powersoh_2.ipynb

{
  "cells": [
    {
      "cell_type": "code",
      "source": [
        "# plt 한글 깨짐을 해결하기 위해 이 코드를 실행 후 런타임 재시작\n",
        "\n",
        "!sudo apt-get install -y fonts-nanum\n",
        "!sudo fc-cache -fv\n",
        "!rm ~/.cache/matplotlib -rf"
      ],
      "metadata": {
        "id": "dvRBeXpksxWh"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# 런타임 다시시작 후 실행\n",
        "\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "plt.rc('font', family='NanumBarunGothic')"
      ],
      "metadata": {
        "id": "cgZVnb5ssx10"
      },
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-Z9UOwOk-fb8",
        "outputId": "3c373d77-9b2b-4e65-b298-ab8702c3ab99"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ],
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {
        "id": "GTPDqgFp-Sml"
      },
      "outputs": [],
      "source": [
        "import warnings\n",
        "warnings.filterwarnings('ignore')\n",
        "\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import numpy as np\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.preprocessing import StandardScaler\n",
        "from sklearn.metrics import accuracy_score\n",
        "from sklearn.metrics import confusion_matrix, classification_report\n",
        "from sklearn.ensemble import RandomForestClassifier\n",
        "from sklearn.pipeline import make_pipeline\n",
        "from random import randint\n",
        "from sklearn.model_selection import RandomizedSearchCV\n",
        "import pickle"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {
        "id": "oDAcCi60eg5m"
      },
      "outputs": [],
      "source": [
        "train=pd.read_csv('/content/drive/MyDrive/easy_train.csv',encoding='utf-8')\n",
        "submit=pd.read_csv('/content/drive/MyDrive/esay_test.csv',encoding='utf-8')\n",
        "sample_submission=pd.read_csv('/content/drive/MyDrive/easy_sample_submission_7.csv',encoding='utf-8')      ### ai허브에 제출하기 위한 csv"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7gj0Hy1eAh2T",
        "outputId": "c07bb525-7802-4463-dd43-83025774ee64"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "((2420565, 27), (313267, 24))"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ],
      "source": [
        "train.shape, submit.shape"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 297
        },
        "id": "sVEe8VIxhiwB",
        "outputId": "37cb5d30-a65a-43a6-cfb2-7e3688f1f8b4"
      },
      "outputs": [
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          "data": {
            "text/plain": [
              "   index       누적전력량   유효전력평균   무효전력평균        주파수        전류평균       상전압평균  \\\n",
              "0      0   2248930.5  28963.0  20237.0  59.854076   45.197918  259.916656   \n",
              "1      1         0.0      0.0      0.0   0.000000  101.312500    0.000000   \n",
              "2      2   5375707.0  35244.0  19826.0  59.975650  107.385414  125.416664   \n",
              "3      3  17781200.0  77056.0  39520.0  59.863000  244.854000  118.083000   \n",
              "4      4  10143988.0      0.0      0.0  59.798140    0.000000  133.750000   \n",
              "\n",
              "       선간전압평균      온도   R상유효전력  ...    S상전압  S상선간전압   T상유효전력   T상무효전력  \\\n",
              "0  449.916656  47.500   8663.0  ...  260.75  452.75  10417.0   7304.0   \n",
              "1    0.000000  24.375      0.0  ...    0.00    0.00      0.0      0.0   \n",
              "2  216.750000  18.750  11988.0  ...  125.25  216.25  12236.0   6170.0   \n",
              "3  205.333000  23.125  25796.0  ...  118.75  118.75  24992.0  13704.0   \n",
              "4  231.500000  26.875      0.0  ...  134.50  231.50      0.0      0.0   \n",
              "\n",
              "        T상전류    T상전압  T상선간전압  label_역률평균  label_전류고조파평균  label_전압고조파평균  \n",
              "0   48.71875  260.75  448.75          정상             경고             주의  \n",
              "1  100.68750    0.00    0.00          경고             정상             정상  \n",
              "2  109.56250  125.00  216.25          정상             정상             주의  \n",
              "3  242.18800  118.00  118.00          정상             정상             경고  \n",
              "4    0.00000  133.00  230.25          경고             정상             정상  \n",
              "\n",
              "[5 rows x 27 columns]"
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              "      <th>...</th>\n",
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              "      <td>2248930.5</td>\n",
              "      <td>28963.0</td>\n",
              "      <td>20237.0</td>\n",
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              "      <td>8663.0</td>\n",
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              "      <td>260.75</td>\n",
              "      <td>452.75</td>\n",
              "      <td>10417.0</td>\n",
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              "      <td>48.71875</td>\n",
              "      <td>260.75</td>\n",
              "      <td>448.75</td>\n",
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              "      <td>경고</td>\n",
              "      <td>주의</td>\n",
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              "      <th>1</th>\n",
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              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
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              "      <td>정상</td>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2</td>\n",
              "      <td>5375707.0</td>\n",
              "      <td>35244.0</td>\n",
              "      <td>19826.0</td>\n",
              "      <td>59.975650</td>\n",
              "      <td>107.385414</td>\n",
              "      <td>125.416664</td>\n",
              "      <td>216.750000</td>\n",
              "      <td>18.750</td>\n",
              "      <td>11988.0</td>\n",
              "      <td>...</td>\n",
              "      <td>125.25</td>\n",
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              "      <td>12236.0</td>\n",
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              "      <td>17781200.0</td>\n",
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              "      <td>118.083000</td>\n",
              "      <td>205.333000</td>\n",
              "      <td>23.125</td>\n",
              "      <td>25796.0</td>\n",
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              "      <td>118.75</td>\n",
              "      <td>24992.0</td>\n",
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              "      <td>242.18800</td>\n",
              "      <td>118.00</td>\n",
              "      <td>118.00</td>\n",
              "      <td>정상</td>\n",
              "      <td>정상</td>\n",
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          },
          "metadata": {},
          "execution_count": 7
        }
      ],
      "source": [
        "train.head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "MjbYZjka35Z5",
        "outputId": "25bb09ae-5ea8-41f6-d9f9-06b38a852de8"
      },
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        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "index              int64\n",
              "누적전력량            float64\n",
              "유효전력평균           float64\n",
              "무효전력평균           float64\n",
              "주파수              float64\n",
              "전류평균             float64\n",
              "상전압평균            float64\n",
              "선간전압평균           float64\n",
              "온도               float64\n",
              "R상유효전력           float64\n",
              "R상무효전력           float64\n",
              "R상전류             float64\n",
              "R상전압             float64\n",
              "R상선간전압           float64\n",
              "S상유효전력           float64\n",
              "S상무효전력           float64\n",
              "S상전류             float64\n",
              "S상전압             float64\n",
              "S상선간전압           float64\n",
              "T상유효전력           float64\n",
              "T상무효전력           float64\n",
              "T상전류             float64\n",
              "T상전압             float64\n",
              "T상선간전압           float64\n",
              "label_역률평균        object\n",
              "label_전류고조파평균     object\n",
              "label_전압고조파평균     object\n",
              "dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ],
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        "train.dtypes"
      ]
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      "execution_count": 9,
      "metadata": {
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        "id": "kgDytPXT2ZfU",
        "outputId": "003f8970-8e29-465b-9bf8-3ed7a42ef159"
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      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['index', '누적전력량', '유효전력평균', '무효전력평균', '주파수', '전류평균', '상전압평균', '선간전압평균',\n",
              "       '온도', 'R상유효전력', 'R상무효전력', 'R상전류', 'R상전압', 'R상선간전압', 'S상유효전력', 'S상무효전력',\n",
              "       'S상전류', 'S상전압', 'S상선간전압', 'T상유효전력', 'T상무효전력', 'T상전류', 'T상전압', 'T상선간전압',\n",
              "       'label_역률평균', 'label_전류고조파평균', 'label_전압고조파평균'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ],
      "source": [
        "train.columns"
      ]
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    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {
        "id": "C5uhnrVP4fp8"
      },
      "outputs": [],
      "source": [
        "ifydf = train.dropna()              ##### 전선이 전부 Y결선인지 확인하기 위한 데이터프레임 생성 #####"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 519
        },
        "id": "JOgl8F0X4zO3",
        "outputId": "b195d1d5-6f4b-435f-f529-b84a884861ec"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "           index        누적전력량   유효전력평균   무효전력평균        주파수        전류평균  \\\n",
              "0              0   2248930.50  28963.0  20237.0  59.854076   45.197918   \n",
              "1              1         0.00      0.0      0.0   0.000000  101.312500   \n",
              "2              2   5375707.00  35244.0  19826.0  59.975650  107.385414   \n",
              "3              3  17781200.00  77056.0  39520.0  59.863000  244.854000   \n",
              "4              4  10143988.00      0.0      0.0  59.798140    0.000000   \n",
              "...          ...          ...      ...      ...        ...         ...   \n",
              "2420560  2420561   6229905.00  25925.5  22606.0  57.945000   52.833000   \n",
              "2420561  2420562   6057307.50  91244.0  47068.0  59.928820  152.156250   \n",
              "2420562  2420563   7966820.00  16822.0  11924.8  59.914000   31.363100   \n",
              "2420563  2420564         0.00      0.0      0.0   0.000000   44.572918   \n",
              "2420564  2420565   1296005.63      0.0      0.0  59.807450    0.000000   \n",
              "\n",
              "              상전압평균      선간전압평균       온도    R상유효전력  ...   S상선간전압    T상유효전력  \\\n",
              "0        259.916656  449.916656  47.5000   8663.00  ...  452.750  10417.00   \n",
              "1          0.000000    0.000000  24.3750      0.00  ...    0.000      0.00   \n",
              "2        125.416664  216.750000  18.7500  11988.00  ...  216.250  12236.00   \n",
              "3        118.083000  205.333000  23.1250  25796.00  ...  118.750  24992.00   \n",
              "4        133.750000  231.500000  26.8750      0.00  ...  231.500      0.00   \n",
              "...             ...         ...      ...       ...  ...      ...       ...   \n",
              "2420560  215.327000  372.958000  19.0630   8631.50  ...  216.628   7818.50   \n",
              "2420561  224.416672  388.583344  33.7500  30128.00  ...  386.250  29052.00   \n",
              "2420562  219.233000  379.862000  17.3214   5157.84  ...  219.276   5954.98   \n",
              "2420563    0.000000    0.000000  34.3750      0.00  ...    0.000      0.00   \n",
              "2420564  229.416672  396.916656  24.3750      0.00  ...  394.500      0.00   \n",
              "\n",
              "           T상무효전력       T상전류     T상전압   T상선간전압  label_역률평균  label_전류고조파평균  \\\n",
              "0         7304.00   48.71875  260.750  448.750          정상             경고   \n",
              "1            0.00  100.68750    0.000    0.000          경고             정상   \n",
              "2         6170.00  109.56250  125.000  216.250          정상             정상   \n",
              "3        13704.00  242.18800  118.000  118.000          정상             정상   \n",
              "4            0.00    0.00000  133.000  230.250          경고             정상   \n",
              "...           ...        ...      ...      ...         ...            ...   \n",
              "2420560   7867.00   51.12500  215.128  215.128          주의             정상   \n",
              "2420561  14496.00  145.18750  223.250  388.750          정상             정상   \n",
              "2420562   4172.97   32.79530  219.560  219.560          정상             경고   \n",
              "2420563      0.00   41.96875    0.000    0.000          경고             경고   \n",
              "2420564      0.00    0.00000  229.500  399.500          경고             정상   \n",
              "\n",
              "         label_전압고조파평균     Y결선선간전압  \n",
              "0                   주의  450.188854  \n",
              "1                   정상    0.000000  \n",
              "2                   주의  217.228034  \n",
              "3                   경고  204.525756  \n",
              "4                   정상  231.661796  \n",
              "...                ...         ...  \n",
              "2420560             경고  372.957304  \n",
              "2420561             주의  388.701078  \n",
              "2420562             경고  379.722695  \n",
              "2420563             정상    0.000000  \n",
              "2420564             경고  397.361332  \n",
              "\n",
              "[2417641 rows x 28 columns]"
            ],
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              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>index</th>\n",
              "      <th>누적전력량</th>\n",
              "      <th>유효전력평균</th>\n",
              "      <th>무효전력평균</th>\n",
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              "      <th>선간전압평균</th>\n",
              "      <th>온도</th>\n",
              "      <th>R상유효전력</th>\n",
              "      <th>...</th>\n",
              "      <th>S상선간전압</th>\n",
              "      <th>T상유효전력</th>\n",
              "      <th>T상무효전력</th>\n",
              "      <th>T상전류</th>\n",
              "      <th>T상전압</th>\n",
              "      <th>T상선간전압</th>\n",
              "      <th>label_역률평균</th>\n",
              "      <th>label_전류고조파평균</th>\n",
              "      <th>label_전압고조파평균</th>\n",
              "      <th>Y결선선간전압</th>\n",
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              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>2248930.50</td>\n",
              "      <td>28963.0</td>\n",
              "      <td>20237.0</td>\n",
              "      <td>59.854076</td>\n",
              "      <td>45.197918</td>\n",
              "      <td>259.916656</td>\n",
              "      <td>449.916656</td>\n",
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              "      <td>8663.00</td>\n",
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              "      <td>452.750</td>\n",
              "      <td>10417.00</td>\n",
              "      <td>7304.00</td>\n",
              "      <td>48.71875</td>\n",
              "      <td>260.750</td>\n",
              "      <td>448.750</td>\n",
              "      <td>정상</td>\n",
              "      <td>경고</td>\n",
              "      <td>주의</td>\n",
              "      <td>450.188854</td>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
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              "      <td>24.3750</td>\n",
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              "      <td>0.000</td>\n",
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              "      <td>0.00</td>\n",
              "      <td>100.68750</td>\n",
              "      <td>0.000</td>\n",
              "      <td>0.000</td>\n",
              "      <td>경고</td>\n",
              "      <td>정상</td>\n",
              "      <td>정상</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2</td>\n",
              "      <td>5375707.00</td>\n",
              "      <td>35244.0</td>\n",
              "      <td>19826.0</td>\n",
              "      <td>59.975650</td>\n",
              "      <td>107.385414</td>\n",
              "      <td>125.416664</td>\n",
              "      <td>216.750000</td>\n",
              "      <td>18.7500</td>\n",
              "      <td>11988.00</td>\n",
              "      <td>...</td>\n",
              "      <td>216.250</td>\n",
              "      <td>12236.00</td>\n",
              "      <td>6170.00</td>\n",
              "      <td>109.56250</td>\n",
              "      <td>125.000</td>\n",
              "      <td>216.250</td>\n",
              "      <td>정상</td>\n",
              "      <td>정상</td>\n",
              "      <td>주의</td>\n",
              "      <td>217.228034</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>3</td>\n",
              "      <td>17781200.00</td>\n",
              "      <td>77056.0</td>\n",
              "      <td>39520.0</td>\n",
              "      <td>59.863000</td>\n",
              "      <td>244.854000</td>\n",
              "      <td>118.083000</td>\n",
              "      <td>205.333000</td>\n",
              "      <td>23.1250</td>\n",
              "      <td>25796.00</td>\n",
              "      <td>...</td>\n",
              "      <td>118.750</td>\n",
              "      <td>24992.00</td>\n",
              "      <td>13704.00</td>\n",
              "      <td>242.18800</td>\n",
              "      <td>118.000</td>\n",
              "      <td>118.000</td>\n",
              "      <td>정상</td>\n",
              "      <td>정상</td>\n",
              "      <td>경고</td>\n",
              "      <td>204.525756</td>\n",
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              "      <td>경고</td>\n",
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              "      <td>8631.50</td>\n",
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              "      <td>216.628</td>\n",
              "      <td>7818.50</td>\n",
              "      <td>7867.00</td>\n",
              "      <td>51.12500</td>\n",
              "      <td>215.128</td>\n",
              "      <td>215.128</td>\n",
              "      <td>주의</td>\n",
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              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-ed78d5aa-1a89-42fe-833c-7554c7dba323 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-ed78d5aa-1a89-42fe-833c-7554c7dba323');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? 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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ],
      "source": [
        "ifydf['Y결선선간전압'] = ifydf['상전압평균']*(3**(1/2))\n",
        "ifydf[(ifydf['Y결선선간전압']*0.95 <= ifydf['선간전압평균']) & (ifydf['Y결선선간전압']*1.05 >= ifydf['선간전압평균'])]\n",
        "##### 선간전압이 상전압의 루트3 배이면 Y결선 ####\n",
        "##### drop된 결측치들을 제외하면 row 수가 거의 동일하기에 Y결선임을 알 수 있다. #####"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 13,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 289
        },
        "id": "naGOao5OFce6",
        "outputId": "3c37b302-7770-47e7-91b7-8a6a6e2ae2b7"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ],
      "source": [
        "### 보통 정격주파수는 60Hz ###\n",
        "\n",
        "bins = 100\n",
        "\n",
        "plt.hist(ifydf['주파수'], bins)\n",
        "plt.xlabel('주파수')\n",
        "plt.ylabel('개수')\n",
        "\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 14,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "tWGgkFWYIGSb",
        "outputId": "879ff8a5-9441-4eec-fcc6-e63629a89269"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "유효전력평균  무효전력평균\n",
              "0.0     0.0       88161\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ],
      "source": [
        "ifydf[ifydf['주파수']==0].loc[:,['유효전력평균','무효전력평균']].value_counts()                 #### 주파수가 0이면 측정한 부하설비가 멈춘 상태 임을 알 수 있습니다. ####"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "submit"
      ],
      "metadata": {
        "id": "XRG00NfJrlev",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 485
        },
        "outputId": "834e7c24-717a-4e28-b822-f205c28e154e"
      },
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "            ID         누적전력량   유효전력평균    무효전력평균        주파수        전류평균  \\\n",
              "0            0  5.471566e+06  92992.0  58520.00  59.826096  284.125000   \n",
