wine_quality_EDA.ipynb

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      "source": [
        "#Working on **wine_quality Dataset** by using Sci-Kit Learn"
      ],
      "metadata": {
        "id": "muctC_PhXEem"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Numpy is required for calculations like mean, median, square root, etc.\n",
        "\n",
        "Pandas is used for data processing and working with CSV files with DataFrames."
      ],
      "metadata": {
        "id": "aldIQE4UfZCY"
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        "id": "2J4NULcCCJh7"
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      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "%matplotlib inline\n",
        "import seaborn as sns\n",
        "import sklearn"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "wine_data=pd.read_csv(\"/content/winequality-red.csv\", sep=\";\")"
      ],
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        "id": "zIjGsMVWCR_7"
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      "execution_count": null,
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      "source": [
        "**Input variables:**\n",
        "\n",
        "\n",
        "fixed acidity\n",
        "\n",
        "volatile acidity\n",
        "\n",
        "citric acid\n",
        "\n",
        "residual sugar\n",
        "\n",
        "chlorides\n",
        "\n",
        "free sulfur dioxide\n",
        "\n",
        "total sulfur dioxide\n",
        "\n",
        "density\n",
        "\n",
        "pH\n",
        "\n",
        "sulphates\n",
        "\n",
        "alcohol\n",
        "\n",
        "**Output variable:**\n",
        "\n",
        "quality (score between 0 and 10)"
      ],
      "metadata": {
        "id": "2nSY5cpufJiH"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Find out the total number of rows and columns in the dataset using “.shape”."
      ],
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    {
      "cell_type": "code",
      "source": [
        "wine_data.shape"
      ],
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          "base_uri": "https://localhost:8080/"
        },
        "id": "aOWlJxiCCvz-",
        "outputId": "c1e93bb5-e842-4353-873b-87ab974ec3ba"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(1599, 12)"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
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    {
      "cell_type": "markdown",
      "source": [
        "Dataset comprises 1599 observations(rows) and 12 features(columns).\n",
        "Out of the 12, one is the target variable and rest 11 are input variables."
      ],
      "metadata": {
        "id": "W4HNGjjAfqD2"
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    {
      "cell_type": "markdown",
      "source": [
        "##**Exploratory Data Analysis**"
      ],
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        "id": "_0yfTCzpqNIc"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "To take a closer look at the data, we take the help of “ .head()” function of pandas library which returns the first five observations of the data set. Similarly, “.tail()” returns last five observations of the data set."
      ],
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        "id": "edDVcpS_fime"
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    {
      "cell_type": "code",
      "source": [
        "wine_data.head()"
      ],
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        "outputId": "57145e39-bf6e-4b9c-c858-84d802483127"
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      "execution_count": null,
      "outputs": [
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          "data": {
            "text/plain": [
              "   fixed acidity  volatile acidity  citric acid  residual sugar  chlorides  \\\n",
              "0            7.4              0.70         0.00             1.9      0.076   \n",
              "1            7.8              0.88         0.00             2.6      0.098   \n",
              "2            7.8              0.76         0.04             2.3      0.092   \n",
              "3           11.2              0.28         0.56             1.9      0.075   \n",
              "4            7.4              0.70         0.00             1.9      0.076   \n",
              "\n",
              "   free sulfur dioxide  total sulfur dioxide  density    pH  sulphates  \\\n",
              "0                 11.0                  34.0   0.9978  3.51       0.56   \n",
              "1                 25.0                  67.0   0.9968  3.20       0.68   \n",
              "2                 15.0                  54.0   0.9970  3.26       0.65   \n",
              "3                 17.0                  60.0   0.9980  3.16       0.58   \n",
              "4                 11.0                  34.0   0.9978  3.51       0.56   \n",
              "\n",
              "   alcohol  quality  \n",
              "0      9.4        5  \n",
              "1      9.8        5  \n",
              "2      9.8        5  \n",
              "3      9.8        6  \n",
              "4      9.4        5  "
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              "      <th>fixed acidity</th>\n",
