{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "generate_prediction.ipynb",
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "id": "TB2mZGOKD5lp",
        "outputId": "71c0f9b6-c119-41bb-d792-9f75c925e787",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/gdrive/')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Mounted at /content/gdrive/\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6toBcxODD60f"
      },
      "source": [
        "folder = '/content/gdrive/My Drive/colab_data/cap_di/'\n",
        "weather = folder+'세종시 날씨.csv'\n",
        "generate = folder+'세종시.csv'"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "kkN1rP34E7WC"
      },
      "source": [
        "import pandas as pd"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8NENGSIfE9rH",
        "outputId": "83e74f5a-52f7-41bb-eead-0b56d0f5cab0",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        }
      },
      "source": [
        "wt = pd.read_csv(weather,encoding='CP949')\n",
        "wt.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
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              "    .dataframe tbody tr th:only-of-type {\n",
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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>일시</th>\n",
              "      <th>기온(°C)</th>\n",
              "      <th>강수량(mm)</th>\n",
              "      <th>습도(%)</th>\n",
              "      <th>현지기압(hPa)</th>\n",
              "      <th>일조(hr)</th>\n",
              "      <th>지면온도(°C)</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2019-07-01 1:00</td>\n",
              "      <td>22.2</td>\n",
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              "      <td>90</td>\n",
              "      <td>993.5</td>\n",
              "      <td>NaN</td>\n",
              "      <td>22.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2019-07-01 2:00</td>\n",
              "      <td>22.4</td>\n",
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              "      <td>993.4</td>\n",
              "      <td>NaN</td>\n",
              "      <td>22.2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2019-07-01 3:00</td>\n",
              "      <td>22.3</td>\n",
              "      <td>NaN</td>\n",
              "      <td>90</td>\n",
              "      <td>993.4</td>\n",
              "      <td>NaN</td>\n",
              "      <td>22.1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2019-07-01 4:00</td>\n",
              "      <td>21.9</td>\n",
              "      <td>NaN</td>\n",
              "      <td>91</td>\n",
              "      <td>993.4</td>\n",
              "      <td>NaN</td>\n",
              "      <td>21.4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2019-07-01 5:00</td>\n",
              "      <td>21.8</td>\n",
              "      <td>NaN</td>\n",
              "      <td>91</td>\n",
              "      <td>993.9</td>\n",
              "      <td>NaN</td>\n",
              "      <td>21.2</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                일시  기온(°C)  강수량(mm)  습도(%)  현지기압(hPa)  일조(hr)  지면온도(°C)\n",
              "0  2019-07-01 1:00    22.2      NaN     90      993.5     NaN      22.0\n",
              "1  2019-07-01 2:00    22.4      NaN     89      993.4     NaN      22.2\n",
              "2  2019-07-01 3:00    22.3      NaN     90      993.4     NaN      22.1\n",
              "3  2019-07-01 4:00    21.9      NaN     91      993.4     NaN      21.4\n",
              "4  2019-07-01 5:00    21.8      NaN     91      993.9     NaN      21.2"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YRZ9hz42FdDE",
        "outputId": "c205e81a-87f0-49b8-8602-1a54d5b88b26",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 235
        }
      },
      "source": [
        "variables=[\"기온(°C)\",\"강수량(mm)\",\"습도(%)\",\"현지기압(hPa)\",\"지면온도(°C)\"]\n",
        "wtData=wt[variables]\n",
        "wtData.index=wt['일시']\n",
        "wtData.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>기온(°C)</th>\n",
              "      <th>강수량(mm)</th>\n",
              "      <th>습도(%)</th>\n",
              "      <th>현지기압(hPa)</th>\n",
              "      <th>지면온도(°C)</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>일시</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2019-07-01 1:00</th>\n",
              "      <td>22.2</td>\n",
              "      <td>NaN</td>\n",
              "      <td>90</td>\n",
              "      <td>993.5</td>\n",
              "      <td>22.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-07-01 2:00</th>\n",
              "      <td>22.4</td>\n",
              "      <td>NaN</td>\n",
              "      <td>89</td>\n",
              "      <td>993.4</td>\n",
              "      <td>22.2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-07-01 3:00</th>\n",
              "      <td>22.3</td>\n",
              "      <td>NaN</td>\n",
              "      <td>90</td>\n",
              "      <td>993.4</td>\n",
              "      <td>22.1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-07-01 4:00</th>\n",
              "      <td>21.9</td>\n",
              "      <td>NaN</td>\n",
              "      <td>91</td>\n",