              "1            1  1.814760e-01      0.0      0.00  59.816770    0.000000   \n",
              "2            2  1.882077e+07  41165.0  11259.00  59.929000   62.302000   \n",
              "3            3  1.425333e+07  72496.0  46050.00  59.826096  131.833328   \n",
              "4            4  3.713425e+06  13205.5  21464.75  58.975000   39.125000   \n",
              "...        ...           ...      ...       ...        ...         ...   \n",
              "313262  313263  2.969156e+06      0.0      0.00  59.854070    0.000000   \n",
              "313263  313264  8.162921e+05      0.0      0.00  59.854103    0.000000   \n",
              "313264  313265  9.445837e+06      0.0      0.00  59.863403    0.000000   \n",
              "313265  313266  1.803930e+07      0.0      0.00  59.948000    0.000000   \n",
              "313266  313267  3.378865e+06      0.0      0.00  59.900784    0.000000   \n",
              "\n",
              "             상전압평균      선간전압평균      온도   R상유효전력  ...   S상유효전력   S상무효전력  \\\n",
              "0       129.416672  224.000000  26.875  30856.0  ...  31472.0  19440.0   \n",
              "1       229.333328  396.916656  23.125      0.0  ...      0.0      0.0   \n",
              "2       228.333000  395.000000  15.000  13584.0  ...  14114.0   3904.0   \n",
              "3       216.250000  374.166656  28.125  25164.0  ...  24656.0  16654.0   \n",
              "4       215.995000  374.113000  10.000   4327.5  ...   5432.5   7740.5   \n",
              "...            ...         ...     ...      ...  ...      ...      ...   \n",
              "313262  264.083344  457.250000  29.375      0.0  ...      0.0      0.0   \n",
              "313263  226.083328  391.166656  28.125      0.0  ...      0.0      0.0   \n",
              "313264  130.500000  225.916672  26.875      0.0  ...      0.0      0.0   \n",
              "313265  265.667000  460.000000  29.375      0.0  ...      0.0      0.0   \n",
              "313266  261.000000  451.833344  27.500      0.0  ...      0.0      0.0   \n",
              "\n",
              "            S상전류     S상전압   S상선간전압   T상유효전력   T상무효전력      T상전류     T상전압  \\\n",
              "0       286.7500  129.500  224.000  30664.0  19048.0  280.3125  129.250   \n",
              "1         0.0000  229.500  395.000      0.0      0.0    0.0000  228.000   \n",
              "2        63.9690  228.750  228.750  13467.0   3557.0   61.2810  227.500   \n",
              "3       136.1875  217.250  374.500  22676.0  15068.0  125.8750  215.500   \n",
              "4        43.5000  217.289  217.289   3445.5   7653.0   39.1250  216.078   \n",
              "...          ...      ...      ...      ...      ...       ...      ...   \n",
              "313262    0.0000  265.250  458.250      0.0      0.0    0.0000  263.500   \n",
              "313263    0.0000  226.250  392.250      0.0      0.0    0.0000  226.500   \n",
              "313264    0.0000  131.250  225.750      0.0      0.0    0.0000  129.500   \n",
              "313265    0.0000  267.000  267.000      0.0      0.0    0.0000  264.500   \n",
              "313266    0.0000  262.500  453.500      0.0      0.0    0.0000  260.500   \n",
              "\n",
              "         T상선간전압  \n",
              "0       223.750  \n",
              "1       396.500  \n",
              "2       227.500  \n",
              "3       372.500  \n",
              "4       216.078  \n",
              "...         ...  \n",
              "313262  455.250  \n",
              "313263  390.750  \n",
              "313264  224.500  \n",
              "313265  264.500  \n",
              "313266  449.250  \n",
              "\n",
              "[313267 rows x 24 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-3e926a8e-f239-462c-aa72-c254d5effb51\">\n",
              "    <div 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>ID</th>\n",
              "      <th>누적전력량</th>\n",
              "      <th>유효전력평균</th>\n",
              "      <th>무효전력평균</th>\n",
              "      <th>주파수</th>\n",
              "      <th>전류평균</th>\n",
              "      <th>상전압평균</th>\n",
              "      <th>선간전압평균</th>\n",
              "      <th>온도</th>\n",
              "      <th>R상유효전력</th>\n",
              "      <th>...</th>\n",
              "      <th>S상유효전력</th>\n",
              "      <th>S상무효전력</th>\n",
              "      <th>S상전류</th>\n",
              "      <th>S상전압</th>\n",
              "      <th>S상선간전압</th>\n",
              "      <th>T상유효전력</th>\n",
              "      <th>T상무효전력</th>\n",
              "      <th>T상전류</th>\n",
              "      <th>T상전압</th>\n",
              "      <th>T상선간전압</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>5.471566e+06</td>\n",
              "      <td>92992.0</td>\n",
              "      <td>58520.00</td>\n",
              "      <td>59.826096</td>\n",
              "      <td>284.125000</td>\n",
              "      <td>129.416672</td>\n",
              "      <td>224.000000</td>\n",
              "      <td>26.875</td>\n",
              "      <td>30856.0</td>\n",
              "      <td>...</td>\n",
              "      <td>31472.0</td>\n",
              "      <td>19440.0</td>\n",
              "      <td>286.7500</td>\n",
              "      <td>129.500</td>\n",
              "      <td>224.000</td>\n",
              "      <td>30664.0</td>\n",
              "      <td>19048.0</td>\n",
              "      <td>280.3125</td>\n",
              "      <td>129.250</td>\n",
              "      <td>223.750</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>1.814760e-01</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>59.816770</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>229.333328</td>\n",
              "      <td>396.916656</td>\n",
              "      <td>23.125</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>229.500</td>\n",
              "      <td>395.000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>228.000</td>\n",
              "      <td>396.500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2</td>\n",
              "      <td>1.882077e+07</td>\n",
              "      <td>41165.0</td>\n",
              "      <td>11259.00</td>\n",
              "      <td>59.929000</td>\n",
              "      <td>62.302000</td>\n",
              "      <td>228.333000</td>\n",
              "      <td>395.000000</td>\n",
              "      <td>15.000</td>\n",
              "      <td>13584.0</td>\n",
              "      <td>...</td>\n",
              "      <td>14114.0</td>\n",
              "      <td>3904.0</td>\n",
              "      <td>63.9690</td>\n",
              "      <td>228.750</td>\n",
              "      <td>228.750</td>\n",
              "      <td>13467.0</td>\n",
              "      <td>3557.0</td>\n",
              "      <td>61.2810</td>\n",
              "      <td>227.500</td>\n",
              "      <td>227.500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>3</td>\n",
              "      <td>1.425333e+07</td>\n",
              "      <td>72496.0</td>\n",
              "      <td>46050.00</td>\n",
              "      <td>59.826096</td>\n",
              "      <td>131.833328</td>\n",
              "      <td>216.250000</td>\n",
              "      <td>374.166656</td>\n",
              "      <td>28.125</td>\n",
              "      <td>25164.0</td>\n",
              "      <td>...</td>\n",
              "      <td>24656.0</td>\n",
              "      <td>16654.0</td>\n",
              "      <td>136.1875</td>\n",
              "      <td>217.250</td>\n",
              "      <td>374.500</td>\n",
              "      <td>22676.0</td>\n",
              "      <td>15068.0</td>\n",
              "      <td>125.8750</td>\n",
              "      <td>215.500</td>\n",
              "      <td>372.500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>4</td>\n",
              "      <td>3.713425e+06</td>\n",
              "      <td>13205.5</td>\n",
              "      <td>21464.75</td>\n",
              "      <td>58.975000</td>\n",
              "      <td>39.125000</td>\n",
              "      <td>215.995000</td>\n",
              "      <td>374.113000</td>\n",
              "      <td>10.000</td>\n",
              "      <td>4327.5</td>\n",
              "      <td>...</td>\n",
              "      <td>5432.5</td>\n",
              "      <td>7740.5</td>\n",
              "      <td>43.5000</td>\n",
              "      <td>217.289</td>\n",
              "      <td>217.289</td>\n",
              "      <td>3445.5</td>\n",
              "      <td>7653.0</td>\n",
              "      <td>39.1250</td>\n",
              "      <td>216.078</td>\n",
              "      <td>216.078</td>\n",
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              "    <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",
              "      <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",
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              "    <tr>\n",
              "      <th>313262</th>\n",
              "      <td>313263</td>\n",
              "      <td>2.969156e+06</td>\n",
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              "      <td>0.00</td>\n",
              "      <td>59.854070</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>264.083344</td>\n",
              "      <td>457.250000</td>\n",
              "      <td>29.375</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>265.250</td>\n",
              "      <td>458.250</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>263.500</td>\n",
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              "    <tr>\n",
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              "      <td>28.125</td>\n",
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              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>226.250</td>\n",
              "      <td>392.250</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>226.500</td>\n",
              "      <td>390.750</td>\n",
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              "    <tr>\n",
              "      <th>313264</th>\n",
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              "      <td>9.445837e+06</td>\n",
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              "      <td>59.863403</td>\n",
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              "      <td>225.916672</td>\n",
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              "      <td>0.0</td>\n",
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              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>131.250</td>\n",
              "      <td>225.750</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>129.500</td>\n",
              "      <td>224.500</td>\n",
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              "    <tr>\n",
              "      <th>313265</th>\n",
              "      <td>313266</td>\n",
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              "      <td>59.948000</td>\n",
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              "      <td>265.667000</td>\n",
              "      <td>460.000000</td>\n",
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              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>267.000</td>\n",
              "      <td>267.000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>264.500</td>\n",
              "      <td>264.500</td>\n",
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              "    <tr>\n",
              "      <th>313266</th>\n",
              "      <td>313267</td>\n",
              "      <td>3.378865e+06</td>\n",
              "      <td>0.0</td>\n",
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              "      <td>59.900784</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>261.000000</td>\n",
              "      <td>451.833344</td>\n",
              "      <td>27.500</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>262.500</td>\n",
              "      <td>453.500</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>260.500</td>\n",
              "      <td>449.250</td>\n",
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              "  </tbody>\n",
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              "<p>313267 rows × 24 columns</p>\n",
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              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-3e926a8e-f239-462c-aa72-c254d5effb51');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? 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",
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              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sample_submission"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "GjU-4Vd-rA8o",
        "outputId": "5fe0271c-e268-4bee-d1cc-35e09cb53b36"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "            ID label_역률평균 label_전류고조파평균 label_전압고조파평균\n",
              "0            0         정상            정상            정상\n",
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              "...        ...        ...           ...           ...\n",
              "313262  313263         정상            정상            정상\n",
              "313263  313264         정상            정상            정상\n",
              "313264  313265         정상            정상            정상\n",
              "313265  313266         정상            정상            정상\n",
              "313266  313267         정상            정상            정상\n",
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              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\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",
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              "    .colab-df-convert:hover {\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
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              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
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              "\n",
              "      <script>\n",
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              "        buttonEl.style.display =\n",
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              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
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              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Nrb7UHoVCmjM"
      },
      "source": [
        "# train의 NaN값\n",
        "### case1\n",
        "'누적전력량', '유효전력평균', '무효전력평균', '주파수', '전류평균', '상전압평균', '선간전압평균', '온도'\n",
        "</br>\n",
        "</br>\n",
        "### case2\n",
        "'R상유효전력', 'R상무효전력', 'R상전류', 'R상전압', 'R상선간전압', 'S상유효전력', 'S상무효전력', 'S상전류', 'S상전압', 'S상선간전압', 'T상유효전력', 'T상무효전력', 'T상전류', 'T상전압', 'T상선간전압'\n",
        "</br>\n",
        "</br>\n",
        "### case3\n",
        "'S상유효전력', 'S상무효전력', 'S상전류', 'S상전압', 'S상선간전압', 'T상유효전력', 'T상무효전력', 'T상전류', 'T상전압', 'T상선간전압'\n",
        "</br>\n",
        "</br>\n",
        "### case4\n",
        "'T상유효전력', 'T상무효전력', 'T상전류', 'T상전압', 'T상선간전압'\n",
        "</br>\n",
        "</br>\n",
        "### case5\n",
        "ALL NaN"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 17,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "d16rlr93gopD",
        "outputId": "cbc8c561-9148-4adc-ff00-9d5052554599"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "index               0\n",
              "누적전력량              17\n",
              "유효전력평균             17\n",
              "무효전력평균             17\n",
              "주파수                17\n",
              "전류평균               17\n",
              "상전압평균              17\n",
              "선간전압평균             17\n",
              "온도                 17\n",
              "R상유효전력             18\n",
              "R상무효전력             18\n",
              "R상전류               18\n",
              "R상전압               18\n",
              "R상선간전압             18\n",
              "S상유효전력           1380\n",
              "S상무효전력           1380\n",
              "S상전류             1380\n",
              "S상전압             1380\n",
              "S상선간전압           1380\n",
              "T상유효전력           2898\n",
              "T상무효전력           2898\n",
              "T상전류             2898\n",
              "T상전압             2898\n",
              "T상선간전압           2898\n",
              "label_역률평균          0\n",
              "label_전류고조파평균       0\n",
              "label_전압고조파평균       0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ],
      "source": [
        "train.isnull().sum()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 18,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 673
        },
        "id": "s-w7JdAUO8kW",
        "outputId": "7ec631c3-cba4-424f-f056-7b13506800e1"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "           index  누적전력량  유효전력평균  무효전력평균  주파수  전류평균  상전압평균  선간전압평균  온도  \\\n",
              "58148      58148    NaN     NaN     NaN  NaN   NaN    NaN     NaN NaN   \n",
              "84362      84362    NaN     NaN     NaN  NaN   NaN    NaN     NaN NaN   \n",
              "112756    112756    NaN     NaN     NaN  NaN   NaN    NaN     NaN NaN   \n",
              "134213    134213    NaN     NaN     NaN  NaN   NaN    NaN     NaN NaN   \n",
              "314942    314942    NaN     NaN     NaN  NaN   NaN    NaN     NaN NaN   \n",
              "453368    453368    NaN     NaN     NaN  NaN   NaN    NaN     NaN NaN   \n",
              "604576    604576    NaN     NaN     NaN  NaN   NaN    NaN     NaN NaN   \n",
              "636506    636506    NaN     NaN     NaN  NaN   NaN    NaN     NaN NaN   \n",
              "771315    771315    NaN     NaN     NaN  NaN   NaN    NaN     NaN NaN   \n",
              "893046    893046    NaN     NaN     NaN  NaN   NaN    NaN     NaN NaN   \n",
              "910188    910188    NaN     NaN     NaN  NaN   NaN    NaN     NaN NaN   \n",
              "981621    981621    NaN     NaN     NaN  NaN   NaN    NaN     NaN NaN   \n",
              "987163    987163    NaN     NaN     NaN  NaN   NaN    NaN     NaN NaN   \n",
              "1410829  1410829    NaN     NaN     NaN  NaN   NaN    NaN     NaN NaN   \n",
              "1583113  1583113    NaN     NaN     NaN  NaN   NaN    NaN     NaN NaN   \n",
              "2023192  2023193    NaN     NaN     NaN  NaN   NaN    NaN     NaN NaN   \n",
              "2226529  2226530    NaN     NaN     NaN  NaN   NaN    NaN     NaN NaN   \n",
              "\n",
              "          R상유효전력  ...     S상전압   S상선간전압   T상유효전력   T상무효전력       T상전류     T상전압  \\\n",
              "58148        0.0  ...  128.625  222.125      0.0      0.0    0.00000  128.500   \n",
              "84362    25752.0  ...  123.250  213.750  25568.0  14432.0  238.37500  122.750   \n",
              "112756   25304.0  ...  117.750  203.750  24952.0  13256.0  242.43750  117.000   \n",
              "134213   37696.0  ...  228.000  391.750  34266.0  14348.0  165.03125  226.125   \n",
              "314942       NaN  ...      NaN      NaN      NaN      NaN        NaN      NaN   \n",
              "453368   26416.0  ...  125.750  217.750  26176.0  15332.0  241.62500  125.250   \n",
              "604576   25028.0  ...  118.750  206.000  24576.0  13440.0  237.06250  118.250   \n",
              "636506       0.0  ...  230.000  395.250      0.0      0.0    0.00000  228.125   \n",
              "771315   25776.0  ...  118.500  205.250  25332.0  13532.0  244.18750  117.750   \n",
              "893046   25540.0  ...  121.500  210.750  25360.0  14048.0  240.00000  121.000   \n",
              "910188   25564.0  ...  119.500  207.250  25036.0  13540.0  240.87500  119.000   \n",
              "981621       NaN  ...      NaN      NaN      NaN      NaN        NaN      NaN   \n",
              "987163   25696.0  ...  118.250  204.750  25316.0  13544.0  245.93750  117.500   \n",
              "1410829  29436.0  ...  228.500  394.000  28236.0  17384.0  145.50000  227.000   \n",
              "1583113  25288.0  ...  120.250  208.250  24984.0  13644.0  237.37500  119.500   \n",
              "2023192  25388.0  ...  118.750  205.750  25040.0  13464.0  241.93750  118.250   \n",
              "2226529  26248.0  ...  126.750  220.000  26660.0  15708.0  245.43750  127.000   \n",
              "\n",
              "          T상선간전압  label_역률평균  label_전류고조파평균  label_전압고조파평균  \n",
              "58148    222.250          경고             정상             주의  \n",
              "84362    213.750          정상             정상             경고  \n",
              "112756   204.000          정상             정상             경고  \n",
              "134213   393.375          정상             주의             경고  \n",
              "314942       NaN          정상             정상             주의  \n",
              "453368   218.000          정상             정상             경고  \n",
