Clustering_load_profiles.ipynb

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  "metadata": {
    "colab": {
      "name": "Clustering load profiles.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "toc_visible": true,
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/loredana2314/DAT540_Project/blob/main/Clustering_load_profiles.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "umEpRw2Hl6oa"
      },
      "source": [
        "# Project: Clustering load profiles\n",
        "Group name: CTRL+ALT+Delete\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "hABV5V-iofTa"
      },
      "source": [
        "# 1.Importing and cleaning data "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "shi57hRZma7V"
      },
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import datetime as dt\n",
        "%matplotlib inline"
      ],
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "myUORBlsw2sl"
      },
      "source": [
        "#from google.colab import drive\n",
        "#drive.mount('/content/drive/')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 388
        },
        "id": "Wj77tVdXmb8k",
        "outputId": "2589983c-1bf2-4a29-f7b2-6e741faf2166"
      },
      "source": [
        "#Importing the dataset, parsing datetime \n",
        "df_measurements = pd.read_csv(\"/content/daily_electricity_usage.csv\",parse_dates=['date'], dtype={'Meter ID': object}, index_col='date')\n",
        "df_measurements.info()\n",
        "df_measurements.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "DatetimeIndex: 3291258 entries, 2009-07-14 to 2010-10-17\n",
            "Data columns (total 2 columns):\n",
            " #   Column          Dtype  \n",
            "---  ------          -----  \n",
            " 0   Meter ID        object \n",
            " 1   total daily KW  float64\n",
            "dtypes: float64(1), object(1)\n",
            "memory usage: 75.3+ MB\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Meter ID</th>\n",
              "      <th>total daily KW</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>date</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2009-07-14</th>\n",
              "      <td>1000</td>\n",
              "      <td>11.203</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2009-07-15</th>\n",
              "      <td>1000</td>\n",
              "      <td>8.403</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2009-07-16</th>\n",
              "      <td>1000</td>\n",
              "      <td>7.225</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2009-07-17</th>\n",
              "      <td>1000</td>\n",
              "      <td>11.338</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2009-07-18</th>\n",
              "      <td>1000</td>\n",
              "      <td>11.306</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "           Meter ID  total daily KW\n",
              "date                               \n",
              "2009-07-14     1000          11.203\n",
              "2009-07-15     1000           8.403\n",
              "2009-07-16     1000           7.225\n",
              "2009-07-17     1000          11.338\n",
              "2009-07-18     1000          11.306"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 417
        },
        "id": "1mcE403X797q",
        "outputId": "974a55b9-13cd-4c45-fdc8-9956768d53c7"
      },
      "source": [
        "#pivoting table to see each meter ID per date\n",
        "df_days = df_measurements.pivot_table(index = 'date', columns='Meter ID')\n",
        "df_days.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "  <thead>\n",
              "    <tr>\n",
              "      <th></th>\n",
              "      <th colspan=\"81\" halign=\"left\">total daily KW</th>\n",
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              "    <tr>\n",
              "      <th>Meter ID</th>\n",
              "      <th>1000</th>\n",
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              "      <th>1006</th>\n",
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              "      <th>1014</th>\n",
              "      <th>1015</th>\n",
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              "      <th>1017</th>\n",
              "      <th>1018</th>\n",
              "      <th>1019</th>\n",
              "      <th>1020</th>\n",
              "      <th>1021</th>\n",
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              "      <th>1023</th>\n",
              "      <th>1024</th>\n",
              "      <th>1025</th>\n",
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              "      <th>7414</th>\n",
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              "      <th>7417</th>\n",
              "      <th>7418</th>\n",
              "      <th>7419</th>\n",
              "      <th>7420</th>\n",
              "      <th>7421</th>\n",
              "      <th>7422</th>\n",
              "      <th>7423</th>\n",
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              "      <th>7442</th>\n",
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              "      <th>date</th>\n",
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              "      <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",
              "      <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",
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              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2009-07-14</th>\n",
              "      <td>11.203</td>\n",
              "      <td>6.744</td>\n",
              "      <td>6.355</td>\n",
              "      <td>24.183</td>\n",
              "      <td>50.057</td>\n",
              "      <td>17.765</td>\n",
              "      <td>12.056</td>\n",