              "      <td>993.4</td>\n",
              "      <td>21.4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-07-01 5:00</th>\n",
              "      <td>21.8</td>\n",
              "      <td>NaN</td>\n",
              "      <td>91</td>\n",
              "      <td>993.9</td>\n",
              "      <td>21.2</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                 기온(°C)  강수량(mm)  습도(%)  현지기압(hPa)  지면온도(°C)\n",
              "일시                                                          \n",
              "2019-07-01 1:00    22.2      NaN     90      993.5      22.0\n",
              "2019-07-01 2:00    22.4      NaN     89      993.4      22.2\n",
              "2019-07-01 3:00    22.3      NaN     90      993.4      22.1\n",
              "2019-07-01 4:00    21.9      NaN     91      993.4      21.4\n",
              "2019-07-01 5:00    21.8      NaN     91      993.9      21.2"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4DGaculbN3PN",
        "outputId": "c5a1efb0-c363-4bff-b42d-7b6b2e23901c",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "print(wtData)"
      ],
      "execution_count": 60,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "                  기온(°C)  강수량(mm)  습도(%)  현지기압(hPa)  지면온도(°C)\n",
            "일시                                                           \n",
            "2019-07-01 1:00     22.2      NaN     90      993.5      22.0\n",
            "2019-07-01 2:00     22.4      NaN     89      993.4      22.2\n",
            "2019-07-01 3:00     22.3      NaN     90      993.4      22.1\n",
            "2019-07-01 4:00     21.9      NaN     91      993.4      21.4\n",
            "2019-07-01 5:00     21.8      NaN     91      993.9      21.2\n",
            "...                  ...      ...    ...        ...       ...\n",
            "2020-06-29 20:00    20.0      6.1     93      986.6      21.2\n",
            "2020-06-29 21:00    19.9     11.1     94      984.7      20.9\n",
            "2020-06-29 22:00    20.2      6.0     94      983.4      20.9\n",
            "2020-06-29 23:00    20.2      5.1     94      981.2      20.7\n",
            "2020-06-30 0:00     20.3      2.0     91      979.8      20.6\n",
            "\n",
            "[8760 rows x 5 columns]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6m7FW6rLFXBP",
        "outputId": "f95c389e-1f64-43df-9d51-5d5b81970f06",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        }
      },
      "source": [
        "gnt=pd.read_csv(generate,encoding='CP949')\n",
        "gnt.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>일자</th>\n",
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              "      <th>2:00</th>\n",
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              "      <td>0</td>\n",
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              "      <td>92880</td>\n",
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              "      <th>1</th>\n",
              "      <td>2019-07-02</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <th>2</th>\n",
              "      <td>2019-07-03</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
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              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "           일자  1:00  2:00  3:00  4:00  ...  20:00  21:00  22:00  23:00  0:00\n",
              "0  2019-07-01     0     0     0     0  ...      0      0      0      0     0\n",
              "1  2019-07-02     0     0     0     0  ...   6720      0      0      0     0\n",
              "2  2019-07-03     0     0     0     0  ...      0      0      0      0     0\n",
              "3  2019-07-04     0     0     0     0  ...   2760      0      0      0     0\n",
              "4  2019-07-05     0     0     0     0  ...      0      0      0      0     0\n",
              "\n",
              "[5 rows x 25 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "okcsLKdqGqSZ",
        "outputId": "2657961c-9e5d-4bda-ecd1-356635ac98a7",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 235
        }
      },
      "source": [
        "GNTvariables=['1:00','2:00','3:00','4:00','5:00','6:00','7:00','8:00','9:00','10:00','11:00','12:00','13:00','14:00','15:00','16:00','17:00','18:00','19:00','20:00','21:00','22:00','23:00','0:00']\n",
        "tempGNT=gnt[GNTvariables]\n",
        "tempGNT.index=gnt['일자']\n",
        "tempGNT.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>1:00</th>\n",
              "      <th>2:00</th>\n",
              "      <th>3:00</th>\n",
              "      <th>4:00</th>\n",
              "      <th>5:00</th>\n",
              "      <th>6:00</th>\n",
              "      <th>7:00</th>\n",
              "      <th>8:00</th>\n",
              "      <th>9:00</th>\n",
              "      <th>10:00</th>\n",
              "      <th>11:00</th>\n",
              "      <th>12:00</th>\n",
              "      <th>13:00</th>\n",
              "      <th>14:00</th>\n",
              "      <th>15:00</th>\n",
              "      <th>16:00</th>\n",
              "      <th>17:00</th>\n",
              "      <th>18:00</th>\n",
              "      <th>19:00</th>\n",