              "604576   206.250          정상             정상             경고  \n",
              "636506   396.750          경고             정상             정상  \n",
              "771315   205.500          정상             정상             경고  \n",
              "893046   210.750          정상             정상             경고  \n",
              "910188   207.500          정상             정상             경고  \n",
              "981621       NaN          정상             정상             주의  \n",
              "987163   205.000          정상             정상             경고  \n",
              "1410829  393.000          정상             정상             정상  \n",
              "1583113  208.500          정상             정상             경고  \n",
              "2023192  206.000          정상             정상             경고  \n",
              "2226529  220.000          정상             정상             주의  \n",
              "\n",
              "[17 rows x 27 columns]"
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              "      <th>index</th>\n",
              "      <th>누적전력량</th>\n",
              "      <th>유효전력평균</th>\n",
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              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
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              "      <td>25568.0</td>\n",
              "      <td>14432.0</td>\n",
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              "      <th>112756</th>\n",
              "      <td>112756</td>\n",
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              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>25304.0</td>\n",
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              "      <td>13256.0</td>\n",
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              "      <td>경고</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>604576</th>\n",
              "      <td>604576</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>25028.0</td>\n",
              "      <td>...</td>\n",
              "      <td>118.750</td>\n",
              "      <td>206.000</td>\n",
              "      <td>24576.0</td>\n",
              "      <td>13440.0</td>\n",
              "      <td>237.06250</td>\n",
              "      <td>118.250</td>\n",
              "      <td>206.250</td>\n",
              "      <td>정상</td>\n",
              "      <td>정상</td>\n",
              "      <td>경고</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>636506</th>\n",
              "      <td>636506</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>230.000</td>\n",
              "      <td>395.250</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>228.125</td>\n",
              "      <td>396.750</td>\n",
              "      <td>경고</td>\n",
              "      <td>정상</td>\n",
              "      <td>정상</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>771315</th>\n",
              "      <td>771315</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>25776.0</td>\n",
              "      <td>...</td>\n",
              "      <td>118.500</td>\n",
              "      <td>205.250</td>\n",
              "      <td>25332.0</td>\n",
              "      <td>13532.0</td>\n",
              "      <td>244.18750</td>\n",
              "      <td>117.750</td>\n",
              "      <td>205.500</td>\n",
              "      <td>정상</td>\n",
              "      <td>정상</td>\n",
              "      <td>경고</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>893046</th>\n",
              "      <td>893046</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>25540.0</td>\n",
              "      <td>...</td>\n",
              "      <td>121.500</td>\n",
              "      <td>210.750</td>\n",
              "      <td>25360.0</td>\n",
              "      <td>14048.0</td>\n",
              "      <td>240.00000</td>\n",
              "      <td>121.000</td>\n",
              "      <td>210.750</td>\n",
              "      <td>정상</td>\n",
              "      <td>정상</td>\n",
              "      <td>경고</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>910188</th>\n",
              "      <td>910188</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>25564.0</td>\n",
              "      <td>...</td>\n",
              "      <td>119.500</td>\n",
              "      <td>207.250</td>\n",
              "      <td>25036.0</td>\n",
              "      <td>13540.0</td>\n",
              "      <td>240.87500</td>\n",
              "      <td>119.000</td>\n",
              "      <td>207.500</td>\n",
              "      <td>정상</td>\n",
              "      <td>정상</td>\n",
              "      <td>경고</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>981621</th>\n",
              "      <td>981621</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>정상</td>\n",
              "      <td>정상</td>\n",
              "      <td>주의</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>987163</th>\n",
              "      <td>987163</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>25696.0</td>\n",
              "      <td>...</td>\n",
              "      <td>118.250</td>\n",
              "      <td>204.750</td>\n",
              "      <td>25316.0</td>\n",
              "      <td>13544.0</td>\n",
              "      <td>245.93750</td>\n",
              "      <td>117.500</td>\n",
              "      <td>205.000</td>\n",
              "      <td>정상</td>\n",
              "      <td>정상</td>\n",
              "      <td>경고</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1410829</th>\n",
              "      <td>1410829</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>29436.0</td>\n",
              "      <td>...</td>\n",
              "      <td>228.500</td>\n",
              "      <td>394.000</td>\n",
              "      <td>28236.0</td>\n",
              "      <td>17384.0</td>\n",
              "      <td>145.50000</td>\n",
              "      <td>227.000</td>\n",
              "      <td>393.000</td>\n",
              "      <td>정상</td>\n",
              "      <td>정상</td>\n",
              "      <td>정상</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1583113</th>\n",
              "      <td>1583113</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>25288.0</td>\n",
              "      <td>...</td>\n",
              "      <td>120.250</td>\n",
              "      <td>208.250</td>\n",
              "      <td>24984.0</td>\n",
              "      <td>13644.0</td>\n",
              "      <td>237.37500</td>\n",
              "      <td>119.500</td>\n",
              "      <td>208.500</td>\n",
              "      <td>정상</td>\n",
              "      <td>정상</td>\n",
              "      <td>경고</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2023192</th>\n",
              "      <td>2023193</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>25388.0</td>\n",
              "      <td>...</td>\n",
              "      <td>118.750</td>\n",
              "      <td>205.750</td>\n",
              "      <td>25040.0</td>\n",
              "      <td>13464.0</td>\n",
              "      <td>241.93750</td>\n",
              "      <td>118.250</td>\n",
              "      <td>206.000</td>\n",
              "      <td>정상</td>\n",
              "      <td>정상</td>\n",
              "      <td>경고</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2226529</th>\n",
              "      <td>2226530</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>26248.0</td>\n",
              "      <td>...</td>\n",
              "      <td>126.750</td>\n",
              "      <td>220.000</td>\n",
              "      <td>26660.0</td>\n",
              "      <td>15708.0</td>\n",
              "      <td>245.43750</td>\n",
              "      <td>127.000</td>\n",
              "      <td>220.000</td>\n",
              "      <td>정상</td>\n",
              "      <td>정상</td>\n",
              "      <td>주의</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>17 rows × 27 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-e8567f32-2bfe-447b-9bd6-5976c4d8d037')\"\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 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\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",
              "    [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-e8567f32-2bfe-447b-9bd6-5976c4d8d037 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-e8567f32-2bfe-447b-9bd6-5976c4d8d037');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? 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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 18
        }
      ],
      "source": [
        "train[train['누적전력량'].isnull()]              ### '누적전력량', '유효전력평균', '무효전력평균', '주파수', '전류평균', '상전압평균', '선간전압평균', '온도' ###"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 19,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 704
        },
        "id": "_WheIwnjnPBp",
        "outputId": "78af1d79-6e58-4f2c-d412-a094fc8c9421"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "           index        누적전력량    유효전력평균   무효전력평균        주파수        전류평균  \\\n",
              "116525    116525  13334543.00   78016.0  38100.0  59.956898  248.270828   \n",
              "251838    251838     41331.35    -932.0   6056.0  59.844740  185.812500   \n",
              "314942    314942          NaN       NaN      NaN        NaN         NaN   \n",
              "397035    397035  86272064.00       0.0      0.0  59.807000    0.000000   \n",
              "416847    416847   7923829.50   86532.0  53304.0  59.863403  149.187500   \n",
              "701288    701288  13317905.00   75828.0  37728.0  60.041294  240.979172   \n",
              "825376    825376  86694504.00  111696.0  42868.0  59.920000  175.521000   \n",
              "981621    981621          NaN       NaN      NaN        NaN         NaN   \n",
              "1042872  1042872   3182382.50   79882.0  44316.0  59.928824  242.166672   \n",
              "1064167  1064167  13479208.00   76872.0  38096.0  59.835537  241.625000   \n",
              "1216811  1216811   1300657.44   79828.0  43814.0  59.877449  242.052078   \n",
              "1326016  1326016  13511176.00   76892.0  37876.0  59.919483  242.916672   \n",
              "1605433  1605433  13289742.00   77532.0  37964.0  59.947537  246.500000   \n",
              "1714178  1714179  13541937.00   76572.0  38244.0  59.985020  240.520828   \n",
              "1734274  1734275   2934100.75       0.0      0.0  59.872757    0.000000   \n",
              "2005856  2005857  13524007.00   76400.0  37528.0  59.938183  242.020828   \n",
              "2200581  2200582  13590557.00   78120.0  40608.0  59.956913  238.875000   \n",
              "2366653  2366654  13561094.00   77564.0  39564.0  59.947544  240.458328   \n",
              "\n",
              "              상전압평균      선간전압평균      온도  R상유효전력  ...  S상전압  S상선간전압  T상유효전력  \\\n",
              "116525   117.000000  203.583328  30.625     NaN  ...   NaN     NaN     NaN   \n",
              "251838   226.500000  391.916656  33.125     NaN  ...   NaN     NaN     NaN   \n",
              "314942          NaN         NaN     NaN     NaN  ...   NaN     NaN     NaN   \n",
              "397035   229.917000  397.833000  22.500     NaN  ...   NaN     NaN     NaN   \n",
              "416847   227.833328  394.333344  41.250     NaN  ...   NaN     NaN     NaN   \n",
              "701288   118.250000  205.750000  30.625     NaN  ...   NaN     NaN     NaN   \n",
              "825376   226.833000  392.583000  32.500     NaN  ...   NaN     NaN     NaN   \n",
              "981621          NaN         NaN     NaN     NaN  ...   NaN     NaN     NaN   \n",
              "1042872  126.375000  219.291664  25.000     NaN  ...   NaN     NaN     NaN   \n",
              "1064167  118.333336  205.833328  31.250     NaN  ...   NaN     NaN     NaN   \n",
              "1216811  125.458332  217.958328  23.750     NaN  ...   NaN     NaN     NaN   \n",
              "1326016  118.083336  205.416672  31.250     NaN  ...   NaN     NaN     NaN   \n",
              "1605433  117.000000  203.166672  31.250     NaN  ...   NaN     NaN     NaN   \n",
              "1714178  118.916664  206.833328  31.875     NaN  ...   NaN     NaN     NaN   \n",
              "1734274  128.583328  222.166672   9.375     NaN  ...   NaN     NaN     NaN   \n",
              "2005856  117.416664  204.083328  31.250     NaN  ...   NaN     NaN     NaN   \n",
              "2200581  122.916664  213.500000  31.250     NaN  ...   NaN     NaN     NaN   \n",
              "2366653  120.916664  210.166672  31.250     NaN  ...   NaN     NaN     NaN   \n",
              "\n",
              "         T상무효전력  T상전류  T상전압  T상선간전압  label_역률평균  label_전류고조파평균  label_전압고조파평균  \n",
              "116525      NaN   NaN   NaN     NaN          정상             정상             경고  \n",
              "251838      NaN   NaN   NaN     NaN          경고             주의             경고  \n",
              "314942      NaN   NaN   NaN     NaN          정상             정상             주의  \n",
              "397035      NaN   NaN   NaN     NaN          경고             정상             정상  \n",
              "416847      NaN   NaN   NaN     NaN          정상             정상             정상  \n",
              "701288      NaN   NaN   NaN     NaN          정상             정상             경고  \n",
              "825376      NaN   NaN   NaN     NaN          정상             주의             경고  \n",
              "981621      NaN   NaN   NaN     NaN          정상             정상             주의  \n",
              "1042872     NaN   NaN   NaN     NaN          정상             정상             주의  \n",
              "1064167     NaN   NaN   NaN     NaN          정상             정상             경고  \n",
              "1216811     NaN   NaN   NaN     NaN          정상             정상             경고  \n",
              "1326016     NaN   NaN   NaN     NaN          정상             정상             경고  \n",
              "1605433     NaN   NaN   NaN     NaN          정상             정상             경고  \n",
              "1714178     NaN   NaN   NaN     NaN          정상             정상             경고  \n",
              "1734274     NaN   NaN   NaN     NaN          경고             정상             주의  \n",
              "2005856     NaN   NaN   NaN     NaN          정상             정상             경고  \n",
              "2200581     NaN   NaN   NaN     NaN          정상             정상             경고  \n",
              "2366653     NaN   NaN   NaN     NaN          정상             정상             경고  \n",
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              "      width: 32px;\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
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              "      fill: #174EA6;\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-0a08680d-7398-44b3-8035-41fee1a026f7 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-0a08680d-7398-44b3-8035-41fee1a026f7');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? 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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 19
        }
      ],
      "source": [
        "train[train['R상유효전력'].isnull()]         ### 'R상유효전력', 'R상무효전력', 'R상전류', 'R상전압', 'R상선간전압', 'S상유효전력', 'S상무효전력', 'S상전류', 'S상전압', 'S상선간전압',\n",
        "                                             ### 'T상유효전력', 'T상무효전력', 'T상전류', 'T상전압', 'T상선간전압' ###                                         "
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 20,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 485
        },
        "id": "-6xIXgHTpVog",
        "outputId": "f91ec1ef-3405-4a94-ca88-2c9dd3619805"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "          R상유효전력   R상무효전력     R상전류    R상전압  R상선간전압  S상유효전력  S상무효전력  S상전류  \\\n",
              "3058     52128.0  22676.0  216.875  262.25  262.25     NaN     NaN   NaN   \n",
              "4291         0.0      0.0    0.000  268.50  268.50     NaN     NaN   NaN   \n",
              "11059    53336.0  23580.0  223.063  261.50  261.50     NaN     NaN   NaN   \n",
              "13750        0.0      0.0    0.000  269.75  269.75     NaN     NaN   NaN   \n",
              "14575        0.0      0.0    0.000  269.50  269.50     NaN     NaN   NaN   \n",
              "...          ...      ...      ...     ...     ...     ...     ...   ...   \n",
              "2412980  52604.0  22776.0  219.188  261.75  261.75     NaN     NaN   NaN   \n",
              "2416703      0.0      0.0    0.000  268.25  268.25     NaN     NaN   NaN   \n",
              "2416932  54384.0  24088.0  228.188  261.00  261.00     NaN     NaN   NaN   \n",
              "2417278      0.0      0.0    0.000  267.50  267.50     NaN     NaN   NaN   \n",
              "2419130  52168.0  22616.0  216.875  262.00  262.00     NaN     NaN   NaN   \n",
              "\n",
              "         S상전압  S상선간전압  T상유효전력  T상무효전력  T상전류  T상전압  T상선간전압 label_역률평균  \\\n",
              "3058      NaN     NaN     NaN     NaN   NaN   NaN     NaN         정상   \n",
              "4291      NaN     NaN     NaN     NaN   NaN   NaN     NaN         경고   \n",
              "11059     NaN     NaN     NaN     NaN   NaN   NaN     NaN         정상   \n",
              "13750     NaN     NaN     NaN     NaN   NaN   NaN     NaN         경고   \n",
              "14575     NaN     NaN     NaN     NaN   NaN   NaN     NaN         경고   \n",
              "...       ...     ...     ...     ...   ...   ...     ...        ...   \n",
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              "2417278   NaN     NaN     NaN     NaN   NaN   NaN     NaN         경고   \n",
              "2419130   NaN     NaN     NaN     NaN   NaN   NaN     NaN         정상   \n",
              "\n",
              "        label_전류고조파평균 label_전압고조파평균  \n",
              "3058               정상            정상  \n",
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              "13750              정상            정상  \n",
              "14575              정상            정상  \n",
              "...               ...           ...  \n",
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              "2417278            정상            정상  \n",
              "2419130            정상            정상  \n",
              "\n",
              "[1380 rows x 18 columns]"
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              "      <th>R상유효전력</th>\n",
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              "      <td>정상</td>\n",
              "      <td>정상</td>\n",
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              "      <th>2417278</th>\n",
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              "      <td>정상</td>\n",
              "      <td>정상</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1380 rows × 18 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-5643fa14-c545-4a67-8401-8560cee4043a')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "\n",
              "          const docLinkHtml = 'Like what you see? 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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 20
        }
      ],
      "source": [
        "train[train['S상유효전력'].isnull()].loc[:,'R상유효전력':'label_전압고조파평균']     ### 'S상유효전력', 'S상무효전력', 'S상전류', 'S상전압', 'S상선간전압', 'T상유효전력', 'T상무효전력', 'T상전류', 'T상전압', 'T상선간전압' ###"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 21,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 485
        },
        "id": "3y4r0g6Bqf35",
        "outputId": "f92102f6-1a8e-4816-8c84-87a713abb0c4"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "           index       누적전력량    유효전력평균   무효전력평균     주파수     전류평균    상전압평균  \\\n",
              "1091        1091    643793.5   29283.0  43943.5  59.861   76.542  211.891   \n",
              "2606        2606    596237.0   31921.0  72284.0  59.091   73.625  211.556   \n",
              "3058        3058  55397068.0  156232.0  67968.0  59.985  216.583  262.333   \n",
              "4291        4291  54121632.0       0.0      0.0  59.891    0.000  268.583   \n",
              "5404        5404    932778.0   41812.0  21528.0  58.166   74.792  211.548   \n",
              "...          ...         ...       ...      ...     ...      ...      ...   \n",
              "2416703  2416704  54121632.0       0.0      0.0  59.957    0.000  268.333   \n",
              "2416806  2416807  54121632.0       0.0      0.0  59.901    0.000  267.167   \n",
              "2416932  2416933  54466840.0  162692.0  72720.0  59.863  227.938  261.333   \n",
              "2417278  2417279  54121632.0       0.0      0.0  59.919    0.000  267.500   \n",
              "2419130  2419131  55389280.0  156180.0  67908.0  59.966  216.333  262.167   \n",
              "\n",
              "          선간전압평균      온도   R상유효전력  ...     S상전압   S상선간전압  T상유효전력  T상무효전력  \\\n",
              "1091     367.005  20.313  13242.0  ...  211.780  211.780     NaN     NaN   \n",
