       "      <td>0.430</td>\n",
       "      <td>0.61</td>\n",
       "      <td>11.80</td>\n",
       "      <td>0.045</td>\n",
       "      <td>54.0</td>\n",
       "      <td>155.0</td>\n",
       "      <td>0.99740</td>\n",
       "      <td>3.11</td>\n",
       "      <td>0.45</td>\n",
       "      <td>8.700000</td>\n",
       "      <td>5</td>\n",
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       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>7.1</td>\n",
       "      <td>0.440</td>\n",
       "      <td>0.62</td>\n",
       "      <td>11.80</td>\n",
       "      <td>0.044</td>\n",
       "      <td>52.0</td>\n",
       "      <td>152.0</td>\n",
       "      <td>0.99750</td>\n",
       "      <td>3.12</td>\n",
       "      <td>0.46</td>\n",
       "      <td>8.700000</td>\n",
       "      <td>6</td>\n",
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       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>7.2</td>\n",
       "      <td>0.390</td>\n",
       "      <td>0.63</td>\n",
       "      <td>11.00</td>\n",
       "      <td>0.044</td>\n",
       "      <td>55.0</td>\n",
       "      <td>156.0</td>\n",
       "      <td>0.99740</td>\n",
       "      <td>3.09</td>\n",
       "      <td>0.44</td>\n",
       "      <td>8.700000</td>\n",
       "      <td>6</td>\n",
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       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>6.0</td>\n",
       "      <td>0.340</td>\n",
       "      <td>0.66</td>\n",
       "      <td>15.90</td>\n",
       "      <td>0.046</td>\n",
       "      <td>26.0</td>\n",
       "      <td>164.0</td>\n",
       "      <td>0.99790</td>\n",
       "      <td>3.14</td>\n",
       "      <td>0.50</td>\n",
       "      <td>8.800000</td>\n",
       "      <td>6</td>\n",
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       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>7.4</td>\n",
       "      <td>0.250</td>\n",
       "      <td>0.37</td>\n",
       "      <td>13.50</td>\n",
       "      <td>0.060</td>\n",
       "      <td>52.0</td>\n",
       "      <td>192.0</td>\n",
       "      <td>0.99750</td>\n",
       "      <td>3.00</td>\n",
       "      <td>0.44</td>\n",
       "      <td>9.100000</td>\n",
       "      <td>5</td>\n",
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       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>7.1</td>\n",
       "      <td>0.120</td>\n",
       "      <td>0.32</td>\n",
       "      <td>9.60</td>\n",
       "      <td>0.054</td>\n",
       "      <td>64.0</td>\n",
       "      <td>162.0</td>\n",
       "      <td>0.99620</td>\n",
       "      <td>3.40</td>\n",
       "      <td>0.41</td>\n",
       "      <td>9.400000</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108</th>\n",
       "      <td>7.1</td>\n",
       "      <td>0.230</td>\n",
       "      <td>0.35</td>\n",
       "      <td>16.50</td>\n",
       "      <td>0.040</td>\n",
       "      <td>60.0</td>\n",
       "      <td>171.0</td>\n",
       "      <td>0.99900</td>\n",
       "      <td>3.16</td>\n",
       "      <td>0.59</td>\n",
       "      <td>9.100000</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>114</th>\n",
       "      <td>6.7</td>\n",
       "      <td>0.410</td>\n",
       "      <td>0.34</td>\n",
       "      <td>9.20</td>\n",
       "      <td>0.049</td>\n",
       "      <td>29.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>0.99680</td>\n",
       "      <td>3.22</td>\n",
       "      <td>0.51</td>\n",
       "      <td>9.100000</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>118</th>\n",
       "      <td>7.2</td>\n",
       "      <td>0.310</td>\n",
       "      <td>0.50</td>\n",
       "      <td>13.30</td>\n",
       "      <td>0.056</td>\n",
       "      <td>68.0</td>\n",
       "      <td>195.0</td>\n",
       "      <td>0.99820</td>\n",
       "      <td>3.01</td>\n",
       "      <td>0.47</td>\n",
       "      <td>9.200000</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>131</th>\n",
       "      <td>6.5</td>\n",
       "      <td>0.240</td>\n",
       "      <td>0.32</td>\n",
       "      <td>7.60</td>\n",
       "      <td>0.038</td>\n",
       "      <td>48.0</td>\n",
       "      <td>203.0</td>\n",
       "      <td>0.99580</td>\n",
       "      <td>3.45</td>\n",
       "      <td>0.54</td>\n",
       "      <td>9.700000</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>141</th>\n",
       "      <td>7.1</td>\n",
       "      <td>0.370</td>\n",
       "      <td>0.67</td>\n",
       "      <td>10.50</td>\n",
       "      <td>0.045</td>\n",
       "      <td>49.0</td>\n",
       "      <td>155.0</td>\n",
       "      <td>0.99750</td>\n",
       "      <td>3.16</td>\n",
       "      <td>0.44</td>\n",
       "      <td>8.700000</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>152</th>\n",
       "      <td>6.9</td>\n",
       "      <td>0.250</td>\n",
       "      <td>0.30</td>\n",
       "      <td>4.10</td>\n",
       "      <td>0.054</td>\n",
       "      <td>23.0</td>\n",
