ML_Project/3조/CHIC_ML_project_정유빈.ipynb

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Laina  female  26.0      0   \n","3       Futrelle, Mrs. Jacques Heath (Lily May Peel)  female  35.0      1   \n","4                           Allen, Mr. William Henry    male  35.0      0   \n","\n","   Parch            Ticket     Fare Cabin Embarked  \n","0      0         A/5 21171   7.2500   NaN        S  \n","1      0          PC 17599  71.2833   C85        C  \n","2      0  STON/O2. 3101282   7.9250   NaN        S  \n","3      0            113803  53.1000  C123        S  \n","4      0            373450   8.0500   NaN        S  "],"text/html":["\n","  <div id=\"df-59c9e461-5af6-48ed-aee9-b18c570ac2e7\" 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>PassengerId</th>\n","      <th>Survived</th>\n","      <th>Pclass</th>\n","      <th>Name</th>\n","      <th>Sex</th>\n","      <th>Age</th>\n","      <th>SibSp</th>\n","      <th>Parch</th>\n","      <th>Ticket</th>\n","      <th>Fare</th>\n","      <th>Cabin</th>\n","      <th>Embarked</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>3</td>\n","      <td>Braund, Mr. Owen Harris</td>\n","      <td>male</td>\n","      <td>22.0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>A/5 21171</td>\n","      <td>7.2500</td>\n","      <td>NaN</td>\n","      <td>S</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>2</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n","      <td>female</td>\n","      <td>38.0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>PC 17599</td>\n","      <td>71.2833</td>\n","      <td>C85</td>\n","      <td>C</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>3</td>\n","      <td>1</td>\n","      <td>3</td>\n","      <td>Heikkinen, Miss. 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'/content/drive/My Drive/train.csv'\n","file_path_test = '/content/drive/My Drive/test.csv'\n","\n","\n","# train CSV 파일 읽기\n","df_train = pd.read_csv(file_path_train)\n","\n","# test CSV 파일 읽기\n","df_test = pd.read_csv(file_path_test)\n","\n","# 데이터 출력(잘 들어왔는지 확인)\n","df_train.head()  # 처음 다섯 줄 출력"]},{"cell_type":"code","source":["df_test.head()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":206},"id":"VZSEqfP_1CM1","executionInfo":{"status":"ok","timestamp":1709461286155,"user_tz":-540,"elapsed":299,"user":{"displayName":"정유빈","userId":"15271953189779704919"}},"outputId":"2c698146-4539-4f02-abc8-ac15bfc7d241"},"execution_count":10,"outputs":[{"output_type":"execute_result","data":{"text/plain":["   PassengerId  Pclass                                          Name     Sex  \\\n","0          892       3                              Kelly, Mr. James    male   \n","1          893       3              Wilkes, Mrs. James (Ellen Needs)  female   \n","2          894       2                     Myles, Mr. Thomas Francis    male   \n","3          895       3                              Wirz, Mr. Albert    male   \n","4          896       3  Hirvonen, Mrs. Alexander (Helga E Lindqvist)  female   \n","\n","    Age  SibSp  Parch   Ticket     Fare Cabin Embarked  \n","0  34.5      0      0   330911   7.8292   NaN        Q  \n","1  47.0      1      0   363272   7.0000   NaN        S  \n","2  62.0      0      0   240276   9.6875   NaN        Q  \n","3  27.0      0      0   315154   8.6625   NaN        S  \n","4  22.0      1      1  3101298  12.2875   NaN        S  "],"text/html":["\n","  <div id=\"df-7688b68c-276a-481a-9805-5c47fa253ba5\" 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","    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Emilie\",\n          \"Canavan, Mr. Patrick\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Sex\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"female\",\n          \"male\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Age\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 14.181209235624422,\n        \"min\": 0.17,\n        \"max\": 76.0,\n        \"num_unique_values\": 79,\n        \"samples\": [\n          10.0,\n          34.5\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"SibSp\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 8,\n        \"num_unique_values\": 7,\n        \"samples\": [\n          0,\n          1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Parch\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 9,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          1,\n          6\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Ticket\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 363,\n        \"samples\": [\n          \"2673\",\n          \"W./C. 6607\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Fare\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 55.907576179973844,\n        \"min\": 0.0,\n        \"max\": 512.3292,\n        \"num_unique_values\": 169,\n        \"samples\": [\n          41.5792,\n          57.75\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Cabin\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 76,\n        \"samples\": [\n          \"A21\",\n          \"E45\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Embarked\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 3,\n        \"samples\": [\n          \"Q\",\n          \"S\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"}},"metadata":{},"execution_count":10}]},{"cell_type":"markdown","source":["survival\tSurvival\t0 = No, 1 = Yes  \n","pclass\tTicket class(티켓 등급)\t1 = 1st, 2 = 2nd, 3 = 3rd  \n","sex\tSex\n","Age\tAge in years\n","sibsp\t# of siblings / spouses aboard the Titanic     \n","-> 타이타닉호에 타고 있는 배우자 수\n","parch\t# of parents / children aboard the Titanic\n","-> 타이타닉호에 탑승한 부모/자녀\n","ticket\tTicket number\n","fare\tPassenger fare\n","cabin\tCabin number\t-> 선실 숫자  \n","embarked\tPort of Embarkation\tC = Cherbourg, Q = Queenstown, S = Southampton  \n","-> 탑승자 이름 앞글자\n"],"metadata":{"id":"fEVXxbaBviZT"}},{"cell_type":"code","source":["df_train.info()"],"metadata":{"id":"-6zrc0huuaNO","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1709460998810,"user_tz":-540,"elapsed":6,"user":{"displayName":"정유빈","userId":"15271953189779704919"}},"outputId":"b3f4af26-390c-484c-b4b3-abe77088d688"},"execution_count":2,"outputs":[{"output_type":"stream","name":"stdout","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"]}]},{"cell_type":"code","source":["df_train.shape   # (891, 12)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"q5jOWGYpxOhG","executionInfo":{"status":"ok","timestamp":1708604078792,"user_tz":-540,"elapsed":10,"user":{"displayName":"정유빈","userId":"15271953189779704919"}},"outputId":"50ef2e40-2d00-4acf-e2fc-be4268a6afee"},"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["(891, 12)"]},"metadata":{},"execution_count":61}]},{"cell_type":"code","source":["df_test.shape   # (418, 11) , survided가 없음"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"26LhGQCL1cg1","executionInfo":{"status":"ok","timestamp":1709461332272,"user_tz":-540,"elapsed":3,"user":{"displayName":"정유빈","userId":"15271953189779704919"}},"outputId":"8cbc7327-c52a-442e-a0e3-7bcc45ea3daa"},"execution_count":11,"outputs":[{"output_type":"execute_result","data":{"text/plain":["(418, 11)"]},"metadata":{},"execution_count":11}]},{"cell_type":"code","source":["df_train.isnull().sum()    # Age, Cabin, Embarked 에 null 존재"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"PZPbcBcixldt","executionInfo":{"status":"ok","timestamp":1709461393745,"user_tz":-540,"elapsed":318,"user":{"displayName":"정유빈","userId":"15271953189779704919"}},"outputId":"23e49b79-0bab-40a0-dc91-c7e19faa4911"},"execution_count":14,"outputs":[{"output_type":"execute_result","data":{"text/plain":["PassengerId      0\n","Survived         0\n","Pclass           0\n","Name             0\n","Sex              0\n","Age            177\n","SibSp            0\n","Parch            0\n","Ticket           0\n","Fare             0\n","Cabin          687\n","Embarked         2\n","dtype: int64"]},"metadata":{},"execution_count":14}]},{"cell_type":"code","source":["df_test.isnull().sum()    # Age, Fare, Cabin 에 null 존재"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"9fK4QM4W1pL_","executionInfo":{"status":"ok","timestamp":1709461387217,"user_tz":-540,"elapsed":3,"user":{"displayName":"정유빈","userId":"15271953189779704919"}},"outputId":"a5b8a688-eb33-48d1-f407-707ed6ccc6b8"},"execution_count":13,"outputs":[{"output_type":"execute_result","data":{"text/plain":["PassengerId      0\n","Pclass           0\n","Name             0\n","Sex              0\n","Age             86\n","SibSp            0\n","Parch            0\n","Ticket           0\n","Fare             1\n","Cabin          327\n","Embarked         0\n","dtype: int64"]},"metadata":{},"execution_count":13}]},{"cell_type":"code","source":["df_train.describe()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":300},"id":"PXI0bcarxcpk","executionInfo":{"status":"ok","timestamp":1708605177671,"user_tz":-540,"elapsed":2,"user":{"displayName":"정유빈","userId":"15271953189779704919"}},"outputId":"0ee9efe6-3e21-447d-cc47-4dd4ac54172f"},"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["       PassengerId    Survived      Pclass         Age       SibSp  \\\n","count   891.000000  891.000000  891.000000  714.000000  891.000000   \n","mean    446.000000    0.383838    2.308642   29.699118    0.523008   \n","std     257.353842    0.486592    0.836071   14.526497    1.102743   \n","min       1.000000    0.000000    1.000000    0.420000    0.000000   \n","25%     223.500000    0.000000    2.000000   20.125000    0.000000   \n","50%     446.000000    0.000000    3.000000   28.000000    0.000000   \n","75%     668.500000    1.000000    3.000000   38.000000    1.000000   \n","max     891.000000    1.000000    3.000000   80.000000    8.000000   \n","\n","            Parch        Fare  \n","count  891.000000  891.000000  \n","mean     0.381594   32.204208  \n","std      0.806057   49.693429  \n","min      0.000000    0.000000  \n","25%      0.000000    7.910400  \n","50%      0.000000   14.454200  \n","75%      0.000000   31.000000  \n","max      6.000000  512.329200  "],"text/html":["\n","  <div id=\"df-c785ed21-c31c-430b-be43-1eb64aeab5d8\" 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>PassengerId</th>\n","      <th>Survived</th>\n","      <th>Pclass</th>\n","      <th>Age</th>\n","      <th>SibSp</th>\n","      <th>Parch</th>\n","      <th>Fare</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>count</th>\n","      <td>891.000000</td>\n","      <td>891.000000</td>\n","      <td>891.000000</td>\n","      <td>714.000000</td>\n","      <td>891.000000</td>\n","      <td>891.000000</td>\n","      <td>891.000000</td>\n","    </tr>\n","    <tr>\n","      <th>mean</th>\n","      <td>446.000000</td>\n","      <td>0.383838</td>\n","      <td>2.308642</td>\n","      <td>29.699118</td>\n","      <td>0.523008</td>\n","      <td>0.381594</td>\n","      <td>32.204208</td>\n","    </tr>\n","    <tr>\n","      <th>std</th>\n","      <td>257.353842</td>\n","      <td>0.486592</td>\n","      <td>0.836071</td>\n","      <td>14.526497</td>\n","      <td>1.102743</td>\n","      <td>0.806057</td>\n","      <td>49.693429</td>\n","    </tr>\n","    <tr>\n","      <th>min</th>\n","      <td>1.000000</td>\n","      <td>0.000000</td>\n","      <td>1.000000</td>\n","      <td>0.420000</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","    </tr>\n","    <tr>\n","      <th>25%</th>\n","      <td>223.500000</td>\n","      <td>0.000000</td>\n","      <td>2.000000</td>\n","      <td>20.125000</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>7.910400</td>\n","    </tr>\n","    <tr>\n","      <th>50%</th>\n","      <td>446.000000</td>\n","      <td>0.000000</td>\n","      <td>3.000000</td>\n","      <td>28.000000</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>14.454200</td>\n","    </tr>\n","    <tr>\n","      <th>75%</th>\n","      <td>668.500000</td>\n","      <td>1.000000</td>\n","      <td>3.000000</td>\n","      <td>38.000000</td>\n","      <td>1.000000</td>\n","      <td>0.000000</td>\n","      <td>31.000000</td>\n","    </tr>\n","    <tr>\n","      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     \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Pclass\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 314.2523437079694,\n        \"min\": 0.836071240977049,\n        \"max\": 891.0,\n        \"num_unique_values\": 6,\n        \"samples\": [\n          891.0,\n          2.308641975308642,\n          3.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Age\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 242.9056731818781,\n        \"min\": 0.42,\n        \"max\": 714.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          29.69911764705882,\n          28.0,\n          714.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"SibSp\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 314.4908277465442,\n        \"min\": 0.0,\n        \"max\": 891.0,\n        \"num_unique_values\": 6,\n        \"samples\": [\n          891.0,\n          0.5230078563411896,\n          8.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Parch\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 314.65971717879,\n        \"min\": 0.0,\n        \"max\": 891.0,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          0.38159371492704824,\n          6.0,\n          0.8060572211299483\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Fare\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 330.6256632228578,\n        \"min\": 0.0,\n        \"max\": 891.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          32.204207968574636,\n          14.4542,\n          891.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"}},"metadata":{},"execution_count":78}]},{"cell_type":"code","source":["columns = df_train.columns\n","print(columns)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"Ln5Wx3D1xtPn","executionInfo":{"status":"ok","timestamp":1708604078792,"user_tz":-540,"elapsed":7,"user":{"displayName":"정유빈","userId":"15271953189779704919"}},"outputId":"b193f1ff-6556-4931-d167-c201a34047ae"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["Index(['PassengerId', 'Survived', 'Pclass', 'Name', 'Sex', 'Age', 'SibSp',\n","       'Parch', 'Ticket', 'Fare', 'Cabin', 'Embarked'],\n","      dtype='object')\n"]}]},{"cell_type":"code","source":["import matplotlib.pyplot as plt\n","import math\n","import seaborn as sns\n","\n","columns = ['PassengerId', 'Survived', 