              "2606     366.425  20.313   8862.0  ...  211.955  211.955     NaN     NaN   \n",
              "3058     454.250  33.750  52128.0  ...      NaN      NaN     NaN     NaN   \n",
              "4291     464.917  26.875      0.0  ...      NaN      NaN     NaN     NaN   \n",
              "5404     366.411  15.000  13498.0  ...  211.393  211.393     NaN     NaN   \n",
              "...          ...     ...      ...  ...      ...      ...     ...     ...   \n",
              "2416703  464.667  27.500      0.0  ...      NaN      NaN     NaN     NaN   \n",
              "2416806  462.500  29.375      0.0  ...  268.500  268.500     NaN     NaN   \n",
              "2416932  452.167  28.125  54384.0  ...      NaN      NaN     NaN     NaN   \n",
              "2417278  463.167  28.750      0.0  ...      NaN      NaN     NaN     NaN   \n",
              "2419130  453.833  33.750  52168.0  ...      NaN      NaN     NaN     NaN   \n",
              "\n",
              "         T상전류  T상전압  T상선간전압  label_역률평균  label_전류고조파평균  label_전압고조파평균  \n",
              "1091      NaN   NaN     NaN          정상             정상             경고  \n",
              "2606      NaN   NaN     NaN          정상             정상             경고  \n",
              "3058      NaN   NaN     NaN          정상             정상             정상  \n",
              "4291      NaN   NaN     NaN          경고             정상             정상  \n",
              "5404      NaN   NaN     NaN          주의             정상             경고  \n",
              "...       ...   ...     ...         ...            ...            ...  \n",
              "2416703   NaN   NaN     NaN          경고             정상             정상  \n",
              "2416806   NaN   NaN     NaN          경고             정상             정상  \n",
              "2416932   NaN   NaN     NaN          정상             정상             정상  \n",
              "2417278   NaN   NaN     NaN          경고             정상             정상  \n",
              "2419130   NaN   NaN     NaN          정상             정상             정상  \n",
              "\n",
              "[2898 rows x 27 columns]"
            ],
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>index</th>\n",
              "      <th>누적전력량</th>\n",
              "      <th>유효전력평균</th>\n",
              "      <th>무효전력평균</th>\n",
              "      <th>주파수</th>\n",
              "      <th>전류평균</th>\n",
              "      <th>상전압평균</th>\n",
              "      <th>선간전압평균</th>\n",
              "      <th>온도</th>\n",
              "      <th>R상유효전력</th>\n",
              "      <th>...</th>\n",
              "      <th>S상전압</th>\n",
              "      <th>S상선간전압</th>\n",
              "      <th>T상유효전력</th>\n",
              "      <th>T상무효전력</th>\n",
              "      <th>T상전류</th>\n",
              "      <th>T상전압</th>\n",
              "      <th>T상선간전압</th>\n",
              "      <th>label_역률평균</th>\n",
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              "      <th>label_전압고조파평균</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>1091</th>\n",
              "      <td>1091</td>\n",
              "      <td>643793.5</td>\n",
              "      <td>29283.0</td>\n",
              "      <td>43943.5</td>\n",
              "      <td>59.861</td>\n",
              "      <td>76.542</td>\n",
              "      <td>211.891</td>\n",
              "      <td>367.005</td>\n",
              "      <td>20.313</td>\n",
              "      <td>13242.0</td>\n",
              "      <td>...</td>\n",
              "      <td>211.780</td>\n",
              "      <td>211.780</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>정상</td>\n",
              "      <td>정상</td>\n",
              "      <td>경고</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2606</th>\n",
              "      <td>2606</td>\n",
              "      <td>596237.0</td>\n",
              "      <td>31921.0</td>\n",
              "      <td>72284.0</td>\n",
              "      <td>59.091</td>\n",
              "      <td>73.625</td>\n",
              "      <td>211.556</td>\n",
              "      <td>366.425</td>\n",
              "      <td>20.313</td>\n",
              "      <td>8862.0</td>\n",
              "      <td>...</td>\n",
              "      <td>211.955</td>\n",
              "      <td>211.955</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>정상</td>\n",
              "      <td>정상</td>\n",
              "      <td>경고</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3058</th>\n",
              "      <td>3058</td>\n",
              "      <td>55397068.0</td>\n",
              "      <td>156232.0</td>\n",
              "      <td>67968.0</td>\n",
              "      <td>59.985</td>\n",
              "      <td>216.583</td>\n",
              "      <td>262.333</td>\n",
              "      <td>454.250</td>\n",
              "      <td>33.750</td>\n",
              "      <td>52128.0</td>\n",
              "      <td>...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>정상</td>\n",
              "      <td>정상</td>\n",
              "      <td>정상</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4291</th>\n",
              "      <td>4291</td>\n",
              "      <td>54121632.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>59.891</td>\n",
              "      <td>0.000</td>\n",
              "      <td>268.583</td>\n",
              "      <td>464.917</td>\n",
              "      <td>26.875</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>경고</td>\n",
              "      <td>정상</td>\n",
              "      <td>정상</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5404</th>\n",
              "      <td>5404</td>\n",
              "      <td>932778.0</td>\n",
              "      <td>41812.0</td>\n",
              "      <td>21528.0</td>\n",
              "      <td>58.166</td>\n",
              "      <td>74.792</td>\n",
              "      <td>211.548</td>\n",
              "      <td>366.411</td>\n",
              "      <td>15.000</td>\n",
              "      <td>13498.0</td>\n",
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              "      <td>정상</td>\n",
              "      <td>경고</td>\n",
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              "      <td>2416704</td>\n",
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              "      <td>59.957</td>\n",
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              "      <td>464.667</td>\n",
              "      <td>27.500</td>\n",
              "      <td>0.0</td>\n",
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              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>경고</td>\n",
              "      <td>정상</td>\n",
              "      <td>정상</td>\n",
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              "      <th>2416806</th>\n",
              "      <td>2416807</td>\n",
              "      <td>54121632.0</td>\n",
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              "      <td>0.0</td>\n",
              "      <td>59.901</td>\n",
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              "      <td>29.375</td>\n",
              "      <td>0.0</td>\n",
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              "      <td>NaN</td>\n",
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              "      <td>정상</td>\n",
              "      <td>정상</td>\n",
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              "      <th>2416932</th>\n",
              "      <td>2416933</td>\n",
              "      <td>54466840.0</td>\n",
              "      <td>162692.0</td>\n",
              "      <td>72720.0</td>\n",
              "      <td>59.863</td>\n",
              "      <td>227.938</td>\n",
              "      <td>261.333</td>\n",
              "      <td>452.167</td>\n",
              "      <td>28.125</td>\n",
              "      <td>54384.0</td>\n",
              "      <td>...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>정상</td>\n",
              "      <td>정상</td>\n",
              "      <td>정상</td>\n",
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              "    <tr>\n",
              "      <th>2417278</th>\n",
              "      <td>2417279</td>\n",
              "      <td>54121632.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>59.919</td>\n",
              "      <td>0.000</td>\n",
              "      <td>267.500</td>\n",
              "      <td>463.167</td>\n",
              "      <td>28.750</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>경고</td>\n",
              "      <td>정상</td>\n",
              "      <td>정상</td>\n",
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              "    <tr>\n",
              "      <th>2419130</th>\n",
              "      <td>2419131</td>\n",
              "      <td>55389280.0</td>\n",
              "      <td>156180.0</td>\n",
              "      <td>67908.0</td>\n",
              "      <td>59.966</td>\n",
              "      <td>216.333</td>\n",
              "      <td>262.167</td>\n",
              "      <td>453.833</td>\n",
              "      <td>33.750</td>\n",
              "      <td>52168.0</td>\n",
              "      <td>...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>정상</td>\n",
              "      <td>정상</td>\n",
              "      <td>정상</td>\n",
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              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-85593498-5ff6-4c10-af28-0637515b0d1b');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? 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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 21
        }
      ],
      "source": [
        "train[train['T상유효전력'].isnull()]                        ### 'T상유효전력', 'T상무효전력', 'T상전류', 'T상전압', 'T상선간전압' ###"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "4oGah3xnA_uW"
      },
      "source": [
        "# submit의 NaN값\n",
        "### case1\n",
        "'누적전력량', '유효전력평균', '무효전력평균', '주파수', '전류평균', '상전압평균', '선간전압평균', '온도'\n",
        "</br>\n",
        "</br>\n",
        "### case2\n",
        "'R상유효전력', 'R상무효전력', 'R상전류', 'R상전압', 'R상선간전압', 'S상유효전력', 'S상무효전력', 'S상전류', 'S상전압', 'S상선간전압', 'T상유효전력', 'T상무효전력', 'T상전류', 'T상전압', 'T상선간전압'"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 22,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YZ0V5g_YDV85",
        "outputId": "eb213d2b-82e3-4453-aacf-285066859c7a"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "((313267, 24), (313267, 4))"
            ]
          },
          "metadata": {},
          "execution_count": 22
        }
      ],
      "source": [
        "submit.shape, sample_submission.shape       #### test shape을 sample_submission shape에 맞춰야하므로 dropna는 쓰지못함 ####"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 23,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 297
        },
        "id": "l--Un9DZ1MlO",
        "outputId": "fdb2025e-6f97-406d-ceab-db1ccc567ecf"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   ID         누적전력량   유효전력평균    무효전력평균        주파수        전류평균       상전압평균  \\\n",
              "0   0  5.471566e+06  92992.0  58520.00  59.826096  284.125000  129.416672   \n",
              "1   1  1.814760e-01      0.0      0.00  59.816770    0.000000  229.333328   \n",
              "2   2  1.882077e+07  41165.0  11259.00  59.929000   62.302000  228.333000   \n",
              "3   3  1.425333e+07  72496.0  46050.00  59.826096  131.833328  216.250000   \n",
              "4   4  3.713425e+06  13205.5  21464.75  58.975000   39.125000  215.995000   \n",
              "\n",
              "       선간전압평균      온도   R상유효전력  ...   S상유효전력   S상무효전력      S상전류     S상전압  \\\n",
              "0  224.000000  26.875  30856.0  ...  31472.0  19440.0  286.7500  129.500   \n",
              "1  396.916656  23.125      0.0  ...      0.0      0.0    0.0000  229.500   \n",
              "2  395.000000  15.000  13584.0  ...  14114.0   3904.0   63.9690  228.750   \n",
              "3  374.166656  28.125  25164.0  ...  24656.0  16654.0  136.1875  217.250   \n",
              "4  374.113000  10.000   4327.5  ...   5432.5   7740.5   43.5000  217.289   \n",
              "\n",
              "    S상선간전압   T상유효전력   T상무효전력      T상전류     T상전압   T상선간전압  \n",
              "0  224.000  30664.0  19048.0  280.3125  129.250  223.750  \n",
              "1  395.000      0.0      0.0    0.0000  228.000  396.500  \n",
              "2  228.750  13467.0   3557.0   61.2810  227.500  227.500  \n",
              "3  374.500  22676.0  15068.0  125.8750  215.500  372.500  \n",
              "4  217.289   3445.5   7653.0   39.1250  216.078  216.078  \n",
              "\n",
              "[5 rows x 24 columns]"
            ],
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              "\n",
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              "    <div 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",
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              "\n",
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              "        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>ID</th>\n",
              "      <th>누적전력량</th>\n",
              "      <th>유효전력평균</th>\n",
              "      <th>무효전력평균</th>\n",
              "      <th>주파수</th>\n",
              "      <th>전류평균</th>\n",
              "      <th>상전압평균</th>\n",
              "      <th>선간전압평균</th>\n",
              "      <th>온도</th>\n",
              "      <th>R상유효전력</th>\n",
              "      <th>...</th>\n",
              "      <th>S상유효전력</th>\n",
              "      <th>S상무효전력</th>\n",
              "      <th>S상전류</th>\n",
              "      <th>S상전압</th>\n",
              "      <th>S상선간전압</th>\n",
              "      <th>T상유효전력</th>\n",
              "      <th>T상무효전력</th>\n",
              "      <th>T상전류</th>\n",
              "      <th>T상전압</th>\n",
              "      <th>T상선간전압</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>5.471566e+06</td>\n",
              "      <td>92992.0</td>\n",
              "      <td>58520.00</td>\n",
              "      <td>59.826096</td>\n",
              "      <td>284.125000</td>\n",
              "      <td>129.416672</td>\n",
              "      <td>224.000000</td>\n",
              "      <td>26.875</td>\n",
              "      <td>30856.0</td>\n",
              "      <td>...</td>\n",
              "      <td>31472.0</td>\n",
              "      <td>19440.0</td>\n",
              "      <td>286.7500</td>\n",
              "      <td>129.500</td>\n",
              "      <td>224.000</td>\n",
              "      <td>30664.0</td>\n",
              "      <td>19048.0</td>\n",
              "      <td>280.3125</td>\n",
              "      <td>129.250</td>\n",
              "      <td>223.750</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>1.814760e-01</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>59.816770</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>229.333328</td>\n",
              "      <td>396.916656</td>\n",
              "      <td>23.125</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>229.500</td>\n",
              "      <td>395.000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>228.000</td>\n",
              "      <td>396.500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2</td>\n",
              "      <td>1.882077e+07</td>\n",
              "      <td>41165.0</td>\n",
              "      <td>11259.00</td>\n",
              "      <td>59.929000</td>\n",
              "      <td>62.302000</td>\n",
              "      <td>228.333000</td>\n",
              "      <td>395.000000</td>\n",
              "      <td>15.000</td>\n",
              "      <td>13584.0</td>\n",
              "      <td>...</td>\n",
              "      <td>14114.0</td>\n",
              "      <td>3904.0</td>\n",
              "      <td>63.9690</td>\n",
              "      <td>228.750</td>\n",
              "      <td>228.750</td>\n",
              "      <td>13467.0</td>\n",
              "      <td>3557.0</td>\n",
              "      <td>61.2810</td>\n",
              "      <td>227.500</td>\n",
              "      <td>227.500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>3</td>\n",
              "      <td>1.425333e+07</td>\n",
              "      <td>72496.0</td>\n",
              "      <td>46050.00</td>\n",
              "      <td>59.826096</td>\n",
              "      <td>131.833328</td>\n",
              "      <td>216.250000</td>\n",
              "      <td>374.166656</td>\n",
              "      <td>28.125</td>\n",
              "      <td>25164.0</td>\n",
              "      <td>...</td>\n",
              "      <td>24656.0</td>\n",
              "      <td>16654.0</td>\n",
              "      <td>136.1875</td>\n",
              "      <td>217.250</td>\n",
              "      <td>374.500</td>\n",
              "      <td>22676.0</td>\n",
              "      <td>15068.0</td>\n",
              "      <td>125.8750</td>\n",
              "      <td>215.500</td>\n",
              "      <td>372.500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>4</td>\n",
              "      <td>3.713425e+06</td>\n",
              "      <td>13205.5</td>\n",
              "      <td>21464.75</td>\n",
              "      <td>58.975000</td>\n",
              "      <td>39.125000</td>\n",
              "      <td>215.995000</td>\n",
              "      <td>374.113000</td>\n",
              "      <td>10.000</td>\n",
              "      <td>4327.5</td>\n",
              "      <td>...</td>\n",
              "      <td>5432.5</td>\n",
              "      <td>7740.5</td>\n",
              "      <td>43.5000</td>\n",
              "      <td>217.289</td>\n",
              "      <td>217.289</td>\n",
              "      <td>3445.5</td>\n",
              "      <td>7653.0</td>\n",
              "      <td>39.1250</td>\n",
              "      <td>216.078</td>\n",
              "      <td>216.078</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 24 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-3e1e5ab6-9420-4800-837a-618e1ee6b804')\"\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 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\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",
              "    [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-3e1e5ab6-9420-4800-837a-618e1ee6b804 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-3e1e5ab6-9420-4800-837a-618e1ee6b804');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? 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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 23
        }
      ],
      "source": [
        "submit.head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 24,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "poS1R087maMv",
        "outputId": "c7affd09-cc99-4755-a290-d43840e5534d"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "ID         0\n",
              "누적전력량     61\n",
              "유효전력평균    61\n",
              "무효전력평균    61\n",
              "주파수       61\n",
              "전류평균      61\n",
              "상전압평균     61\n",
              "선간전압평균    61\n",
              "온도        61\n",
              "R상유효전력    61\n",
              "R상무효전력    61\n",
              "R상전류      61\n",
              "R상전압      61\n",
              "R상선간전압    61\n",
              "S상유효전력    61\n",
              "S상무효전력    61\n",
              "S상전류      61\n",
              "S상전압      61\n",
              "S상선간전압    61\n",
              "T상유효전력    61\n",
              "T상무효전력    61\n",
              "T상전류      61\n",
              "T상전압      61\n",
              "T상선간전압    61\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 24
        }
      ],
      "source": [
        "submit.isnull().sum()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 25,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 485
        },
        "id": "t7fVlqcliUnS",
        "outputId": "fb7f540b-8c9f-453e-dc9b-3afa19039ee3"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "            ID  누적전력량  유효전력평균  무효전력평균  주파수  전류평균  상전압평균  선간전압평균  온도   R상유효전력  \\\n",
              "7666      7666    NaN     NaN     NaN  NaN   NaN    NaN     NaN NaN  25604.0   \n",
              "11360    11360    NaN     NaN     NaN  NaN   NaN    NaN     NaN NaN  25492.0   \n",
              "16596    16596    NaN     NaN     NaN  NaN   NaN    NaN     NaN NaN  25340.0   \n",
              "20155    20155    NaN     NaN     NaN  NaN   NaN    NaN     NaN NaN  26292.0   \n",
              "20800    20800    NaN     NaN     NaN  NaN   NaN    NaN     NaN NaN  26176.0   \n",
              "...        ...    ...     ...     ...  ...   ...    ...     ...  ..      ...   \n",
              "290395  290396    NaN     NaN     NaN  NaN   NaN    NaN     NaN NaN  26396.0   \n",
              "293504  293505    NaN     NaN     NaN  NaN   NaN    NaN     NaN NaN  25756.0   \n",
