Multivariate_Time_Series_using_VAR.ipynb

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      "name": "Multivariate Time Series using VAR.ipynb",
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    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
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      "source": [
        "<a href=\"https://colab.research.google.com/github/srivatsan88/End-to-End-Time-Series/blob/master/Multivariate_Time_Series_using_VAR.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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    },
    {
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      "metadata": {
        "id": "A8edhGvXoqdT",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "b0262715-4541-4422-a385-0443ee19d8fa"
      },
      "source": [
        "import pandas as pd\n",
        "import matplotlib as mpl\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "import numpy as np\n",
        "\n",
        "from statsmodels.tsa.stattools import grangercausalitytests\n",
        "from statsmodels.tsa.stattools import adfuller\n",
        "import statsmodels.api as sm\n",
        "from statsmodels.tsa.api import VAR\n",
        "\n",
        "mpl.rcParams['figure.figsize'] = (10, 8)\n",
        "mpl.rcParams['axes.grid'] = False"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/statsmodels/tools/_testing.py:19: FutureWarning: pandas.util.testing is deprecated. Use the functions in the public API at pandas.testing instead.\n",
            "  import pandas.util.testing as tm\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ret6bTxmoxfj"
      },
      "source": [
        "df=pd.read_csv('https://raw.githubusercontent.com/srivatsan88/YouTubeLI/master/dataset/appliance_energy_usage.csv', index_col=0, parse_dates=True)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
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          "base_uri": "https://localhost:8080/",
          "height": 447
        },
        "outputId": "a72419d9-0902-484f-f5e3-014627923fe6"
      },
      "source": [
        "df"
      ],
      "execution_count": null,
      "outputs": [
        {
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              "                     Appliances  lights  ...  Tdewpoint  Visibility\n",
              "date                                     ...                       \n",
              "2016-01-11 17:00:00          60      30  ...   5.300000   63.000000\n",
              "2016-01-11 17:10:00          60      30  ...   5.200000   59.166667\n",
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              "2016-01-11 17:40:00          60      40  ...   4.900000   47.666667\n",
              "...                         ...     ...  ...        ...         ...\n",
              "2016-05-27 17:20:00         100       0  ...  13.333333   23.666667\n",
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              "2016-05-27 17:40:00         270      10  ...  13.266667   25.333333\n",
              "2016-05-27 17:50:00         420      10  ...  13.233333   26.166667\n",
              "2016-05-27 18:00:00         430      10  ...  13.200000   27.000000\n",
              "\n",
              "[19735 rows x 8 columns]"
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      "source": [
        "df=df.resample('1H').mean()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
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      "source": [
        "df"
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      "outputs": [
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              "                     Appliances     lights  ...  Tdewpoint  Visibility\n",
              "date                                        ...                       \n",
              "2016-01-11 17:00:00   55.000000  35.000000  ...   5.050000   53.416667\n",
              "2016-01-11 18:00:00  176.666667  51.666667  ...   4.658333   40.000000\n",
              "2016-01-11 19:00:00  173.333333  25.000000  ...   4.391667   40.000000\n",
              "2016-01-11 20:00:00  125.000000  35.000000  ...   4.016667   40.000000\n",
              "2016-01-11 21:00:00  103.333333  23.333333  ...   3.816667   40.000000\n",
              "...                         ...        ...  ...        ...         ...\n",
              "2016-05-27 14:00:00  101.666667   1.666667  ...  13.475000   21.583333\n",
              "2016-05-27 15:00:00   76.666667   0.000000  ...  13.258333   21.833333\n",
              "2016-05-27 16:00:00  135.000000   0.000000  ...  13.283333   22.583333\n",
              "2016-05-27 17:00:00  180.000000   3.333333  ...  13.316667   24.083333\n",
              "2016-05-27 18:00:00  430.000000  10.000000  ...  13.200000   27.000000\n",
              "\n",
              "[3290 rows x 8 columns]"
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          },
          "metadata": {
            "tags": []
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          "execution_count": 5
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    {
      "cell_type": "code",
      "metadata": {
        "id": "c-KGo1_3YsVd",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "c740c93e-4d4b-4d66-ec58-8efa27932aac"
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      "source": [
        "color_list = [\n",
        "    \"blue\",\n",
        "    \"orange\",\n",
        "    \"green\",\n",
        "    \"red\",\n",
        "    \"purple\",\n",
        "    \"brown\",\n",
        "    \"pink\",\n",
        "    \"gray\",\n",
        "    \"olive\",\n",
        "    \"cyan\",\n",
        "]\n",
        "\n",
        "\n",
        "def Visualize(data):\n",
        "    features= list(df.select_dtypes(include=[np.number]).columns.values)\n",
        "    feature_size=len(features)\n",
        "    fig, axes = plt.subplots(\n",
        "        nrows=int(np.ceil(feature_size/2)), ncols=2, figsize=(14, feature_size*2), dpi=80, facecolor=\"w\", edgecolor=\"k\"\n",
        "    )\n",
        "    for i in range(feature_size):\n",
        "        key = features[i]\n",
        "        c = color_list[i % (len(color_list))]\n",
        "        t_data = data[key]\n",
        "        t_data.head()\n",
        "        ax = t_data.plot(\n",
        "            ax=axes[i // 2, i % 2],\n",
        "            color=c,\n",
        "            title=\"{}\".format(key),\n",
        "            rot=25,\n",
        "        )\n",
        "        ax.legend([key])\n",
        "    plt.tight_layout()\n",
        "\n",
        "\n",
        "Visualize(df)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1120x1280 with 8 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "gU3OKJn6SodQ"
      },
      "source": [
        "Null Hypothesis - Series possesses a unit root and hence is not stationary\n",
        "\n",
        "Alternate Hypothesis - Series is stationary"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "sUsrIiCfOKty",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "c9e09c40-887d-4a32-c9ba-e192d1d06fdd"