              "      <th>20:00</th>\n",
              "      <th>21:00</th>\n",
              "      <th>22:00</th>\n",
              "      <th>23:00</th>\n",
              "      <th>0:00</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>일자</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2019-07-01</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>360</td>\n",
              "      <td>6000</td>\n",
              "      <td>92880</td>\n",
              "      <td>244560</td>\n",
              "      <td>357480</td>\n",
              "      <td>464880</td>\n",
              "      <td>720840</td>\n",
              "      <td>744000</td>\n",
              "      <td>532200</td>\n",
              "      <td>462240</td>\n",
              "      <td>433200</td>\n",
              "      <td>348120</td>\n",
              "      <td>336720</td>\n",
              "      <td>109920</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-07-02</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>120</td>\n",
              "      <td>81720</td>\n",
              "      <td>313800</td>\n",
              "      <td>625680</td>\n",
              "      <td>831360</td>\n",
              "      <td>1062240</td>\n",
              "      <td>861240</td>\n",
              "      <td>849600</td>\n",
              "      <td>785280</td>\n",
              "      <td>915960</td>\n",
              "      <td>843240</td>\n",
              "      <td>565320</td>\n",
              "      <td>178080</td>\n",
              "      <td>115800</td>\n",
              "      <td>6720</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-07-03</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>54480</td>\n",
              "      <td>219720</td>\n",
              "      <td>320400</td>\n",
              "      <td>602400</td>\n",
              "      <td>805440</td>\n",
              "      <td>917280</td>\n",
              "      <td>815760</td>\n",
              "      <td>569520</td>\n",
              "      <td>613080</td>\n",
              "      <td>726480</td>\n",
              "      <td>510120</td>\n",
              "      <td>313440</td>\n",
              "      <td>68400</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-07-04</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>120</td>\n",
              "      <td>65160</td>\n",
              "      <td>310560</td>\n",
              "      <td>623400</td>\n",
              "      <td>877440</td>\n",
              "      <td>1044240</td>\n",
              "      <td>1170240</td>\n",
              "      <td>1202400</td>\n",
              "      <td>1159920</td>\n",
              "      <td>1071600</td>\n",
              "      <td>680280</td>\n",
              "      <td>467640</td>\n",
              "      <td>267000</td>\n",
              "      <td>130560</td>\n",
              "      <td>2760</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-07-05</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>57120</td>\n",
              "      <td>310320</td>\n",
              "      <td>520320</td>\n",
              "      <td>847800</td>\n",
              "      <td>1031760</td>\n",
              "      <td>1145280</td>\n",
              "      <td>1186680</td>\n",
              "      <td>1146360</td>\n",
              "      <td>970200</td>\n",
              "      <td>664920</td>\n",
              "      <td>506520</td>\n",
              "      <td>304200</td>\n",
              "      <td>64560</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "            1:00  2:00  3:00  4:00  5:00  ...  20:00  21:00  22:00  23:00  0:00\n",
              "일자                                        ...                                  \n",
              "2019-07-01     0     0     0     0     0  ...      0      0      0      0     0\n",
              "2019-07-02     0     0     0     0     0  ...   6720      0      0      0     0\n",
              "2019-07-03     0     0     0     0     0  ...      0      0      0      0     0\n",
              "2019-07-04     0     0     0     0     0  ...   2760      0      0      0     0\n",
              "2019-07-05     0     0     0     0     0  ...      0      0      0      0     0\n",
              "\n",
              "[5 rows x 24 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tCCfCxurIETg",
        "outputId": "5be25bb4-050b-4fbe-cafa-615f489c1b9b",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "print(tempGNT.columns)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Index(['1:00', '2:00', '3:00', '4:00', '5:00', '6:00', '7:00', '8:00', '9:00',\n",
            "       '10:00', '11:00', '12:00', '13:00', '14:00', '15:00', '16:00', '17:00',\n",
            "       '18:00', '19:00', '20:00', '21:00', '22:00', '23:00', '0:00'],\n",
            "      dtype='object')\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "i7DnCIAaM_lq"
      },
      "source": [
        "temp=pd.DataFrame(columns=['발전량'])"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "iCbGuA5oKX46"
      },
      "source": [
        "t={}"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vsPgEOdzL63t",