              "      <td>30.399</td>\n",
              "      <td>27.217</td>\n",
              "      <td>51.865</td>\n",
              "      <td>38.259</td>\n",
              "      <td>49.387</td>\n",
              "      <td>95.929</td>\n",
              "      <td>16.889</td>\n",
              "      <td>34.085</td>\n",
              "      <td>15.670</td>\n",
              "      <td>5.002</td>\n",
              "      <td>16.193</td>\n",
              "      <td>50.537</td>\n",
              "      <td>23.977</td>\n",
              "      <td>30.642</td>\n",
              "      <td>19.102</td>\n",
              "      <td>18.392</td>\n",
              "      <td>68.649</td>\n",
              "      <td>11.801</td>\n",
              "      <td>2.838</td>\n",
              "      <td>35.990</td>\n",
              "      <td>6.592</td>\n",
              "      <td>239.145</td>\n",
              "      <td>3.603</td>\n",
              "      <td>18.871</td>\n",
              "      <td>3.956</td>\n",
              "      <td>13.588</td>\n",
              "      <td>41.499</td>\n",
              "      <td>49.974</td>\n",
              "      <td>7.619</td>\n",
              "      <td>8.634</td>\n",
              "      <td>11.457</td>\n",
              "      <td>278.584</td>\n",
              "      <td>32.991</td>\n",
              "      <td>...</td>\n",
              "      <td>24.839</td>\n",
              "      <td>14.094</td>\n",
              "      <td>38.676</td>\n",
              "      <td>16.383</td>\n",
              "      <td>31.405</td>\n",
              "      <td>31.628</td>\n",
              "      <td>19.188</td>\n",
              "      <td>36.086</td>\n",
              "      <td>20.167</td>\n",
              "      <td>16.613</td>\n",
              "      <td>9.172</td>\n",
              "      <td>27.467</td>\n",
              "      <td>18.356</td>\n",
              "      <td>40.054</td>\n",
              "      <td>470.055</td>\n",
              "      <td>25.487</td>\n",
              "      <td>19.589</td>\n",
              "      <td>15.463</td>\n",
              "      <td>22.475</td>\n",
              "      <td>20.367</td>\n",
              "      <td>13.670</td>\n",
              "      <td>NaN</td>\n",
              "      <td>36.923</td>\n",
              "      <td>13.091</td>\n",
              "      <td>20.860</td>\n",
              "      <td>30.366</td>\n",
              "      <td>4.274</td>\n",
              "      <td>9.214</td>\n",
              "      <td>14.319</td>\n",
              "      <td>18.357</td>\n",
              "      <td>15.643</td>\n",
              "      <td>36.500</td>\n",
              "      <td>15.346</td>\n",
              "      <td>0.732</td>\n",
              "      <td>138.130</td>\n",
              "      <td>41.813</td>\n",
              "      <td>14.491</td>\n",
              "      <td>36.813</td>\n",
              "      <td>5.112</td>\n",
              "      <td>52.940</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2009-07-15</th>\n",
              "      <td>8.403</td>\n",
              "      <td>6.949</td>\n",
              "      <td>8.972</td>\n",
              "      <td>26.659</td>\n",
              "      <td>48.813</td>\n",
              "      <td>19.801</td>\n",
              "      <td>17.169</td>\n",
              "      <td>23.976</td>\n",
              "      <td>31.996</td>\n",
              "      <td>42.740</td>\n",
              "      <td>41.706</td>\n",
              "      <td>57.969</td>\n",
              "      <td>100.728</td>\n",
              "      <td>18.383</td>\n",
              "      <td>32.544</td>\n",
              "      <td>19.193</td>\n",
              "      <td>4.211</td>\n",
              "      <td>25.665</td>\n",
              "      <td>52.621</td>\n",
              "      <td>24.010</td>\n",
              "      <td>15.788</td>\n",
              "      <td>7.114</td>\n",
              "      <td>17.287</td>\n",
              "      <td>38.922</td>\n",
              "      <td>9.026</td>\n",
              "      <td>2.833</td>\n",
              "      <td>40.627</td>\n",
              "      <td>5.640</td>\n",
              "      <td>232.750</td>\n",
              "      <td>5.360</td>\n",
              "      <td>14.638</td>\n",
              "      <td>3.994</td>\n",
              "      <td>23.513</td>\n",
              "      <td>35.014</td>\n",
              "      <td>45.599</td>\n",
              "      <td>14.728</td>\n",
              "      <td>8.433</td>\n",
              "      <td>9.968</td>\n",
              "      <td>295.308</td>\n",
              "      <td>33.560</td>\n",
              "      <td>...</td>\n",
              "      <td>23.527</td>\n",
              "      <td>17.207</td>\n",
              "      <td>35.226</td>\n",
              "      <td>17.491</td>\n",
              "      <td>20.719</td>\n",
              "      <td>26.268</td>\n",
              "      <td>15.769</td>\n",
              "      <td>28.641</td>\n",
              "      <td>8.013</td>\n",
              "      <td>18.123</td>\n",
              "      <td>8.777</td>\n",
              "      <td>18.251</td>\n",
              "      <td>18.968</td>\n",
              "      <td>59.596</td>\n",
              "      <td>473.219</td>\n",
              "      <td>27.691</td>\n",
              "      <td>16.575</td>\n",
              "      <td>12.379</td>\n",
              "      <td>26.870</td>\n",
              "      <td>16.428</td>\n",
              "      <td>10.447</td>\n",
              "      <td>NaN</td>\n",
              "      <td>54.772</td>\n",
              "      <td>9.413</td>\n",
              "      <td>15.657</td>\n",
              "      <td>26.507</td>\n",