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              "summary": "{\n  \"name\": \"wine_data\",\n  \"rows\": 1599,\n  \"fields\": [\n    {\n      \"column\": \"fixed acidity\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.7410963181276953,\n        \"min\": 4.6,\n        \"max\": 15.9,\n        \"num_unique_values\": 96,\n        \"samples\": [\n          5.3,\n          12.7,\n          12.6\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"volatile acidity\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.17905970415353537,\n        \"min\": 0.12,\n        \"max\": 1.58,\n        \"num_unique_values\": 143,\n        \"samples\": [\n          1.025,\n          0.4,\n          0.87\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"citric acid\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.19480113740531857,\n        \"min\": 0.0,\n        \"max\": 1.0,\n        \"num_unique_values\": 80,\n        \"samples\": [\n          0.37,\n          0.0,\n          0.09\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"residual sugar\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.4099280595072798,\n        \"min\": 0.9,\n        \"max\": 15.5,\n        \"num_unique_values\": 91,\n        \"samples\": [\n          11.0,\n          3.0,\n          15.5\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"chlorides\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.0470653020100901,\n        \"min\": 0.012,\n        \"max\": 0.611,\n        \"num_unique_values\": 153,\n        \"samples\": [\n          0.096,\n          0.343,\n          0.159\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"free sulfur dioxide\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 10.460156969809725,\n        \"min\": 1.0,\n        \"max\": 72.0,\n        \"num_unique_values\": 60,\n        \"samples\": [\n          11.0,\n          9.0,\n          32.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"total sulfur dioxide\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 32.895324478299074,\n        \"min\": 6.0,\n        \"max\": 289.0,\n        \"num_unique_values\": 144,\n        \"samples\": [\n          68.0,\n          35.0,\n          101.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"density\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.0018873339538425554,\n        \"min\": 0.99007,\n        \"max\": 1.00369,\n        \"num_unique_values\": 436,\n        \"samples\": [\n          0.99974,\n          1.0001,\n          0.99471\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"pH\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.15438646490354277,\n        \"min\": 2.74,\n        \"max\": 4.01,\n        \"num_unique_values\": 89,\n        \"samples\": [\n          3.07,\n          3.0,\n          3.15\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"sulphates\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.16950697959010996,\n        \"min\": 0.33,\n        \"max\": 2.0,\n        \"num_unique_values\": 96,\n        \"samples\": [\n          1.07,\n          1.04,\n          1.18\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"alcohol\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.0656675818473946,\n        \"min\": 8.4,\n        \"max\": 14.9,\n        \"num_unique_values\": 65,\n        \"samples\": [\n          8.5,\n          9.95,\n          9.4\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"quality\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 3,\n        \"max\": 8,\n        \"num_unique_values\": 6,\n        \"samples\": [\n          5,\n          6,\n          3\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "wine_data.describe()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 355
        },
        "id": "kwsQzvubDasi",
        "outputId": "908efd3e-6e36-46ff-8d4a-731589fa8a51"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       fixed acidity  volatile acidity  citric acid  residual sugar  \\\n",
              "count    1599.000000       1599.000000  1599.000000     1599.000000   \n",
              "mean        8.319637          0.527821     0.270976        2.538806   \n",
              "std         1.741096          0.179060     0.194801        1.409928   \n",
              "min         4.600000          0.120000     0.000000        0.900000   \n",
              "25%         7.100000          0.390000     0.090000        1.900000   \n",
              "50%         7.900000          0.520000     0.260000        2.200000   \n",
              "75%         9.200000          0.640000     0.420000        2.600000   \n",
              "max        15.900000          1.580000     1.000000       15.500000   \n",
              "\n",
              "         chlorides  free sulfur dioxide  total sulfur dioxide      density  \\\n",
              "count  1599.000000          1599.000000           1599.000000  1599.000000   \n",
              "mean      0.087467            15.874922             46.467792     0.996747   \n",
              "std       0.047065            10.460157             32.895324     0.001887   \n",
              "min       0.012000             1.000000              6.000000     0.990070   \n",
              "25%       0.070000             7.000000             22.000000     0.995600   \n",
              "50%       0.079000            14.000000             38.000000     0.996750   \n",