        "outputId": "0a722ead-28ce-4540-baae-60d860a9b10b",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "print(tempGNT['0:00']['2019-07-01'])"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "0\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DY2K5OagIB8A"
      },
      "source": [
        "for date in tempGNT.index:\n",
        "  for hour in tempGNT.columns:\n",
        "    t[date+' '+hour]=tempGNT[hour][date]"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9jwM6hWaN-lu",
        "outputId": "e90c4ab0-3a10-4989-8ddc-aef8f078f578",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "print(t.values())"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "dict_values([0, 0, 0, 0, 0, 360, 6000, 92880, 244560, 357480, 464880, 720840, 744000, 532200, 462240, 433200, 348120, 336720, 109920, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 120, 81720, 313800, 625680, 831360, 1062240, 861240, 849600, 785280, 915960, 843240, 565320, 178080, 115800, 6720, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 54480, 219720, 320400, 602400, 805440, 917280, 815760, 569520, 613080, 726480, 510120, 313440, 68400, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 120, 65160, 310560, 623400, 877440, 1044240, 1170240, 1202400, 1159920, 1071600, 680280, 467640, 267000, 130560, 2760, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 57120, 310320, 520320, 847800, 1031760, 1145280, 1186680, 1146360, 970200, 664920, 506520, 304200, 64560, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 120, 56880, 299280, 612240, 883320, 1074720, 1195320, 1219560, 1181520, 1073400, 874560, 622440, 308400, 60600, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 960, 85200, 246720, 429960, 864720, 880440, 881760, 894960, 1055400, 954720, 766680, 402480, 214440, 43920, 0, 0, 0, 0, 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          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "akNtoFUpMUAR"
      },
      "source": [
        "temp=pd.DataFrame(t.values(), index=t.keys())"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "p2a5g_jRMqwy",
        "outputId": "dccec0e2-884a-43c9-b294-4933a6b5de1e",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "print(temp)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "                  0\n",
            "2019-07-01 1:00   0\n",
            "2019-07-01 2:00   0\n",
            "2019-07-01 3:00   0\n",
            "2019-07-01 4:00   0\n",
            "2019-07-01 5:00   0\n",
            "...              ..\n",
            "2020-06-30 20:00  0\n",
            "2020-06-30 21:00  0\n",
            "2020-06-30 22:00  0\n",
            "2020-06-30 23:00  0\n",
            "2020-06-30 0:00   0\n",
            "\n",
            "[8784 rows x 1 columns]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "yv-wtS5tNLNv",
        "outputId": "351f0e0c-3e97-4e4a-a982-3571c0a64e07",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 235
        }
      },
      "source": [
        "temp.columns=['발전량']\n",
        "temp.index.names=['일자']\n",
        "temp.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>발전량</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>일자</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2019-07-01 1:00</th>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-07-01 2:00</th>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-07-01 3:00</th>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-07-01 4:00</th>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-07-01 5:00</th>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                 발전량\n",
              "일자                  \n",
              "2019-07-01 1:00    0\n",
              "2019-07-01 2:00    0\n",
              "2019-07-01 3:00    0\n",
              "2019-07-01 4:00    0\n",
              "2019-07-01 5:00    0"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 57
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "sYP_krzqQ7OS"
      },
      "source": [
        "def min_max_normalize(lst):\n",
        "  normalize = []\n",
        "\n",
        "  for value in lst:\n",
        "    normalized_num=(value - min(lst))/(max(lst)-min(lst))\n",
        "    normalize.append(normalized_num)\n",
        "\n",
        "  return normalize"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "nRTowLdHWfHp",
        "outputId": "15589397-2570-437f-e421-b1f5c9e8a8b1",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 343
        }
      },
      "source": [
        "wtData['발전량']=0\n",
        "wtData.head()"
      ],
      "execution_count": 61,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:1: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \"\"\"Entry point for launching an IPython kernel.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "execute_result",
          "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>기온(°C)</th>\n",
              "      <th>강수량(mm)</th>\n",
              "      <th>습도(%)</th>\n",
              "      <th>현지기압(hPa)</th>\n",
              "      <th>지면온도(°C)</th>\n",
              "      <th>발전량</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>일시</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2019-07-01 1:00</th>\n",
              "      <td>22.2</td>\n",
              "      <td>NaN</td>\n",
              "      <td>90</td>\n",