      },
      "source": [
        "for i in range(len(df.columns)):\n",
        "  result = adfuller(df[df.columns[i]])\n",
        "\n",
        "  if result[1] > 0.05 :\n",
        "    print('{} - Series is not Stationary'.format(df.columns[i]))\n",
        "  else:\n",
        "    print('{} - Series is Stationary'.format(df.columns[i]))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Appliances - Series is Stationary\n",
            "lights - Series is Stationary\n",
            "T_out - Series is Stationary\n",
            "Press_mm_hg - Series is Stationary\n",
            "RH_out - Series is Stationary\n",
            "Windspeed - Series is Stationary\n",
            "Tdewpoint - Series is Stationary\n",
            "Visibility - Series is Stationary\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "UkaMJYpO1TNO"
      },
      "source": [
        " H0: Xt does not granger causes Yt\n",
        " \n",
        " H1: Xt granger causes Yt"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1GC9090oFc-l"
      },
      "source": [
        "max_lags=8\n",
        "y='Appliances'"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0v246-Mi67d_",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "988c76d8-da28-4eb4-a921-a12a24314f90"
      },
      "source": [
        "for i in range(len(df.columns)-1):\n",
        "  results=grangercausalitytests(df[[y,df.columns[i+1]]], max_lags, verbose=False)\n",
        "  p_values=[round(results[i+1][0]['ssr_ftest'][1],4) for i in range(max_lags)]\n",
        "  print('Column - {} : P_Values - {}'.format(df.columns[i+1],p_values))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Column - lights : P_Values - [0.1451, 0.0005, 0.0001, 0.0002, 0.0001, 0.0001, 0.0006, 0.0012]\n",
            "Column - T_out : P_Values - [0.002, 0.0001, 0.0001, 0.0, 0.0, 0.0, 0.0, 0.0]\n",
            "Column - Press_mm_hg : P_Values - [0.0985, 0.1956, 0.0351, 0.0016, 0.0, 0.0001, 0.0, 0.0]\n",
            "Column - RH_out : P_Values - [0.0, 0.0004, 0.0004, 0.0, 0.0, 0.0, 0.0, 0.0]\n",
            "Column - Windspeed : P_Values - [0.0004, 0.0041, 0.0094, 0.0082, 0.0163, 0.0119, 0.0009, 0.0002]\n",
            "Column - Tdewpoint : P_Values - [0.4348, 0.4494, 0.5005, 0.3887, 0.05, 0.0694, 0.0992, 0.1152]\n",
            "Column - Visibility : P_Values - [0.7071, 0.5372, 0.7338, 0.8265, 0.544, 0.3324, 0.2521, 0.3465]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ccsOCsmY_lJh"
      },
      "source": [
        "df_input=df[['Appliances','T_out','Windspeed']]"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mM64CwUk_lCB",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 447
        },
        "outputId": "a6d4c1cb-10f3-45c7-eb7d-bfc47c4e543c"
      },
      "source": [
        "df_input"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Appliances</th>\n",
              "      <th>T_out</th>\n",
              "      <th>Windspeed</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>date</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2016-01-11 17:00:00</th>\n",
              "      <td>55.000000</td>\n",
              "      <td>6.308333</td>\n",
              "      <td>6.166667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-01-11 18:00:00</th>\n",
              "      <td>176.666667</td>\n",
              "      <td>5.941667</td>\n",
              "      <td>5.416667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-01-11 19:00:00</th>\n",
              "      <td>173.333333</td>\n",
              "      <td>6.000000</td>\n",
              "      <td>6.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-01-11 20:00:00</th>\n",
              "      <td>125.000000</td>\n",
              "      <td>6.000000</td>\n",
              "      <td>6.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-01-11 21:00:00</th>\n",
              "      <td>103.333333</td>\n",
              "      <td>5.833333</td>\n",
              "      <td>6.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-05-27 14:00:00</th>\n",
              "      <td>101.666667</td>\n",
              "      <td>21.916667</td>\n",
              "      <td>2.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-05-27 15:00:00</th>\n",
              "      <td>76.666667</td>\n",
              "      <td>22.216667</td>\n",
              "      <td>2.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-05-27 16:00:00</th>\n",
              "      <td>135.000000</td>\n",
              "      <td>22.883333</td>\n",
              "      <td>2.416667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-05-27 17:00:00</th>\n",
              "      <td>180.000000</td>\n",
              "      <td>22.666667</td>\n",
              "      <td>3.416667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-05-27 18:00:00</th>\n",
              "      <td>430.000000</td>\n",
              "      <td>22.200000</td>\n",
              "      <td>4.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>3290 rows × 3 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                     Appliances      T_out  Windspeed\n",
              "date                                                 \n",
              "2016-01-11 17:00:00   55.000000   6.308333   6.166667\n",
              "2016-01-11 18:00:00  176.666667   5.941667   5.416667\n",
              "2016-01-11 19:00:00  173.333333   6.000000   6.000000\n",
              "2016-01-11 20:00:00  125.000000   6.000000   6.000000\n",
              "2016-01-11 21:00:00  103.333333   5.833333   6.000000\n",
              "...                         ...        ...        ...\n",
              "2016-05-27 14:00:00  101.666667  21.916667   2.000000\n",
              "2016-05-27 15:00:00   76.666667  22.216667   2.000000\n",
              "2016-05-27 16:00:00  135.000000  22.883333   2.416667\n",
              "2016-05-27 17:00:00  180.000000  22.666667   3.416667\n",
              "2016-05-27 18:00:00  430.000000  22.200000   4.000000\n",
              "\n",
              "[3290 rows x 3 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zflJjxO9_k4H"
      },
      "source": [
        "df_train = df_input[:int(0.9*(len(df_input)))]\n",
        "df_test = df_input[int(0.9*(len(df_input))):]"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "kObZX1w8AaOb",
        "outputId": "22007c59-82f1-4f60-89eb-32283e849310"
      },
      "source": [
        "df_train.shape"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(2961, 3)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "tsno9RVDAUjs",
        "outputId": "75e3f685-8edd-4cbb-ccd1-803f64969fda"
      },
      "source": [
        "df_test.shape"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(329, 3)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mLmRHWJ4eO7C"
      },
      "source": [
        "![link text](https://wikimedia.org/api/rest_v1/media/math/render/svg/d79bead4e9192d7fe2470a7936e4623e9ff252e1)\n",
        "\n",