              "75%       0.090000            21.000000             62.000000     0.997835   \n",
              "max       0.611000            72.000000            289.000000     1.003690   \n",
              "\n",
              "                pH    sulphates      alcohol      quality  \n",
              "count  1599.000000  1599.000000  1599.000000  1599.000000  \n",
              "mean      3.311113     0.658149    10.422983     5.636023  \n",
              "std       0.154386     0.169507     1.065668     0.807569  \n",
              "min       2.740000     0.330000     8.400000     3.000000  \n",
              "25%       3.210000     0.550000     9.500000     5.000000  \n",
              "50%       3.310000     0.620000    10.200000     6.000000  \n",
              "75%       3.400000     0.730000    11.100000     6.000000  \n",
              "max       4.010000     2.000000    14.900000     8.000000  "
            ],
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>fixed acidity</th>\n",
              "      <th>volatile acidity</th>\n",
              "      <th>citric acid</th>\n",
              "      <th>residual sugar</th>\n",
              "      <th>chlorides</th>\n",
              "      <th>free sulfur dioxide</th>\n",
              "      <th>total sulfur dioxide</th>\n",
              "      <th>density</th>\n",
              "      <th>pH</th>\n",
              "      <th>sulphates</th>\n",
              "      <th>alcohol</th>\n",
              "      <th>quality</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>1599.000000</td>\n",
              "      <td>1599.000000</td>\n",
              "      <td>1599.000000</td>\n",
              "      <td>1599.000000</td>\n",
              "      <td>1599.000000</td>\n",
              "      <td>1599.000000</td>\n",
              "      <td>1599.000000</td>\n",
              "      <td>1599.000000</td>\n",
              "      <td>1599.000000</td>\n",
              "      <td>1599.000000</td>\n",
              "      <td>1599.000000</td>\n",
              "      <td>1599.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>8.319637</td>\n",
              "      <td>0.527821</td>\n",
              "      <td>0.270976</td>\n",
              "      <td>2.538806</td>\n",
              "      <td>0.087467</td>\n",
              "      <td>15.874922</td>\n",
              "      <td>46.467792</td>\n",
              "      <td>0.996747</td>\n",
              "      <td>3.311113</td>\n",
              "      <td>0.658149</td>\n",
              "      <td>10.422983</td>\n",
              "      <td>5.636023</td>\n",
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              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>1.741096</td>\n",
              "      <td>0.179060</td>\n",
              "      <td>0.194801</td>\n",
              "      <td>1.409928</td>\n",
              "      <td>0.047065</td>\n",
              "      <td>10.460157</td>\n",
              "      <td>32.895324</td>\n",
              "      <td>0.001887</td>\n",
              "      <td>0.154386</td>\n",
              "      <td>0.169507</td>\n",
              "      <td>1.065668</td>\n",
              "      <td>0.807569</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>4.600000</td>\n",
              "      <td>0.120000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.900000</td>\n",
              "      <td>0.012000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>6.000000</td>\n",
              "      <td>0.990070</td>\n",
              "      <td>2.740000</td>\n",
              "      <td>0.330000</td>\n",
              "      <td>8.400000</td>\n",
              "      <td>3.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>7.100000</td>\n",
              "      <td>0.390000</td>\n",
              "      <td>0.090000</td>\n",
              "      <td>1.900000</td>\n",
              "      <td>0.070000</td>\n",
              "      <td>7.000000</td>\n",
              "      <td>22.000000</td>\n",
              "      <td>0.995600</td>\n",
              "      <td>3.210000</td>\n",
              "      <td>0.550000</td>\n",
              "      <td>9.500000</td>\n",
              "      <td>5.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>7.900000</td>\n",
              "      <td>0.520000</td>\n",
              "      <td>0.260000</td>\n",
              "      <td>2.200000</td>\n",
              "      <td>0.079000</td>\n",
              "      <td>14.000000</td>\n",
              "      <td>38.000000</td>\n",
              "      <td>0.996750</td>\n",
              "      <td>3.310000</td>\n",
              "      <td>0.620000</td>\n",
              "      <td>10.200000</td>\n",
              "      <td>6.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>9.200000</td>\n",
              "      <td>0.640000</td>\n",
              "      <td>0.420000</td>\n",
              "      <td>2.600000</td>\n",
              "      <td>0.090000</td>\n",
              "      <td>21.000000</td>\n",
              "      <td>62.000000</td>\n",
              "      <td>0.997835</td>\n",
              "      <td>3.400000</td>\n",
              "      <td>0.730000</td>\n",
              "      <td>11.100000</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>1.000000</td>\n",
              "      <td>15.500000</td>\n",
