temp_preprocessing.ipynb

{
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  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "mkjeJaWNTsGm",
    "outputId": "8fa617a3-a4b2-45bd-8c85-84d4847d4aae"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mounted at /content/drive\n"
     ]
    }
   ],
   "source": [
    "from google.colab import drive\n",
    "drive.mount('/content/drive') "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "id": "Nt5ux_5qjLeO"
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "# import os"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "id": "43bw7kFQjMs1"
   },
   "outputs": [],
   "source": [
    "# main = pd.read_csv(\"/content/drive/MyDrive/BDP/gas_data/main.csv\", encoding=\"cp949\")\n",
    "# oil = pd.read_csv(\"/content/drive/MyDrive/BDP/gas_data/oil.csv\", encoding=\"cp949\")\n",
    "# electricity = pd.read_csv(\"/content/drive/MyDrive/BDP/gas_data/electricity.csv\", encoding=\"cp949\")\n",
    "# production_index = pd.read_csv(\"/content/drive/MyDrive/BDP/gas_data/production_index.csv\", encoding=\"cp949\")\n",
    "\n",
    "# temp2013 = pd.read_csv(\"/content/drive/MyDrive/BDP/gas_data/temp2013.csv\", encoding=\"cp949\")\n",
    "# temp2014 = pd.read_csv(\"/content/drive/MyDrive/BDP/gas_data/temp2014.csv\", encoding=\"cp949\")\n",
    "# temp2015 = pd.read_csv(\"/content/drive/MyDrive/BDP/gas_data/temp2015.csv\", encoding=\"cp949\")\n",
    "# temp2016 = pd.read_csv(\"/content/drive/MyDrive/BDP/gas_data/temp2016.csv\", encoding=\"cp949\")\n",
    "# temp2017 = pd.read_csv(\"/content/drive/MyDrive/BDP/gas_data/temp2017.csv\", encoding=\"cp949\")\n",
    "# temp2018 = pd.read_csv(\"/content/drive/MyDrive/BDP/gas_data/temp2018.csv\", encoding=\"cp949\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "main = pd.read_csv(\"gas_data/main.csv\", encoding=\"cp949\")\n",
    "oil = pd.read_csv(\"gas_data/oil.csv\", encoding=\"cp949\")\n",
    "electricity = pd.read_csv(\"gas_data/electricity.csv\", encoding=\"cp949\")\n",
    "# production_index = pd.read_csv(\"gas_data/production_index.csv\", encoding=\"cp949\")\n",
    "\n",
    "temp2013 = pd.read_csv(\"gas_data/temp2013.csv\", encoding=\"cp949\")\n",
    "temp2014 = pd.read_csv(\"gas_data/temp2014.csv\", encoding=\"cp949\")\n",
    "temp2015 = pd.read_csv(\"gas_data/temp2015.csv\", encoding=\"cp949\")\n",
    "temp2016 = pd.read_csv(\"gas_data/temp2016.csv\", encoding=\"cp949\")\n",
    "temp2017 = pd.read_csv(\"gas_data/temp2017.csv\", encoding=\"cp949\")\n",
    "temp2018 = pd.read_csv(\"gas_data/temp2018.csv\", encoding=\"cp949\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 206
    },
    "id": "dboi1rfmGamK",
    "outputId": "918c2683-471f-4f45-efdd-49702ab2d661"
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   "outputs": [
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>연월일</th>\n",
       "      <th>시간</th>\n",
       "      <th>구분</th>\n",
       "      <th>공급량</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2013-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>A</td>\n",
       "      <td>2497.129</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2013-01-01</td>\n",
       "      <td>2</td>\n",
       "      <td>A</td>\n",
       "      <td>2363.265</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2013-01-01</td>\n",
       "      <td>3</td>\n",
       "      <td>A</td>\n",
       "      <td>2258.505</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2013-01-01</td>\n",
       "      <td>4</td>\n",
       "      <td>A</td>\n",
       "      <td>2243.969</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2013-01-01</td>\n",
       "      <td>5</td>\n",
       "      <td>A</td>\n",
       "      <td>2344.105</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      ],
      "text/plain": [
       "          연월일  시간 구분       공급량\n",
       "0  2013-01-01   1  A  2497.129\n",
       "1  2013-01-01   2  A  2363.265\n",
       "2  2013-01-01   3  A  2258.505\n",
       "3  2013-01-01   4  A  2243.969\n",
