4. 231128titanic_preprocessing.ipynb

{"cells":[{"cell_type":"code","execution_count":1,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":30706,"status":"ok","timestamp":1701155180132,"user":{"displayName":"Seyong Jung","userId":"10440673311570958840"},"user_tz":-540},"id":"FS0JsGZx24fq","outputId":"18ea14ec-9cb4-4cc8-f765-2554e0c280d4"},"outputs":[{"name":"stdout","output_type":"stream","text":["Mounted at /content/drive\n"]}],"source":["# Python 3.10.12\n","# Numpy : 1.23.5\n","# Pandas : 1.5.3\n","# Matplotlib : 3.7.1\n","# Seaborn : 0.12.2\n","# Scikit-learn : 1.2.2\n","# Created: OCT. 23. 2023\n","# Author: D.W. SHIN\n","\n","import numpy as np\n","import pandas as pd\n","import matplotlib.pyplot as plt\n","import seaborn as sns\n","\n","from sklearn.preprocessing import LabelEncoder\n","from sklearn.model_selection import train_test_split\n","\n","from sklearn.linear_model import LogisticRegression\n","from sklearn.linear_model import SGDClassifier\n","from sklearn.ensemble import RandomForestClassifier\n","from sklearn.ensemble import GradientBoostingClassifier\n","from sklearn.ensemble import VotingClassifier\n","from sklearn.model_selection import GridSearchCV\n","from sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score\n","from sklearn.model_selection import cross_val_score\n","\n","# 구글 드라이브 마운트\n","from google.colab import drive\n","drive.mount('/content/drive')"]},{"cell_type":"code","execution_count":2,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":3182,"status":"ok","timestamp":1701155200507,"user":{"displayName":"Seyong Jung","userId":"10440673311570958840"},"user_tz":-540},"id":"lbTGO5d13OYZ","outputId":"d233c7c3-b300-4a6d-d685-1019511c549d"},"outputs":[{"name":"stdout","output_type":"stream","text":["<class 'pandas.core.frame.DataFrame'>\n","RangeIndex: 891 entries, 0 to 890\n","Data columns (total 12 columns):\n"," #   Column       Non-Null Count  Dtype  \n","---  ------       --------------  -----  \n"," 0   PassengerId  891 non-null    int64  \n"," 1   Survived     891 non-null    int64  \n"," 2   Pclass       891 non-null    int64  \n"," 3   Name         891 non-null    object \n"," 4   Sex          891 non-null    object \n"," 5   Age          714 non-null    float64\n"," 6   SibSp        891 non-null    int64  \n"," 7   Parch        891 non-null    int64  \n"," 8   Ticket       891 non-null    object \n"," 9   Fare         891 non-null    float64\n"," 10  Cabin        204 non-null    object \n"," 11  Embarked     889 non-null    object \n","dtypes: float64(2), int64(5), object(5)\n","memory usage: 83.7+ KB\n"]}],"source":["# csv파일 경로 설정\n","trainCSV = '/content/drive/MyDrive/구글클라우드인공지능개발자과정/scikit-learn/data/titanic/train.csv'\n","testCSV  = '/content/drive/MyDrive/구글클라우드인공지능개발자과정/scikit-learn/data/titanic/test.csv'\n","\n","# csv파일 불러오기\n","train_df = pd.read_csv(trainCSV)\n","train_df.info()"]},{"cell_type":"markdown","metadata":{"id":"a9PfI-x-uiCb"},"source":["### 결측치 처리 부분"]},{"cell_type":"code","execution_count":3,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":4,"status":"ok","timestamp":1701155206335,"user":{"displayName":"Seyong Jung","userId":"10440673311570958840"},"user_tz":-540},"id":"l1N1ueI6Xi-Z","outputId":"348c9a43-04ba-4d82-81b0-87d6598420c2"},"outputs":[{"data":{"text/plain":["0"]},"execution_count":3,"metadata":{},"output_type":"execute_result"}],"source":["train_df['Age'].fillna(train_df['Age'].mean(), inplace=True)\n","train_df['Age'].isnull().sum()"]},{"cell_type":"code","execution_count":4,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":5,"status":"ok","timestamp":1701155208148,"user":{"displayName":"Seyong Jung","userId":"10440673311570958840"},"user_tz":-540},"id":"tCqawg3RuqyM","outputId":"3d9e61a3-71bf-450f-a54d-d6219975d1b1"},"outputs":[{"data":{"text/plain":["0"]},"execution_count":4,"metadata":{},"output_type":"execute_result"}],"source":["train_df['Embarked'].fillna(train_df['Embarked'].mode()[0], inplace=True)\n","train_df['Embarked'].isnull().sum()"]},{"cell_type":"markdown","metadata":{"id":"4Bf28sPQuvgK"},"source":["### 추가 