        "![link text](https://wikimedia.org/api/rest_v1/media/math/render/svg/d88ac4002c0641b2e93fb6d35f961ea63352b6a9)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZMKkIsDmBUrx",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "b8176cbb-74b1-4d5a-a1cf-0e5238008fb2"
      },
      "source": [
        "model = VAR(df_train, freq=\"1H\")\n",
        "for i in range(48):\n",
        "    results = model.fit(i+1)\n",
        "    print('Order = ', i+1)\n",
        "    print('AIC: ', results.aic)\n",
        "    print('BIC: ', results.bic)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Order =  1\n",
            "AIC:  7.126785098024289\n",
            "BIC:  7.151080819162065\n",
            "Order =  2\n",
            "AIC:  6.13876916892782\n",
            "BIC:  6.181298651759994\n",
            "Order =  3\n",
            "AIC:  6.019982255185912\n",
            "BIC:  6.0807557708377455\n",
            "Order =  4\n",
            "AIC:  5.960526790759722\n",
            "BIC:  6.03955461973309\n",
            "Order =  5\n",
            "AIC:  5.908069667837071\n",
            "BIC:  6.005362100022209\n",
            "Order =  6\n",
            "AIC:  5.891197292905782\n",
            "BIC:  6.006764627593054\n",
            "Order =  7\n",
            "AIC:  5.852250355011839\n",
            "BIC:  5.986102900903521\n",
            "Order =  8\n",
            "AIC:  5.841915871050664\n",
            "BIC:  5.994063946272741\n",
            "Order =  9\n",
            "AIC:  5.827889041110311\n",
            "BIC:  5.998342973224305\n",
            "Order =  10\n",
            "AIC:  5.825120732509795\n",
            "BIC:  6.013890858524602\n",
            "Order =  11\n",
            "AIC:  5.791083147024334\n",
            "BIC:  5.998179813408081\n",
            "Order =  12\n",
            "AIC:  5.78322849534456\n",
            "BIC:  6.008662058036488\n",
            "Order =  13\n",
            "AIC:  5.764122425516565\n",
            "BIC:  6.007903249938921\n",
            "Order =  14\n",
            "AIC:  5.754516806234101\n",
            "BIC:  6.016655267304057\n",
            "Order =  15\n",
            "AIC:  5.745057263179904\n",
            "BIC:  6.025563745321491\n",
            "Order =  16\n",
            "AIC:  5.734159567395153\n",
            "BIC:  6.033044464551212\n",
            "Order =  17\n",
            "AIC:  5.734437324119505\n",
            "BIC:  6.051711039763665\n",
            "Order =  18\n",
            "AIC:  5.727535892320577\n",
            "BIC:  6.063208839469243\n",
            "Order =  19\n",
            "AIC:  5.718040422951478\n",
            "BIC:  6.072123024175842\n",
            "Order =  20\n",
            "AIC:  5.719535954093963\n",
            "BIC:  6.0920386415320396\n",
            "Order =  21\n",
            "AIC:  5.722525512492248\n",
            "BIC:  6.113458727860916\n",
            "Order =  22\n",
            "AIC:  5.719011568286695\n",
            "BIC:  6.128385762893774\n",
            "Order =  23\n",
            "AIC:  5.683257270961978\n",
            "BIC:  6.111082905718311\n",
            "Order =  24\n",
            "AIC:  5.669514653667391\n",
            "BIC:  6.115802199098953\n",
            "Order =  25\n",
            "AIC:  5.655808323518035\n",
            "BIC:  6.1205682597780635\n",
            "Order =  26\n",
            "AIC:  5.64939288890614\n",
            "BIC:  6.132635705787279\n",
            "Order =  27\n",
            "AIC:  5.651075212992242\n",
            "BIC:  6.152811409938704\n",
            "Order =  28\n",
            "AIC:  5.65066984090543\n",
            "BIC:  6.170909927025189\n",
            "Order =  29\n",
            "AIC:  5.653956702770681\n",
            "BIC:  6.192711196847668\n",
            "Order =  30\n",
            "AIC:  5.655668951805995\n",
            "BIC:  6.212948382312332\n",
            "Order =  31\n",
            "AIC:  5.659937876803568\n",
            "BIC:  6.235752781911804\n",
            "Order =  32\n",
            "AIC:  5.662846403783327\n",
            "BIC:  6.257207331378708\n",
            "Order =  33\n",
            "AIC:  5.667486003112628\n",
            "BIC:  6.280403510805374\n",
            "Order =  34\n",
            "AIC:  5.671153194283653\n",
            "BIC:  6.302637849421266\n",
            "Order =  35\n",
            "AIC:  5.6759528026859885\n",
            "BIC:  6.3260151823655715\n",
            "Order =  36\n",
            "AIC:  5.675885857212917\n",
            "BIC:  6.344536548293521\n",
            "Order =  37\n",
            "AIC:  5.678621402950432\n",
            "BIC:  6.365871002065415\n",
            "Order =  38\n",
            "AIC:  5.682019346497948\n",
            "BIC:  6.3878784600673555\n",
            "Order =  39\n",
            "AIC:  5.686659110233012\n",
            "BIC:  6.411138354475985\n",
            "Order =  40\n",
            "AIC:  5.690122942935505\n",
            "BIC:  6.433232943882698\n",
            "Order =  41\n",
            "AIC:  5.693432426703917\n",
            "BIC:  6.455183820209939\n",
            "Order =  42\n",
            "AIC:  5.695957820037172\n",
            "BIC:  6.476361251793054\n",
            "Order =  43\n",
            "AIC:  5.700324426427202\n",
            "BIC:  6.499390551972873\n",
            "Order =  44\n",
            "AIC:  5.702238759433133\n",
            "BIC:  6.519978244169924\n",
            "Order =  45\n",
            "AIC:  5.70534531946816\n",
            "BIC:  6.541768838671331\n",
            "Order =  46\n",
            "AIC:  5.707954489202293\n",
            "BIC:  6.563072728033571\n",
            "Order =  47\n",
            "AIC:  5.69976008667805\n",
            "BIC:  6.573583740198192\n",
            "Order =  48\n",
            "AIC:  5.698390341067919\n",
            "BIC:  6.590930114249296\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "M89Cq70uOMGv",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "b992503d-6ab7-48ba-ea6b-1117bb01ebd0"
      },
      "source": [
        "model.select_order(48).summary()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<table class=\"simpletable\">\n",
              "<caption>VAR Order Selection (* highlights the minimums)</caption>\n",
              "<tr>\n",