       "4  2013-01-01   5  A  2344.105"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "main.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 206
    },
    "id": "xoTOCDVgMVtG",
    "outputId": "7a06aa91-2eb0-4b3f-a50e-d1944388398e"
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   "outputs": [
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       "      <th></th>\n",
       "      <th>연월</th>\n",
       "      <th>가스가격</th>\n",
       "      <th>기름가격</th>\n",
       "      <th>상대가격</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2007-01-01</td>\n",
       "      <td>73.60</td>\n",
       "      <td>97.08</td>\n",
       "      <td>0.76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2007-02-01</td>\n",
       "      <td>73.60</td>\n",
       "      <td>97.25</td>\n",
       "      <td>0.76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2007-03-01</td>\n",
       "      <td>71.55</td>\n",
       "      <td>100.61</td>\n",
       "      <td>0.72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2007-04-01</td>\n",
       "      <td>71.55</td>\n",
       "      <td>103.96</td>\n",
       "      <td>0.69</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2007-05-01</td>\n",
       "      <td>74.89</td>\n",
       "      <td>107.27</td>\n",
       "      <td>0.70</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           연월   가스가격    기름가격  상대가격\n",
       "0  2007-01-01  73.60   97.08  0.76\n",
       "1  2007-02-01  73.60   97.25  0.76\n",
       "2  2007-03-01  71.55  100.61  0.72\n",
       "3  2007-04-01  71.55  103.96  0.69\n",
       "4  2007-05-01  74.89  107.27  0.70"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "oil.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 206
    },
    "id": "wPtFN9ltMd6T",
    "outputId": "ec6c8b6e-850a-4baa-e126-e3f599ddf184"
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>연월</th>\n",
       "      <th>가스가격</th>\n",
       "      <th>전기가격</th>\n",
       "      <th>상대가격</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2007-01-01</td>\n",
       "      <td>88.14</td>\n",
       "      <td>104.5</td>\n",
       "      <td>84.34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2007-02-01</td>\n",
       "      <td>88.14</td>\n",
       "      <td>104.5</td>\n",
       "      <td>84.34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2007-03-01</td>\n",
       "      <td>86.15</td>\n",
       "      <td>104.5</td>\n",
       "      <td>82.44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2007-04-01</td>\n",
       "      <td>86.15</td>\n",
       "      <td>104.5</td>\n",
       "      <td>82.44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2007-05-01</td>\n",
       "      <td>89.45</td>\n",
       "      <td>104.5</td>\n",
       "      <td>85.60</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           연월   가스가격   전기가격   상대가격\n",
       "0  2007-01-01  88.14  104.5  84.34\n",
       "1  2007-02-01  88.14  104.5  84.34\n",
       "2  2007-03-01  86.15  104.5  82.44\n",
       "3  2007-04-01  86.15  104.5  82.44\n",
       "4  2007-05-01  89.45  104.5  85.60"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "electricity.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 206
    },
    "id": "LN_ytPzwMjae",
    "outputId": "ea047bf3-1aa7-4a4e-ac52-170f644de044"
   },
   "outputs": [],
   "source": [
    "# production_index.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 206
    },
    "id": "js9d6f4nMQEm",
    "outputId": "c7751d5f-a10c-4d3e-8a23-decfe1ca6bbe"
   },
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>날짜</th>\n",
       "      <th>지점</th>\n",
       "      <th>평균기온(℃)</th>\n",
       "      <th>최저기온(℃)</th>\n",
       "      <th>최고기온(℃)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>\\t2013-01-01</td>\n",
       "      <td>108.0</td>\n",
       "      <td>-4.7</td>\n",
       "      <td>-8.7</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>\\t2013-01-02</td>\n",
       "      <td>108.0</td>\n",
       "      <td>-11.7</td>\n",
       "      <td>-15.1</td>\n",
       "      <td>-4.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>\\t2013-01-03</td>\n",