              "      <td>993.5</td>\n",
              "      <td>22.0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-07-01 2:00</th>\n",
              "      <td>22.4</td>\n",
              "      <td>NaN</td>\n",
              "      <td>89</td>\n",
              "      <td>993.4</td>\n",
              "      <td>22.2</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-07-01 3:00</th>\n",
              "      <td>22.3</td>\n",
              "      <td>NaN</td>\n",
              "      <td>90</td>\n",
              "      <td>993.4</td>\n",
              "      <td>22.1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-07-01 4:00</th>\n",
              "      <td>21.9</td>\n",
              "      <td>NaN</td>\n",
              "      <td>91</td>\n",
              "      <td>993.4</td>\n",
              "      <td>21.4</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-07-01 5:00</th>\n",
              "      <td>21.8</td>\n",
              "      <td>NaN</td>\n",
              "      <td>91</td>\n",
              "      <td>993.9</td>\n",
              "      <td>21.2</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                 기온(°C)  강수량(mm)  습도(%)  현지기압(hPa)  지면온도(°C)  발전량\n",
              "일시                                                               \n",
              "2019-07-01 1:00    22.2      NaN     90      993.5      22.0    0\n",
              "2019-07-01 2:00    22.4      NaN     89      993.4      22.2    0\n",
              "2019-07-01 3:00    22.3      NaN     90      993.4      22.1    0\n",
              "2019-07-01 4:00    21.9      NaN     91      993.4      21.4    0\n",
              "2019-07-01 5:00    21.8      NaN     91      993.9      21.2    0"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 61
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xAfRDfGsS5Gh",
        "outputId": "d7433755-bf6e-4e49-d0b8-cf99339883bf",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "for date1 in wtData.index:\n",
        "  for date2 in temp.index:\n",
        "    if date1==date2:\n",
        "      wtData['발전량'][date1]=temp['발전량'][date2]"
      ],
      "execution_count": 62,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:4: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  after removing the cwd from sys.path.\n",
            "/usr/local/lib/python3.6/dist-packages/IPython/core/interactiveshell.py:2882: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  exec(code_obj, self.user_global_ns, self.user_ns)\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QcgiXXo0XJfY",
        "outputId": "3910dc06-297d-4caf-d18a-a0a0c9f30377",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 235
        }
      },
      "source": [
        "wtData.head()"
      ],
      "execution_count": 63,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>기온(°C)</th>\n",
              "      <th>강수량(mm)</th>\n",
              "      <th>습도(%)</th>\n",
              "      <th>현지기압(hPa)</th>\n",
              "      <th>지면온도(°C)</th>\n",
              "      <th>발전량</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>일시</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2019-07-01 1:00</th>\n",
              "      <td>22.2</td>\n",
              "      <td>NaN</td>\n",
              "      <td>90</td>\n",
              "      <td>993.5</td>\n",
              "      <td>22.0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-07-01 2:00</th>\n",
              "      <td>22.4</td>\n",
              "      <td>NaN</td>\n",
              "      <td>89</td>\n",
              "      <td>993.4</td>\n",
              "      <td>22.2</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-07-01 3:00</th>\n",
              "      <td>22.3</td>\n",
              "      <td>NaN</td>\n",
              "      <td>90</td>\n",
              "      <td>993.4</td>\n",
              "      <td>22.1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-07-01 4:00</th>\n",
              "      <td>21.9</td>\n",
              "      <td>NaN</td>\n",
              "      <td>91</td>\n",
              "      <td>993.4</td>\n",
              "      <td>21.4</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-07-01 5:00</th>\n",
              "      <td>21.8</td>\n",
              "      <td>NaN</td>\n",
              "      <td>91</td>\n",
              "      <td>993.9</td>\n",
              "      <td>21.2</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                 기온(°C)  강수량(mm)  습도(%)  현지기압(hPa)  지면온도(°C)  발전량\n",
              "일시                                                               \n",
              "2019-07-01 1:00    22.2      NaN     90      993.5      22.0    0\n",
              "2019-07-01 2:00    22.4      NaN     89      993.4      22.2    0\n",
              "2019-07-01 3:00    22.3      NaN     90      993.4      22.1    0\n",
              "2019-07-01 4:00    21.9      NaN     91      993.4      21.4    0\n",
              "2019-07-01 5:00    21.8      NaN     91      993.9      21.2    0"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 63
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "p27JCDz8XRaA"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}