       "      <td>116.0</td>\n",
       "      <td>0.99400</td>\n",
       "      <td>2.99</td>\n",
       "      <td>0.38</td>\n",
       "      <td>9.400000</td>\n",
       "      <td>6</td>\n",
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       "    <tr>\n",
       "      <th>156</th>\n",
       "      <td>7.4</td>\n",
       "      <td>0.240</td>\n",
       "      <td>0.42</td>\n",
       "      <td>14.00</td>\n",
       "      <td>0.066</td>\n",
       "      <td>48.0</td>\n",
       "      <td>198.0</td>\n",
       "      <td>0.99790</td>\n",
       "      <td>2.89</td>\n",
       "      <td>0.42</td>\n",
       "      <td>8.900000</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159</th>\n",
       "      <td>5.2</td>\n",
       "      <td>0.440</td>\n",
       "      <td>0.04</td>\n",
       "      <td>1.40</td>\n",
       "      <td>0.036</td>\n",
       "      <td>43.0</td>\n",
       "      <td>119.0</td>\n",
       "      <td>0.98940</td>\n",
       "      <td>3.36</td>\n",
       "      <td>0.33</td>\n",
       "      <td>12.100000</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>160</th>\n",
       "      <td>6.1</td>\n",
       "      <td>0.320</td>\n",
       "      <td>0.24</td>\n",
       "      <td>1.50</td>\n",
       "      <td>0.036</td>\n",
       "      <td>38.0</td>\n",
       "      <td>124.0</td>\n",
       "      <td>0.98980</td>\n",
       "      <td>3.29</td>\n",
       "      <td>0.42</td>\n",
       "      <td>12.400000</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>163</th>\n",
       "      <td>7.4</td>\n",
       "      <td>0.240</td>\n",
       "      <td>0.42</td>\n",
       "      <td>14.00</td>\n",
       "      <td>0.066</td>\n",
       "      <td>48.0</td>\n",
       "      <td>198.0</td>\n",
       "      <td>0.99790</td>\n",
       "      <td>2.89</td>\n",
       "      <td>0.42</td>\n",
       "      <td>8.900000</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>191</th>\n",
       "      <td>6.8</td>\n",
       "      <td>0.280</td>\n",
       "      <td>0.40</td>\n",
       "      <td>22.00</td>\n",
       "      <td>0.048</td>\n",
       "      <td>48.0</td>\n",
       "      <td>167.0</td>\n",
       "      <td>1.00100</td>\n",
       "      <td>2.93</td>\n",
       "      <td>0.50</td>\n",
       "      <td>8.700000</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>199</th>\n",
       "      <td>6.8</td>\n",
       "      <td>0.260</td>\n",
       "      <td>0.24</td>\n",
       "      <td>7.80</td>\n",
       "      <td>0.052</td>\n",
       "      <td>54.0</td>\n",
       "      <td>214.0</td>\n",
       "      <td>0.99610</td>\n",
       "      <td>3.13</td>\n",
       "      <td>0.47</td>\n",
       "      <td>8.900000</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>201</th>\n",
       "      <td>7.1</td>\n",
       "      <td>0.320</td>\n",
       "      <td>0.24</td>\n",
       "      <td>13.10</td>\n",
       "      <td>0.050</td>\n",
       "      <td>52.0</td>\n",
       "      <td>204.0</td>\n",
       "      <td>0.99800</td>\n",
       "      <td>3.10</td>\n",
       "      <td>0.49</td>\n",
       "      <td>8.800000</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4693</th>\n",
       "      <td>6.7</td>\n",
       "      <td>0.160</td>\n",
       "      <td>0.32</td>\n",
       "      <td>12.50</td>\n",
       "      <td>0.035</td>\n",
       "      <td>18.0</td>\n",
       "      <td>156.0</td>\n",
       "      <td>0.99666</td>\n",
       "      <td>2.88</td>\n",
       "      <td>0.36</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4694</th>\n",
       "      <td>6.9</td>\n",
       "      <td>0.190</td>\n",
       "      <td>0.31</td>\n",
       "      <td>19.25</td>\n",
       "      <td>0.043</td>\n",
       "      <td>38.0</td>\n",
       "      <td>167.0</td>\n",
       "      <td>0.99954</td>\n",
       "      <td>2.93</td>\n",
       "      <td>0.52</td>\n",
       "      <td>9.100000</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4697</th>\n",
       "      <td>6.7</td>\n",
       "      <td>0.350</td>\n",
       "      <td>0.32</td>\n",
       "      <td>9.00</td>\n",
       "      <td>0.032</td>\n",
       "      <td>29.0</td>\n",
       "      <td>113.0</td>\n",
       "      <td>0.99188</td>\n",
       "      <td>3.13</td>\n",
       "      <td>0.65</td>\n",
       "      <td>12.900000</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4700</th>\n",
       "      <td>6.8</td>\n",
       "      <td>0.300</td>\n",
       "      <td>0.33</td>\n",
       "      <td>12.80</td>\n",
       "      <td>0.041</td>\n",
       "      <td>60.0</td>\n",
       "      <td>168.0</td>\n",
       "      <td>0.99659</td>\n",
       "      <td>3.10</td>\n",
       "      <td>0.56</td>\n",
       "      <td>9.800000</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4702</th>\n",
       "      <td>6.4</td>\n",
       "      <td>0.690</td>\n",
       "      <td>0.09</td>\n",
       "      <td>7.60</td>\n",
       "      <td>0.044</td>\n",
       "      <td>34.0</td>\n",
       "      <td>144.0</td>\n",