'Pclass', 'Name', 'Sex', 'Age', 'SibSp',\n","       'Parch', 'Ticket', 'Fare', 'Cabin', 'Embarked']\n","\n","\n","# 그래프의 크기 및 행, 열 설정\n","num_cols_count = len(columns)\n","num_cols_per_row = 4  # 각 행당 그래프 수를 조절\n","num_rows = int(math.ceil(num_cols_count / num_cols_per_row))\n","\n","plt.figure(figsize=(30, 3 * num_rows))\n","\n","for i, feature in enumerate(columns, 1):\n","    plt.subplot(num_rows, num_cols_per_row, i)\n","    sns.histplot(df_train[feature], kde=True)\n","    plt.title(f'Distribution of {feature}')\n","\n","# 그래프 출력\n","plt.tight_layout()\n","plt.show()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":367},"id":"8QXDGlJa0P-h","executionInfo":{"status":"ok","timestamp":1708604106569,"user_tz":-540,"elapsed":23898,"user":{"displayName":"정유빈","userId":"15271953189779704919"}},"outputId":"55fb5e2a-5d3d-4e85-9932-75b814db6090"},"execution_count":null,"outputs":[{"output_type":"display_data","data":{"text/plain":["<Figure size 3000x900 with 12 Axes>"],"image/png":"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\n"},"metadata":{}}]},{"cell_type":"code","source":["df = pd.DataFrame(df_train)\n","\n","# 모든 열 간의 상관관계 계산\n","correlation_matrix = df.corr()\n","\n","# 히트맵 시각화\n","plt.figure(figsize=(10, 6))  # 그래프 크기 설정\n","sns.heatmap(correlation_matrix, annot=True, cmap='coolwarm')  # 히트맵 생성\n","plt.show()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":585},"id":"RO1-K12H0sMG","executionInfo":{"status":"ok","timestamp":1708593897835,"user_tz":-540,"elapsed":663,"user":{"displayName":"정유빈","userId":"15271953189779704919"}},"outputId":"66db60c6-a8a2-41ba-eb48-c5a28b8b5976"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stderr","text":["<ipython-input-42-bd8dc4be6ee9>:4: FutureWarning: The default value of numeric_only in DataFrame.corr is deprecated. In a future version, it will default to False. Select only valid columns or specify the value of numeric_only to silence this warning.\n","  correlation_matrix = df.corr()\n"]},{"output_type":"display_data","data":{"text/plain":["<Figure size 1000x600 with 2 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\n"},"metadata":{}}]},{"cell_type":"markdown","source":["# survided 비율 보기"],"metadata":{"id":"9B0dzMGG2l-I"}},{"cell_type":"code","source":["# 'survived' 열의 값에 따른 데이터 그룹화\n","survived_counts = df_train['Survived'].value_counts()\n","\n","# 원형 그래프 그리기\n","plt.figure(figsize=(8, 6))\n","plt.pie(survived_counts, labels=['Not Survived', 'Survived'], autopct='%1.1f%%', startangle=140)\n","plt.title('Survival Distribution')\n","plt.axis('equal')  # 원이 둥그런 형태가 되도록 하는 옵션\n","plt.show()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":521},"id":"uiw6FsrD1-ew","executionInfo":{"status":"ok","timestamp":1709461665248,"user_tz":-540,"elapsed":744,"user":{"displayName":"정유빈","userId":"15271953189779704919"}},"outputId":"75425ede-b12c-4da5-8ea0-4684b13c523e"},"execution_count":16,"outputs":[{"output_type":"display_data","data":{"text/plain":["<Figure size 800x600 with 1 Axes>"],"image/png":"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\n"},"metadata":{}}]},{"cell_type":"markdown","source":["### 필요없는거 버리기"],"metadata":{"id":"B9b2PaEVHATE"}},{"cell_type":"code","source":["df_train = df_train.drop(['Name', 'Ticket', 'Cabin','Embarked','Fare'], axis=1)\n","df_test = df_test.drop(['Name', 'Ticket', 'Cabin','Embarked', 'Fare'], axis=1)"],"metadata":{"id":"YlxOE8UgHRed","executionInfo":{"status":"ok","timestamp":1709461970968,"user_tz":-540,"elapsed":440,"user":{"displayName":"정유빈","userId":"15271953189779704919"}}},"execution_count":17,"outputs":[]},{"cell_type":"markdown","source":["### 성별을 숫자로 