컬럼"]},{"cell_type":"code","execution_count":5,"metadata":{"executionInfo":{"elapsed":604,"status":"ok","timestamp":1701155218408,"user":{"displayName":"Seyong Jung","userId":"10440673311570958840"},"user_tz":-540},"id":"AJGghxUF3lHI"},"outputs":[],"source":["train_df['Age_Cat'] = pd.cut(train_df['Age'],\n","                             bins=[0, 3, 7, 15, 30, 60, 100],\n","                             include_lowest=True,\n","                             labels=['Baby', 'Children', 'Teenage', 'Young', 'Adult', 'Old'])"]},{"cell_type":"code","execution_count":6,"metadata":{"executionInfo":{"elapsed":3,"status":"ok","timestamp":1701155220121,"user":{"displayName":"Seyong Jung","userId":"10440673311570958840"},"user_tz":-540},"id":"v5IAcUzhu1AR"},"outputs":[],"source":["train_df['FamilySize'] = train_df['SibSp'] + train_df['Parch'] + 1"]},{"cell_type":"code","execution_count":7,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":206},"executionInfo":{"elapsed":443,"status":"ok","timestamp":1701155233905,"user":{"displayName":"Seyong Jung","userId":"10440673311570958840"},"user_tz":-540},"id":"-Rcq9MFT3vO_","outputId":"2770b245-3a15-4237-a1b0-6407c4af18eb"},"outputs":[{"data":{"text/html":["\n","  <div id=\"df-552b52f1-c93e-4a6b-94cf-83840c997d1a\" class=\"colab-df-container\">\n","    <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>AgeBand</th>\n","      <th>Survived</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>(0.34, 16.336]</td>\n","      <td>0.550000</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>(16.336, 32.252]</td>\n","      <td>0.344168</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>(32.252, 48.168]</td>\n","      <td>0.404255</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>(48.168, 64.084]</td>\n","      <td>0.434783</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>(64.084, 80.0]</td>\n","      <td>0.090909</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>\n","    <div class=\"colab-df-buttons\">\n","\n","  <div class=\"colab-df-container\">\n","    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-552b52f1-c93e-4a6b-94cf-83840c997d1a')\"\n","            title=\"Convert this dataframe to an interactive table.\"\n","            style=\"display:none;\">\n","\n","  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n","    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Laina</td>\n","      <td>female</td>\n","      <td>1.0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>STON/O2. 3101282</td>\n","      <td>7.9250</td>\n","      <td>NaN</td>\n","      <td>S</td>\n","      <td>Young</td>\n","      <td>1</td>\n","      <td>(16.336, 32.252]</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>4</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n","      <td>female</td>\n","      <td>2.0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>113803</td>\n","      <td>53.1000</td>\n","      <td>C123</td>\n","      <td>S</td>\n","      <td>Adult</td>\n","      <td>2</td>\n","      <td>(32.252, 48.168]</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>5</td>\n","      <td>0</td>\n","      <td>3</td>\n","      <td>Allen, Mr. William Henry</td>\n","      <td>male</td>\n","      <td>2.0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>373450</td>\n","      <td>8.0500</td>\n","      <td>NaN</td>\n","      <td>S</td>\n","      <td>Adult</td>\n","      <td>1</td>\n","      <td>(32.252, 48.168]</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>\n","    <div class=\"colab-df-buttons\">\n","\n","  <div class=\"colab-df-container\">\n","    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-8a41f3fb-aebd-44c1-b05d-1bae1d0b2532')\"\n","            title=\"Convert this dataframe to an interactive table.