       "      <td>0.99480</td>\n",
       "      <td>3.26</td>\n",
       "      <td>0.38</td>\n",
       "      <td>10.100000</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4712</th>\n",
       "      <td>5.7</td>\n",
       "      <td>0.270</td>\n",
       "      <td>0.16</td>\n",
       "      <td>9.00</td>\n",
       "      <td>0.053</td>\n",
       "      <td>32.0</td>\n",
       "      <td>111.0</td>\n",
       "      <td>0.99474</td>\n",
       "      <td>3.36</td>\n",
       "      <td>0.37</td>\n",
       "      <td>10.400000</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4714</th>\n",
       "      <td>6.1</td>\n",
       "      <td>0.220</td>\n",
       "      <td>0.40</td>\n",
       "      <td>1.85</td>\n",
       "      <td>0.031</td>\n",
       "      <td>25.0</td>\n",
       "      <td>111.0</td>\n",
       "      <td>0.98966</td>\n",
       "      <td>3.03</td>\n",
       "      <td>0.30</td>\n",
       "      <td>11.800000</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4719</th>\n",
       "      <td>6.7</td>\n",
       "      <td>0.150</td>\n",
       "      <td>0.32</td>\n",
       "      <td>7.90</td>\n",
       "      <td>0.034</td>\n",
       "      <td>17.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>0.99512</td>\n",
       "      <td>3.29</td>\n",
       "      <td>0.31</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4724</th>\n",
       "      <td>6.1</td>\n",
       "      <td>0.320</td>\n",
       "      <td>0.33</td>\n",
       "      <td>10.70</td>\n",
       "      <td>0.036</td>\n",
       "      <td>27.0</td>\n",
       "      <td>98.0</td>\n",
       "      <td>0.99521</td>\n",
       "      <td>3.34</td>\n",
       "      <td>0.52</td>\n",
       "      <td>10.200000</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4727</th>\n",
       "      <td>6.0</td>\n",
       "      <td>0.250</td>\n",
       "      <td>0.28</td>\n",
       "      <td>7.70</td>\n",
       "      <td>0.053</td>\n",
       "      <td>37.0</td>\n",
       "      <td>132.0</td>\n",
       "      <td>0.99489</td>\n",
       "      <td>3.06</td>\n",
       "      <td>0.50</td>\n",
       "      <td>9.400000</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4732</th>\n",
       "      <td>5.3</td>\n",
       "      <td>0.310</td>\n",
       "      <td>0.38</td>\n",
       "      <td>10.50</td>\n",
       "      <td>0.031</td>\n",
       "      <td>53.0</td>\n",
       "      <td>140.0</td>\n",
       "      <td>0.99321</td>\n",
       "      <td>3.34</td>\n",
       "      <td>0.46</td>\n",
       "      <td>11.700000</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4750</th>\n",
       "      <td>6.0</td>\n",
       "      <td>0.140</td>\n",
       "      <td>0.37</td>\n",
       "      <td>1.20</td>\n",
       "      <td>0.032</td>\n",
       "      <td>63.0</td>\n",
       "      <td>148.0</td>\n",
       "      <td>0.99185</td>\n",
       "      <td>3.32</td>\n",
       "      <td>0.44</td>\n",
       "      <td>11.200000</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4757</th>\n",
       "      <td>6.0</td>\n",
       "      <td>0.380</td>\n",
       "      <td>0.26</td>\n",
       "      <td>3.50</td>\n",
       "      <td>0.035</td>\n",
       "      <td>38.0</td>\n",
       "      <td>111.0</td>\n",
       "      <td>0.98872</td>\n",
       "      <td>3.18</td>\n",
       "      <td>0.47</td>\n",
       "      <td>13.600000</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4760</th>\n",
       "      <td>6.6</td>\n",
       "      <td>0.170</td>\n",
       "      <td>0.26</td>\n",
       "      <td>7.40</td>\n",
       "      <td>0.052</td>\n",
       "      <td>45.0</td>\n",
       "      <td>128.0</td>\n",
       "      <td>0.99388</td>\n",
       "      <td>3.16</td>\n",
       "      <td>0.37</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4769</th>\n",
       "      <td>6.8</td>\n",
       "      <td>0.270</td>\n",
       "      <td>0.30</td>\n",
       "      <td>13.00</td>\n",
       "      <td>0.047</td>\n",
       "      <td>69.0</td>\n",
       "      <td>160.0</td>\n",
       "      <td>0.99705</td>\n",
       "      <td>3.16</td>\n",
       "      <td>0.50</td>\n",
       "      <td>9.600000</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4770</th>\n",
       "      <td>6.8</td>\n",
       "      <td>0.270</td>\n",
       "      <td>0.30</td>\n",
       "      <td>13.00</td>\n",
       "      <td>0.047</td>\n",
       "      <td>69.0</td>\n",
       "      <td>160.0</td>\n",
       "      <td>0.99705</td>\n",
       "      <td>3.16</td>\n",
       "      <td>0.50</td>\n",
       "      <td>9.600000</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4771</th>\n",
       "      <td>6.8</td>\n",
       "      <td>0.270</td>\n",
       "      <td>0.30</td>\n",
       "      <td>13.00</td>\n",
       "      <td>0.047</td>\n",
       "      <td>69.0</td>\n",
       "      <td>160.0</td>\n",
       "      <td>0.99705</td>\n",
       "      <td>3.16</td>\n",
       "      <td>0.50</td>\n",
       "      <td>9.600000</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4783</th>\n",