              "   <td></td>      <th>AIC</th>         <th>BIC</th>         <th>FPE</th>        <th>HQIC</th>    \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>0</th>  <td>     13.82</td>  <td>     13.83</td>  <td> 1.005e+06</td>  <td>     13.82</td> \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>1</th>  <td>     7.139</td>  <td>     7.163</td>  <td>     1260.</td>  <td>     7.148</td> \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>2</th>  <td>     6.149</td>  <td>     6.192</td>  <td>     468.3</td>  <td>     6.165</td> \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>3</th>  <td>     6.031</td>  <td>     6.093</td>  <td>     416.2</td>  <td>     6.053</td> \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>4</th>  <td>     5.970</td>  <td>     6.050</td>  <td>     391.7</td>  <td>     5.999</td> \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>5</th>  <td>     5.917</td>  <td>     6.015</td>  <td>     371.3</td>  <td>     5.952</td> \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>6</th>  <td>     5.902</td>  <td>     6.019</td>  <td>     365.7</td>  <td>     5.944</td> \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>7</th>  <td>     5.863</td>  <td>     5.999*</td> <td>     351.9</td>  <td>     5.912</td> \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>8</th>  <td>     5.852</td>  <td>     6.006</td>  <td>     348.1</td>  <td>     5.908</td> \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>9</th>  <td>     5.837</td>  <td>     6.010</td>  <td>     342.9</td>  <td>     5.900</td> \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>10</th> <td>     5.835</td>  <td>     6.026</td>  <td>     342.2</td>  <td>     5.904</td> \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>11</th> <td>     5.801</td>  <td>     6.010</td>  <td>     330.5</td>  <td>     5.876</td> \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>12</th> <td>     5.791</td>  <td>     6.019</td>  <td>     327.5</td>  <td>     5.874</td> \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>13</th> <td>     5.772</td>  <td>     6.018</td>  <td>     321.2</td>  <td>     5.861</td> \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>14</th> <td>     5.761</td>  <td>     6.026</td>  <td>     317.8</td>  <td>     5.857</td> \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>15</th> <td>     5.751</td>  <td>     6.034</td>  <td>     314.5</td>  <td>     5.853</td> \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>16</th> <td>     5.739</td>  <td>     6.041</td>  <td>     310.8</td>  <td>     5.848</td> \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>17</th> <td>     5.739</td>  <td>     6.059</td>  <td>     310.6</td>  <td>     5.854</td> \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>18</th> <td>     5.733</td>  <td>     6.072</td>  <td>     309.0</td>  <td>     5.855</td> \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>19</th> <td>     5.724</td>  <td>     6.081</td>  <td>     306.3</td>  <td>     5.853</td> \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>20</th> <td>     5.726</td>  <td>     6.101</td>  <td>     306.7</td>  <td>     5.861</td> \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>21</th> <td>     5.728</td>  <td>     6.122</td>  <td>     307.3</td>  <td>     5.870</td> \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>22</th> <td>     5.724</td>  <td>     6.136</td>  <td>     306.1</td>  <td>     5.872</td> \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>23</th> <td>     5.691</td>  <td>     6.121</td>  <td>     296.1</td>  <td>     5.846</td> \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>24</th> <td>     5.677</td>  <td>     6.126</td>  <td>     292.1</td>  <td>     5.839</td> \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>25</th> <td>     5.666</td>  <td>     6.134</td>  <td>     288.8</td>  <td>     5.834*</td>\n",
              "</tr>\n",
              "<tr>\n",
              "  <th>26</th> <td>     5.660*</td> <td>     6.146</td>  <td>     287.2*</td> <td>     5.835</td> \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>27</th> <td>     5.661</td>  <td>     6.166</td>  <td>     287.6</td>  <td>     5.843</td> \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>28</th> <td>     5.660</td>  <td>     6.183</td>  <td>     287.2</td>  <td>     5.849</td> \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>29</th> <td>     5.663</td>  <td>     6.205</td>  <td>     288.0</td>  <td>     5.858</td> \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>30</th> <td>     5.664</td>  <td>     6.224</td>  <td>     288.2</td>  <td>     5.865</td> \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>31</th> <td>     5.667</td>  <td>     6.246</td>  <td>     289.2</td>  <td>     5.876</td> \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>32</th> <td>     5.671</td>  <td>     6.268</td>  <td>     290.3</td>  <td>     5.886</td> \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>33</th> <td>     5.675</td>  <td>     6.290</td>  <td>     291.4</td>  <td>     5.896</td> \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>34</th> <td>     5.678</td>  <td>     6.312</td>  <td>     292.3</td>  <td>     5.906</td> \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>35</th> <td>     5.682</td>  <td>     6.334</td>  <td>     293.4</td>  <td>     5.917</td> \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>36</th> <td>     5.681</td>  <td>     6.352</td>  <td>     293.2</td>  <td>     5.923</td> \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>37</th> <td>     5.683</td>  <td>     6.372</td>  <td>     293.7</td>  <td>     5.931</td> \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>38</th> <td>     5.685</td>  <td>     6.393</td>  <td>     294.5</td>  <td>     5.940</td> \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>39</th> <td>     5.689</td>  <td>     6.416</td>  <td>     295.7</td>  <td>     5.951</td> \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>40</th> <td>     5.694</td>  <td>     6.439</td>  <td>     297.1</td>  <td>     5.962</td> \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>41</th> <td>     5.697</td>  <td>     6.460</td>  <td>     297.9</td>  <td>     5.972</td> \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>42</th> <td>     5.699</td>  <td>     6.481</td>  <td>     298.7</td>  <td>     5.981</td> \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>43</th> <td>     5.703</td>  <td>     6.503</td>  <td>     299.8</td>  <td>     5.991</td> \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>44</th> <td>     5.704</td>  <td>     6.523</td>  <td>     300.1</td>  <td>     5.999</td> \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>45</th> <td>     5.707</td>  <td>     6.544</td>  <td>     301.0</td>  <td>     6.008</td> \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>46</th> <td>     5.709</td>  <td>     6.564</td>  <td>     301.6</td>  <td>     6.017</td> \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>47</th> <td>     5.700</td>  <td>     6.574</td>  <td>     299.0</td>  <td>     6.015</td> \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>48</th> <td>     5.698</td>  <td>     6.591</td>  <td>     298.5</td>  <td>     6.020</td> \n",
              "</tr>\n",
              "</table>"
            ],
            "text/plain": [
              "<class 'statsmodels.iolib.table.SimpleTable'>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TCmSUixyB45K"
      },
      "source": [
        "model = VAR(df_train, freq=\"1H\")\n",
        "results = model.fit(7)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Mt__k6JGEWKt",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "6686c5bf-7772-40e1-81a6-fb222d334f21"
      },
      "source": [
        "print(results.summary())"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "  Summary of Regression Results   \n",
            "==================================\n",
            "Model:                         VAR\n",