\"\n","            style=\"display:none;\">\n","\n","  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n","    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n","  </svg>\n","    </button>\n","\n","  <style>\n","    .colab-df-container {\n","      display:flex;\n","      gap: 12px;\n","    }\n","\n","    .colab-df-convert {\n","      background-color: #E8F0FE;\n","      border: none;\n","      border-radius: 50%;\n","      cursor: pointer;\n","      display: none;\n","      fill: #1967D2;\n","      height: 32px;\n","      padding: 0 0 0 0;\n","      width: 32px;\n","    }\n","\n","    .colab-df-convert:hover {\n","      background-color: #E2EBFA;\n","      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n","      fill: #174EA6;\n","    }\n","\n","    .colab-df-buttons div {\n","      margin-bottom: 4px;\n","    }\n","\n","    [theme=dark] .colab-df-convert {\n","      background-color: #3B4455;\n","      fill: #D2E3FC;\n","    }\n","\n","    [theme=dark] .colab-df-convert:hover {\n","      background-color: #434B5C;\n","      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n","      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n","      fill: #FFFFFF;\n","    }\n","  </style>\n","\n","    <script>\n","      const buttonEl =\n","        document.querySelector('#df-8a41f3fb-aebd-44c1-b05d-1bae1d0b2532 button.colab-df-convert');\n","      buttonEl.style.display =\n","        google.colab.kernel.accessAllowed ? 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Visit the ' +\n","          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n","          + ' to learn more about interactive tables.';\n","        element.innerHTML = '';\n","        dataTable['output_type'] = 'display_data';\n","        await google.colab.output.renderOutput(dataTable, element);\n","        const docLink = document.createElement('div');\n","        docLink.innerHTML = docLinkHtml;\n","        element.appendChild(docLink);\n","      }\n","    </script>\n","  </div>\n","\n","\n","<div id=\"df-ef9cc116-270e-4597-9b20-ae68de5ff302\">\n","  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-ef9cc116-270e-4597-9b20-ae68de5ff302')\"\n","            title=\"Suggest charts\"\n","            style=\"display:none;\">\n","\n","<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n","     width=\"24px\">\n","    <g>\n","        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n","    </g>\n","</svg>\n","  </button>\n","\n","<style>\n","  .colab-df-quickchart {\n","      --bg-color: #E8F0FE;\n","      --fill-color: #1967D2;\n","      --hover-bg-color: #E2EBFA;\n","      --hover-fill-color: #174EA6;\n","      --disabled-fill-color: #AAA;\n","      --disabled-bg-color: #DDD;\n","  }\n","\n","  [theme=dark] .colab-df-quickchart {\n","      --bg-color: #3B4455;\n","      --fill-color: #D2E3FC;\n","      --hover-bg-color: #434B5C;\n","      --hover-fill-color: #FFFFFF;\n","      --disabled-bg-color: #3B4455;\n","      --disabled-fill-color: #666;\n","  }\n","\n","  .colab-df-quickchart {\n","    background-color: var(--bg-color);\n","    border: none;\n","    border-radius: 50%;\n","    cursor: pointer;\n","    display: none;\n","    fill: var(--fill-color);\n","    height: 32px;\n","    padding: 0;\n","    width: 32px;\n","  }\n","\n","  .colab-df-quickchart:hover {\n","    background-color: var(--hover-bg-color);\n","    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n","    fill: var(--button-hover-fill-color);\n","  }\n","\n","  .colab-df-quickchart-complete:disabled,\n","  .colab-df-quickchart-complete:disabled:hover {\n","    background-color: var(--disabled-bg-color);\n","    fill: var(--disabled-fill-color);\n","    box-shadow: none;\n","  }\n","\n","  .colab-df-spinner {\n","    border: 2px solid var(--fill-color);\n","    border-color: transparent;\n","    border-bottom-color: var(--fill-color);\n","    animation:\n","      spin 1s steps(1) infinite;\n","  }\n","\n","  @keyframes spin {\n","    0% {\n","      border-color: transparent;\n","      border-bottom-color: var(--fill-color);\n","      border-left-color: var(--fill-color);\n","    }\n","    20% {\n","      border-color: transparent;\n","      border-left-color: var(--fill-color);\n","      border-top-color: var(--fill-color);\n","    }\n","    30% {\n","      border-color: transparent;\n","      border-left-color: var(--fill-color);\n","      border-top-color: var(--fill-color);\n","      border-right-color: var(--fill-color);\n","    }\n","    40% {\n","      border-color: transparent;\n","      border-right-color: var(--fill-color);\n","      border-top-color: var(--fill-color);\n","    }\n","    60% {\n","      border-color: transparent;\n","      border-right-color: var(--fill-color);\n","    }\n","    80% {\n","      border-color: transparent;\n","      border-right-color: var(--fill-color);\n","      border-bottom-color: var(--fill-color);\n","    }\n","    90% {\n","      border-color: transparent;\n","      border-bottom-color: var(--fill-color);\n","    }\n","  }\n","</style>\n","\n","  <script>\n","    async function quickchart(key) {\n","      const quickchartButtonEl =\n","        document.querySelector('#' + key + ' button');\n","      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n","      quickchartButtonEl.classList.add('colab-df-spinner');\n","      try {\n","        const charts = await google.colab.kernel.invokeFunction(\n","            'suggestCharts', [key], {});\n","      } catch (error) {\n","        console.error('Error during call to suggestCharts:', error);\n","      }\n","      quickchartButtonEl.classList.remove('colab-df-spinner');\n","      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n","    }\n","    (() => {\n","      let quickchartButtonEl =\n","        document.querySelector('#df-ef9cc116-270e-4597-9b20-ae68de5ff302 button');\n","      quickchartButtonEl.style.display =\n","        google.colab.kernel.accessAllowed ? 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Laina  female  1.0      0   \n","3       Futrelle, Mrs. Jacques Heath (Lily May Peel)  female  2.0      1   \n","4                           Allen, Mr. William Henry    male  2.0      0   \n","\n","   Parch            Ticket     Fare Cabin Embarked Age_Cat  FamilySize  \\\n","0      0         A/5 21171   7.2500   NaN        S   Young           2   \n","1      0          PC 17599  71.2833   C85        C   Adult           2   \n","2      0  STON/O2. 3101282   7.9250   NaN        S   Young           1   \n","3      0            113803  53.1000  C123        S   Adult           2   \n","4      0            373450   8.0500   NaN        S   Adult           1   \n","\n","            AgeBand  \n","0  (16.336, 32.252]  \n","1  (32.252, 48.168]  \n","2  (16.336, 32.252]  \n","3  (32.252, 48.168]  \n","4  (32.252, 48.168]  "]},"execution_count":8,"metadata":{},"output_type":"execute_result"}],"source":["train_df.loc[ train_df['Age'] <= 16, 'Age'] = 0\n","train_df.loc[(train_df['Age'] > 16) & (train_df['Age'] <= 32), 'Age'] = 1\n","train_df.loc[(train_df['Age'] > 32) & (train_df['Age'] <= 48), 'Age'] = 2\n","train_df.loc[(train_df['Age'] > 48) & (train_df['Age'] <= 64), 'Age'] = 3\n","train_df.loc[ train_df['Age'] > 64, 'Age'] = 4\n","\n","train_df.head()"]},{"cell_type":"markdown","metadata":{"id":"HApVWDSKvHYx"},"source":["### 레이블링 작업"]},{"cell_type":"code","execution_count":9,"metadata":{"executionInfo":{"elapsed":448,"status":"ok","timestamp":1701155251847,"user":{"displayName":"Seyong Jung","userId":"10440673311570958840"},"user_tz":-540},"id":"hZQO3g7I-I5d"},"outputs":[],"source":["le = LabelEncoder()\n","train_df['Sex'] = le.fit_transform(train_df['Sex'])\n","train_df['Embarked'] = le.fit_transform(train_df['Embarked'])\n","train_df['Age_Cat'] = le.fit_transform(train_df['Age_Cat'])"]},{"cell_type":"markdown","metadata":{"id":"t7t_7zrGvSTa"},"source":["### 컬럼 삭제"]},{"cell_type":"code","execution_count":10,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":206},"executionInfo":{"elapsed":435,"status":"ok","timestamp":1701155259383,"user":{"displayName":"Seyong Jung","userId":"10440673311570958840"},"user_tz":-540},"id":"PPbBqmmb_wqX","outputId":"6e4e4e5b-cff4-40a8-8272-923bcac1ed0b"},"outputs":[{"data":{"text/html":["\n","  <div id=\"df-8c1fdbbe-157e-4c5e-b12c-d2036cc39adc\" class=\"colab-df-container\">\n","    <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>Survived</th>\n","      <th>Pclass</th>\n","      <th>Sex</th>\n","      <th>Age</th>\n","      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