       "      <td>6.7</td>\n",
       "      <td>0.300</td>\n",
       "      <td>0.50</td>\n",
       "      <td>12.10</td>\n",
       "      <td>0.045</td>\n",
       "      <td>38.0</td>\n",
       "      <td>127.0</td>\n",
       "      <td>0.99740</td>\n",
       "      <td>3.04</td>\n",
       "      <td>0.53</td>\n",
       "      <td>8.900000</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4788</th>\n",
       "      <td>6.4</td>\n",
       "      <td>0.310</td>\n",
       "      <td>0.31</td>\n",
       "      <td>12.90</td>\n",
       "      <td>0.045</td>\n",
       "      <td>55.0</td>\n",
       "      <td>161.0</td>\n",
       "      <td>0.99546</td>\n",
       "      <td>3.02</td>\n",
       "      <td>0.59</td>\n",
       "      <td>10.200000</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4791</th>\n",
       "      <td>6.7</td>\n",
       "      <td>0.300</td>\n",
       "      <td>0.50</td>\n",
       "      <td>12.10</td>\n",
       "      <td>0.045</td>\n",
       "      <td>38.0</td>\n",
       "      <td>127.0</td>\n",
       "      <td>0.99740</td>\n",
       "      <td>3.04</td>\n",
       "      <td>0.53</td>\n",
       "      <td>8.900000</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4796</th>\n",
       "      <td>6.4</td>\n",
       "      <td>0.105</td>\n",
       "      <td>0.29</td>\n",
       "      <td>1.10</td>\n",
       "      <td>0.035</td>\n",
       "      <td>44.0</td>\n",
       "      <td>140.0</td>\n",
       "      <td>0.99142</td>\n",
       "      <td>3.17</td>\n",
       "      <td>0.55</td>\n",
       "      <td>10.700000</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4801</th>\n",
       "      <td>6.4</td>\n",
       "      <td>0.105</td>\n",
       "      <td>0.29</td>\n",
       "      <td>1.10</td>\n",
       "      <td>0.035</td>\n",
       "      <td>44.0</td>\n",
       "      <td>140.0</td>\n",
       "      <td>0.99142</td>\n",
       "      <td>3.17</td>\n",
       "      <td>0.55</td>\n",
       "      <td>10.700000</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4819</th>\n",
       "      <td>5.7</td>\n",
       "      <td>0.400</td>\n",
       "      <td>0.35</td>\n",
       "      <td>5.10</td>\n",
       "      <td>0.026</td>\n",
       "      <td>17.0</td>\n",
       "      <td>113.0</td>\n",
       "      <td>0.99052</td>\n",
       "      <td>3.18</td>\n",
       "      <td>0.67</td>\n",
       "      <td>12.400000</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4820</th>\n",
       "      <td>5.8</td>\n",
       "      <td>0.360</td>\n",
       "      <td>0.50</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.127</td>\n",
       "      <td>63.0</td>\n",
       "      <td>178.0</td>\n",
       "      <td>0.99212</td>\n",
       "      <td>3.10</td>\n",
       "      <td>0.45</td>\n",
       "      <td>9.700000</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4826</th>\n",
       "      <td>6.0</td>\n",
       "      <td>0.340</td>\n",
       "      <td>0.29</td>\n",
       "      <td>6.10</td>\n",
       "      <td>0.046</td>\n",
       "      <td>29.0</td>\n",
       "      <td>134.0</td>\n",
       "      <td>0.99462</td>\n",
       "      <td>3.48</td>\n",
       "      <td>0.57</td>\n",
       "      <td>10.700000</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4828</th>\n",
       "      <td>6.4</td>\n",
       "      <td>0.230</td>\n",
       "      <td>0.35</td>\n",
       "      <td>10.30</td>\n",
       "      <td>0.042</td>\n",
       "      <td>54.0</td>\n",
       "      <td>140.0</td>\n",
       "      <td>0.99670</td>\n",
       "      <td>3.23</td>\n",
       "      <td>0.47</td>\n",
       "      <td>9.200000</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4850</th>\n",
       "      <td>7.0</td>\n",
       "      <td>0.360</td>\n",
       "      <td>0.35</td>\n",
       "      <td>2.50</td>\n",
       "      <td>0.048</td>\n",
       "      <td>67.0</td>\n",
       "      <td>161.0</td>\n",
       "      <td>0.99146</td>\n",
       "      <td>3.05</td>\n",
       "      <td>0.56</td>\n",
       "      <td>11.100000</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4851</th>\n",
       "      <td>6.4</td>\n",
       "      <td>0.330</td>\n",
       "      <td>0.44</td>\n",
       "      <td>8.90</td>\n",
       "      <td>0.055</td>\n",
       "      <td>52.0</td>\n",
       "      <td>164.0</td>\n",
       "      <td>0.99488</td>\n",
       "      <td>3.10</td>\n",
       "      <td>0.48</td>\n",
       "      <td>9.600000</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4856</th>\n",
       "      <td>7.1</td>\n",
       "      <td>0.230</td>\n",
       "      <td>0.39</td>\n",
       "      <td>13.70</td>\n",
       "      <td>0.058</td>\n",
       "      <td>26.0</td>\n",
       "      <td>172.0</td>\n",
       "      <td>0.99755</td>\n",
       "      <td>2.90</td>\n",
       "      <td>0.46</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4880</th>\n",
       "      <td>6.6</td>\n",
       "      <td>0.340</td>\n",