              "      <td>4.263</td>\n",
              "      <td>20.573</td>\n",
              "      <td>17.819</td>\n",
              "      <td>25.509</td>\n",
              "      <td>14.667</td>\n",
              "      <td>29.443</td>\n",
              "      <td>26.156</td>\n",
              "      <td>0.685</td>\n",
              "      <td>115.893</td>\n",
              "      <td>31.572</td>\n",
              "      <td>12.597</td>\n",
              "      <td>40.492</td>\n",
              "      <td>18.233</td>\n",
              "      <td>35.582</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2009-07-16</th>\n",
              "      <td>7.225</td>\n",
              "      <td>7.255</td>\n",
              "      <td>8.794</td>\n",
              "      <td>32.017</td>\n",
              "      <td>32.555</td>\n",
              "      <td>15.216</td>\n",
              "      <td>16.260</td>\n",
              "      <td>34.534</td>\n",
              "      <td>24.363</td>\n",
              "      <td>56.390</td>\n",
              "      <td>52.198</td>\n",
              "      <td>52.062</td>\n",
              "      <td>101.940</td>\n",
              "      <td>6.771</td>\n",
              "      <td>31.324</td>\n",
              "      <td>16.683</td>\n",
              "      <td>4.006</td>\n",
              "      <td>13.857</td>\n",
              "      <td>42.536</td>\n",
              "      <td>24.628</td>\n",
              "      <td>29.175</td>\n",
              "      <td>23.169</td>\n",
              "      <td>14.899</td>\n",
              "      <td>73.193</td>\n",
              "      <td>14.859</td>\n",
              "      <td>2.896</td>\n",
              "      <td>47.016</td>\n",
              "      <td>8.619</td>\n",
              "      <td>228.443</td>\n",
              "      <td>5.265</td>\n",
              "      <td>10.801</td>\n",
              "      <td>4.073</td>\n",
              "      <td>24.917</td>\n",
              "      <td>35.139</td>\n",
              "      <td>35.180</td>\n",
              "      <td>9.150</td>\n",
              "      <td>9.763</td>\n",
              "      <td>9.611</td>\n",
              "      <td>291.704</td>\n",
              "      <td>30.067</td>\n",
              "      <td>...</td>\n",
              "      <td>12.796</td>\n",
              "      <td>12.346</td>\n",
              "      <td>31.713</td>\n",
              "      <td>18.771</td>\n",
              "      <td>8.748</td>\n",
              "      <td>34.587</td>\n",
              "      <td>18.920</td>\n",
              "      <td>38.871</td>\n",
              "      <td>7.336</td>\n",
              "      <td>25.997</td>\n",
              "      <td>9.369</td>\n",
              "      <td>23.874</td>\n",
              "      <td>18.544</td>\n",
              "      <td>35.521</td>\n",
              "      <td>478.952</td>\n",
              "      <td>32.803</td>\n",
              "      <td>19.351</td>\n",
              "      <td>19.566</td>\n",
              "      <td>16.261</td>\n",
              "      <td>17.194</td>\n",
              "      <td>11.487</td>\n",
              "      <td>NaN</td>\n",
              "      <td>14.831</td>\n",
              "      <td>8.368</td>\n",
              "      <td>19.139</td>\n",
              "      <td>38.481</td>\n",
              "      <td>4.236</td>\n",
              "      <td>15.118</td>\n",
              "      <td>17.562</td>\n",
              "      <td>21.360</td>\n",
              "      <td>18.037</td>\n",
              "      <td>28.786</td>\n",
              "      <td>23.945</td>\n",
              "      <td>0.707</td>\n",
              "      <td>127.698</td>\n",
              "      <td>32.618</td>\n",
              "      <td>15.816</td>\n",
              "      <td>41.487</td>\n",
              "      <td>6.925</td>\n",
              "      <td>29.307</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2009-07-17</th>\n",
              "      <td>11.338</td>\n",
              "      <td>7.190</td>\n",
              "      <td>8.306</td>\n",
              "      <td>33.032</td>\n",
              "      <td>46.727</td>\n",
              "      <td>23.418</td>\n",
              "      <td>14.813</td>\n",
              "      <td>19.251</td>\n",
              "      <td>23.122</td>\n",
              "      <td>43.604</td>\n",
              "      <td>47.171</td>\n",
              "      <td>63.930</td>\n",
              "      <td>103.671</td>\n",
              "      <td>5.977</td>\n",
              "      <td>36.053</td>\n",
              "      <td>17.922</td>\n",
              "      <td>3.801</td>\n",
              "      <td>15.039</td>\n",
              "      <td>44.322</td>\n",
              "      <td>40.112</td>\n",
              "      <td>29.844</td>\n",
              "      <td>6.164</td>\n",
              "      <td>17.034</td>\n",
              "      <td>57.148</td>\n",
              "      <td>12.984</td>\n",
              "      <td>7.660</td>\n",
              "      <td>39.778</td>\n",
              "      <td>7.374</td>\n",
              "      <td>210.062</td>\n",
              "      <td>4.885</td>\n",
              "      <td>5.186</td>\n",
              "      <td>4.058</td>\n",
              "      <td>19.441</td>\n",
              "      <td>29.927</td>\n",
              "      <td>24.133</td>\n",
              "      <td>9.895</td>\n",
              "      <td>9.299</td>\n",
              "      <td>14.908</td>\n",
              "      <td>293.524</td>\n",
              "      <td>32.053</td>\n",
              "      <td>...</td>\n",
              "      <td>16.583</td>\n",
              "      <td>16.157</td>\n",
              "      <td>34.367</td>\n",