       "      <td>108.0</td>\n",
       "      <td>-13.2</td>\n",
       "      <td>-16.4</td>\n",
       "      <td>-9.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>\\t2013-01-04</td>\n",
       "      <td>108.0</td>\n",
       "      <td>-10.7</td>\n",
       "      <td>-14.8</td>\n",
       "      <td>-5.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>\\t2013-01-05</td>\n",
       "      <td>108.0</td>\n",
       "      <td>-7.0</td>\n",
       "      <td>-12.1</td>\n",
       "      <td>-1.2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             날짜     지점  평균기온(℃)  최저기온(℃)  최고기온(℃)\n",
       "0  \\t2013-01-01  108.0     -4.7     -8.7      0.0\n",
       "1  \\t2013-01-02  108.0    -11.7    -15.1     -4.8\n",
       "2  \\t2013-01-03  108.0    -13.2    -16.4     -9.3\n",
       "3  \\t2013-01-04  108.0    -10.7    -14.8     -5.8\n",
       "4  \\t2013-01-05  108.0     -7.0    -12.1     -1.2"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp2013.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Bmz1b2GUYgaZ"
   },
   "source": [
    "# 기온변수 전처리"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "id": "oGVJwOZyGPkW"
   },
   "outputs": [],
   "source": [
    "temp_mean2013 = pd.pivot_table(temp2013, values=\"평균기온(℃)\", index=[\"날짜\"], aggfunc = np.mean).reset_index()\n",
    "temp_mean2014 = pd.pivot_table(temp2014, values=\"평균기온(℃)\", index=[\"날짜\"], aggfunc = np.mean).reset_index()\n",
    "temp_mean2015 = pd.pivot_table(temp2015, values=\"평균기온(℃)\", index=[\"날짜\"], aggfunc = np.mean).reset_index()\n",
    "temp_mean2016 = pd.pivot_table(temp2016, values=\"평균기온(℃)\", index=[\"날짜\"], aggfunc = np.mean).reset_index()\n",
    "temp_mean2017 = pd.pivot_table(temp2017, values=\"평균기온(℃)\", index=[\"날짜\"], aggfunc = np.mean).reset_index()\n",
    "temp_mean2018 = pd.pivot_table(temp2018, values=\"평균기온(℃)\", index=[\"날짜\"], aggfunc = np.mean).reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>날짜</th>\n",
       "      <th>지점</th>\n",
       "      <th>평균기온(℃)</th>\n",
       "      <th>최저기온(℃)</th>\n",
       "      <th>최고기온(℃)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>\\t2013-01-01</td>\n",
       "      <td>108.0</td>\n",
       "      <td>-4.7</td>\n",
       "      <td>-8.7</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>\\t2013-01-02</td>\n",
       "      <td>108.0</td>\n",
       "      <td>-11.7</td>\n",
       "      <td>-15.1</td>\n",
       "      <td>-4.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>\\t2013-01-03</td>\n",
       "      <td>108.0</td>\n",
       "      <td>-13.2</td>\n",
       "      <td>-16.4</td>\n",
       "      <td>-9.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>\\t2013-01-04</td>\n",
       "      <td>108.0</td>\n",
       "      <td>-10.7</td>\n",
       "      <td>-14.8</td>\n",
       "      <td>-5.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>\\t2013-01-05</td>\n",
       "      <td>108.0</td>\n",
       "      <td>-7.0</td>\n",
       "      <td>-12.1</td>\n",
       "      <td>-1.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>361</th>\n",
       "      <td>\\t2013-12-28</td>\n",
       "      <td>108.0</td>\n",
       "      <td>-6.5</td>\n",
       "      <td>-9.8</td>\n",
       "      <td>-2.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>362</th>\n",
       "      <td>\\t2013-12-29</td>\n",
       "      <td>108.0</td>\n",
       "      <td>-2.9</td>\n",
       "      <td>-8.0</td>\n",
       "      <td>1.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>363</th>\n",
       "      <td>\\t2013-12-30</td>\n",
       "      <td>108.0</td>\n",
       "      <td>2.2</td>\n",
       "      <td>-1.9</td>\n",
       "      <td>6.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>364</th>\n",
       "      <td>\\t2013-12-31</td>\n",
       "      <td>108.0</td>\n",
       "      <td>3.8</td>\n",
       "      <td>0.5</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>365</th>\n",
       "      <td>\\t</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>366 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               날짜     지점  평균기온(℃)  최저기온(℃)  최고기온(℃)\n",