       "      <td>0.40</td>\n",
       "      <td>8.10</td>\n",
       "      <td>0.046</td>\n",
       "      <td>68.0</td>\n",
       "      <td>170.0</td>\n",
       "      <td>0.99494</td>\n",
       "      <td>3.15</td>\n",
       "      <td>0.50</td>\n",
       "      <td>9.533333</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>937 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      fixed acidity  volatile acidity  ...    alcohol  quality\n",
       "4               7.2             0.230  ...   9.900000        6\n",
       "5               8.1             0.280  ...  10.100000        6\n",
       "7               7.0             0.270  ...   8.800000        6\n",
       "8               6.3             0.300  ...   9.500000        6\n",
       "20              6.2             0.660  ...  12.800000        8\n",
       "39              7.3             0.240  ...   8.600000        5\n",
       "48              7.0             0.310  ...   9.800000        6\n",
       "61              6.0             0.190  ...   8.900000        6\n",
       "63              6.6             0.380  ...  10.200000        6\n",
       "74              6.7             0.230  ...  10.700000        8\n",
       "75              7.4             0.240  ...   9.500000        5\n",
       "88              7.1             0.430  ...   8.700000        5\n",
       "89              7.1             0.440  ...   8.700000        6\n",
       "90              7.2             0.390  ...   8.700000        6\n",
       "99              6.0             0.340  ...   8.800000        6\n",
       "104             7.4             0.250  ...   9.100000        5\n",
       "106             7.1             0.120  ...   9.400000        5\n",
       "108             7.1             0.230  ...   9.100000        6\n",
       "114             6.7             0.410  ...   9.100000        5\n",
       "118             7.2             0.310  ...   9.200000        5\n",
       "131             6.5             0.240  ...   9.700000        7\n",
       "141             7.1             0.370  ...   8.700000        5\n",
       "152             6.9             0.250  ...   9.400000        6\n",
       "156             7.4             0.240  ...   8.900000        6\n",
       "159             5.2             0.440  ...  12.100000        8\n",
       "160             6.1             0.320  ...  12.400000        7\n",
       "163             7.4             0.240  ...   8.900000        6\n",
       "191             6.8             0.280  ...   8.700000        5\n",
       "199             6.8             0.260  ...   8.900000        5\n",
       "201             7.1             0.320  ...   8.800000        5\n",
       "...             ...               ...  ...        ...      ...\n",
       "4693            6.7             0.160  ...   9.000000        6\n",
       "4694            6.9             0.190  ...   9.100000        7\n",
       "4697            6.7             0.350  ...  12.900000        7\n",
       "4700            6.8             0.300  ...   9.800000        5\n",
       "4702            6.4             0.690  ...  10.100000        6\n",
       "4712            5.7             0.270  ...  10.400000        6\n",
       "4714            6.1             0.220  ...  11.800000        7\n",
       "4719            6.7             0.150  ...  10.000000        6\n",
       "4724            6.1             0.320  ...  10.200000        6\n",
       "4727            6.0             0.250  ...   9.400000        6\n",
       "4732            5.3             0.310  ...  11.700000        6\n",
       "4750            6.0             0.140  ...  11.200000        5\n",
       "4757            6.0             0.380  ...  13.600000        7\n",
       "4760            6.6             0.170  ...  10.000000        6\n",
       "4769            6.8             0.270  ...   9.600000        6\n",
       "4770            6.8             0.270  ...   9.600000        6\n",
       "4771            6.8             0.270  ...   9.600000        6\n",
       "4783            6.7             0.300  ...   8.900000        6\n",
       "4788            6.4             0.310  ...  10.200000        5\n",
       "4791            6.7             0.300  ...   8.900000        6\n",
       "4796            6.4             0.105  ...  10.700000        7\n",
       "4801            6.4             0.105  ...  10.700000        7\n",
       "4819            5.7             0.400  ...  12.400000        6\n",
       "4820            5.8             0.360  ...   9.700000        5\n",
       "4826            6.0             0.340  ...  10.700000        6\n",
       "4828            6.4             0.230  ...   9.200000        5\n",
       "4850            7.0             0.360  ...  11.100000        6\n",
       "4851            6.4             0.330  ...   9.600000        5\n",
       "4856            7.1             0.230  ...   9.000000        6\n",
       "4880            6.6             0.340  ...   9.533333        6\n",
       "\n",