              "      <td>17.198</td>\n",
              "      <td>13.558</td>\n",
              "      <td>28.446</td>\n",
              "      <td>17.948</td>\n",
              "      <td>27.458</td>\n",
              "      <td>7.345</td>\n",
              "      <td>27.533</td>\n",
              "      <td>8.141</td>\n",
              "      <td>22.416</td>\n",
              "      <td>13.553</td>\n",
              "      <td>13.235</td>\n",
              "      <td>572.609</td>\n",
              "      <td>31.078</td>\n",
              "      <td>14.382</td>\n",
              "      <td>13.978</td>\n",
              "      <td>7.716</td>\n",
              "      <td>26.905</td>\n",
              "      <td>6.623</td>\n",
              "      <td>NaN</td>\n",
              "      <td>14.396</td>\n",
              "      <td>10.794</td>\n",
              "      <td>19.851</td>\n",
              "      <td>28.909</td>\n",
              "      <td>4.200</td>\n",
              "      <td>30.427</td>\n",
              "      <td>15.063</td>\n",
              "      <td>17.576</td>\n",
              "      <td>11.512</td>\n",
              "      <td>31.394</td>\n",
              "      <td>23.118</td>\n",
              "      <td>0.655</td>\n",
              "      <td>142.211</td>\n",
              "      <td>36.614</td>\n",
              "      <td>13.162</td>\n",
              "      <td>43.986</td>\n",
              "      <td>5.370</td>\n",
              "      <td>40.986</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2009-07-18</th>\n",
              "      <td>11.306</td>\n",
              "      <td>6.805</td>\n",
              "      <td>10.119</td>\n",
              "      <td>31.238</td>\n",
              "      <td>35.215</td>\n",
              "      <td>29.392</td>\n",
              "      <td>12.325</td>\n",
              "      <td>21.392</td>\n",
              "      <td>25.721</td>\n",
              "      <td>41.581</td>\n",
              "      <td>41.226</td>\n",
              "      <td>46.862</td>\n",
              "      <td>107.139</td>\n",
              "      <td>7.850</td>\n",
              "      <td>37.845</td>\n",
              "      <td>15.976</td>\n",
              "      <td>3.699</td>\n",
              "      <td>15.832</td>\n",
              "      <td>37.231</td>\n",
              "      <td>43.964</td>\n",
              "      <td>28.045</td>\n",
              "      <td>10.650</td>\n",
              "      <td>23.125</td>\n",
              "      <td>26.250</td>\n",
              "      <td>18.473</td>\n",
              "      <td>8.452</td>\n",
              "      <td>23.098</td>\n",
              "      <td>6.716</td>\n",
              "      <td>117.681</td>\n",
              "      <td>5.553</td>\n",
              "      <td>16.435</td>\n",
              "      <td>15.603</td>\n",
              "      <td>33.140</td>\n",
              "      <td>34.793</td>\n",
              "      <td>20.710</td>\n",
              "      <td>5.309</td>\n",
              "      <td>12.640</td>\n",
              "      <td>9.869</td>\n",
              "      <td>290.710</td>\n",
              "      <td>39.695</td>\n",
              "      <td>...</td>\n",
              "      <td>13.533</td>\n",
              "      <td>20.365</td>\n",
              "      <td>37.902</td>\n",
              "      <td>14.290</td>\n",
              "      <td>11.367</td>\n",
              "      <td>21.963</td>\n",
              "      <td>20.461</td>\n",
              "      <td>29.295</td>\n",
              "      <td>7.362</td>\n",
              "      <td>30.252</td>\n",
              "      <td>8.232</td>\n",
              "      <td>23.913</td>\n",
              "      <td>20.415</td>\n",
              "      <td>43.819</td>\n",
              "      <td>535.448</td>\n",
              "      <td>42.829</td>\n",
              "      <td>19.822</td>\n",
              "      <td>9.634</td>\n",
              "      <td>16.033</td>\n",
              "      <td>28.201</td>\n",
              "      <td>5.505</td>\n",
              "      <td>NaN</td>\n",
              "      <td>14.676</td>\n",
              "      <td>9.928</td>\n",
              "      <td>17.213</td>\n",
              "      <td>32.016</td>\n",
              "      <td>4.200</td>\n",
              "      <td>20.712</td>\n",
              "      <td>20.230</td>\n",
              "      <td>25.962</td>\n",
              "      <td>30.767</td>\n",
              "      <td>22.112</td>\n",
              "      <td>15.582</td>\n",
              "      <td>0.682</td>\n",
              "      <td>4.641</td>\n",
              "      <td>27.982</td>\n",
              "      <td>13.301</td>\n",
              "      <td>41.018</td>\n",
              "      <td>6.751</td>\n",
              "      <td>40.270</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 6435 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "           total daily KW                 ...                        \n",
              "Meter ID             1000   1001    1002  ...    7442    7443    7444\n",
              "date                                      ...                        \n",
              "2009-07-14         11.203  6.744   6.355  ...  36.813   5.112  52.940\n",
              "2009-07-15          8.403  6.949   8.972  ...  40.492  18.233  35.582\n",
              "2009-07-16          7.225  7.255   8.794  ...  41.487   6.925  29.307\n",
              "2009-07-17         11.338  7.190   8.306  ...  43.986   5.370  40.986\n",
              "2009-07-18         11.306  6.805  10.119  ...  41.018   6.751  40.270\n",
              "\n",
              "[5 rows x 6435 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 417
        },
        "id": "CCZesSoG8vUs",