            "Method:                        OLS\n",
            "Date:           Tue, 22, Dec, 2020\n",
            "Time:                     02:27:32\n",
            "--------------------------------------------------------------------\n",
            "No. of Equations:         3.00000    BIC:                    5.98610\n",
            "Nobs:                     2954.00    HQIC:                   5.90043\n",
            "Log likelihood:          -21152.4    FPE:                    348.017\n",
            "AIC:                      5.85225    Det(Omega_mle):         340.356\n",
            "--------------------------------------------------------------------\n",
            "Results for equation Appliances\n",
            "================================================================================\n",
            "                   coefficient       std. error           t-stat            prob\n",
            "--------------------------------------------------------------------------------\n",
            "const                37.865935         3.448219           10.981           0.000\n",
            "L1.Appliances         0.451436         0.018470           24.442           0.000\n",
            "L1.T_out              2.328238         2.534185            0.919           0.358\n",
            "L1.Windspeed          2.268735         1.999042            1.135           0.256\n",
            "L2.Appliances         0.222279         0.020225           10.990           0.000\n",
            "L2.T_out             -4.372626         5.543555           -0.789           0.430\n",
            "L2.Windspeed         -1.481847         3.372020           -0.439           0.660\n",
            "L3.Appliances        -0.019489         0.020657           -0.943           0.345\n",
            "L3.T_out              5.606923         6.595733            0.850           0.395\n",
            "L3.Windspeed          0.184615         3.671449            0.050           0.960\n",
            "L4.Appliances        -0.043691         0.020657           -2.115           0.034\n",
            "L4.T_out             -5.435304         6.756484           -0.804           0.421\n",
            "L4.Windspeed         -0.086856         3.777195           -0.023           0.982\n",
            "L5.Appliances         0.007386         0.020673            0.357           0.721\n",
            "L5.T_out              5.171913         6.600647            0.784           0.433\n",
            "L5.Windspeed         -1.990310         3.671521           -0.542           0.588\n",
            "L6.Appliances        -0.016838         0.020263           -0.831           0.406\n",
            "L6.T_out              3.227034         5.582566            0.578           0.563\n",
            "L6.Windspeed          4.971647         3.365821            1.477           0.140\n",
            "L7.Appliances        -0.010919         0.018518           -0.590           0.555\n",
            "L7.T_out             -6.777338         2.558105           -2.649           0.008\n",
            "L7.Windspeed         -2.972593         1.993290           -1.491           0.136\n",
            "================================================================================\n",
            "\n",
            "Results for equation T_out\n",
            "================================================================================\n",
            "                   coefficient       std. error           t-stat            prob\n",
            "--------------------------------------------------------------------------------\n",
            "const                 0.231136         0.025269            9.147           0.000\n",
            "L1.Appliances         0.000246         0.000135            1.820           0.069\n",
            "L1.T_out              1.986331         0.018571          106.959           0.000\n",
            "L1.Windspeed         -0.022509         0.014649           -1.537           0.124\n",
            "L2.Appliances        -0.000193         0.000148           -1.305           0.192\n",
            "L2.T_out             -1.522224         0.040624          -37.471           0.000\n",
            "L2.Windspeed          0.037810         0.024711            1.530           0.126\n",
            "L3.Appliances        -0.000273         0.000151           -1.804           0.071\n",
            "L3.T_out              0.961124         0.048335           19.885           0.000\n",
            "L3.Windspeed         -0.042122         0.026905           -1.566           0.117\n",
            "L4.Appliances         0.000028         0.000151            0.187           0.852\n",
            "L4.T_out             -0.771764         0.049513          -15.587           0.000\n",
            "L4.Windspeed          0.034870         0.027680            1.260           0.208\n",
            "L5.Appliances        -0.000224         0.000151           -1.481           0.139\n",
            "L5.T_out              0.570844         0.048371           11.801           0.000\n",
            "L5.Windspeed         -0.012856         0.026905           -0.478           0.633\n",
            "L6.Appliances        -0.000184         0.000148           -1.239           0.215\n",
            "L6.T_out             -0.408795         0.040910           -9.993           0.000\n",
            "L6.Windspeed          0.032718         0.024665            1.326           0.185\n",
            "L7.Appliances        -0.000418         0.000136           -3.080           0.002\n",
            "L7.T_out              0.171528         0.018746            9.150           0.000\n",
            "L7.Windspeed         -0.038363         0.014607           -2.626           0.009\n",
            "================================================================================\n",
            "\n",
            "Results for equation Windspeed\n",
            "================================================================================\n",
            "                   coefficient       std. error           t-stat            prob\n",
            "--------------------------------------------------------------------------------\n",
            "const                 0.213512         0.032405            6.589           0.000\n",
            "L1.Appliances        -0.000340         0.000174           -1.957           0.050\n",
            "L1.T_out              0.251047         0.023815           10.542           0.000\n",
            "L1.Windspeed          1.361232         0.018786           72.460           0.000\n",
            "L2.Appliances         0.000264         0.000190            1.390           0.164\n",
            "L2.T_out             -0.354257         0.052095           -6.800           0.000\n",
            "L2.Windspeed         -0.773838         0.031688          -24.420           0.000\n",
            "L3.Appliances        -0.000321         0.000194           -1.655           0.098\n",
            "L3.T_out              0.178001         0.061983            2.872           0.004\n",