              "      <td>0.611000</td>\n",
              "      <td>72.000000</td>\n",
              "      <td>289.000000</td>\n",
              "      <td>1.003690</td>\n",
              "      <td>4.010000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>14.900000</td>\n",
              "      <td>8.000000</td>\n",
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              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-9f411e77-71b8-4669-885e-8cdc83b5721d button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"wine_data\",\n  \"rows\": 8,\n  \"fields\": [\n    {\n      \"column\": \"fixed acidity\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 562.5806745048905,\n        \"min\": 1.7410963181276953,\n        \"max\": 1599.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          8.31963727329581,\n          7.9,\n          1599.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"volatile acidity\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 565.1321980080039,\n        \"min\": 0.12,\n        \"max\": 1599.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          0.5278205128205128,\n          0.52,\n          1599.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"citric acid\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 565.2190298438521,\n        \"min\": 0.0,\n        \"max\": 1599.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          0.2709756097560976,\n          0.26,\n          1599.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"residual sugar\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 563.9859918397555,\n        \"min\": 0.9,\n        \"max\": 1599.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          2.53880550343965,\n          2.2,\n          1599.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"chlorides\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 565.2815720420849,\n        \"min\": 0.012,\n        \"max\": 1599.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          0.08746654158849279,\n          0.079,\n          1599.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"free sulfur dioxide\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 558.6255652064851,\n        \"min\": 1.0,\n        \"max\": 1599.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          15.874921826141339,\n          14.0,\n          1599.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"total sulfur dioxide\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 547.7946740169228,\n        \"min\": 6.0,\n        \"max\": 1599.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          46.46779237023139,\n          38.0,\n          1599.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"density\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 565.0298129526795,\n        \"min\": 0.0018873339538425554,\n        \"max\": 1599.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          0.9967466791744841,\n          0.99675,\n          1599.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"pH\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 564.3160746075234,\n        \"min\": 0.15438646490354277,\n        \"max\": 1599.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          3.3111131957473416,\n          3.31,\n          1599.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"sulphates\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 565.0766914059569,\n        \"min\": 0.16950697959010996,\n        \"max\": 1599.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          0.6581488430268917,\n          0.62,\n          1599.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"alcohol\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 562.0325260314485,\n        \"min\": 1.0656675818473946,\n        \"max\": 1599.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          10.422983114446529,\n          10.2,\n          1599.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"quality\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 563.5963817822505,\n        \"min\": 0.807569439734705,\n        \"max\": 1599.0,\n        \"num_unique_values\": 7,\n        \"samples\": [\n          1599.0,\n          5.6360225140712945,\n          6.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "wine_data.columns"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xG42PiWAEtGj",
        "outputId": "36ed398e-e226-4d03-a91e-ffc48f518c3a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['fixed acidity', 'volatile acidity', 'citric acid', 'residual sugar',\n",
              "       'chlorides', 'free sulfur dioxide', 'total sulfur dioxide', 'density',\n",
              "       'pH', 'sulphates', 'alcohol', 'quality'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "wine_data['quality'].unique()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "w9yCM8WqFAQk",
        "outputId": "f1094fa1-eada-4184-e256-1df73313be21"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([5, 6, 7, 4, 8, 3])"
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Target variable/Dependent variable is discrete and categorical in nature.\n",
        "“quality” score scale ranges from 1 to 10; 1 being poor and 10 being the best.\n",
        "1,2,9 & 10 Quality ratings are not given by any observation. Only scores obtained are between 3 to 8."