        "outputId": "5137db9d-a982-460a-cf56-138c97004ccc"
      },
      "source": [
        "#Replace NAN with daily average \n",
        "df_days = df_days.fillna(df_days.mean())\n",
        "df_days.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 tr th {\n",
              "        text-align: left;\n",
              "    }\n",
              "\n",
              "    .dataframe thead tr:last-of-type th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th></th>\n",
              "      <th colspan=\"81\" halign=\"left\">total daily KW</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Meter ID</th>\n",
              "      <th>1000</th>\n",
              "      <th>1001</th>\n",
              "      <th>1002</th>\n",
              "      <th>1003</th>\n",
              "      <th>1004</th>\n",
              "      <th>1005</th>\n",
              "      <th>1006</th>\n",
              "      <th>1007</th>\n",
              "      <th>1008</th>\n",
              "      <th>1009</th>\n",
              "      <th>1010</th>\n",
              "      <th>1011</th>\n",
              "      <th>1012</th>\n",
              "      <th>1013</th>\n",
              "      <th>1014</th>\n",
              "      <th>1015</th>\n",
              "      <th>1016</th>\n",
              "      <th>1017</th>\n",
              "      <th>1018</th>\n",
              "      <th>1019</th>\n",
              "      <th>1020</th>\n",
              "      <th>1021</th>\n",
              "      <th>1022</th>\n",
              "      <th>1023</th>\n",
              "      <th>1024</th>\n",
              "      <th>1025</th>\n",
              "      <th>1026</th>\n",
              "      <th>1027</th>\n",
              "      <th>1028</th>\n",
              "      <th>1029</th>\n",
              "      <th>1030</th>\n",
              "      <th>1031</th>\n",
              "      <th>1032</th>\n",
              "      <th>1033</th>\n",
              "      <th>1034</th>\n",
              "      <th>1035</th>\n",
              "      <th>1036</th>\n",
              "      <th>1037</th>\n",
              "      <th>1038</th>\n",
              "      <th>1039</th>\n",
              "      <th>...</th>\n",
              "      <th>7405</th>\n",
              "      <th>7406</th>\n",
              "      <th>7407</th>\n",
              "      <th>7408</th>\n",
              "      <th>7409</th>\n",
              "      <th>7410</th>\n",
              "      <th>7411</th>\n",
              "      <th>7412</th>\n",
              "      <th>7413</th>\n",
              "      <th>7414</th>\n",
              "      <th>7415</th>\n",
              "      <th>7416</th>\n",
              "      <th>7417</th>\n",
              "      <th>7418</th>\n",
              "      <th>7419</th>\n",
              "      <th>7420</th>\n",
              "      <th>7421</th>\n",
              "      <th>7422</th>\n",
              "      <th>7423</th>\n",
              "      <th>7424</th>\n",
              "      <th>7425</th>\n",
              "      <th>7426</th>\n",
              "      <th>7427</th>\n",
              "      <th>7428</th>\n",
              "      <th>7429</th>\n",
              "      <th>7430</th>\n",
              "      <th>7431</th>\n",
              "      <th>7432</th>\n",
              "      <th>7433</th>\n",
              "      <th>7434</th>\n",
              "      <th>7435</th>\n",
              "      <th>7436</th>\n",
              "      <th>7437</th>\n",
              "      <th>7438</th>\n",
              "      <th>7439</th>\n",
              "      <th>7440</th>\n",
              "      <th>7441</th>\n",
              "      <th>7442</th>\n",
              "      <th>7443</th>\n",
              "      <th>7444</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>date</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",
              "      <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",
              "      <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",
              "      <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>2009-07-14</th>\n",
              "      <td>11.203</td>\n",
              "      <td>6.744</td>\n",
              "      <td>6.355</td>\n",
              "      <td>24.183</td>\n",
              "      <td>50.057</td>\n",
              "      <td>17.765</td>\n",
              "      <td>12.056</td>\n",
              "      <td>30.399</td>\n",
              "      <td>27.217</td>\n",
              "      <td>51.865</td>\n",
              "      <td>38.259</td>\n",
              "      <td>49.387</td>\n",
              "      <td>95.929</td>\n",
              "      <td>16.889</td>\n",
              "      <td>34.085</td>\n",
              "      <td>15.670</td>\n",
              "      <td>5.002</td>\n",
              "      <td>16.193</td>\n",
              "      <td>50.537</td>\n",
              "      <td>23.977</td>\n",
              "      <td>30.642</td>\n",
              "      <td>19.102</td>\n",
              "      <td>18.392</td>\n",
              "      <td>68.649</td>\n",
              "      <td>11.801</td>\n",
              "      <td>2.838</td>\n",
              "      <td>35.990</td>\n",
              "      <td>6.592</td>\n",
              "      <td>239.145</td>\n",
              "      <td>3.603</td>\n",
              "      <td>18.871</td>\n",
              "      <td>3.956</td>\n",
              "      <td>13.588</td>\n",
              "      <td>41.499</td>\n",
              "      <td>49.974</td>\n",
              "      <td>7.619</td>\n",
              "      <td>8.634</td>\n",
              "      <td>11.457</td>\n",
              "      <td>278.584</td>\n",
              "      <td>32.991</td>\n",
              "      <td>...</td>\n",