            "L3.Windspeed          0.623610         0.034502           18.074           0.000\n",
            "L4.Appliances         0.000217         0.000194            1.116           0.265\n",
            "L4.T_out             -0.142536         0.063494           -2.245           0.025\n",
            "L4.Windspeed         -0.443014         0.035496          -12.481           0.000\n",
            "L5.Appliances        -0.000298         0.000194           -1.536           0.124\n",
            "L5.T_out              0.056396         0.062029            0.909           0.363\n",
            "L5.Windspeed          0.297190         0.034503            8.613           0.000\n",
            "L6.Appliances         0.000250         0.000190            1.310           0.190\n",
            "L6.T_out              0.032108         0.052462            0.612           0.541\n",
            "L6.Windspeed         -0.170770         0.031630           -5.399           0.000\n",
            "L7.Appliances        -0.000290         0.000174           -1.664           0.096\n",
            "L7.T_out             -0.020804         0.024040           -0.865           0.387\n",
            "L7.Windspeed          0.065985         0.018732            3.523           0.000\n",
            "================================================================================\n",
            "\n",
            "Correlation matrix of residuals\n",
            "              Appliances     T_out  Windspeed\n",
            "Appliances      1.000000  0.081108   0.011828\n",
            "T_out           0.081108  1.000000   0.199185\n",
            "Windspeed       0.011828  0.199185   1.000000\n",
            "\n",
            "\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ybVtC9NtFEHu"
      },
      "source": [
        "lag=results.k_ar"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "I6W7dPfOHWsW",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "ee86e783-1f25-4e58-9067-d0c20adb1f7f"
      },
      "source": [
        "results.forecast(df_train.values[-lag:],steps=5)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[44.34598018,  8.92651619,  3.99333186],\n",
              "       [33.70923187,  8.81719814,  4.13871016],\n",
              "       [38.32344216,  9.01953267,  4.188856  ],\n",
              "       [53.39756915,  9.3356185 ,  4.31429082],\n",
              "       [60.93798924,  9.56974211,  4.40093836]])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "J72s5LjaJLjo",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 233
        },
        "outputId": "42a224bf-9d43-4d08-f58e-f8f92ff38448"
      },
      "source": [
        "df_test[0:5]"
      ],
      "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>Appliances</th>\n",
              "      <th>T_out</th>\n",
              "      <th>Windspeed</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>date</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2016-05-14 02:00:00</th>\n",
              "      <td>60.000000</td>\n",
              "      <td>8.891667</td>\n",
              "      <td>3.166667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-05-14 03:00:00</th>\n",
              "      <td>60.000000</td>\n",
              "      <td>8.725000</td>\n",
              "      <td>2.833333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-05-14 04:00:00</th>\n",
              "      <td>60.000000</td>\n",
              "      <td>8.775000</td>\n",
              "      <td>4.416667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-05-14 05:00:00</th>\n",
              "      <td>56.666667</td>\n",
              "      <td>8.683333</td>\n",
              "      <td>5.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-05-14 06:00:00</th>\n",
              "      <td>63.333333</td>\n",
              "      <td>8.716667</td>\n",
              "      <td>5.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                     Appliances     T_out  Windspeed\n",
              "date                                                \n",
              "2016-05-14 02:00:00   60.000000  8.891667   3.166667\n",
              "2016-05-14 03:00:00   60.000000  8.725000   2.833333\n",
              "2016-05-14 04:00:00   60.000000  8.775000   4.416667\n",
              "2016-05-14 05:00:00   56.666667  8.683333   5.000000\n",
              "2016-05-14 06:00:00   63.333333  8.716667   5.000000"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "OYRnQZkkTAwI"
      },
      "source": [
        "df_coeff=pd.DataFrame([results.params['Appliances'],results.pvalues['Appliances']]).T"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Embi1JA0TAlU",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 725
        },
        "outputId": "e1429493-8496-4250-c7c3-462062b369c0"
      },
      "source": [
        "df_coeff"
      ],
      "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>Appliances</th>\n",
              "      <th>Appliances</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>const</th>\n",
              "      <td>37.865935</td>\n",
              "      <td>4.701032e-28</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>L1.Appliances</th>\n",
              "      <td>0.451436</td>\n",
              "      <td>6.138160e-132</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>L1.T_out</th>\n",
              "      <td>2.328238</td>\n",
              "      <td>3.582355e-01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>L1.Windspeed</th>\n",
              "      <td>2.268735</td>\n",
              "      <td>2.564126e-01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>L2.Appliances</th>\n",
              "      <td>0.222279</td>\n",
              "      <td>4.255512e-28</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>L2.T_out</th>\n",
              "      <td>-4.372626</td>\n",
              "      <td>4.302427e-01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>L2.Windspeed</th>\n",
              "      <td>-1.481847</td>\n",
              "      <td>6.603327e-01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>L3.Appliances</th>\n",
              "      <td>-0.019489</td>\n",
              "      <td>3.454670e-01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>L3.T_out</th>\n",
              "      <td>5.606923</td>\n",
              "      <td>3.952787e-01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>L3.Windspeed</th>\n",
              "      <td>0.184615</td>\n",
              "      <td>9.598961e-01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>L4.Appliances</th>\n",
              "      <td>-0.043691</td>\n",
              "      <td>3.442733e-02</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>L4.T_out</th>\n",
              "      <td>-5.435304</td>\n",
              "      <td>4.211329e-01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>L4.Windspeed</th>\n",
              "      <td>-0.086856</td>\n",
              "      <td>9.816543e-01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>L5.Appliances</th>\n",