      ],
      "metadata": {
        "id": "A0oxzEfXf3G1"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "wine_data_data['quality'].value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7ziuuhBQFZMY",
        "outputId": "3d367321-1580-48b5-bf1c-7f2b555861f5"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "quality\n",
              "6    2198\n",
              "5    1457\n",
              "7     880\n",
              "8     175\n",
              "4     163\n",
              "3      20\n",
              "9       5\n",
              "Name: count, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 60
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "This tells us the vote count of each quality score in descending order.\n",
        "“quality” has most values concentrated in the categories 5, 6 and 7.\n",
        "Only a few observations made for the categories 3 & 8."
      ],
      "metadata": {
        "id": "oSfQhe9Cf7_d"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Let's rename the columns which contain spaces in their names and replace the spaces with underscores."
      ],
      "metadata": {
        "id": "jEd32i1HgDPV"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "wine_data.rename(columns={'fixed acidity':'fixed_acidity', 'volatile acidity':'volatile_acidity', 'citric acid': 'citric_acid', 'residual sugar': 'residual_sugar', 'free sulfur dioxide': 'free_sulfur_dioxide', 'total sulfur dioxide': 'total_sulfur_dioxide'}, inplace = True)"
      ],
      "metadata": {
        "id": "iNeJLEOFF31l"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "wine_data.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 226
        },
        "id": "E5VqdaaAGxrW",
        "outputId": "a1273af0-af40-421a-a790-468612ec6526"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   fixed_acidity  volatile_acidity  citric_acid  residual_sugar  chlorides  \\\n",
              "0            7.4              0.70         0.00             1.9      0.076   \n",
              "1            7.8              0.88         0.00             2.6      0.098   \n",
              "2            7.8              0.76         0.04             2.3      0.092   \n",
              "3           11.2              0.28         0.56             1.9      0.075   \n",
              "4            7.4              0.70         0.00             1.9      0.076   \n",
              "\n",
              "   free_sulfur_dioxide  total_sulfur_dioxide  density    pH  sulphates  \\\n",
              "0                 11.0                  34.0   0.9978  3.51       0.56   \n",
              "1                 25.0                  67.0   0.9968  3.20       0.68   \n",
              "2                 15.0                  54.0   0.9970  3.26       0.65   \n",
              "3                 17.0                  60.0   0.9980  3.16       0.58   \n",
              "4                 11.0                  34.0   0.9978  3.51       0.56   \n",
              "\n",
              "   alcohol  quality  \n",
              "0      9.4        5  \n",
              "1      9.8        5  \n",
              "2      9.8        5  \n",
              "3      9.8        6  \n",
              "4      9.4        5  "
            ],
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              "      <th>fixed_acidity</th>\n",
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              "    }\n",
              "  }\n",
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              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
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              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
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            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "wine_data",
              "summary": "{\n  \"name\": \"wine_data\",\n  \"rows\": 1599,\n  \"fields\": [\n    {\n      \"column\": \"fixed_acidity\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.7410963181276953,\n        \"min\": 4.6,\n        \"max\": 15.9,\n        \"num_unique_values\": 96,\n        \"samples\": [\n          5.3,\n          12.7,\n          12.6\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"volatile_acidity\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.17905970415353537,\n        \"min\": 0.12,\n        \"max\": 1.58,\n        \"num_unique_values\": 143,\n        \"samples\": [\n          1.025,\n          0.4,\n          0.87\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"citric_acid\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.19480113740531857,\n        \"min\": 0.0,\n        \"max\": 1.0,\n        \"num_unique_values\": 80,\n        \"samples\": [\n          0.37,\n          0.0,\n          0.09\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"residual_sugar\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.4099280595072798,\n        \"min\": 0.9,\n        \"max\": 15.5,\n        \"num_unique_values\": 91,\n        \"samples\": [\n          11.0,\n          3.0,\n          15.5\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"chlorides\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.0470653020100901,\n        \"min\": 0.012,\n        \"max\": 0.611,\n        \"num_unique_values\": 153,\n        \"samples\": [\n          0.096,\n          0.343,\n          0.159\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"free_sulfur_dioxide\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 10.460156969809725,\n        \"min\": 1.0,\n        \"max\": 72.0,\n        \"num_unique_values\": 60,\n        \"samples\": [\n          11.0,\n          9.0,\n          32.