              "      <td>24.839</td>\n",
              "      <td>14.094</td>\n",
              "      <td>38.676</td>\n",
              "      <td>16.383</td>\n",
              "      <td>31.405</td>\n",
              "      <td>31.628</td>\n",
              "      <td>19.188</td>\n",
              "      <td>36.086</td>\n",
              "      <td>20.167</td>\n",
              "      <td>16.613</td>\n",
              "      <td>9.172</td>\n",
              "      <td>27.467</td>\n",
              "      <td>18.356</td>\n",
              "      <td>40.054</td>\n",
              "      <td>470.055</td>\n",
              "      <td>25.487</td>\n",
              "      <td>19.589</td>\n",
              "      <td>15.463</td>\n",
              "      <td>22.475</td>\n",
              "      <td>20.367</td>\n",
              "      <td>13.670</td>\n",
              "      <td>22.481</td>\n",
              "      <td>36.923</td>\n",
              "      <td>13.091</td>\n",
              "      <td>20.860</td>\n",
              "      <td>30.366</td>\n",
              "      <td>4.274</td>\n",
              "      <td>9.214</td>\n",
              "      <td>14.319</td>\n",
              "      <td>18.357</td>\n",
              "      <td>15.643</td>\n",
              "      <td>36.500</td>\n",
              "      <td>15.346</td>\n",
              "      <td>0.732</td>\n",
              "      <td>138.130</td>\n",
              "      <td>41.813</td>\n",
              "      <td>14.491</td>\n",
              "      <td>36.813</td>\n",
              "      <td>5.112</td>\n",
              "      <td>52.940</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2009-07-15</th>\n",
              "      <td>8.403</td>\n",
              "      <td>6.949</td>\n",
              "      <td>8.972</td>\n",
              "      <td>26.659</td>\n",
              "      <td>48.813</td>\n",
              "      <td>19.801</td>\n",
              "      <td>17.169</td>\n",
              "      <td>23.976</td>\n",
              "      <td>31.996</td>\n",
              "      <td>42.740</td>\n",
              "      <td>41.706</td>\n",
              "      <td>57.969</td>\n",
              "      <td>100.728</td>\n",
              "      <td>18.383</td>\n",
              "      <td>32.544</td>\n",
              "      <td>19.193</td>\n",
              "      <td>4.211</td>\n",
              "      <td>25.665</td>\n",
              "      <td>52.621</td>\n",
              "      <td>24.010</td>\n",
              "      <td>15.788</td>\n",
              "      <td>7.114</td>\n",
              "      <td>17.287</td>\n",
              "      <td>38.922</td>\n",
              "      <td>9.026</td>\n",
              "      <td>2.833</td>\n",
              "      <td>40.627</td>\n",
              "      <td>5.640</td>\n",
              "      <td>232.750</td>\n",
              "      <td>5.360</td>\n",
              "      <td>14.638</td>\n",
              "      <td>3.994</td>\n",
              "      <td>23.513</td>\n",
              "      <td>35.014</td>\n",
              "      <td>45.599</td>\n",
              "      <td>14.728</td>\n",
              "      <td>8.433</td>\n",
              "      <td>9.968</td>\n",
              "      <td>295.308</td>\n",
              "      <td>33.560</td>\n",
              "      <td>...</td>\n",
              "      <td>23.527</td>\n",
              "      <td>17.207</td>\n",
              "      <td>35.226</td>\n",
              "      <td>17.491</td>\n",
              "      <td>20.719</td>\n",
              "      <td>26.268</td>\n",
              "      <td>15.769</td>\n",
              "      <td>28.641</td>\n",
              "      <td>8.013</td>\n",
              "      <td>18.123</td>\n",
              "      <td>8.777</td>\n",
              "      <td>18.251</td>\n",
              "      <td>18.968</td>\n",
              "      <td>59.596</td>\n",
              "      <td>473.219</td>\n",
              "      <td>27.691</td>\n",
              "      <td>16.575</td>\n",
              "      <td>12.379</td>\n",
              "      <td>26.870</td>\n",
              "      <td>16.428</td>\n",
              "      <td>10.447</td>\n",
              "      <td>22.481</td>\n",
              "      <td>54.772</td>\n",
              "      <td>9.413</td>\n",
              "      <td>15.657</td>\n",
              "      <td>26.507</td>\n",
              "      <td>4.263</td>\n",
              "      <td>20.573</td>\n",
              "      <td>17.819</td>\n",
              "      <td>25.509</td>\n",
              "      <td>14.667</td>\n",
              "      <td>29.443</td>\n",
              "      <td>26.156</td>\n",
              "      <td>0.685</td>\n",
              "      <td>115.893</td>\n",
              "      <td>31.572</td>\n",
              "      <td>12.597</td>\n",
              "      <td>40.492</td>\n",
              "      <td>18.233</td>\n",
              "      <td>35.582</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2009-07-16</th>\n",
              "      <td>7.225</td>\n",
              "      <td>7.255</td>\n",
              "      <td>8.794</td>\n",
              "      <td>32.017</td>\n",
              "      <td>32.555</td>\n",
              "      <td>15.216</td>\n",
              "      <td>16.260</td>\n",
              "      <td>34.534</td>\n",
              "      <td>24.363</td>\n",
              "      <td>56.390</td>\n",
              "      <td>52.198</td>\n",
              "      <td>52.062</td>\n",
              "      <td>101.940</td>\n",
              "      <td>6.771</td>\n",
              "      <td>31.324</td>\n",
              "      <td>16.683</td>\n",
              "      <td>4.006</td>\n",
              "      <td>13.857</td>\n",
              "      <td>42.536</td>\n",