       "[937 rows x 12 columns]"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.duplicated() == True]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-16T04:10:15.000323Z",
     "start_time": "2020-01-16T04:10:14.990427Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "fixed acidity           0\n",
       "volatile acidity        0\n",
       "citric acid             0\n",
       "residual sugar          0\n",
       "chlorides               0\n",
       "free sulfur dioxide     0\n",
       "total sulfur dioxide    0\n",
       "density                 0\n",
       "pH                      0\n",
       "sulphates               0\n",
       "alcohol                 0\n",
       "quality                 0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-16T04:11:28.423537Z",
     "start_time": "2020-01-16T04:11:28.414853Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6    2198\n",
       "5    1457\n",
       "7     880\n",
       "8     175\n",
       "4     163\n",
       "3      20\n",
       "9       5\n",
       "Name: quality, dtype: int64"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['quality'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-16T04:11:56.871354Z",
     "start_time": "2020-01-16T04:11:56.864593Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9940273764801959"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['density'].mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 重新整理数据集"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 合并两个文件"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-16T04:45:49.085918Z",
     "start_time": "2020-01-16T04:45:48.985711Z"
    }
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "\n",
    "df1 = pd.read_csv('winequality-red.csv',sep=';')\n",
    "df2 = pd.read_csv('winequality-white.csv',sep=';')\n",
    "# 红、白葡萄酒分别新增一列类型，填充为 red 和 white\n",
    "df1['type'] = 'red'\n",
    "df2['type'] = 'white'\n",
    "df = pd.concat([df1,df2],ignore_index=True)\n",
    "df.to_csv('winequality_edited.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-16T04:51:30.115401Z",
     "start_time": "2020-01-16T04:51:30.058018Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>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>type</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",
       "    </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",
       "    </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",
       "    </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",
       "    </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",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   fixed acidity  volatile acidity  citric acid  ...  alcohol  quality  type\n",
       "0            7.4              0.70         0.00  ...      9.4        5   red\n",
       "1            7.8              0.88         0.00  ...      9.8        5   red\n",
       "2            7.8              0.76         0.04  ...      9.8        5   red\n",
       "3           11.2              0.28         0.56  ...      9.8        6   red\n",
       "4            7.4              0.70         0.00  ...      9.4        5   red\n",
       "\n",
       "[5 rows x 13 columns]"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wine_df = pd.read_csv('winequality_edited.csv',index_col=0)\n",
    "wine_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 整理数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-16T04:58:27.350022Z",
     "start_time": "2020-01-16T04:58:27.295057Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "fixed acidity             7.215307\n",
       "volatile acidity          0.339666\n",
       "citric acid               0.318633\n",
       "residual sugar            5.443235\n",
       "chlorides                 0.056034\n",
       "free sulfur dioxide      30.525319\n",
       "total sulfur dioxide    115.744574\n",
       "density                   0.994697\n",
       "pH                        3.218501\n",
       "sulphates                 0.531268\n",
       "alcohol                  10.491801\n",
       "quality                   5.818378\n",
       "dtype: float64"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wine_df.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-16T05:03:25.734819Z",
     "start_time": "2020-01-16T05:03:25.682465Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>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>7.853333</td>\n",
       "      <td>0.517000</td>\n",
       "      <td>0.281000</td>\n",
       "      <td>5.140000</td>\n",
       "      <td>0.077033</td>\n",
       "      <td>39.216667</td>\n",
       "      <td>122.033333</td>\n",
       "      <td>0.995744</td>\n",
       "      <td>3.257667</td>\n",
       "      <td>0.506333</td>\n",
       "      <td>10.215000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>7.288889</td>\n",
       "      <td>0.457963</td>\n",
       "      <td>0.272315</td>\n",
       "      <td>4.153704</td>\n",
       "      <td>0.060056</td>\n",
       "      <td>20.636574</td>\n",
       "      <td>103.432870</td>\n",
       "      <td>0.994833</td>\n",
       "      <td>3.231620</td>\n",