              "      <td>0.007386</td>\n",
              "      <td>7.208724e-01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>L5.T_out</th>\n",
              "      <td>5.171913</td>\n",
              "      <td>4.333064e-01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>L5.Windspeed</th>\n",
              "      <td>-1.990310</td>\n",
              "      <td>5.877537e-01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>L6.Appliances</th>\n",
              "      <td>-0.016838</td>\n",
              "      <td>4.059770e-01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>L6.T_out</th>\n",
              "      <td>3.227034</td>\n",
              "      <td>5.632265e-01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>L6.Windspeed</th>\n",
              "      <td>4.971647</td>\n",
              "      <td>1.396495e-01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>L7.Appliances</th>\n",
              "      <td>-0.010919</td>\n",
              "      <td>5.554416e-01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>L7.T_out</th>\n",
              "      <td>-6.777338</td>\n",
              "      <td>8.064473e-03</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>L7.Windspeed</th>\n",
              "      <td>-2.972593</td>\n",
              "      <td>1.358828e-01</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "               Appliances     Appliances\n",
              "const           37.865935   4.701032e-28\n",
              "L1.Appliances    0.451436  6.138160e-132\n",
              "L1.T_out         2.328238   3.582355e-01\n",
              "L1.Windspeed     2.268735   2.564126e-01\n",
              "L2.Appliances    0.222279   4.255512e-28\n",
              "L2.T_out        -4.372626   4.302427e-01\n",
              "L2.Windspeed    -1.481847   6.603327e-01\n",
              "L3.Appliances   -0.019489   3.454670e-01\n",
              "L3.T_out         5.606923   3.952787e-01\n",
              "L3.Windspeed     0.184615   9.598961e-01\n",
              "L4.Appliances   -0.043691   3.442733e-02\n",
              "L4.T_out        -5.435304   4.211329e-01\n",
              "L4.Windspeed    -0.086856   9.816543e-01\n",
              "L5.Appliances    0.007386   7.208724e-01\n",
              "L5.T_out         5.171913   4.333064e-01\n",
              "L5.Windspeed    -1.990310   5.877537e-01\n",
              "L6.Appliances   -0.016838   4.059770e-01\n",
              "L6.T_out         3.227034   5.632265e-01\n",
              "L6.Windspeed     4.971647   1.396495e-01\n",
              "L7.Appliances   -0.010919   5.554416e-01\n",
              "L7.T_out        -6.777338   8.064473e-03\n",
              "L7.Windspeed    -2.972593   1.358828e-01"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ENYNTvKCr08L"
      },
      "source": [
        "df_coeff.columns = ['coeff','pval']"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "L8_x8m7TsASq",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "e24adf4b-9a38-4349-d44d-a7f8d5e448f5"
      },
      "source": [
        "df_coeff.query('pval < 0.05')\n",
        "np.where(df_coeff['pval'] < 0.05,1, 0)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([1, 1, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "L37Mls_FtTAa"
      },
      "source": [
        "df_coeff['valid']=np.where(df_coeff['pval'] < 0.05,1, 0)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xrB5Ngwc6OhI",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 725
        },
        "outputId": "87e567c2-0e8a-4225-f6ad-559526b6b891"
      },
      "source": [
        "df_coeff"
      ],
      "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>coeff</th>\n",
              "      <th>pval</th>\n",
              "      <th>valid</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>const</th>\n",
              "      <td>37.865935</td>\n",
              "      <td>4.701032e-28</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>L1.Appliances</th>\n",
              "      <td>0.451436</td>\n",
              "      <td>6.138160e-132</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>L1.T_out</th>\n",
              "      <td>2.328238</td>\n",
              "      <td>3.582355e-01</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>L1.Windspeed</th>\n",
              "      <td>2.268735</td>\n",
              "      <td>2.564126e-01</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>L2.Appliances</th>\n",
              "      <td>0.222279</td>\n",
              "      <td>4.255512e-28</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>L2.T_out</th>\n",
              "      <td>-4.372626</td>\n",
              "      <td>4.302427e-01</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>L2.Windspeed</th>\n",
              "      <td>-1.481847</td>\n",
              "      <td>6.603327e-01</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>L3.Appliances</th>\n",
              "      <td>-0.019489</td>\n",
              "      <td>3.454670e-01</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>L3.T_out</th>\n",
              "      <td>5.606923</td>\n",
              "      <td>3.952787e-01</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>L3.Windspeed</th>\n",
              "      <td>0.184615</td>\n",
              "      <td>9.598961e-01</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>L4.Appliances</th>\n",
              "      <td>-0.043691</td>\n",
              "      <td>3.442733e-02</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>L4.T_out</th>\n",
              "      <td>-5.435304</td>\n",
              "      <td>4.211329e-01</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>L4.Windspeed</th>\n",
              "      <td>-0.086856</td>\n",
              "      <td>9.816543e-01</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>L5.Appliances</th>\n",
              "      <td>0.007386</td>\n",
              "      <td>7.208724e-01</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>L5.T_out</th>\n",
              "      <td>5.171913</td>\n",
              "      <td>4.333064e-01</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>L5.Windspeed</th>\n",
              "      <td>-1.990310</td>\n",
              "      <td>5.877537e-01</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>L6.Appliances</th>\n",
              "      <td>-0.016838</td>\n",
              "      <td>4.059770e-01</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>L6.T_out</th>\n",
              "      <td>3.227034</td>\n",
              "      <td>5.632265e-01</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>L6.Windspeed</th>\n",
              "      <td>4.971647</td>\n",
              "      <td>1.396495e-01</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>L7.Appliances</th>\n",
              "      <td>-0.010919</td>\n",
              "      <td>5.554416e-01</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>L7.T_out</th>\n",
              "      <td>-6.777338</td>\n",
              "      <td>8.064473e-03</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>L7.Windspeed</th>\n",