              "      <td>24.628</td>\n",
              "      <td>29.175</td>\n",
              "      <td>23.169</td>\n",
              "      <td>14.899</td>\n",
              "      <td>73.193</td>\n",
              "      <td>14.859</td>\n",
              "      <td>2.896</td>\n",
              "      <td>47.016</td>\n",
              "      <td>8.619</td>\n",
              "      <td>228.443</td>\n",
              "      <td>5.265</td>\n",
              "      <td>10.801</td>\n",
              "      <td>4.073</td>\n",
              "      <td>24.917</td>\n",
              "      <td>35.139</td>\n",
              "      <td>35.180</td>\n",
              "      <td>9.150</td>\n",
              "      <td>9.763</td>\n",
              "      <td>9.611</td>\n",
              "      <td>291.704</td>\n",
              "      <td>30.067</td>\n",
              "      <td>...</td>\n",
              "      <td>12.796</td>\n",
              "      <td>12.346</td>\n",
              "      <td>31.713</td>\n",
              "      <td>18.771</td>\n",
              "      <td>8.748</td>\n",
              "      <td>34.587</td>\n",
              "      <td>18.920</td>\n",
              "      <td>38.871</td>\n",
              "      <td>7.336</td>\n",
              "      <td>25.997</td>\n",
              "      <td>9.369</td>\n",
              "      <td>23.874</td>\n",
              "      <td>18.544</td>\n",
              "      <td>35.521</td>\n",
              "      <td>478.952</td>\n",
              "      <td>32.803</td>\n",
              "      <td>19.351</td>\n",
              "      <td>19.566</td>\n",
              "      <td>16.261</td>\n",
              "      <td>17.194</td>\n",
              "      <td>11.487</td>\n",
              "      <td>22.481</td>\n",
              "      <td>14.831</td>\n",
              "      <td>8.368</td>\n",
              "      <td>19.139</td>\n",
              "      <td>38.481</td>\n",
              "      <td>4.236</td>\n",
              "      <td>15.118</td>\n",
              "      <td>17.562</td>\n",
              "      <td>21.360</td>\n",
              "      <td>18.037</td>\n",
              "      <td>28.786</td>\n",
              "      <td>23.945</td>\n",
              "      <td>0.707</td>\n",
              "      <td>127.698</td>\n",
              "      <td>32.618</td>\n",
              "      <td>15.816</td>\n",
              "      <td>41.487</td>\n",
              "      <td>6.925</td>\n",
              "      <td>29.307</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2009-07-17</th>\n",
              "      <td>11.338</td>\n",
              "      <td>7.190</td>\n",
              "      <td>8.306</td>\n",
              "      <td>33.032</td>\n",
              "      <td>46.727</td>\n",
              "      <td>23.418</td>\n",
              "      <td>14.813</td>\n",
              "      <td>19.251</td>\n",
              "      <td>23.122</td>\n",
              "      <td>43.604</td>\n",
              "      <td>47.171</td>\n",
              "      <td>63.930</td>\n",
              "      <td>103.671</td>\n",
              "      <td>5.977</td>\n",
              "      <td>36.053</td>\n",
              "      <td>17.922</td>\n",
              "      <td>3.801</td>\n",
              "      <td>15.039</td>\n",
              "      <td>44.322</td>\n",
              "      <td>40.112</td>\n",
              "      <td>29.844</td>\n",
              "      <td>6.164</td>\n",
              "      <td>17.034</td>\n",
              "      <td>57.148</td>\n",
              "      <td>12.984</td>\n",
              "      <td>7.660</td>\n",
              "      <td>39.778</td>\n",
              "      <td>7.374</td>\n",
              "      <td>210.062</td>\n",
              "      <td>4.885</td>\n",
              "      <td>5.186</td>\n",
              "      <td>4.058</td>\n",
              "      <td>19.441</td>\n",
              "      <td>29.927</td>\n",
              "      <td>24.133</td>\n",
              "      <td>9.895</td>\n",
              "      <td>9.299</td>\n",
              "      <td>14.908</td>\n",
              "      <td>293.524</td>\n",
              "      <td>32.053</td>\n",
              "      <td>...</td>\n",
              "      <td>16.583</td>\n",
              "      <td>16.157</td>\n",
              "      <td>34.367</td>\n",
              "      <td>17.198</td>\n",
              "      <td>13.558</td>\n",
              "      <td>28.446</td>\n",
              "      <td>17.948</td>\n",
              "      <td>27.458</td>\n",
              "      <td>7.345</td>\n",
              "      <td>27.533</td>\n",
              "      <td>8.141</td>\n",
              "      <td>22.416</td>\n",
              "      <td>13.553</td>\n",
              "      <td>13.235</td>\n",
              "      <td>572.609</td>\n",
              "      <td>31.078</td>\n",
              "      <td>14.382</td>\n",
              "      <td>13.978</td>\n",
              "      <td>7.716</td>\n",
              "      <td>26.905</td>\n",
              "      <td>6.623</td>\n",
              "      <td>22.481</td>\n",
              "      <td>14.396</td>\n",
              "      <td>10.794</td>\n",
              "      <td>19.851</td>\n",
              "      <td>28.909</td>\n",
              "      <td>4.200</td>\n",
              "      <td>30.427</td>\n",
              "      <td>15.063</td>\n",
              "      <td>17.576</td>\n",
              "      <td>11.512</td>\n",
              "      <td>31.394</td>\n",
              "      <td>23.118</td>\n",
              "      <td>0.655</td>\n",
              "      <td>142.211</td>\n",
              "      <td>36.614</td>\n",
              "      <td>13.162</td>\n",
              "      <td>43.986</td>\n",