       "0    \\t2013-01-01  108.0     -4.7     -8.7      0.0\n",
       "1    \\t2013-01-02  108.0    -11.7    -15.1     -4.8\n",
       "2    \\t2013-01-03  108.0    -13.2    -16.4     -9.3\n",
       "3    \\t2013-01-04  108.0    -10.7    -14.8     -5.8\n",
       "4    \\t2013-01-05  108.0     -7.0    -12.1     -1.2\n",
       "..            ...    ...      ...      ...      ...\n",
       "361  \\t2013-12-28  108.0     -6.5     -9.8     -2.7\n",
       "362  \\t2013-12-29  108.0     -2.9     -8.0      1.6\n",
       "363  \\t2013-12-30  108.0      2.2     -1.9      6.3\n",
       "364  \\t2013-12-31  108.0      3.8      0.5      8.0\n",
       "365            \\t    NaN      NaN      NaN      NaN\n",
       "\n",
       "[366 rows x 5 columns]"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp2013"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "id": "sgP5SnK0bMWk"
   },
   "outputs": [],
   "source": [
    "def df_duplicate(df):\n",
    "  new_df = pd.DataFrame()\n",
    "  for _ in range(7):\n",
    "    new_df = pd.concat([new_df, df])\n",
    "  return new_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "id": "4CRo2K9NjXtu"
   },
   "outputs": [],
   "source": [
    "temp_mean2013['날짜'] = temp_mean2013['날짜'].str.slice(1,)\n",
    "temp_mean2014['날짜'] = temp_mean2014['날짜'].str.slice(1,)\n",
    "temp_mean2015['날짜'] = temp_mean2015['날짜'].str.slice(1,)\n",
    "temp_mean2016['날짜'] = temp_mean2016['날짜'].str.slice(1,)\n",
    "temp_mean2017['날짜'] = temp_mean2017['날짜'].str.slice(1,)\n",
    "temp_mean2018['날짜'] = temp_mean2018['날짜'].str.slice(1,)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "id": "kJqE6ff6bflq"
   },
   "outputs": [],
   "source": [
    "weather_2013_total = df_duplicate(temp_mean2013)\n",
    "weather_2014_total = df_duplicate(temp_mean2014)\n",
    "weather_2015_total = df_duplicate(temp_mean2015)\n",
    "weather_2016_total = df_duplicate(temp_mean2016)\n",
    "weather_2017_total = df_duplicate(temp_mean2017)\n",
    "weather_2018_total = df_duplicate(temp_mean2018)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "id": "ZkaQAE7nbgGY"
   },
   "outputs": [],
   "source": [
    "weather_total = pd.concat([weather_2013_total, weather_2014_total, weather_2015_total, \n",
    "                           weather_2016_total, weather_2017_total, weather_2018_total])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 424
    },
    "id": "AdYeuNRAb_RD",
    "outputId": "cd735e3f-fc79-4b9f-e6c1-a17b6e184861"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>날짜</th>\n",
       "      <th>평균기온(℃)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2013-01-01</td>\n",
       "      <td>-4.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2013-01-02</td>\n",
       "      <td>-11.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2013-01-03</td>\n",
       "      <td>-13.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2013-01-04</td>\n",
       "      <td>-10.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2013-01-05</td>\n",
       "      <td>-7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>360</th>\n",
       "      <td>2018-12-27</td>\n",
       "      <td>-10.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>361</th>\n",
       "      <td>2018-12-28</td>\n",
       "      <td>-10.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>362</th>\n",
       "      <td>2018-12-29</td>\n",
       "      <td>-7.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>363</th>\n",
       "      <td>2018-12-30</td>\n",
       "      <td>-6.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>364</th>\n",
       "      <td>2018-12-31</td>\n",
       "      <td>-5.4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>15337 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             날짜  평균기온(℃)\n",
       "0    2013-01-01     -4.7\n",
       "1    2013-01-02    -11.7\n",
       "2    2013-01-03    -13.2\n",
       "3    2013-01-04    -10.7\n",
       "4    2013-01-05     -7.0\n",