       "      <td>0.505648</td>\n",
       "      <td>10.180093</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>7.326801</td>\n",
       "      <td>0.389614</td>\n",
       "      <td>0.307722</td>\n",
       "      <td>5.804116</td>\n",
       "      <td>0.064666</td>\n",
       "      <td>30.237371</td>\n",
       "      <td>120.839102</td>\n",
       "      <td>0.995849</td>\n",
       "      <td>3.212189</td>\n",
       "      <td>0.526403</td>\n",
       "      <td>9.837783</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7.177257</td>\n",
       "      <td>0.313863</td>\n",
       "      <td>0.323583</td>\n",
       "      <td>5.549753</td>\n",
       "      <td>0.054157</td>\n",
       "      <td>31.165021</td>\n",
       "      <td>115.410790</td>\n",
       "      <td>0.994558</td>\n",
       "      <td>3.217726</td>\n",
       "      <td>0.532549</td>\n",
       "      <td>10.587553</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>7.128962</td>\n",
       "      <td>0.288800</td>\n",
       "      <td>0.334764</td>\n",
       "      <td>4.731696</td>\n",
       "      <td>0.045272</td>\n",
       "      <td>30.422150</td>\n",
       "      <td>108.498610</td>\n",
       "      <td>0.993126</td>\n",
       "      <td>3.228072</td>\n",
       "      <td>0.547025</td>\n",
       "      <td>11.386006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>6.835233</td>\n",
       "      <td>0.291010</td>\n",
       "      <td>0.332539</td>\n",
       "      <td>5.382902</td>\n",
       "      <td>0.041124</td>\n",
       "      <td>34.533679</td>\n",
       "      <td>117.518135</td>\n",
       "      <td>0.992514</td>\n",
       "      <td>3.223212</td>\n",
       "      <td>0.512487</td>\n",
       "      <td>11.678756</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>7.420000</td>\n",
       "      <td>0.298000</td>\n",
       "      <td>0.386000</td>\n",
       "      <td>4.120000</td>\n",
       "      <td>0.027400</td>\n",
       "      <td>33.400000</td>\n",
       "      <td>116.000000</td>\n",
       "      <td>0.991460</td>\n",
       "      <td>3.308000</td>\n",
       "      <td>0.466000</td>\n",
       "      <td>12.180000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         fixed acidity  volatile acidity  ...  sulphates    alcohol\n",
       "quality                                   ...                      \n",
       "3             7.853333          0.517000  ...   0.506333  10.215000\n",
       "4             7.288889          0.457963  ...   0.505648  10.180093\n",
       "5             7.326801          0.389614  ...   0.526403   9.837783\n",
       "6             7.177257          0.313863  ...   0.532549  10.587553\n",
       "7             7.128962          0.288800  ...   0.547025  11.386006\n",
       "8             6.835233          0.291010  ...   0.512487  11.678756\n",
       "9             7.420000          0.298000  ...   0.466000  12.180000\n",
       "\n",
       "[7 rows x 11 columns]"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# groupby \n",
    "wine_df.groupby('quality').mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-16T05:15:21.115797Z",
     "start_time": "2020-01-16T05:15:21.106387Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "quality  type \n",
       "3        red      3.398000\n",
       "         white    3.187500\n",
       "4        red      3.381509\n",
       "         white    3.182883\n",
       "5        red      3.304949\n",
       "         white    3.168833\n",
       "6        red      3.318072\n",
       "         white    3.188599\n",
       "7        red      3.290754\n",
       "         white    3.213898\n",
       "8        red      3.267222\n",
       "         white    3.218686\n",
       "9        white    3.308000\n",
       "Name: pH, dtype: float64"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wine_df.groupby(['quality','type'])['pH'].mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 答：两种类型的葡萄酒，哪种质量更高？\n",
    "白葡萄酒"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-16T05:19:16.767535Z",
     "start_time": "2020-01-16T05:19:16.749484Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "type\n",
       "red      5.636023\n",
       "white    5.877909\n",
       "Name: quality, dtype: float64"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wine_df.groupby('type')['quality'].mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 答：哪个水平的酸度（pH值）获得的评价等级最高？"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-16T09:43:04.853217Z",
     "start_time": "2020-01-16T09:43:04.780270Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\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>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  ...      alcohol      quality\n",
       "count    6497.000000       6497.000000  ...  6497.000000  6497.000000\n",
       "mean        7.215307          0.339666  ...    10.491801     5.818378\n",
       "std         1.296434          0.164636  ...     1.192712     0.873255\n",
       "min         3.800000          0.080000  ...     8.000000     3.000000\n",