              "294513  294514    NaN     NaN     NaN  NaN   NaN    NaN     NaN NaN  24988.0   \n",
              "295852  295853    NaN     NaN     NaN  NaN   NaN    NaN     NaN NaN  26056.0   \n",
              "311181  311182    NaN     NaN     NaN  NaN   NaN    NaN     NaN NaN  25900.0   \n",
              "\n",
              "        ...   S상유효전력   S상무효전력      S상전류    S상전압  S상선간전압   T상유효전력   T상무효전력  \\\n",
              "7666    ...  26732.0  13660.0  246.6250  121.00  209.75  25136.0  14284.0   \n",
              "11360   ...  25912.0  13468.0  242.2500  121.25  209.75  24780.0  13808.0   \n",
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              "\n",
              "            T상전류    T상전압  T상선간전압  \n",
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          "metadata": {},
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      ]
    },
    {
      "cell_type": "code",
      "execution_count": 26,
      "metadata": {
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          "height": 485
        },
        "id": "OH9gqD5MFPK-",
        "outputId": "d54a3475-32c5-4862-836e-c8f6c6656fb1"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "            ID       누적전력량   유효전력평균   무효전력평균        주파수        전류평균  \\\n",
              "3113      3113  32224420.0  76956.0  39220.0  59.928820  242.187500   \n",
              "5284      5284  24529634.0  76092.0  38032.0  59.844830  240.604172   \n",
              "10204    10204  30391494.0  80116.0  44760.0  59.928820  241.791672   \n",
              "13852    13852  28497384.0  79904.0  44088.0  59.938183  241.958328   \n",
              "14909    14909  26363986.0  75964.0  38476.0  59.900765  237.770828   \n",
              "...        ...         ...      ...      ...        ...         ...   \n",
              "253260  253261  30170734.0  79568.0  45128.0  59.872757  239.750000   \n",
              "265940  265941  24225962.0  76612.0  40120.0  59.919464  235.937500   \n",
              "268138  268139  30853350.0  79696.0  46276.0  59.891440  240.479172   \n",
              "290094  290095  30504350.0  79724.0  44688.0  59.928820  242.208328   \n",
              "294294  294295  26613608.0  53520.0  29244.0  59.882103  238.145828   \n",
              "\n",
              "             상전압평균      선간전압평균      온도  R상유효전력  ...  S상유효전력  S상무효전력  S상전류  \\\n",
              "3113    118.416664  205.750000  22.500     NaN  ...     NaN     NaN   NaN   \n",
              "5284    117.500000  204.166672  25.625     NaN  ...     NaN     NaN   NaN   \n",
              "10204   126.083336  218.916672  20.000     NaN  ...     NaN     NaN   NaN   \n",
              "13852   125.833336  218.500000  23.125     NaN  ...     NaN     NaN   NaN   \n",
              "14909   119.583336  207.833328  27.500     NaN  ...     NaN     NaN   NaN   \n",
              "...            ...         ...     ...     ...  ...     ...     ...   ...   \n",
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              "\n",
              "        S상전압  S상선간전압  T상유효전력  T상무효전력  T상전류  T상전압  T상선간전압  \n",
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              "...      ...     ...     ...     ...   ...   ...     ...  \n",
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              "290094   NaN     NaN     NaN     NaN   NaN   NaN     NaN  \n",
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              "\n",
              "[61 rows x 24 columns]"
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              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
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              "<p>61 rows × 24 columns</p>\n",
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-2a394279-d401-4dc7-9302-881edad8b130')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
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              "    .colab-df-container {\n",
              "      display:flex;\n",
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              "      gap: 12px;\n",
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              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
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              "      border-radius: 50%;\n",
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              "\n",
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              "          document.querySelector('#df-2a394279-d401-4dc7-9302-881edad8b130 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-2a394279-d401-4dc7-9302-881edad8b130');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? 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",
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              "          element.appendChild(docLink);\n",
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              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 26
        }
      ],
      "source": [
        "submit[submit['R상유효전력'].isnull()] "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "NGYa98VaSsqX"
      },
      "source": [
        "sumit NaN값 case가 train NaN값 case에 포함되므로 train NaN값 케이스를 기준으로 processing 진행"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "_CW-kfL_TfTr"
      },
      "outputs": [],
      "source": [
        "case1 = '누적전력량', '유효전력평균', '무효전력평균', '주파수', '전류평균', '상전압평균', '선간전압평균', '온도'\n",
        "case2 = 'R상유효전력', 'R상무효전력', 'R상전류', 'R상전압', 'R상선간전압', 'S상유효전력', 'S상무효전력', 'S상전류', 'S상전압', 'S상선간전압', 'T상유효전력', 'T상무효전력', 'T상전류', 'T상전압', 'T상선간전압'\n",
        "case3 = 'S상유효전력', 'S상무효전력', 'S상전류', 'S상전압', 'S상선간전압', 'T상유효전력', 'T상무효전력', 'T상전류', 'T상전압', 'T상선간전압'\n",
        "case4 = 'T상유효전력', 'T상무효전력', 'T상전류', 'T상전압', 'T상선간전압'\n",
        "case5 = '누적전력량', '유효전력평균', '무효전력평균', '주파수', '전류평균', '상전압평균', '선간전압평균', '온도', 'R상유효전력', 'R상무효전력', 'R상전류', 'R상전압', 'R상선간전압', 'S상유효전력', 'S상무효전력', 'S상전류', 'S상전압', 'S상선간전압', 'T상유효전력', 'T상무효전력', 'T상전류', 'T상전압', 'T상선간전압'"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "0QiqPq592jTR"
      },
      "outputs": [],
      "source": [
        "### case1 ###\n",
        "# 누적전력량 -> 앞뒤의 평균값\n",
        "# 유효전력평균 -> 각 유효전력 더하기\n",
        "# 무효전력평균 -> 각 무효전력 더하기\n",
        "# 주파수 -> 앞뒤의 평균값\n",
        "# 전류평균 -> 각 전류 더하고 / 3\n",
        "# 상전압평균 -> 각 상전압 더하고 / 3\n",
        "# 선간전압평균 -> 각 선간전압 더하고 / 3\n",
        "# 온도 -> 앞뒤의 평균값"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "9vB9R7FAFLbU"
      },
      "outputs": [],
      "source": [
        "### case2 ###\n",
        "# 각 상 유효전력 -> 유효전력평균 / 3\n",
        "# 각 상 무효전력 -> 뮤효전력평균 / 3\n",
        "# 각 상 전류 -> 전류평균\n",
        "# 각 상 전압 -> 상전압평균\n",
        "# 각 상 선간전압 -> 선간전압평균"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "Vy_2PQWcGbEE"
      },
      "outputs": [],
      "source": [
        "### case3 ###\n",
        "# S,T상 유효전력 -> (유효전력평균 - R상유효전력)/2\n",
        "# S,T상 무효전력 -> (무효전력평균 - R상무효전력)/2\n",
        "# S,T상 전류 -> (전류평균*3 - R상전류)/2\n",
        "# S,T상 전압 -> (상전압평균*3 - R상전압)/2\n",
        "# S,T상 선간전압 -> (선간전압평균*3 - R상선간전압)/2"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "Cc1AWEIsJAQL"
      },
      "outputs": [],
      "source": [
        "### case4 ###\n",
        "# T상유효전력 -> 유효전력평균 - R상유효전력 - S상유효전력\n",
        "# T상무효전력 -> 무효전력평균 - R상무효전력 - S상무효전력\n",
        "# T상전류 -> 전류평균*3 - R상전류 - S상전류\n",
        "# T상전압 -> 상전압평균*3 - R상전압 - S상전압\n",
        "# T상선간전압 -> 선간전압평균*3 - R상선간전압 - S상선간전압"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "N0W1rR0hivBR"
      },
      "outputs": [],
      "source": [
        "### case5 ###\n",
        "# 올 NAN -> 제거"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 27,
      "metadata": {
        "id": "Fm8Z_rgMjLZE"
      },
      "outputs": [],
      "source": [
        "def nanprocessing(df):  # case5 먼저 처리한 후 순서대로 처리 \n",
        "\n",
        "    case1 = df['유효전력평균'].isnull()       \n",
        "    case2 = df['R상유효전력'].isnull() & df['T상유효전력'].isnull()\n",
        "    case3 = df['S상유효전력'].isnull() & df['T상유효전력'].isnull()\n",
        "    case4 = df['T상유효전력'].isnull()\n",
        "    case5 = df['누적전력량'].isnull() & df['R상유효전력'].isnull()\n",
        "\n",
        "    npdf = df.drop(df[case5].index)\n",
        "\n",
        "    for id in npdf[case1]['유효전력평균'].index:\n",
        "        npdf.loc[id,'유효전력평균'] = npdf.loc[id,'R상유효전력'] + npdf.loc[id,'S상유효전력'] + npdf.loc[id,'T상유효전력']\n",
        "        npdf.loc[id,'무효전력평균'] = npdf.loc[id,'R상무효전력'] + npdf.loc[id,'S상무효전력'] + npdf.loc[id,'T상무효전력']\n",
        "        npdf.loc[id,'전류평균'] = (npdf.loc[id,'R상전류'] + npdf.loc[id,'S상전류'] + npdf.loc[id,'T상전류']) / 3\n",
        "        npdf.loc[id,'상전압평균'] = (npdf.loc[id,'R상전압'] + npdf.loc[id,'S상전압'] + npdf.loc[id,'T상전압']) / 3\n",
        "        npdf.loc[id,'선간전압평균'] = (npdf.loc[id,'R상선간전압'] + npdf.loc[id,'S상선간전압'] + npdf.loc[id,'T상선간전압']) / 3\n",
        "\n",
        "    for id in npdf[case2]['R상유효전력'].index:\n",
        "        npdf.loc[id,'R상유효전력'] = npdf.loc[id,'유효전력평균'] / 3\n",
        "        npdf.loc[id,'R상무효전력'] = npdf.loc[id,'무효전력평균'] / 3\n",
        "        npdf.loc[id,'R상전류'] = npdf.loc[id,'전류평균']\n",
        "        npdf.loc[id,'R상전압'] = npdf.loc[id,'상전압평균']\n",
        "        npdf.loc[id,'R상선간전압'] = npdf.loc[id,'선간전압평균']\n",
        "\n",
        "        npdf.loc[id,'S상유효전력'] = npdf.loc[id,'유효전력평균'] / 3\n",
        "        npdf.loc[id,'S상무효전력'] = npdf.loc[id,'무효전력평균'] / 3\n",
        "        npdf.loc[id,'S상전류'] = npdf.loc[id,'전류평균']\n",
        "        npdf.loc[id,'S상전압'] = npdf.loc[id,'상전압평균']\n",
        "        npdf.loc[id,'S상선간전압'] = npdf.loc[id,'선간전압평균']\n",
        "\n",
        "        npdf.loc[id,'T상유효전력'] = npdf.loc[id,'유효전력평균'] / 3\n",
        "        npdf.loc[id,'T상무효전력'] = npdf.loc[id,'무효전력평균'] / 3\n",
        "        npdf.loc[id,'T상전류'] = npdf.loc[id,'전류평균']\n",
        "        npdf.loc[id,'T상전압'] = npdf.loc[id,'상전압평균']\n",
        "        npdf.loc[id,'T상선간전압'] = npdf.loc[id,'선간전압평균']\n",
        "\n",
        "    for id in npdf[case3]['S상유효전력'].index:\n",
        "        npdf.loc[id,'S상유효전력'] = (npdf.loc[id,'유효전력평균'] - npdf.loc[id,'R상유효전력']) / 2\n",
        "        npdf.loc[id,'S상무효전력'] = (npdf.loc[id,'무효전력평균'] - npdf.loc[id,'R상무효전력']) / 2\n",
        "        npdf.loc[id,'S상전류'] = (npdf.loc[id,'전류평균'] * 3 - npdf.loc[id,'R상전류']) / 2\n",
        "        npdf.loc[id,'S상전압'] = (npdf.loc[id,'상전압평균'] * 3 - npdf.loc[id,'R상전압']) / 2\n",
        "        npdf.loc[id,'S상선간전압'] = (npdf.loc[id,'선간전압평균'] * 3 - npdf.loc[id,'R상선간전압']) / 2\n",
        "\n",
        "        npdf.loc[id,'T상유효전력'] = (npdf.loc[id,'유효전력평균'] - npdf.loc[id,'R상유효전력']) / 2\n",
        "        npdf.loc[id,'T상무효전력'] = (npdf.loc[id,'무효전력평균'] - npdf.loc[id,'R상무효전력']) / 2\n",
        "        npdf.loc[id,'T상전류'] = (npdf.loc[id,'전류평균'] * 3 - npdf.loc[id,'R상전류']) / 2\n",
        "        npdf.loc[id,'T상전압'] = (npdf.loc[id,'상전압평균'] * 3 - npdf.loc[id,'R상전압']) / 2\n",
        "        npdf.loc[id,'T상선간전압'] = (npdf.loc[id,'선간전압평균'] * 3 - npdf.loc[id,'R상선간전압']) / 2\n",
        "\n",
        "    for id in npdf[case4]['T상유효전력'].index:\n",
        "        npdf.loc[id,'T상유효전력'] = npdf.loc[id,'유효전력평균'] - npdf.loc[id,'R상유효전력'] - npdf.loc[id,'S상유효전력']\n",
        "        npdf.loc[id,'T상무효전력'] = npdf.loc[id,'무효전력평균'] - npdf.loc[id,'R상무효전력'] - npdf.loc[id,'S상무효전력']\n",
        "        npdf.loc[id,'T상전류'] = npdf.loc[id,'전류평균'] * 3 - npdf.loc[id,'R상전류'] - npdf.loc[id,'S상전류']\n",
        "        npdf.loc[id,'T상전압'] = npdf.loc[id,'상전압평균'] * 3 - npdf.loc[id,'R상전압'] - npdf.loc[id,'S상전압']\n",
        "        npdf.loc[id,'T상선간전압'] = npdf.loc[id,'선간전압평균'] * 3 - npdf.loc[id,'R상선간전압'] - npdf.loc[id,'S상선간전압']\n",
        "\n",
        "    npdf = npdf.interpolate()\n",
        "\n",
        "    return npdf"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 28,
      "metadata": {
        "id": "8BAVNDrdLCEI"
      },
      "outputs": [],
      "source": [
        "nptrain = nanprocessing(train)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 29,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "pv_Vor3rQVtS",
        "outputId": "b9a186c6-198c-4ca0-96e2-c661e86d9aa8"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "index            0\n",
              "누적전력량            0\n",
              "유효전력평균           0\n",
              "무효전력평균           0\n",
              "주파수              0\n",
              "전류평균             0\n",
              "상전압평균            0\n",
              "선간전압평균           0\n",
              "온도               0\n",
              "R상유효전력           0\n",
              "R상무효전력           0\n",
              "R상전류             0\n",
              "R상전압             0\n",
              "R상선간전압           0\n",
              "S상유효전력           0\n",
              "S상무효전력           0\n",
              "S상전류             0\n",
              "S상전압             0\n",
              "S상선간전압           0\n",
              "T상유효전력           0\n",
              "T상무효전력           0\n",
              "T상전류             0\n",
              "T상전압             0\n",
              "T상선간전압           0\n",
              "label_역률평균       0\n",
              "label_전류고조파평균    0\n",
              "label_전압고조파평균    0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 29
        }
      ],
      "source": [
        "nptrain.isnull().sum()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 30,
      "metadata": {
        "id": "S8-xenJ2gzNM"
      },
      "outputs": [],
      "source": [
        "npsubmit = nanprocessing(submit)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 31,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "zsCsw07xiCye",
        "outputId": "892ee211-ec97-4e65-a380-f55060a7311b"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "ID        0\n",
              "누적전력량     0\n",
              "유효전력평균    0\n",
              "무효전력평균    0\n",
              "주파수       0\n",
              "전류평균      0\n",
              "상전압평균     0\n",
              "선간전압평균    0\n",
              "온도        0\n",
              "R상유효전력    0\n",
              "R상무효전력    0\n",
              "R상전류      0\n",
              "R상전압      0\n",
              "R상선간전압    0\n",
              "S상유효전력    0\n",
              "S상무효전력    0\n",
              "S상전류      0\n",
              "S상전압      0\n",
              "S상선간전압    0\n",
              "T상유효전력    0\n",
              "T상무효전력    0\n",
              "T상전류      0\n",
              "T상전압      0\n",
              "T상선간전압    0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 31
        }
      ],
      "source": [
        "npsubmit.isnull().sum()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 32,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "lvcwaUgl199R",
        "outputId": "58ae0ad9-9169-4b14-c547-ac910dbda677"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "정상    1317382\n",
            "경고     948810\n",
            "주의     154373\n",
            "Name: label_역률평균, dtype: int64 \n",
            "\n",
            "정상    1953656\n",
            "주의     391041\n",
            "경고      75868\n",
            "Name: label_전류고조파평균, dtype: int64 \n",
            "\n",
            "정상    994194\n",
            "경고    735155\n",
            "주의    691216\n",
            "Name: label_전압고조파평균, dtype: int64\n"
          ]
        }
      ],
      "source": [
        "# 타겟 불균형\n",
        "print(train['label_역률평균'].value_counts(),'\\n')\n",
        "print(train['label_전류고조파평균'].value_counts(),'\\n')\n",
        "print(train['label_전압고조파평균'].value_counts())"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 33,
      "metadata": {
        "id": "kKCETgzmwDsF"
      },
      "outputs": [],
      "source": [
        "# 각 라벨에 따른 df 만들기\n",
        "def myengineering(df):\n",
        "    prodf = df.copy()\n",
        "\n",
        "    if 'index' in prodf.columns or 'ID' in prodf.columns:\n",
        "        id = prodf.iloc[:,0]\n",
        "        prodf = prodf.iloc[:,1:]\n",
        "\n",
        "    if 'label_역률평균' in prodf.columns:\n",
        "        # 정상->0 , 주의->1, 경고->2\n",
        "        prodf['label_역률평균']=prodf['label_역률평균'].str.replace('정상','0')\n",
        "        prodf['label_역률평균']=prodf['label_역률평균'].str.replace('주의','1')\n",
        "        prodf['label_역률평균']=prodf['label_역률평균'].str.replace('경고','2').apply(int)\n",
        "        prodf['label_전류고조파평균']=prodf['label_전류고조파평균'].str.replace('정상','0')\n",
        "        prodf['label_전류고조파평균']=prodf['label_전류고조파평균'].str.replace('주의','1')\n",
        "        prodf['label_전류고조파평균']=prodf['label_전류고조파평균'].str.replace('경고','2').apply(int)\n",
        "        prodf['label_전압고조파평균']=prodf['label_전압고조파평균'].str.replace('정상','0')\n",
        "        prodf['label_전압고조파평균']=prodf['label_전압고조파평균'].str.replace('주의','1')\n",
        "        prodf['label_전압고조파평균']=prodf['label_전압고조파평균'].str.replace('경고','2').apply(int)\n",
        "\n",
        "    # 역률 df\n",
        "    # 역률 = P/S -> '유효전력평균'/sqrt('유효전력평균'**2+'무효전력평균'**2)\n",
        "    prodf['역률']=prodf['유효전력평균']/np.sqrt(np.power(prodf['유효전력평균'],2)+np.power(prodf['무효전력평균'],2))\n",
        "    prodf['역률']=prodf['역률'].replace(np.nan,'0').apply(float)\n",
        "    prodf['R상역률']=prodf['R상유효전력']/np.sqrt(np.power(prodf['R상유효전력'],2)+np.power(prodf['R상무효전력'],2))\n",
        "    prodf['R상역률']=prodf['R상역률'].replace(np.nan,'0').apply(float)\n",
        "    prodf['S상역률']=prodf['S상유효전력']/np.sqrt(np.power(prodf['S상유효전력'],2)+np.power(prodf['S상무효전력'],2))\n",
        "    prodf['S상역률']=prodf['S상역률'].replace(np.nan,'0').apply(float)\n",
        "    prodf['T상역률']=prodf['T상유효전력']/np.sqrt(np.power(prodf['T상유효전력'],2)+np.power(prodf['T상무효전력'],2))\n",
        "    prodf['T상역률']=prodf['T상역률'].replace(np.nan,'0').apply(float)\n",
        "    if 'label_역률평균' in prodf.columns:\n",
        "        pfdf = prodf[['온도','역률','R상역률','S상역률','T상역률','label_역률평균']]\n",
        "    else:\n",
        "        pfdf = prodf[['온도','역률','R상역률','S상역률','T상역률']]\n",
        "\n",
        "    # 고조파를 구하려면 fft가 필요한데 이 데이터로 fft를 할 수 없을 것 같음\n",
        "    # 전류고조파 df\n",
        "    if 'label_전류고조파평균' in prodf.columns:\n",
        "        ithddf = prodf[['주파수','온도','전류평균','R상전류','S상전류','T상전류','label_전류고조파평균']]\n",
        "    else:\n",
        "        ithddf = prodf[['주파수','온도','전류평균','R상전류','S상전류','T상전류']]\n",
        "    # 전압고조파 df\n",
        "    if 'label_전압고조파평균' in prodf.columns:\n",
        "        vthddf = prodf[['누적전력량','주파수','온도','전류평균','상전압평균','선간전압평균','R상전류','R상전압','R상선간전압','S상전류', 'S상전압','S상선간전압','T상전류','T상전압','T상선간전압','label_전압고조파평균']]\n",
        "    else:\n",
        "        vthddf = prodf[['누적전력량','주파수','온도','전류평균','상전압평균','선간전압평균','R상전류','R상전압','R상선간전압','S상전류', 'S상전압','S상선간전압','T상전류','T상전압','T상선간전압']]\n",
        "\n",
        "    return pfdf, ithddf, vthddf"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 86,
      "metadata": {
        "id": "dG1Seo1NqSeB"
      },
      "outputs": [],
      "source": [
        "# df를 train, val, test로 나눠주고 Xy로 나눠주고 스케일러, submit도 스케일러\n",
        "def splitandscale(df,submit):\n",
        "    train, test = train_test_split(df, test_size=0.2, random_state=2, stratify = df.iloc[:,-1])\n",
        "    train, val = train_test_split(train, test_size=0.2, random_state=2, stratify = train.iloc[:,-1])\n",
        "\n",
        "    X_train = train.iloc[:,:-1]\n",
        "    y_train = train.iloc[:,[-1]]\n",
        "\n",
        "    X_val = val.iloc[:,:-1]\n",
        "    y_val = val.iloc[:,[-1]]\n",
        "\n",
        "    X_test = test.iloc[:,:-1]\n",
        "    y_test = test.iloc[:,[-1]]\n",
        "\n",
        "    print(X_train.shape, X_val.shape, X_test.shape)\n",
        "\n",
        "    scaler = StandardScaler()\n",
        "    scaler.fit(X_train)\n",
        "    X_train_scaled = scaler.transform(X_train)\n",
        "    X_val_scaled = scaler.transform(X_val)\n",
        "    X_test_scaled = scaler.transform(X_test)\n",
        "    submit_scaled = scaler.transform(submit)\n",
        "\n",
        "    return X_train_scaled, y_train, X_val_scaled, y_val, X_test_scaled, y_test, submit_scaled"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 35,
      "metadata": {
        "id": "cK2oOSuhMxLd"
      },
      "outputs": [],
      "source": [
        "pfdf, ithddf, vthddf = myengineering(nptrain)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 36,
      "metadata": {
        "id": "UIjc5qYwmM9N"
      },
      "outputs": [],
      "source": [
        "submit_pf, submit_ithd, submit_vthd = myengineering(npsubmit)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2LiTeFa4ofj0"
      },
      "source": [
        "# 1. 역률"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 37,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "qVmq1pmLNBF1",
        "outputId": "1a7b4aca-227f-493c-8beb-2266a9dbf198"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "              온도        역률      R상역률      S상역률      T상역률  label_역률평균\n",
              "0        47.5000  0.819725  0.813994  0.825737  0.818785           0\n",