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"total_sulfur_dioxide\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 32.895324478299074,\n        \"min\": 6.0,\n        \"max\": 289.0,\n        \"num_unique_values\": 144,\n        \"samples\": [\n          68.0,\n          35.0,\n          101.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"density\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.0018873339538425554,\n        \"min\": 0.99007,\n        \"max\": 1.00369,\n        \"num_unique_values\": 436,\n        \"samples\": [\n          0.99974,\n          1.0001,\n          0.99471\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"pH\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.15438646490354277,\n        \"min\": 2.74,\n        \"max\": 4.01,\n        \"num_unique_values\": 89,\n        \"samples\": [\n          3.07,\n          3.0,\n          3.15\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"sulphates\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.16950697959010996,\n        \"min\": 0.33,\n        \"max\": 2.0,\n        \"num_unique_values\": 96,\n        \"samples\": [\n          1.07,\n          1.04,\n          1.18\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"alcohol\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.0656675818473946,\n        \"min\": 8.4,\n        \"max\": 14.9,\n        \"num_unique_values\": 65,\n        \"samples\": [\n          8.5,\n          9.95,\n          9.4\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"quality\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 3,\n        \"max\": 8,\n        \"num_unique_values\": 6,\n        \"samples\": [\n          5,\n          6,\n          3\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "wine_data.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "oIzuUP7iHJMw",
        "outputId": "3fd6d5d0-104f-4468-fc69-f42a3862998b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 1599 entries, 0 to 1598\n",
            "Data columns (total 12 columns):\n",
            " #   Column                Non-Null Count  Dtype  \n",
            "---  ------                --------------  -----  \n",
            " 0   fixed_acidity         1599 non-null   float64\n",
            " 1   volatile_acidity      1599 non-null   float64\n",
            " 2   citric_acid           1599 non-null   float64\n",
            " 3   residual_sugar        1599 non-null   float64\n",
            " 4   chlorides             1599 non-null   float64\n",
            " 5   free_sulfur_dioxide   1599 non-null   float64\n",
            " 6   total_sulfur_dioxide  1599 non-null   float64\n",
            " 7   density               1599 non-null   float64\n",
            " 8   pH                    1599 non-null   float64\n",
            " 9   sulphates             1599 non-null   float64\n",
            " 10  alcohol               1599 non-null   float64\n",
            " 11  quality               1599 non-null   int64  \n",
            "dtypes: float64(11), int64(1)\n",
            "memory usage: 150.0 KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "The data has only float and integer values.\n",
        "\n",
        "There are no missing values"
      ],
      "metadata": {
        "id": "Un_hXFX3gUFd"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "duplicate=wine_data[wine_data.duplicated()]\n",
        "duplicate.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "NYQ3xROXHuxg",
        "outputId": "0fbe2595-fdac-477b-dc89-24a71d4df9be"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(240, 12)"
            ]
          },
          "metadata": {},
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "There are 240 duplicates. The quality ratings for the same/similar wine were given by different wine tasters so there is a possibility of similar reviews. We can thus keep these duplicates.\n",
        "\n"
      ],
      "metadata": {
        "id": "tIdATqyugli1"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "x=wine_data.drop('quality', axis=1)\n",
        "y=wine_data['quality']"
      ],
      "metadata": {
        "id": "kqF5f5c5OEXA"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "X now contains all the features except Quality.\n",
        "\n",
        "y contains Quality."
      ],
      "metadata": {
        "id": "IS_H-mdhgszc"
      }
    }
  ]
}