              "      <td>-2.972593</td>\n",
              "      <td>1.358828e-01</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                   coeff           pval  valid\n",
              "const          37.865935   4.701032e-28      1\n",
              "L1.Appliances   0.451436  6.138160e-132      1\n",
              "L1.T_out        2.328238   3.582355e-01      0\n",
              "L1.Windspeed    2.268735   2.564126e-01      0\n",
              "L2.Appliances   0.222279   4.255512e-28      1\n",
              "L2.T_out       -4.372626   4.302427e-01      0\n",
              "L2.Windspeed   -1.481847   6.603327e-01      0\n",
              "L3.Appliances  -0.019489   3.454670e-01      0\n",
              "L3.T_out        5.606923   3.952787e-01      0\n",
              "L3.Windspeed    0.184615   9.598961e-01      0\n",
              "L4.Appliances  -0.043691   3.442733e-02      1\n",
              "L4.T_out       -5.435304   4.211329e-01      0\n",
              "L4.Windspeed   -0.086856   9.816543e-01      0\n",
              "L5.Appliances   0.007386   7.208724e-01      0\n",
              "L5.T_out        5.171913   4.333064e-01      0\n",
              "L5.Windspeed   -1.990310   5.877537e-01      0\n",
              "L6.Appliances  -0.016838   4.059770e-01      0\n",
              "L6.T_out        3.227034   5.632265e-01      0\n",
              "L6.Windspeed    4.971647   1.396495e-01      0\n",
              "L7.Appliances  -0.010919   5.554416e-01      0\n",
              "L7.T_out       -6.777338   8.064473e-03      1\n",
              "L7.Windspeed   -2.972593   1.358828e-01      0"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-r0g84p66Ulg"
      },
      "source": [
        "#coeff_arr=np.multiply(df_coeff['coeff'], df_coeff['valid'])[1:].values\n",
        "coeff_arr=df_coeff['coeff'][1:].values"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NKmlS-DA-74O",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "ebb8e747-c067-4552-fd23-5e4e33e115ca"
      },
      "source": [
        "coeff_arr.shape"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(21,)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xkXCQBWgCu8T",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "0270fff2-2c07-4f2c-8324-f0448e1948ff"
      },
      "source": [
        "coeff_arr"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([ 0.45143647,  2.32823846,  2.26873466,  0.2222793 , -4.37262576,\n",
              "       -1.48184722, -0.01948858,  5.60692324,  0.18461514, -0.04369054,\n",
              "       -5.43530357, -0.08685622,  0.00738616,  5.17191268, -1.99030973,\n",
              "       -0.01683822,  3.22703425,  4.97164661, -0.01091878, -6.77733848,\n",
              "       -2.97259279])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YYhgjior6UN6",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 295
        },
        "outputId": "83be1fe3-d525-443e-d1ae-2d664eacacb4"
      },
      "source": [
        "df_train[-lag:]"
      ],
      "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>Appliances</th>\n",
              "      <th>T_out</th>\n",
              "      <th>Windspeed</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>date</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2016-05-13 19:00:00</th>\n",
              "      <td>208.333333</td>\n",
              "      <td>19.333333</td>\n",
              "      <td>9.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-05-13 20:00:00</th>\n",
              "      <td>120.000000</td>\n",
              "      <td>17.066667</td>\n",
              "      <td>8.166667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-05-13 21:00:00</th>\n",
              "      <td>63.333333</td>\n",
              "      <td>14.116667</td>\n",
              "      <td>6.583333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-05-13 22:00:00</th>\n",
              "      <td>55.000000</td>\n",
              "      <td>11.850000</td>\n",
              "      <td>6.833333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-05-13 23:00:00</th>\n",
              "      <td>61.666667</td>\n",
              "      <td>10.466667</td>\n",
              "      <td>7.583333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-05-14 00:00:00</th>\n",
              "      <td>58.333333</td>\n",
              "      <td>9.791667</td>\n",
              "      <td>5.750000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-05-14 01:00:00</th>\n",
              "      <td>63.333333</td>\n",
              "      <td>9.333333</td>\n",
              "      <td>4.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                     Appliances      T_out  Windspeed\n",
              "date                                                 \n",
              "2016-05-13 19:00:00  208.333333  19.333333   9.000000\n",
              "2016-05-13 20:00:00  120.000000  17.066667   8.166667\n",
              "2016-05-13 21:00:00   63.333333  14.116667   6.583333\n",
              "2016-05-13 22:00:00   55.000000  11.850000   6.833333\n",
              "2016-05-13 23:00:00   61.666667  10.466667   7.583333\n",
              "2016-05-14 00:00:00   58.333333   9.791667   5.750000\n",
              "2016-05-14 01:00:00   63.333333   9.333333   4.000000"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 31
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "saFUyF_N7TsI"
      },
      "source": [
        "in_arr=df_train[-lag:][::-1].stack().to_frame().T.values"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wWk02qd67Tem",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "e013ba6a-d4c9-41ff-9004-cc566bcdadca"
      },
      "source": [
        "in_arr.shape"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(1, 21)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 33
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "593Luc1u_60o",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "5c315bc9-c206-4f4b-f0c8-28a4fbbe7604"
      },
      "source": [
        "in_arr"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[ 63.33333333,   9.33333333,   4.        ,  58.33333333,\n",
              "          9.79166667,   5.75      ,  61.66666667,  10.46666667,\n",
              "          7.58333333,  55.        ,  11.85      ,   6.83333333,\n",
              "         63.33333333,  14.11666667,   6.58333333, 120.        ,\n",
              "         17.06666667,   8.16666667, 208.33333333,  19.33333333,\n",
              "          9.        ]])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 34
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bVVxyZNo_A4X",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "a774e452-8188-4de8-89db-b1ffbc385ad9"
      },
      "source": [
        "np.dot(in_arr, coeff_arr)+df_coeff['coeff'][:1].values"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([44.34598018])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 35
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lGfrzBT3NAr_"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}