              "1        24.3750  0.000000  0.000000  0.000000  0.000000           2\n",
              "2        18.7500  0.871562  0.851444  0.869096  0.892904           0\n",
              "3        23.1250  0.889798  0.903401  0.888423  0.876831           0\n",
              "4        26.8750  0.000000  0.000000  0.000000  0.000000           2\n",
              "...          ...       ...       ...       ...       ...         ...\n",
              "2420560  19.0630  0.753711  0.791254  0.761371  0.704917           1\n",
              "2420561  33.7500  0.888723  0.866852  0.903129  0.894796           0\n",
              "2420562  17.3214  0.815814  0.804598  0.822688  0.818942           0\n",
              "2420563  34.3750  0.000000  0.000000  0.000000  0.000000           2\n",
              "2420564  24.3750  0.000000  0.000000  0.000000  0.000000           2\n",
              "\n",
              "[2420563 rows x 6 columns]"
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              "      <th></th>\n",
              "      <th>온도</th>\n",
              "      <th>역률</th>\n",
              "      <th>R상역률</th>\n",
              "      <th>S상역률</th>\n",
              "      <th>T상역률</th>\n",
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              "  <tbody>\n",
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              "      <th>0</th>\n",
              "      <td>47.5000</td>\n",
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              "      <td>0.825737</td>\n",
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              "      <td>0</td>\n",
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              "      <td>0.851444</td>\n",
              "      <td>0.869096</td>\n",
              "      <td>0.892904</td>\n",
              "      <td>0</td>\n",
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              "      <th>3</th>\n",
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              "      <td>0.888423</td>\n",
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              "      <td>0</td>\n",
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              "    <tr>\n",
              "      <th>4</th>\n",
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              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
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              "      <th>...</th>\n",
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              "      <td>...</td>\n",
              "      <td>...</td>\n",
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              "      <th>2420560</th>\n",
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              "      <td>0.791254</td>\n",
              "      <td>0.761371</td>\n",
              "      <td>0.704917</td>\n",
              "      <td>1</td>\n",
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              "      <th>2420561</th>\n",
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              "      <td>0.888723</td>\n",
              "      <td>0.866852</td>\n",
              "      <td>0.903129</td>\n",
              "      <td>0.894796</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2420562</th>\n",
              "      <td>17.3214</td>\n",
              "      <td>0.815814</td>\n",
              "      <td>0.804598</td>\n",
              "      <td>0.822688</td>\n",
              "      <td>0.818942</td>\n",
              "      <td>0</td>\n",
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              "    <tr>\n",
              "      <th>2420563</th>\n",
              "      <td>34.3750</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
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              "      <td>2</td>\n",
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              "    <tr>\n",
              "      <th>2420564</th>\n",
              "      <td>24.3750</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>2420563 rows × 6 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-c88b1547-1d89-4c2d-8752-0a1f44fc87e2')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "      \n",
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              "\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
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              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
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              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-c88b1547-1d89-4c2d-8752-0a1f44fc87e2 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-c88b1547-1d89-4c2d-8752-0a1f44fc87e2');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? 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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 37
        }
      ],
      "source": [
        "pfdf"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 88,
      "metadata": {
        "id": "qVHqpOYOssVY",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "7d30ef4f-2d51-4b61-8639-a63e452a5294"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "(1549160, 5) (387290, 5) (484113, 5)\n"
          ]
        }
      ],
      "source": [
        "# train, val, test 각각 X,y로 나누고 스케일러\n",
        "X_train_pf, y_train_pf, X_val_pf, y_val_pf, X_test_pf, y_test_pf, submit_pf_scaled = splitandscale(pfdf, submit_pf)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 39,
      "metadata": {
        "id": "5FpnXoi06Yka",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "70909373-dc19-427c-b279-76c0ca4f34ee"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "훈련세트 accuracy:  0.5442452684035219\n",
            "검증세트 accuracy:  0.5442459139146376\n"
          ]
        }
      ],
      "source": [
        "# 기준 모델 - 최빈값\n",
        "\n",
        "major = y_train_pf.mode().iloc[0][0]\n",
        "y_pred = [major] * len(y_train_pf)\n",
        "print(\"훈련세트 accuracy: \", accuracy_score(y_train_pf, y_pred))\n",
        "\n",
        "major = y_val_pf.mode().iloc[0][0]\n",
        "y_pred = [major] * len(y_val_pf)\n",
        "print(\"검증세트 accuracy: \", accuracy_score(y_val_pf, y_pred))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 42,
      "metadata": {
        "id": "cQtranl49_my",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 357
        },
        "outputId": "83b2256b-9a24-4adc-e2f4-6e5b18a6f081"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Predicted       0  1  2\n",
              "Actual                 \n",
              "0          263476  0  0\n",
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              "2          189762  0  0"
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              "      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",
              "    [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-06cf051a-e22b-46be-aa22-76bb2cf481bd button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-06cf051a-e22b-46be-aa22-76bb2cf481bd');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? 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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "              precision    recall  f1-score   support\n",
            "\n",
            "           0       0.54      1.00      0.70    263476\n",
            "           1       0.00      0.00      0.00     30875\n",
            "           2       0.00      0.00      0.00    189762\n",
            "\n",
            "    accuracy                           0.54    484113\n",
            "   macro avg       0.18      0.33      0.23    484113\n",
            "weighted avg       0.30      0.54      0.38    484113\n",
            "\n"
          ]
        }
      ],
      "source": [
        "# test셋에 대한 f1_macro\n",
        "\n",
        "major = y_test_pf.mode().iloc[0][0]\n",
        "y_pred = [major] * len(y_test_pf)\n",
        "\n",
        "cm = confusion_matrix(y_test_pf, y_pred)\n",
        "cm = pd.DataFrame(cm, index=[\"0\",\"1\", \"2\"], columns=[\"0\",\"1\", \"2\"])   \n",
        "cm.index.name = \"Actual\"\n",
        "cm.columns.name = \"Predicted\"\n",
        "display(cm)\n",
        "\n",
        "print(classification_report(y_test_pf, y_pred))\n",
        "# f1_macro: 0.23"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 41,
      "metadata": {
        "id": "fobg_DL-_pUb",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "cd5e3199-524c-4f5c-dbec-7051218bb966"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Fitting 3 folds for each of 5 candidates, totalling 15 fits\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "RandomizedSearchCV(cv=3,\n",
              "                   estimator=Pipeline(steps=[('randomforestclassifier',\n",
              "                                              RandomForestClassifier(class_weight='balanced',\n",
              "                                                                     n_jobs=-1,\n",
              "                                                                     oob_score=True,\n",
              "                                                                     random_state=2))]),\n",
              "                   n_iter=5, n_jobs=-1,\n",
              "                   param_distributions={'randomforestclassifier__max_depth': [3,\n",
              "                                                                              None],\n",
              "                                        'randomforestclassifier__n_estimators': [50,\n",
              "                                                                                 100,\n",
              "                                                                                 150]},\n",
              "                   scoring='f1_macro', verbose=1)"
            ]
          },
          "metadata": {},
          "execution_count": 41
        }
      ],
      "source": [
        "# 랜덤포레스트분류\n",
        "\n",
        "model_pf= make_pipeline(\n",
        "    RandomForestClassifier(random_state=2,n_jobs=-1,oob_score=True,class_weight='balanced')\n",
        ")\n",
        "\n",
        "\n",
        "dists = {\n",
        "        'randomforestclassifier__max_depth':[3,None],\n",
        "        'randomforestclassifier__n_estimators':[50, 100, 150]\n",
        "    }\n",
        "\n",
        "\n",
        "clf_pf = RandomizedSearchCV(\n",
        "        model_pf, \n",
        "        param_distributions=dists, \n",
        "        n_iter=5, \n",
        "        cv=3,\n",
        "        scoring='f1_macro',\n",
        "        verbose=1,\n",
        "        n_jobs=-1\n",
        "    )\n",
        "    \n",
        "\n",
        "clf_pf.fit(X_train_pf,y_train_pf)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 43,
      "metadata": {
        "id": "PS-i80IZkhUm",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "a64f72eb-f47b-4b05-a14e-a56fed350cab"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Optimal Hyperparameter: {'randomforestclassifier__n_estimators': 100, 'randomforestclassifier__max_depth': None}\n"
          ]
        }
      ],
      "source": [
        "print(\"Optimal Hyperparameter:\", clf_pf.best_params_)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 44,
      "metadata": {
        "id": "ejGUm_r_kkoA",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "45cce187-b830-495f-9050-d47e140278e2"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "훈련세트 accuracy:  0.9989749283482662\n",
            "검증세트 accuracy:  0.9756797232048335\n"
          ]
        }
      ],
      "source": [
        "print(\"훈련세트 accuracy: \", accuracy_score(y_train_pf, clf_pf.predict(X_train_pf)))\n",
        "print(\"검증세트 accuracy: \", accuracy_score(y_val_pf, clf_pf.predict(X_val_pf)))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 45,
      "metadata": {
        "id": "5RmlvTOHklcI",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 357
        },
        "outputId": "dafbc70d-aba2-46f1-c2df-0e6457f57316"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Predicted       0      1       2\n",
              "Actual                          \n",
              "0          260215   2024    1237\n",
              "1            4846  24831    1198\n",
              "2            1366   1059  187337"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-b919537e-65c8-4a22-afd8-c51a8fa36a4f\">\n",
              "    <div 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>Predicted</th>\n",
              "      <th>0</th>\n",
              "      <th>1</th>\n",
              "      <th>2</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Actual</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>260215</td>\n",
              "      <td>2024</td>\n",
              "      <td>1237</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>4846</td>\n",
              "      <td>24831</td>\n",
              "      <td>1198</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1366</td>\n",
              "      <td>1059</td>\n",
              "      <td>187337</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-b919537e-65c8-4a22-afd8-c51a8fa36a4f')\"\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 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\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",
              "    [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-b919537e-65c8-4a22-afd8-c51a8fa36a4f button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-b919537e-65c8-4a22-afd8-c51a8fa36a4f');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? 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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "              precision    recall  f1-score   support\n",
            "\n",
            "           0       0.98      0.99      0.98    263476\n",
            "           1       0.89      0.80      0.84     30875\n",
            "           2       0.99      0.99      0.99    189762\n",
            "\n",
            "    accuracy                           0.98    484113\n",
            "   macro avg       0.95      0.93      0.94    484113\n",
            "weighted avg       0.98      0.98      0.98    484113\n",
            "\n"
          ]
        }
      ],
      "source": [
        "y_pred = clf_pf.predict(X_test_pf)\n",
        "\n",
        "cm = confusion_matrix(y_test_pf, y_pred)\n",
        "cm = pd.DataFrame(cm, index=[\"0\",\"1\", \"2\"], columns=[\"0\",\"1\", \"2\"])   \n",
        "cm.index.name = \"Actual\"\n",
        "cm.columns.name = \"Predicted\"\n",
        "display(cm)\n",
        "\n",
        "print(classification_report(y_test_pf, y_pred))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 46,
      "metadata": {
        "id": "7UTqUTpMiiJ5"
      },
      "outputs": [],
      "source": [
        "# model 저장\n",
        "\n",
        "with open('/content/drive/MyDrive/powersohmodel/model_pf_rf.pickle','wb') as fw:\n",
        "    pickle.dump(clf_pf, fw)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "X3FgyEa2jiBk"
      },
      "outputs": [],
      "source": [
        "# model 불러오기\n",
        "\n",
        "# with open('/content/drive/MyDrive/powersohmodel/model_pf_rf.pickle', 'rb') as f: \n",
        "#     clf_pf = pickle.load(f)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 89,
      "metadata": {
        "id": "bDDiWXuHr4bd"
      },
      "outputs": [],
      "source": [
        "# submit_pf_scaled 예측 결과 sample_submission에 넣기\n",
        "\n",
        "sample_submission['label_역률평균']=clf_pf.predict(submit_pf_scaled)\n",
        "sample_submission['label_역률평균']=sample_submission['label_역률평균'].apply(str).replace('0','정상')\n",
        "sample_submission['label_역률평균']=sample_submission['label_역률평균'].replace('1','주의')\n",
        "sample_submission['label_역률평균']=sample_submission['label_역률평균'].replace('2','경고')"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sample_submission['label_역률평균'].value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "wNHKqhNDhx_F",
        "outputId": "454ade33-dfc0-4e9d-933c-b40d68109335"
      },
      "execution_count": 90,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "정상    173797\n",
              "경고    120909\n",
              "주의     18561\n",
              "Name: label_역률평균, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 90
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "iE9v_ajEtM3D"
      },
      "source": [
        "#2. 전류고조파평균"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 48,
      "metadata": {
        "id": "JGaFgCsEq5Dq",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "outputId": "b3b656c4-4035-4998-abbf-d37f690b23cb"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "               주파수       온도        전류평균       R상전류       S상전류       T상전류  \\\n",
              "0        59.854076  47.5000   45.197918   40.84375   46.03125   48.71875   \n",
              "1         0.000000  24.3750  101.312500  101.75000  101.50000  100.68750   \n",
              "2        59.975650  18.7500  107.385414  111.53125  101.06250  109.56250   \n",
              "3        59.863000  23.1250  244.854000  243.18800  249.18800  242.18800   \n",
              "4        59.798140  26.8750    0.000000    0.00000    0.00000    0.00000   \n",
              "...            ...      ...         ...        ...        ...        ...   \n",
              "2420560  57.945000  19.0630   52.833000   50.50000   56.87500   51.12500   \n",
              "2420561  59.928820  33.7500  152.156250  153.53125  157.75000  145.18750   \n",
              "2420562  59.914000  17.3214   31.363100   29.37930   31.91490   32.79530   \n",
              "2420563   0.000000  34.3750   44.572918   47.93750   43.81250   41.96875   \n",
              "2420564  59.807450  24.3750    0.000000    0.00000    0.00000    0.00000   \n",
              "\n",
              "         label_전류고조파평균  \n",
              "0                    2  \n",
              "1                    0  \n",
              "2                    0  \n",
              "3                    0  \n",
              "4                    0  \n",
              "...                ...  \n",
              "2420560              0  \n",
              "2420561              0  \n",
              "2420562              2  \n",
              "2420563              2  \n",
              "2420564              0  \n",
              "\n",
              "[2420563 rows x 7 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-3c931ac0-c1a5-4124-8b50-bffb5b9658e4\">\n",
              "    <div 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>주파수</th>\n",
              "      <th>온도</th>\n",
              "      <th>전류평균</th>\n",
              "      <th>R상전류</th>\n",
              "      <th>S상전류</th>\n",
              "      <th>T상전류</th>\n",
              "      <th>label_전류고조파평균</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>59.854076</td>\n",
              "      <td>47.5000</td>\n",
              "      <td>45.197918</td>\n",
              "      <td>40.84375</td>\n",
              "      <td>46.03125</td>\n",
              "      <td>48.71875</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0.000000</td>\n",
              "      <td>24.3750</td>\n",
              "      <td>101.312500</td>\n",
              "      <td>101.75000</td>\n",
              "      <td>101.50000</td>\n",
              "      <td>100.68750</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>59.975650</td>\n",
              "      <td>18.7500</td>\n",
              "      <td>107.385414</td>\n",
              "      <td>111.53125</td>\n",
              "      <td>101.06250</td>\n",
              "      <td>109.56250</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>59.863000</td>\n",
              "      <td>23.1250</td>\n",
              "      <td>244.854000</td>\n",
              "      <td>243.18800</td>\n",
              "      <td>249.18800</td>\n",
              "      <td>242.18800</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>59.798140</td>\n",
              "      <td>26.8750</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0</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",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2420560</th>\n",
              "      <td>57.945000</td>\n",
              "      <td>19.0630</td>\n",
              "      <td>52.833000</td>\n",
              "      <td>50.50000</td>\n",
              "      <td>56.87500</td>\n",
              "      <td>51.12500</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2420561</th>\n",
              "      <td>59.928820</td>\n",
              "      <td>33.7500</td>\n",
              "      <td>152.156250</td>\n",
              "      <td>153.53125</td>\n",
              "      <td>157.75000</td>\n",
              "      <td>145.18750</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2420562</th>\n",
              "      <td>59.914000</td>\n",