       "..          ...      ...\n",
       "360  2018-12-27    -10.1\n",
       "361  2018-12-28    -10.5\n",
       "362  2018-12-29     -7.6\n",
       "363  2018-12-30     -6.8\n",
       "364  2018-12-31     -5.4\n",
       "\n",
       "[15337 rows x 2 columns]"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "weather_total"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [],
   "source": [
    "weather_total['날짜'] = pd.to_datetime(weather_total['날짜'])\n",
    "weather_total['year'] = weather_total['날짜'].dt.year \n",
    "weather_total['month'] = weather_total['날짜'].dt.month \n",
    "weather_total['day'] = weather_total['날짜'].dt.day"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>날짜</th>\n",
       "      <th>평균기온(℃)</th>\n",
       "      <th>year</th>\n",
       "      <th>month</th>\n",
       "      <th>day</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2013-01-01</td>\n",
       "      <td>-4.7</td>\n",
       "      <td>2013</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2013-01-02</td>\n",
       "      <td>-11.7</td>\n",
       "      <td>2013</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2013-01-03</td>\n",
       "      <td>-13.2</td>\n",
       "      <td>2013</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2013-01-04</td>\n",
       "      <td>-10.7</td>\n",
       "      <td>2013</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2013-01-05</td>\n",
       "      <td>-7.0</td>\n",
       "      <td>2013</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>360</th>\n",
       "      <td>2018-12-27</td>\n",
       "      <td>-10.1</td>\n",
       "      <td>2018</td>\n",
       "      <td>12</td>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>361</th>\n",
       "      <td>2018-12-28</td>\n",
       "      <td>-10.5</td>\n",
       "      <td>2018</td>\n",
       "      <td>12</td>\n",
       "      <td>28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>362</th>\n",
       "      <td>2018-12-29</td>\n",
       "      <td>-7.6</td>\n",
       "      <td>2018</td>\n",
       "      <td>12</td>\n",
       "      <td>29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>363</th>\n",
       "      <td>2018-12-30</td>\n",
       "      <td>-6.8</td>\n",
       "      <td>2018</td>\n",
       "      <td>12</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>364</th>\n",
       "      <td>2018-12-31</td>\n",
       "      <td>-5.4</td>\n",
       "      <td>2018</td>\n",
       "      <td>12</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>15337 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            날짜  평균기온(℃)  year  month  day\n",
       "0   2013-01-01     -4.7  2013      1    1\n",
       "1   2013-01-02    -11.7  2013      1    2\n",
       "2   2013-01-03    -13.2  2013      1    3\n",
       "3   2013-01-04    -10.7  2013      1    4\n",
       "4   2013-01-05     -7.0  2013      1    5\n",
       "..         ...      ...   ...    ...  ...\n",
       "360 2018-12-27    -10.1  2018     12   27\n",
       "361 2018-12-28    -10.5  2018     12   28\n",
       "362 2018-12-29     -7.6  2018     12   29\n",
       "363 2018-12-30     -6.8  2018     12   30\n",
       "364 2018-12-31     -5.4  2018     12   31\n",
       "\n",
       "[15337 rows x 5 columns]"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "weather_total"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "F0zdyEx_ciCm"
   },
   "source": [
    "# 날씨 데이터 전처리 끝!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>연월일</th>\n",
       "      <th>시간</th>\n",
       "      <th>구분</th>\n",
       "      <th>공급량</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2013-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>A</td>\n",
       "      <td>2497.129</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2013-01-01</td>\n",
       "      <td>2</td>\n",
       "      <td>A</td>\n",
       "      <td>2363.265</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2013-01-01</td>\n",
       "      <td>3</td>\n",
       "      <td>A</td>\n",