       "25%         6.400000          0.230000  ...     9.500000     5.000000\n",
       "50%         7.000000          0.290000  ...    10.300000     6.000000\n",
       "75%         7.700000          0.400000  ...    11.300000     6.000000\n",
       "max        15.900000          1.580000  ...    14.900000     9.000000\n",
       "\n",
       "[8 rows x 12 columns]"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wine_df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 待解决"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 答：酒精度含量高的，是否质量也更高？\n",
    "\n",
    "是的"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-16T10:08:00.738664Z",
     "start_time": "2020-01-16T10:08:00.726067Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10.3\n",
      "5.484673748103186\n",
      "6.161773891317926\n"
     ]
    }
   ],
   "source": [
    "print(wine_df['alcohol'].median())\n",
    "\n",
    "wine_df_low = wine_df.query('alcohol <= 10.3')\n",
    "wine_df_high = wine_df.query('alcohol > 10.3')\n",
    "\n",
    "print(wine_df_low['quality'].mean())\n",
    "print(wine_df_high['quality'].mean())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 答：残糖含量越高，质量是否越高？"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-16T10:15:02.833000Z",
     "start_time": "2020-01-16T10:15:02.827449Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3.0\n"
     ]
    }
   ],
   "source": [
    "print(wine_df['residual sugar'].median())\n",
    "\n",
    "wine_df_1 = wine_df.query('residual sugar <= 3.0')\n",
    "wine_df_2 = wine_df.query('residual sugar > 3.0')\n",
    "\n",
    "print(wine_df_1['quality'].mean())\n",
    "print(wine_df_2['quality'].mean())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 用数据可视化看数据趋势"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 答：哪种葡萄酒的质量更高？"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-16T10:32:18.080760Z",
     "start_time": "2020-01-16T10:32:18.039430Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
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       "    }\n",
       "</style>\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>type</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",
       "    </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",
       "    </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",
       "    </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",
       "    </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",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   fixed acidity  volatile acidity  citric acid  ...  alcohol  quality  type\n",
       "0            7.4              0.70         0.00  ...      9.4        5   red\n",
       "1            7.8              0.88         0.00  ...      9.8        5   red\n",
       "2            7.8              0.76         0.04  ...      9.8        5   red\n",
       "3           11.2              0.28         0.56  ...      9.8        6   red\n",
       "4            7.4              0.70         0.00  ...      9.4        5   red\n",
       "\n",
       "[5 rows x 13 columns]"
      ]
     },
     "execution_count": 108,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "%matplotlib inline\n",
    "\n",
    "wine_df = pd.read_csv('winequality_edited.csv', index_col=0)\n",
    "wine_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-16T10:41:21.008183Z",
     "start_time": "2020-01-16T10:41:20.817521Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Quality')"
      ]
     },
     "execution_count": 113,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "color_means = wine_df.groupby('type')['quality'].mean()\n",
    "color_means.plot(kind='bar', title='Average Wine Quality', color=['red','blue'], alpha=.7)\n",
    "plt.xlabel('Colors', fontsize=18)\n",
    "plt.ylabel('Quality', fontsize=18)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-16T10:38:00.052806Z",
     "start_time": "2020-01-16T10:37:59.818358Z"
    },
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Count')"
      ]
     },
     "execution_count": 111,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "counts = wine_df.groupby(['quality','type']).count()['pH']\n",
    "counts.plot(kind='bar', title='Counts by Wine Color and Quality',color=['red','blue'], alpha=.7)\n",
    "plt.xlabel('Quality and Color', fontsize=18)\n",
    "plt.ylabel('Count', fontsize=18)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-16T10:42:47.305015Z",
     "start_time": "2020-01-16T10:42:47.053646Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Proportion')"
      ]
     },
     "execution_count": 114,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
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   ],
   "source": [
    "totals = wine_df.groupby('type').count()['pH']\n",
    "proportions = counts / totals\n",
    "proportions.plot(kind='bar', title='Proportion by Wine Color and Quality',color=['red','blue'], alpha=.7)\n",
    "plt.xlabel('Quality and Color', fontsize=18)\n",
    "plt.ylabel('Proportion', fontsize=18)"
   ]
  }
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