              "      <td>17.3214</td>\n",
              "      <td>31.363100</td>\n",
              "      <td>29.37930</td>\n",
              "      <td>31.91490</td>\n",
              "      <td>32.79530</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2420563</th>\n",
              "      <td>0.000000</td>\n",
              "      <td>34.3750</td>\n",
              "      <td>44.572918</td>\n",
              "      <td>47.93750</td>\n",
              "      <td>43.81250</td>\n",
              "      <td>41.96875</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2420564</th>\n",
              "      <td>59.807450</td>\n",
              "      <td>24.3750</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>2420563 rows × 7 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-3c931ac0-c1a5-4124-8b50-bffb5b9658e4')\"\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 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\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",
              "    [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-3c931ac0-c1a5-4124-8b50-bffb5b9658e4 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-3c931ac0-c1a5-4124-8b50-bffb5b9658e4');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? 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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 48
        }
      ],
      "source": [
        "ithddf"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 91,
      "metadata": {
        "id": "lx4dsmap8W-o",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "e3162db7-63d0-4ab4-8a7e-23fa1e43ce5b"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "(1549160, 6) (387290, 6) (484113, 6)\n"
          ]
        }
      ],
      "source": [
        "# train, val, test 각각 X,y로 나누고 스케일러\n",
        "X_train_ithd, y_train_ithd, X_val_ithd, y_val_ithd, X_test_ithd, y_test_ithd, submit_ithd_scaled = splitandscale(ithddf, submit_ithd)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 50,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_QQXUfVY-Rak",
        "outputId": "b84c0ef0-91bd-4279-a56b-e7c5c7d33237"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "훈련세트 accuracy:  0.8071070773838726\n",
            "검증세트 accuracy:  0.807108368406104\n"
          ]
        }
      ],
      "source": [
        "# 기준 모델 - 최빈값\n",
        "\n",
        "major = y_train_ithd.mode().iloc[0][0]\n",
        "\n",
        "y_pred = [major] * len(y_train_ithd)\n",
        "print(\"훈련세트 accuracy: \", accuracy_score(y_train_ithd, y_pred))\n",
        "\n",
        "y_pred = [major] * len(y_val_ithd)\n",
        "print(\"검증세트 accuracy: \", accuracy_score(y_val_ithd, y_pred))"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# test셋에 대한 f1_macro\n",
        "\n",
        "major = y_test_ithd.mode().iloc[0][0]\n",
        "y_pred = [major] * len(y_test_ithd)\n",
        "\n",
        "cm = confusion_matrix(y_test_ithd, y_pred)\n",
        "cm = pd.DataFrame(cm, index=[\"0\",\"1\", \"2\"], columns=[\"0\",\"1\", \"2\"])   \n",
        "cm.index.name = \"Actual\"\n",
        "cm.columns.name = \"Predicted\"\n",
        "display(cm)\n",
        "\n",
        "print(classification_report(y_test_ithd, y_pred))\n",
        "# f1_macro: 0.30"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 357
        },
        "id": "tkcFAVDUzORe",
        "outputId": "1687b551-6355-43a2-a12e-db2380fecad3"
      },
      "execution_count": 51,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Predicted       0  1  2\n",
              "Actual                 \n",
              "0          390731  0  0\n",
              "1           78208  0  0\n",
              "2           15174  0  0"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-d6c3acb5-1968-48c0-902d-26d2ac364de2\">\n",
              "    <div 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>Predicted</th>\n",
              "      <th>0</th>\n",
              "      <th>1</th>\n",
              "      <th>2</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Actual</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>390731</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>78208</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>15174</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-d6c3acb5-1968-48c0-902d-26d2ac364de2')\"\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 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\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",
              "    [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-d6c3acb5-1968-48c0-902d-26d2ac364de2 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-d6c3acb5-1968-48c0-902d-26d2ac364de2');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? 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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "              precision    recall  f1-score   support\n",
            "\n",
            "           0       0.81      1.00      0.89    390731\n",
            "           1       0.00      0.00      0.00     78208\n",
            "           2       0.00      0.00      0.00     15174\n",
            "\n",
            "    accuracy                           0.81    484113\n",
            "   macro avg       0.27      0.33      0.30    484113\n",
            "weighted avg       0.65      0.81      0.72    484113\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 52,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "rVZ1c88k_E00",
        "outputId": "7fc4b422-74fb-4aca-edaf-151a4a158d6e"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Fitting 3 folds for each of 5 candidates, totalling 15 fits\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "RandomizedSearchCV(cv=3,\n",
              "                   estimator=Pipeline(steps=[('randomforestclassifier',\n",
              "                                              RandomForestClassifier(class_weight='balanced',\n",
              "                                                                     n_jobs=-1,\n",
              "                                                                     oob_score=True,\n",
              "                                                                     random_state=2))]),\n",
              "                   n_iter=5, n_jobs=-1,\n",
              "                   param_distributions={'randomforestclassifier__max_depth': [4,\n",
              "                                                                              None],\n",
              "                                        'randomforestclassifier__n_estimators': [50,\n",
              "                                                                                 100,\n",
              "                                                                                 150]},\n",
              "                   scoring='f1_macro', verbose=1)"
            ]
          },
          "metadata": {},
          "execution_count": 52
        }
      ],
      "source": [
        "# 랜덤포레스트분류\n",
        "\n",
        "model_ithd=make_pipeline(\n",
        "    RandomForestClassifier(random_state=2,n_jobs=-1,oob_score=True,class_weight='balanced')\n",
        ")\n",
        "\n",
        "dists = {\n",
        "        'randomforestclassifier__max_depth':[4,None],\n",
        "        'randomforestclassifier__n_estimators':[50,100,150]\n",
        "    }\n",
        "clf_ithd = RandomizedSearchCV(\n",
        "        model_ithd, \n",
        "        param_distributions=dists, \n",
        "        n_iter=5, \n",
        "        cv=3,\n",
        "        scoring='f1_macro',\n",
        "        verbose=1,\n",
        "        n_jobs=-1\n",
        "    )\n",
        "\n",
        "clf_ithd.fit(X_train_ithd,y_train_ithd)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 53,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qMYeBGGjsr5c",
        "outputId": "118f1c36-43fb-400a-8f3f-3ab10534dc7e"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Optimal Hyperparameter: {'randomforestclassifier__n_estimators': 150, 'randomforestclassifier__max_depth': None}\n"
          ]
        }
      ],
      "source": [
        "print(\"Optimal Hyperparameter:\", clf_ithd.best_params_)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 54,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "CZfYenJG_gjF",
        "outputId": "8122767c-205b-4dd4-b89b-6e7e034b0ce3"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "훈련세트 accuracy:  0.9978775594515737\n",
            "검증세트 accuracy:  0.9772625164605334\n"
          ]
        }
      ],
      "source": [
        "print(\"훈련세트 accuracy: \", accuracy_score(y_train_ithd, clf_ithd.predict(X_train_ithd)))\n",
        "print(\"검증세트 accuracy: \", accuracy_score(y_val_ithd, clf_ithd.predict(X_val_ithd)))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 55,
      "metadata": {
        "id": "qXzTOh2BqL7L",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 357
        },
        "outputId": "89e90d23-7c8a-438a-c5e8-d064a28f80dc"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Predicted       0      1      2\n",
              "Actual                         \n",
              "0          386472   4032    227\n",
              "1            5159  72292    757\n",
              "2             179    902  14093"
            ],
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              "\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th>Predicted</th>\n",
              "      <th>0</th>\n",
              "      <th>1</th>\n",
              "      <th>2</th>\n",
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              "    <tr>\n",
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              "      <td>386472</td>\n",
              "      <td>4032</td>\n",
              "      <td>227</td>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>5159</td>\n",
              "      <td>72292</td>\n",
              "      <td>757</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>179</td>\n",
              "      <td>902</td>\n",
              "      <td>14093</td>\n",
              "    </tr>\n",
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              "</table>\n",
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              "      \n",
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              "      gap: 12px;\n",
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              "\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
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              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-0aae4e71-c3af-4a23-bfd2-9ce2821c9311 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-0aae4e71-c3af-4a23-bfd2-9ce2821c9311');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? 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",
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              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
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              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "              precision    recall  f1-score   support\n",
            "\n",
            "           0       0.99      0.99      0.99    390731\n",
            "           1       0.94      0.92      0.93     78208\n",
            "           2       0.93      0.93      0.93     15174\n",
            "\n",
            "    accuracy                           0.98    484113\n",
            "   macro avg       0.95      0.95      0.95    484113\n",
            "weighted avg       0.98      0.98      0.98    484113\n",
            "\n"
          ]
        }
      ],
      "source": [
        "y_pred = clf_ithd.predict(X_test_ithd)\n",
        "\n",
        "cm = confusion_matrix(y_test_ithd, y_pred)\n",
        "cm = pd.DataFrame(cm, index=[\"0\",\"1\", \"2\"], columns=[\"0\",\"1\", \"2\"])   \n",
        "cm.index.name = \"Actual\"\n",
        "cm.columns.name = \"Predicted\"\n",
        "display(cm)\n",
        "\n",
        "print(classification_report(y_test_ithd, y_pred))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 56,
      "metadata": {
        "id": "x-rhiz0HqbAO"
      },
      "outputs": [],
      "source": [
        "# model 저장\n",
        "\n",
        "with open('/content/drive/MyDrive/powersohmodel/model_ithd_rf.pickle','wb') as fw:\n",
        "    pickle.dump(clf_ithd, fw)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "4Gkcvjraqbsy"
      },
      "outputs": [],
      "source": [
        "# model 불러오기\n",
        "\n",
        "# with open('/content/drive/MyDrive/powersohmodel/model_ithd_rf.pickle', 'rb') as f: \n",
        "#     clf_ithd = pickle.load(f)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 92,
      "metadata": {
        "id": "dNQ-bRKHuVOV"
      },
      "outputs": [],
      "source": [
        "# sumbit_ithd_scaled 예측결과 sample_submission에 넣기\n",
        "\n",
        "sample_submission['label_전류고조파평균']=clf_ithd.predict(submit_ithd_scaled)\n",
        "sample_submission['label_전류고조파평균']=sample_submission['label_전류고조파평균'].apply(str).replace('0','정상')\n",
        "sample_submission['label_전류고조파평균']=sample_submission['label_전류고조파평균'].replace('1','주의')\n",
        "sample_submission['label_전류고조파평균']=sample_submission['label_전류고조파평균'].replace('2','경고')"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sample_submission['label_전류고조파평균'].value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "vk70Eh1Xh6O0",
        "outputId": "39d876c6-8e42-4d3b-eb2e-0519b8f75d72"
      },
      "execution_count": 93,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "정상    260912\n",
              "주의     43723\n",
              "경고      8632\n",
              "Name: label_전류고조파평균, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 93
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9iKKKPuK_tA_"
      },
      "source": [
        "#3. 전압고조파평균"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 58,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "OTJcHMw8naDp",
        "outputId": "de5ae7e4-465c-4866-f328-06bd51d7e610"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "               누적전력량        주파수       온도        전류평균       상전압평균      선간전압평균  \\\n",
              "0         2248930.50  59.854076  47.5000   45.197918  259.916656  449.916656   \n",
              "1               0.00   0.000000  24.3750  101.312500    0.000000    0.000000   \n",
              "2         5375707.00  59.975650  18.7500  107.385414  125.416664  216.750000   \n",
              "3        17781200.00  59.863000  23.1250  244.854000  118.083000  205.333000   \n",
              "4        10143988.00  59.798140  26.8750    0.000000  133.750000  231.500000   \n",
              "...              ...        ...      ...         ...         ...         ...   \n",
              "2420560   6229905.00  57.945000  19.0630   52.833000  215.327000  372.958000   \n",
              "2420561   6057307.50  59.928820  33.7500  152.156250  224.416672  388.583344   \n",
              "2420562   7966820.00  59.914000  17.3214   31.363100  219.233000  379.862000   \n",
              "2420563         0.00   0.000000  34.3750   44.572918    0.000000    0.000000   \n",
              "2420564   1296005.63  59.807450  24.3750    0.000000  229.416672  396.916656   \n",
              "\n",
              "              R상전류     R상전압   R상선간전압       S상전류     S상전압   S상선간전압       T상전류  \\\n",
              "0         40.84375  258.250  448.250   46.03125  260.750  452.750   48.71875   \n",
              "1        101.75000    0.000    0.000  101.50000    0.000    0.000  100.68750   \n",
              "2        111.53125  126.000  217.750  101.06250  125.250  216.250  109.56250   \n",
              "3        243.18800  117.500  117.500  249.18800  118.750  118.750  242.18800   \n",
              "4          0.00000  133.750  232.750    0.00000  134.500  231.500    0.00000   \n",
              "...            ...      ...      ...        ...      ...      ...        ...   \n",
              "2420560   50.50000  214.227  214.227   56.87500  216.628  216.628   51.12500   \n",
              "2420561  153.53125  225.750  390.750  157.75000  224.250  386.250  145.18750   \n",
              "2420562   29.37930  218.862  218.862   31.91490  219.276  219.276   32.79530   \n",
              "2420563   47.93750    0.000    0.000   43.81250    0.000    0.000   41.96875   \n",
              "2420564    0.00000  230.750  396.750    0.00000  228.000  394.500    0.00000   \n",
              "\n",
              "            T상전압   T상선간전압  label_전압고조파평균  \n",
              "0        260.750  448.750              1  \n",
              "1          0.000    0.000              0  \n",
              "2        125.000  216.250              1  \n",
              "3        118.000  118.000              2  \n",
              "4        133.000  230.250              0  \n",
              "...          ...      ...            ...  \n",
              "2420560  215.128  215.128              2  \n",
              "2420561  223.250  388.750              1  \n",
              "2420562  219.560  219.560              2  \n",
              "2420563    0.000    0.000              0  \n",
              "2420564  229.500  399.500              2  \n",
              "\n",
              "[2420563 rows x 16 columns]"
            ],
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              "\n",
              "  <div id=\"df-01dea03f-94b4-4045-a7ec-6ce992abec40\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>누적전력량</th>\n",
              "      <th>주파수</th>\n",
              "      <th>온도</th>\n",
              "      <th>전류평균</th>\n",
              "      <th>상전압평균</th>\n",
              "      <th>선간전압평균</th>\n",
              "      <th>R상전류</th>\n",
              "      <th>R상전압</th>\n",
              "      <th>R상선간전압</th>\n",
              "      <th>S상전류</th>\n",
              "      <th>S상전압</th>\n",
              "      <th>S상선간전압</th>\n",
              "      <th>T상전류</th>\n",
              "      <th>T상전압</th>\n",
              "      <th>T상선간전압</th>\n",
              "      <th>label_전압고조파평균</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2248930.50</td>\n",
              "      <td>59.854076</td>\n",
              "      <td>47.5000</td>\n",
              "      <td>45.197918</td>\n",
              "      <td>259.916656</td>\n",
              "      <td>449.916656</td>\n",
              "      <td>40.84375</td>\n",
              "      <td>258.250</td>\n",
              "      <td>448.250</td>\n",
              "      <td>46.03125</td>\n",
              "      <td>260.750</td>\n",
              "      <td>452.750</td>\n",
              "      <td>48.71875</td>\n",
              "      <td>260.750</td>\n",
              "      <td>448.750</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>24.3750</td>\n",
              "      <td>101.312500</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>101.75000</td>\n",
              "      <td>0.000</td>\n",
              "      <td>0.000</td>\n",
              "      <td>101.50000</td>\n",
              "      <td>0.000</td>\n",
              "      <td>0.000</td>\n",
              "      <td>100.68750</td>\n",
              "      <td>0.000</td>\n",
              "      <td>0.000</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>5375707.00</td>\n",
              "      <td>59.975650</td>\n",
              "      <td>18.7500</td>\n",
              "      <td>107.385414</td>\n",
              "      <td>125.416664</td>\n",
              "      <td>216.750000</td>\n",
              "      <td>111.53125</td>\n",
              "      <td>126.000</td>\n",
              "      <td>217.750</td>\n",
              "      <td>101.06250</td>\n",
              "      <td>125.250</td>\n",
              "      <td>216.250</td>\n",
              "      <td>109.56250</td>\n",
              "      <td>125.000</td>\n",
              "      <td>216.250</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>17781200.00</td>\n",
              "      <td>59.863000</td>\n",
              "      <td>23.1250</td>\n",
              "      <td>244.854000</td>\n",
              "      <td>118.083000</td>\n",
              "      <td>205.333000</td>\n",
              "      <td>243.18800</td>\n",
              "      <td>117.500</td>\n",
              "      <td>117.500</td>\n",
              "      <td>249.18800</td>\n",
              "      <td>118.750</td>\n",
              "      <td>118.750</td>\n",
              "      <td>242.18800</td>\n",
              "      <td>118.000</td>\n",
              "      <td>118.000</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>10143988.00</td>\n",
              "      <td>59.798140</td>\n",
              "      <td>26.8750</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>133.750000</td>\n",
              "      <td>231.500000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>133.750</td>\n",