변환(범주형 데이터 -> 숫자형 데이터)"],"metadata":{"id":"CPqDOMPwHe7e"}},{"cell_type":"code","source":["from sklearn.preprocessing import LabelEncoder\n","\n","# LabelEncoder 객체 생성\n","label_encoder = LabelEncoder()\n","\n","# 'Sex' 열의 값에 대해 Label Encoding 적용\n","df_train['Sex'] = label_encoder.fit_transform(df_train['Sex'])\n","df_test['Sex'] = label_encoder.fit_transform(df_test['Sex'])\n","\n","# 변환된 값 확인\n","print(df_train['Sex'])\n","print(df_test['Sex'])"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"vlBgmUAnHldo","executionInfo":{"status":"ok","timestamp":1709461973630,"user_tz":-540,"elapsed":5,"user":{"displayName":"정유빈","userId":"15271953189779704919"}},"outputId":"13d81a75-917b-42a5-d05b-92993a56e399"},"execution_count":18,"outputs":[{"output_type":"stream","name":"stdout","text":["0      1\n","1      0\n","2      0\n","3      0\n","4      1\n","      ..\n","886    1\n","887    0\n","888    0\n","889    1\n","890    1\n","Name: Sex, Length: 891, dtype: int64\n","0      1\n","1      0\n","2      1\n","3      1\n","4      0\n","      ..\n","413    1\n","414    0\n","415    1\n","416    1\n","417    1\n","Name: Sex, Length: 418, dtype: int64\n"]}]},{"cell_type":"markdown","source":["### 데이터 결측치 채우기\n","\n","* 평균"],"metadata":{"id":"btWsWG5BJGeD"}},{"cell_type":"code","source":["import pandas as pd\n","from sklearn.model_selection import train_test_split\n","from sklearn.ensemble import RandomForestClassifier\n","from sklearn.metrics import accuracy_score\n","from sklearn.impute import SimpleImputer\n","\n","from sklearn.impute import SimpleImputer\n","\n","# SimpleImputer 객체 생성\n","imputer = SimpleImputer(strategy='mean')\n","\n","# Age 열에 대해 결측치를 평균값으로 대체\n","df_train['Age'] = imputer.fit_transform(df_train[['Age']])\n","df_test['Age'] = imputer.transform(df_test[['Age']])\n","\n","# 실수를 정수로 변환\n","df_train['Age'] = df_train['Age'].astype(int)\n","df_test['Age'] = df_test['Age'].astype(int)"],"metadata":{"id":"LiA5oNrt3FY8","executionInfo":{"status":"ok","timestamp":1709465091920,"user_tz":-540,"elapsed":339,"user":{"displayName":"정유빈","userId":"15271953189779704919"}}},"execution_count":39,"outputs":[]},{"cell_type":"markdown","source":["- 중앙값(그래프가 정규분포 형태를 띄고 있으며 약간 왼쪽으로 치우쳐져 있음)"],"metadata":{"id":"HcEZgIrz-Q-y"}},{"cell_type":"code","source":["from sklearn.impute import SimpleImputer\n","\n","# SimpleImputer 객체 생성\n","imputer = SimpleImputer(strategy='median')\n","\n","# Age 열에 대해 결측치를 중앙값으로 대체\n","df_train['Age'] = imputer.fit_transform(df_train[['Age']])\n","df_test['Age'] = imputer.transform(df_test[['Age']])\n","\n","# 실수를 정수로 변환\n","df_train['Age'] = df_train['Age'].astype(int)\n","df_test['Age'] = df_test['Age'].astype(int)"],"metadata":{"id":"s1yHR9ez-Vje","executionInfo":{"status":"ok","timestamp":1709464070238,"user_tz":-540,"elapsed":366,"user":{"displayName":"정유빈","userId":"15271953189779704919"}}},"execution_count":26,"outputs":[]},{"cell_type":"markdown","source":["# Null값 재확인"],"metadata":{"id":"YdhdoWRo27sM"}},{"cell_type":"code","source":["df_train.isnull().sum()    # null 없음"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"ONwzjRZV27ce","executionInfo":{"status":"ok","timestamp":1709464073619,"user_tz":-540,"elapsed":10,"user":{"displayName":"정유빈","userId":"15271953189779704919"}},"outputId":"f1e7afce-b7d1-44b9-816b-a0e7156f81d8"},"execution_count":27,"outputs":[{"output_type":"execute_result","data":{"text/plain":["PassengerId    0\n","Survived       0\n","Pclass         0\n","Sex            0\n","Age            0\n","SibSp          0\n","Parch          0\n","dtype: int64"]},"metadata":{},"execution_count":27}]},{"cell_type":"code","source":["df_test.isnull().sum()   # null 없음"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"rrcarFyU4DGF","executionInfo":{"status":"ok","timestamp":1709464076069,"user_tz":-540,"elapsed":411,"user":{"displayName":"정유빈","userId":"15271953189779704919"}},"outputId":"bf4ac8c4-a84d-4fef-b68f-3784f847f01e"},"execution_count":28,"outputs":[{"output_type":"execute_result","data":{"text/plain":["PassengerId    0\n","Pclass         0\n","Sex            0\n","Age            0\n","SibSp          0\n","Parch          0\n","dtype: int64"]},"metadata":{},"execution_count":28}]},{"cell_type":"markdown","source":["### 테스트 결과"],"metadata":{"id":"u6eKEMdwrI8u"}},{"cell_type":"code","source":["df_test.shape\n","\n","# 테스트 데이터에서 입력 변수(X_test) 추출\n","X_test = df_test  # 테스트 데이터에서 생존 여부(Survived) 열을 제외하고 모든 열을 사용"],"metadata":{"id":"XSx_nzwQro8Y","executionInfo":{"status":"ok","timestamp":1709464079565,"user_tz":-540,"elapsed":366,"user":{"displayName":"정유빈","userId":"15271953189779704919"}}},"execution_count":29,"outputs":[]},{"cell_type":"markdown","source":["- train 데이터 평가"],"metadata":{"id":"BRY1F5A8KDeZ"}},{"cell_type":"code","source":["from sklearn.model_selection import train_test_split\n","from sklearn.ensemble import RandomForestClassifier\n","from sklearn.metrics import accuracy_score, f1_score, recall_score, precision_score\n","from sklearn.preprocessing import StandardScaler, OneHotEncoder\n","from sklearn.compose import ColumnTransformer\n","from sklearn.pipeline import Pipeline\n","from sklearn.impute import SimpleImputer\n","\n","# Define numerical and categorical features\n","numerical_features = ['Age']   # 숫자형\n","categorical_features = ['Sex']  # 범주형\n","\n","# Create preprocessing pipeline : 전처리 파이프라인 생성\n","# Pipeline 클래스를 사용하여 numerical 및 categorical feature에 대한 전처리 파이프 라인을 생성\n","numerical_transformer = Pipeline(steps=[\n","    ('imputer', SimpleImputer(strategy='mean')),   # 결측값을 평균값으로 채우기(Age)\n","    ('scaler', StandardScaler())\n","])\n","\n","# Age를 중앙값으로 해보기(mean, median) 비교해보기\n","\n","# numerical_transformer = Pipeline(steps=[\n","#     ('imputer', SimpleImputer(strategy='median')),   # 결측값을 평균값으로 채우기(Age)\n","#     ('scaler', StandardScaler())\n","# ])\n","\n","categorical_transformer = Pipeline(steps=[\n","    ('imputer', SimpleImputer(strategy='most_frequent')),  # 가장 빈번한 값으로 채우기(Sex)\n","    ('onehot', OneHotEncoder(handle_unknown='ignore'))\n","])\n","\n","preprocessor = ColumnTransformer(transformers=[\n","    ('num', numerical_transformer, numerical_features),\n","    ('cat', categorical_transformer, categorical_features)\n","])\n","\n","# Define model\n","model = RandomForestClassifier(random_state=42)\n","\n","# Create full pipeline with preprocessing and model\n","pipeline = Pipeline(steps=[\n","    ('preprocessor', preprocessor),\n","    ('model', model)\n","])\n","\n","# Split data into features and target\n","X = df_train.drop('Survived', axis=1)\n","y = df_train['Survived']\n","\n","# Split data into train and validation sets\n","X_train, X_val, y_train, y_val = train_test_split(X, y, test_size=0.2, random_state=42)\n","\n","# Train model\n","pipeline.fit(X_train, y_train)\n","\n","# Predict on validation set\n","y_pred = pipeline.predict(X_val)\n","\n","# Evaluate model\n","accuracy = accuracy_score(y_val, y_pred)\n","f1 = f1_score(y_val, y_pred)\n","recall = recall_score(y_val, y_pred)\n","precision = precision_score(y_val, y_pred)\n","\n","print(\"Accuracy:\", accuracy)\n","print(\"F1 