       "      <td>2258.505</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2013-01-01</td>\n",
       "      <td>4</td>\n",
       "      <td>A</td>\n",
       "      <td>2243.969</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2013-01-01</td>\n",
       "      <td>5</td>\n",
       "      <td>A</td>\n",
       "      <td>2344.105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>368083</th>\n",
       "      <td>2018-12-31</td>\n",
       "      <td>20</td>\n",
       "      <td>H</td>\n",
       "      <td>681.033</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>368084</th>\n",
       "      <td>2018-12-31</td>\n",
       "      <td>21</td>\n",
       "      <td>H</td>\n",
       "      <td>669.961</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>368085</th>\n",
       "      <td>2018-12-31</td>\n",
       "      <td>22</td>\n",
       "      <td>H</td>\n",
       "      <td>657.941</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>368086</th>\n",
       "      <td>2018-12-31</td>\n",
       "      <td>23</td>\n",
       "      <td>H</td>\n",
       "      <td>610.953</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>368087</th>\n",
       "      <td>2018-12-31</td>\n",
       "      <td>24</td>\n",
       "      <td>H</td>\n",
       "      <td>560.896</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>368088 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               연월일  시간 구분       공급량\n",
       "0       2013-01-01   1  A  2497.129\n",
       "1       2013-01-01   2  A  2363.265\n",
       "2       2013-01-01   3  A  2258.505\n",
       "3       2013-01-01   4  A  2243.969\n",
       "4       2013-01-01   5  A  2344.105\n",
       "...            ...  .. ..       ...\n",
       "368083  2018-12-31  20  H   681.033\n",
       "368084  2018-12-31  21  H   669.961\n",
       "368085  2018-12-31  22  H   657.941\n",
       "368086  2018-12-31  23  H   610.953\n",
       "368087  2018-12-31  24  H   560.896\n",
       "\n",
       "[368088 rows x 4 columns]"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 앞에 메인데이터 전처리하는 과정 필요함\n",
    "main"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [],
   "source": [
    "main['월평균_기온'] = \"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [],
   "source": [
    "temp_join = pd.merge(main, weather_total, how=\"inner\", on=(\"year\", \"month\", \"day\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>시간</th>\n",
       "      <th>구분</th>\n",
       "      <th>공급량</th>\n",
       "      <th>year</th>\n",
       "      <th>month</th>\n",
       "      <th>day</th>\n",
       "      <th>lower</th>\n",
       "      <th>upper</th>\n",
       "      <th>이상치처리_공급량</th>\n",
       "      <th>월평균_기온</th>\n",
       "      <th>날짜</th>\n",
       "      <th>평균기온(℃)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2013-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2497.129</td>\n",
       "      <td>2013</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>2013-01-01</td>\n",
       "      <td>-4.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2013-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2497.129</td>\n",
       "      <td>2013</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>2013-01-01</td>\n",
       "      <td>-4.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2013-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2497.129</td>\n",
       "      <td>2013</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>2013-01-01</td>\n",
       "      <td>-4.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2013-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2497.129</td>\n",
       "      <td>2013</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>2013-01-01</td>\n",
       "      <td>-4.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2013-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2497.129</td>\n",
       "      <td>2013</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>2013-01-01</td>\n",
       "      <td>-4.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2576611</th>\n",
       "      <td>2018-12-31</td>\n",