              "      <td>232.750</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>134.500</td>\n",
              "      <td>231.500</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>133.000</td>\n",
              "      <td>230.250</td>\n",
              "      <td>0</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",
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              "      <td>...</td>\n",
              "      <td>...</td>\n",
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              "      <td>...</td>\n",
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              "    <tr>\n",
              "      <th>2420560</th>\n",
              "      <td>6229905.00</td>\n",
              "      <td>57.945000</td>\n",
              "      <td>19.0630</td>\n",
              "      <td>52.833000</td>\n",
              "      <td>215.327000</td>\n",
              "      <td>372.958000</td>\n",
              "      <td>50.50000</td>\n",
              "      <td>214.227</td>\n",
              "      <td>214.227</td>\n",
              "      <td>56.87500</td>\n",
              "      <td>216.628</td>\n",
              "      <td>216.628</td>\n",
              "      <td>51.12500</td>\n",
              "      <td>215.128</td>\n",
              "      <td>215.128</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2420561</th>\n",
              "      <td>6057307.50</td>\n",
              "      <td>59.928820</td>\n",
              "      <td>33.7500</td>\n",
              "      <td>152.156250</td>\n",
              "      <td>224.416672</td>\n",
              "      <td>388.583344</td>\n",
              "      <td>153.53125</td>\n",
              "      <td>225.750</td>\n",
              "      <td>390.750</td>\n",
              "      <td>157.75000</td>\n",
              "      <td>224.250</td>\n",
              "      <td>386.250</td>\n",
              "      <td>145.18750</td>\n",
              "      <td>223.250</td>\n",
              "      <td>388.750</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2420562</th>\n",
              "      <td>7966820.00</td>\n",
              "      <td>59.914000</td>\n",
              "      <td>17.3214</td>\n",
              "      <td>31.363100</td>\n",
              "      <td>219.233000</td>\n",
              "      <td>379.862000</td>\n",
              "      <td>29.37930</td>\n",
              "      <td>218.862</td>\n",
              "      <td>218.862</td>\n",
              "      <td>31.91490</td>\n",
              "      <td>219.276</td>\n",
              "      <td>219.276</td>\n",
              "      <td>32.79530</td>\n",
              "      <td>219.560</td>\n",
              "      <td>219.560</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2420563</th>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>34.3750</td>\n",
              "      <td>44.572918</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>47.93750</td>\n",
              "      <td>0.000</td>\n",
              "      <td>0.000</td>\n",
              "      <td>43.81250</td>\n",
              "      <td>0.000</td>\n",
              "      <td>0.000</td>\n",
              "      <td>41.96875</td>\n",
              "      <td>0.000</td>\n",
              "      <td>0.000</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2420564</th>\n",
              "      <td>1296005.63</td>\n",
              "      <td>59.807450</td>\n",
              "      <td>24.3750</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>229.416672</td>\n",
              "      <td>396.916656</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>230.750</td>\n",
              "      <td>396.750</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>228.000</td>\n",
              "      <td>394.500</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>229.500</td>\n",
              "      <td>399.500</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>2420563 rows × 16 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-01dea03f-94b4-4045-a7ec-6ce992abec40')\"\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 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\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",
              "    [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-01dea03f-94b4-4045-a7ec-6ce992abec40 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-01dea03f-94b4-4045-a7ec-6ce992abec40');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? 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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 58
        }
      ],
      "source": [
        "vthddf"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 94,
      "metadata": {
        "id": "ab8FwZU_nnSm",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "df84d12d-21d5-4b50-b5b8-64369a12d883"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "(1549160, 15) (387290, 15) (484113, 15)\n"
          ]
        }
      ],
      "source": [
        "# train, val, test 각각 X,y로 나누고 스케일러\n",
        "X_train_vthd, y_train_vthd, X_val_vthd, y_val_vthd, X_test_vthd, y_test_vthd, submit_vthd_scaled = splitandscale(vthddf, submit_vthd)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 60,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6gK5tCaKn8gn",
        "outputId": "62abfc22-ccbe-4a2e-ed2c-3fd99643b4e4"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "훈련세트 accuracy:  0.41072839474295747\n",
            "검증세트 accuracy:  0.41072839474295747\n"
          ]
        }
      ],
      "source": [
        "# 기준 모델 - 최빈값\n",
        "\n",
        "major = y_train_vthd.mode().iloc[0][0]\n",
        "\n",
        "y_pred = [major] * len(y_train_vthd)\n",
        "print(\"훈련세트 accuracy: \", accuracy_score(y_train_vthd, y_pred))\n",
        "\n",
        "y_pred = [major] * len(y_val_vthd)\n",
        "print(\"검증세트 accuracy: \", accuracy_score(y_val_vthd, y_pred))"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# test셋에 대한 f1_macro\n",
        "\n",
        "major = y_test_vthd.mode().iloc[0][0]\n",
        "y_pred = [major] * len(y_test_vthd)\n",
        "\n",
        "cm = confusion_matrix(y_test_vthd, y_pred)\n",
        "cm = pd.DataFrame(cm, index=[\"0\",\"1\", \"2\"], columns=[\"0\",\"1\", \"2\"])   \n",
        "cm.index.name = \"Actual\"\n",
        "cm.columns.name = \"Predicted\"\n",
        "display(cm)\n",
        "\n",
        "print(classification_report(y_test_vthd, y_pred))\n",
        "# f1_macro: 0.19"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 357
        },
        "id": "HR1euALTzXzb",
        "outputId": "69825813-f99b-472a-d8c9-36a4b628c160"
      },
      "execution_count": 61,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Predicted       0  1  2\n",
              "Actual                 \n",
              "0          198839  0  0\n",
              "1          138243  0  0\n",
              "2          147031  0  0"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-f8450c78-eee9-463c-b51a-b89f064ac9f0\">\n",
              "    <div 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>Predicted</th>\n",
              "      <th>0</th>\n",
              "      <th>1</th>\n",
              "      <th>2</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Actual</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>198839</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>138243</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>147031</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-f8450c78-eee9-463c-b51a-b89f064ac9f0')\"\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 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\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",
              "    [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-f8450c78-eee9-463c-b51a-b89f064ac9f0 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-f8450c78-eee9-463c-b51a-b89f064ac9f0');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? 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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "              precision    recall  f1-score   support\n",
            "\n",
            "           0       0.41      1.00      0.58    198839\n",
            "           1       0.00      0.00      0.00    138243\n",
            "           2       0.00      0.00      0.00    147031\n",
            "\n",
            "    accuracy                           0.41    484113\n",
            "   macro avg       0.14      0.33      0.19    484113\n",
            "weighted avg       0.17      0.41      0.24    484113\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 62,
      "metadata": {
        "id": "vkJp1VbaJ--M",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "ef1db101-f2a9-482e-a976-a45c9acd62da"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Fitting 3 folds for each of 5 candidates, totalling 15 fits\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "RandomizedSearchCV(cv=3,\n",
              "                   estimator=Pipeline(steps=[('randomforestclassifier',\n",
              "                                              RandomForestClassifier(class_weight='balanced',\n",
              "                                                                     n_jobs=-1,\n",
              "                                                                     oob_score=True,\n",
              "                                                                     random_state=2))]),\n",
              "                   n_iter=5, n_jobs=-1,\n",
              "                   param_distributions={'randomforestclassifier__max_depth': [5,\n",
              "                                                                              None],\n",
              "                                        'randomforestclassifier__n_estimators': [50,\n",
              "                                                                                 100,\n",
              "                                                                                 150]},\n",
              "                   scoring='f1_macro', verbose=1)"
            ]
          },
          "metadata": {},
          "execution_count": 62
        }
      ],
      "source": [
        "# 랜덤포레스트 분류\n",
        "\n",
        "model_vthd=make_pipeline(\n",
        "    RandomForestClassifier(random_state=2,n_jobs=-1,oob_score=True,class_weight='balanced')\n",
        ")\n",
        "\n",
        "dists = {\n",
        "        'randomforestclassifier__max_depth':[5,None],\n",
        "        'randomforestclassifier__n_estimators':[50,100,150]\n",
        "    }\n",
        "clf_vthd = RandomizedSearchCV(\n",
        "        model_vthd, \n",
        "        param_distributions=dists, \n",
        "        n_iter=5, \n",
        "        cv=3,\n",
        "        scoring='f1_macro',\n",
        "        verbose=1,\n",
        "        n_jobs=-1\n",
        "    )\n",
        "\n",
        "clf_vthd.fit(X_train_vthd, y_train_vthd)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 63,
      "metadata": {
        "id": "52fi5SufKUjO",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "17582955-f16b-47ba-e57c-e77a0c0c6e7a"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Optimal Hyperparameter: {'randomforestclassifier__n_estimators': 100, 'randomforestclassifier__max_depth': None}\n"
          ]
        }
      ],
      "source": [
        "print(\"Optimal Hyperparameter:\", clf_vthd.best_params_)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 64,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ln18NxD2uj6Y",
        "outputId": "2f26b24b-9900-4574-c1a9-2e5343df7e09"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "훈련세트 accuracy:  0.9996765989310336\n",
            "검증세트 accuracy:  0.9277079191303674\n"
          ]
        }
      ],
      "source": [
        "print(\"훈련세트 accuracy: \", accuracy_score(y_train_vthd, clf_vthd.predict(X_train_vthd)))\n",
        "print(\"검증세트 accuracy: \", accuracy_score(y_val_vthd, clf_vthd.predict(X_val_vthd)))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 65,
      "metadata": {
        "id": "tFcpHkY7nmiT",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 357
        },
        "outputId": "6021b8e5-084e-43dd-b23e-45b5541e3c84"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Predicted       0       1       2\n",
              "Actual                           \n",
              "0          189430    8993     416\n",
              "1           10234  121702    6307\n",
              "2             837    8419  137775"
            ],
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              "</style>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
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              "\n",
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              "\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",
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              "  </style>\n",
              "\n",
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              "          document.querySelector('#df-404501b7-c911-4670-8958-502ad9682af8 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-404501b7-c911-4670-8958-502ad9682af8');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? 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",
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              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
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              "  </div>\n",
              "  "
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "              precision    recall  f1-score   support\n",
            "\n",
            "           0       0.94      0.95      0.95    198839\n",
            "           1       0.87      0.88      0.88    138243\n",
            "           2       0.95      0.94      0.95    147031\n",
            "\n",
            "    accuracy                           0.93    484113\n",
            "   macro avg       0.92      0.92      0.92    484113\n",
            "weighted avg       0.93      0.93      0.93    484113\n",
            "\n"
          ]
        }
      ],
      "source": [
        "y_pred = clf_vthd.predict(X_test_vthd)\n",
        "\n",
        "cm = confusion_matrix(y_test_vthd, y_pred)\n",
        "cm = pd.DataFrame(cm, index=[\"0\",\"1\", \"2\"], columns=[\"0\",\"1\", \"2\"])   \n",
        "cm.index.name = \"Actual\"\n",
        "cm.columns.name = \"Predicted\"\n",
        "display(cm)\n",
        "\n",
        "print(classification_report(y_test_vthd, y_pred))"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# model 저장\n",
        "\n",
        "with open('/content/drive/MyDrive/powersohmodel/model_vthd_rf.pickle','wb') as fw:\n",
        "    pickle.dump(clf_vthd, fw)"
      ],
      "metadata": {
        "id": "ND39B-sZs0zg"
      },
      "execution_count": 67,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# # model 불러오기\n",
        "\n",
        "# with open('/content/drive/MyDrive/powersohmodel/model_vthd_rf.pickle', 'rb') as f:\n",
        "#     clf_vthd = pickle.load(f)"
      ],
      "metadata": {
        "id": "_zWpxNURs4MH"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# sumbit_vthd_scaled 예측결과 sample_submission에 넣기\n",
        "\n",
        "sample_submission['label_전압고조파평균']=clf_vthd.predict(submit_vthd_scaled)\n",
        "sample_submission['label_전압고조파평균']=sample_submission['label_전압고조파평균'].apply(str).replace('0','정상')\n",
        "sample_submission['label_전압고조파평균']=sample_submission['label_전압고조파평균'].replace('1','주의')\n",
        "sample_submission['label_전압고조파평균']=sample_submission['label_전압고조파평균'].replace('2','경고')"
      ],
      "metadata": {
        "id": "nbJkShpWq2V3"
      },
      "execution_count": 95,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "sample_submission['label_전압고조파평균'].value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "UPNaKcDKlC-R",
        "outputId": "c8b98f75-d0ef-4259-9e4d-0a3b509cf896"
      },
      "execution_count": 96,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "정상    120482\n",
              "경고     98112\n",
              "주의     94673\n",
              "Name: label_전압고조파평균, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 96
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 97,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "8kzsnJrz1a9x",
        "outputId": "ba22e126-565d-40c1-ed48-547d0b58779a"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "            ID label_역률평균 label_전류고조파평균 label_전압고조파평균\n",
              "0            0         주의            정상            정상\n",
              "1            1         경고            정상            정상\n",
              "2            2         정상            정상            경고\n",
              "3            3         정상            정상            정상\n",
              "4            4         경고            주의            경고\n",
              "...        ...        ...           ...           ...\n",
              "313262  313263         경고            정상            정상\n",
              "313263  313264         경고            정상            주의\n",
              "313264  313265         경고            정상            정상\n",
              "313265  313266         경고            정상            정상\n",
              "313266  313267         경고            정상            정상\n",
              "\n",
              "[313267 rows x 4 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-5ee363c5-b682-472e-a2f8-822df64834d3\">\n",
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              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "  <tbody>\n",
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              "      <th>0</th>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>경고</td>\n",
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              "      <td>정상</td>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2</td>\n",
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              "      <th>3</th>\n",
              "      <td>3</td>\n",
              "      <td>정상</td>\n",
              "      <td>정상</td>\n",
              "      <td>정상</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>4</td>\n",
              "      <td>경고</td>\n",
              "      <td>주의</td>\n",
              "      <td>경고</td>\n",
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              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
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              "    <tr>\n",
              "      <th>313262</th>\n",
              "      <td>313263</td>\n",
              "      <td>경고</td>\n",
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              "      <td>정상</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>313263</th>\n",
              "      <td>313264</td>\n",
              "      <td>경고</td>\n",
              "      <td>정상</td>\n",
              "      <td>주의</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>313264</th>\n",
              "      <td>313265</td>\n",
              "      <td>경고</td>\n",
              "      <td>정상</td>\n",
              "      <td>정상</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>313265</th>\n",
              "      <td>313266</td>\n",
              "      <td>경고</td>\n",
              "      <td>정상</td>\n",
              "      <td>정상</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>313266</th>\n",
              "      <td>313267</td>\n",
              "      <td>경고</td>\n",
              "      <td>정상</td>\n",
              "      <td>정상</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>313267 rows × 4 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-5ee363c5-b682-472e-a2f8-822df64834d3')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
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              "      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",
              "    [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-5ee363c5-b682-472e-a2f8-822df64834d3 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-5ee363c5-b682-472e-a2f8-822df64834d3');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? 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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 97
        }
      ],
      "source": [
        "sample_submission"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 98,
      "metadata": {
        "id": "VTMJeEkXjt8e"
      },
      "outputs": [],
      "source": [
        "sample_submission.to_csv('powersoh_2.csv')"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 제출 결과\n",
        "f1_macro : 0.875442359400000"
      ],
      "metadata": {
        "id": "iF1f5yBfwUzl"
      }
    }
  ],
  "metadata": {
    "colab": {
      "collapsed_sections": [],
      "provenance": []
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}