Score:\", f1)\n","print(\"Recall:\", recall)\n","print(\"Precision:\", precision)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"YSYqwF49KDQy","executionInfo":{"status":"ok","timestamp":1709469340055,"user_tz":-540,"elapsed":860,"user":{"displayName":"정유빈","userId":"15271953189779704919"}},"outputId":"59440f7d-42b3-4318-9ffb-ef50ab88349e"},"execution_count":64,"outputs":[{"output_type":"stream","name":"stdout","text":["Accuracy: 0.776536312849162\n","F1 Score: 0.7222222222222223\n","Recall: 0.7027027027027027\n","Precision: 0.7428571428571429\n"]}]},{"cell_type":"markdown","source":["- 파이프 라인을 쓰는 이유 : 전처리부터 학습 과정까지 각 단계의 과정을 정확한 순서대로 할 수 있어서\n","\n","> 파이프 라인의 목적은 cross_validated(교차 검증 가능한) 여러가지의 단계들을 합쳐놓은 것이다."],"metadata":{"id":"81nsFORYP8-e"}},{"cell_type":"markdown","source":["- 확인 필요"],"metadata":{"id":"_glqe6VMKGNi"}},{"cell_type":"markdown","source":["# 성능 평가"],"metadata":{"id":"aWrhMP1R1gxY"}},{"cell_type":"code","source":["import pandas as pd\n","from sklearn.ensemble import RandomForestClassifier\n","from sklearn.impute import SimpleImputer\n","from sklearn.preprocessing import StandardScaler, OneHotEncoder\n","from sklearn.compose import ColumnTransformer\n","from sklearn.pipeline import Pipeline\n","\n","\n","# Drop unnecessary columns\n","train_data = df_train.drop(['Name', 'Ticket', 'Cabin', 'Embarked', 'Fare'], axis=1)\n","\n","# Split train data into features and target\n","X_train = train_data.drop('Survived', axis=1)\n","y_train = train_data['Survived']\n","\n","# Define numerical and categorical features\n","numerical_features = ['Age']\n","categorical_features = ['Sex']\n","\n","# Create preprocessing pipeline\n","numerical_transformer = Pipeline(steps=[\n","    ('imputer', SimpleImputer(strategy='mean')),\n","    ('scaler', StandardScaler())\n","])\n","\n","categorical_transformer = Pipeline(steps=[\n","    ('imputer', SimpleImputer(strategy='most_frequent')),\n","    ('onehot', OneHotEncoder(handle_unknown='ignore'))\n","])\n","\n","preprocessor = ColumnTransformer(transformers=[\n","    ('num', numerical_transformer, numerical_features),\n","    ('cat', categorical_transformer, categorical_features)\n","])\n","\n","# Define model\n","model = RandomForestClassifier(random_state=42)\n","\n","# Create full pipeline with preprocessing and model\n","pipeline = Pipeline(steps=[\n","    ('preprocessor', preprocessor),\n","    ('model', model)\n","])\n","\n","# Train model\n","pipeline.fit(X_train, y_train)\n","\n","\n","# Drop unnecessary columns\n","test_data = df_test.drop(['Name', 'Ticket', 'Cabin', 'Embarked', 'Fare'], axis=1)\n","\n","# Predict on test data\n","y_pred = pipeline.predict(test_data)\n","\n","# Create DataFrame for submission\n","submission_df = pd.DataFrame({'PassengerId': test_data['PassengerId'], 'Survived': y_pred})\n","\n","# Save submission DataFrame to CSV file\n","submission_df.to_csv('/content/drive/My Drive/submission.csv', index=False)\n"],"metadata":{"id":"LUwBW71NRZ5a","executionInfo":{"status":"ok","timestamp":1709469824583,"user_tz":-540,"elapsed":441,"user":{"displayName":"정유빈","userId":"15271953189779704919"}}},"execution_count":71,"outputs":[]},{"cell_type":"markdown","source":["### csv 파일로 저장"],"metadata":{"id":"b7g37tB4As7h"}},{"cell_type":"code","source":["import pandas as pd\n","\n","# 예측 결과를 DataFrame으로 변환\n","result_df = pd.DataFrame({'Survived': y_pred})\n","\n","# CSV 파일로 저장\n","result_df.to_csv('/content/drive/My Drive/y_pred.csv', index=False)"],"metadata":{"id":"bDVYKvP90-RS","executionInfo":{"status":"ok","timestamp":1709464667830,"user_tz":-540,"elapsed":8,"user":{"displayName":"정유빈","userId":"15271953189779704919"}}},"execution_count":33,"outputs":[]},{"cell_type":"code","source":[],"metadata":{"id":"XvrOwJ1nA0hh"},"execution_count":null,"outputs":[]}]}