       "      <td>24</td>\n",
       "      <td>6</td>\n",
       "      <td>560.896</td>\n",
       "      <td>2018</td>\n",
       "      <td>12</td>\n",
       "      <td>31</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>2018-12-31</td>\n",
       "      <td>-5.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2576612</th>\n",
       "      <td>2018-12-31</td>\n",
       "      <td>24</td>\n",
       "      <td>6</td>\n",
       "      <td>560.896</td>\n",
       "      <td>2018</td>\n",
       "      <td>12</td>\n",
       "      <td>31</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>2018-12-31</td>\n",
       "      <td>-5.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2576613</th>\n",
       "      <td>2018-12-31</td>\n",
       "      <td>24</td>\n",
       "      <td>6</td>\n",
       "      <td>560.896</td>\n",
       "      <td>2018</td>\n",
       "      <td>12</td>\n",
       "      <td>31</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>2018-12-31</td>\n",
       "      <td>-5.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2576614</th>\n",
       "      <td>2018-12-31</td>\n",
       "      <td>24</td>\n",
       "      <td>6</td>\n",
       "      <td>560.896</td>\n",
       "      <td>2018</td>\n",
       "      <td>12</td>\n",
       "      <td>31</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>2018-12-31</td>\n",
       "      <td>-5.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2576615</th>\n",
       "      <td>2018-12-31</td>\n",
       "      <td>24</td>\n",
       "      <td>6</td>\n",
       "      <td>560.896</td>\n",
       "      <td>2018</td>\n",
       "      <td>12</td>\n",
       "      <td>31</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>2018-12-31</td>\n",
       "      <td>-5.4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2576616 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               연월일  시간  구분       공급량  year  month  day lower upper 이상치처리_공급량  \\\n",
       "0       2013-01-01   1   0  2497.129  2013      1    1                         \n",
       "1       2013-01-01   1   0  2497.129  2013      1    1                         \n",
       "2       2013-01-01   1   0  2497.129  2013      1    1                         \n",
       "3       2013-01-01   1   0  2497.129  2013      1    1                         \n",
       "4       2013-01-01   1   0  2497.129  2013      1    1                         \n",
       "...            ...  ..  ..       ...   ...    ...  ...   ...   ...       ...   \n",
       "2576611 2018-12-31  24   6   560.896  2018     12   31                         \n",
       "2576612 2018-12-31  24   6   560.896  2018     12   31                         \n",
       "2576613 2018-12-31  24   6   560.896  2018     12   31                         \n",
       "2576614 2018-12-31  24   6   560.896  2018     12   31                         \n",
       "2576615 2018-12-31  24   6   560.896  2018     12   31                         \n",
       "\n",
       "        월평균_기온         날짜  평균기온(℃)  \n",
       "0              2013-01-01     -4.7  \n",
       "1              2013-01-01     -4.7  \n",
       "2              2013-01-01     -4.7  \n",
       "3              2013-01-01     -4.7  \n",
       "4              2013-01-01     -4.7  \n",
       "...        ...        ...      ...  \n",
       "2576611        2018-12-31     -5.4  \n",
       "2576612        2018-12-31     -5.4  \n",
       "2576613        2018-12-31     -5.4  \n",
       "2576614        2018-12-31     -5.4  \n",
       "2576615        2018-12-31     -5.4  \n",
       "\n",
       "[2576616 rows x 13 columns]"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp_join"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "❤️깃허브에 올리기 위해 이것좀 써놓을게요❤️\n"
     ]
    }
   ],
   "source": [
    "print(\"❤️깃허브에 올리기 위해 이것좀 써놓을게요❤️\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "wV4nhXF_cl0y"
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "-bg0OwGccmYD"
   },
   "outputs": [],
   "source": []
  }
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