              "      <td>5.370</td>\n",
              "      <td>40.986</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2009-07-18</th>\n",
              "      <td>11.306</td>\n",
              "      <td>6.805</td>\n",
              "      <td>10.119</td>\n",
              "      <td>31.238</td>\n",
              "      <td>35.215</td>\n",
              "      <td>29.392</td>\n",
              "      <td>12.325</td>\n",
              "      <td>21.392</td>\n",
              "      <td>25.721</td>\n",
              "      <td>41.581</td>\n",
              "      <td>41.226</td>\n",
              "      <td>46.862</td>\n",
              "      <td>107.139</td>\n",
              "      <td>7.850</td>\n",
              "      <td>37.845</td>\n",
              "      <td>15.976</td>\n",
              "      <td>3.699</td>\n",
              "      <td>15.832</td>\n",
              "      <td>37.231</td>\n",
              "      <td>43.964</td>\n",
              "      <td>28.045</td>\n",
              "      <td>10.650</td>\n",
              "      <td>23.125</td>\n",
              "      <td>26.250</td>\n",
              "      <td>18.473</td>\n",
              "      <td>8.452</td>\n",
              "      <td>23.098</td>\n",
              "      <td>6.716</td>\n",
              "      <td>117.681</td>\n",
              "      <td>5.553</td>\n",
              "      <td>16.435</td>\n",
              "      <td>15.603</td>\n",
              "      <td>33.140</td>\n",
              "      <td>34.793</td>\n",
              "      <td>20.710</td>\n",
              "      <td>5.309</td>\n",
              "      <td>12.640</td>\n",
              "      <td>9.869</td>\n",
              "      <td>290.710</td>\n",
              "      <td>39.695</td>\n",
              "      <td>...</td>\n",
              "      <td>13.533</td>\n",
              "      <td>20.365</td>\n",
              "      <td>37.902</td>\n",
              "      <td>14.290</td>\n",
              "      <td>11.367</td>\n",
              "      <td>21.963</td>\n",
              "      <td>20.461</td>\n",
              "      <td>29.295</td>\n",
              "      <td>7.362</td>\n",
              "      <td>30.252</td>\n",
              "      <td>8.232</td>\n",
              "      <td>23.913</td>\n",
              "      <td>20.415</td>\n",
              "      <td>43.819</td>\n",
              "      <td>535.448</td>\n",
              "      <td>42.829</td>\n",
              "      <td>19.822</td>\n",
              "      <td>9.634</td>\n",
              "      <td>16.033</td>\n",
              "      <td>28.201</td>\n",
              "      <td>5.505</td>\n",
              "      <td>22.481</td>\n",
              "      <td>14.676</td>\n",
              "      <td>9.928</td>\n",
              "      <td>17.213</td>\n",
              "      <td>32.016</td>\n",
              "      <td>4.200</td>\n",
              "      <td>20.712</td>\n",
              "      <td>20.230</td>\n",
              "      <td>25.962</td>\n",
              "      <td>30.767</td>\n",
              "      <td>22.112</td>\n",
              "      <td>15.582</td>\n",
              "      <td>0.682</td>\n",
              "      <td>4.641</td>\n",
              "      <td>27.982</td>\n",
              "      <td>13.301</td>\n",
              "      <td>41.018</td>\n",
              "      <td>6.751</td>\n",
              "      <td>40.270</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 6435 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "           total daily KW                 ...                        \n",
              "Meter ID             1000   1001    1002  ...    7442    7443    7444\n",
              "date                                      ...                        \n",
              "2009-07-14         11.203  6.744   6.355  ...  36.813   5.112  52.940\n",
              "2009-07-15          8.403  6.949   8.972  ...  40.492  18.233  35.582\n",
              "2009-07-16          7.225  7.255   8.794  ...  41.487   6.925  29.307\n",
              "2009-07-17         11.338  7.190   8.306  ...  43.986   5.370  40.986\n",
              "2009-07-18         11.306  6.805  10.119  ...  41.018   6.751  40.270\n",
              "\n",
              "[5 rows x 6435 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 35
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "XIRe_clJoxLr"
      },
      "source": [
        "# 2.Segment the data for each meter-ID"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "id": "J_Q5aG5WtwI7",
        "outputId": "d62d40d8-9a90-4e78-8c2a-397d1d87a21f"
      },
      "source": [
        "#unsure about this. Thomas\n",
        "#probably make a new DF from scratch ?!?\n",
        "\n",
        "#df_meters=df_days[0:].agg(['sum','mean']).T.rename(columns={'mean':'total','total KW':'average KW'})\n",
        "#df_meters.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></th>\n",
              "      <th>sum</th>\n",
              "      <th>total</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th rowspan=\"5\" valign=\"top\">total daily KW</th>\n",
              "      <th>1000</th>\n",
              "      <td>5515.675</td>\n",
              "      <td>10.290438</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1001</th>\n",
              "      <td>5090.375</td>\n",
              "      <td>9.496968</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1002</th>\n",
              "      <td>5352.830</td>\n",
              "      <td>9.986623</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1003</th>\n",
              "      <td>16305.581</td>\n",
              "      <td>30.420860</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1004</th>\n",
              "      <td>25326.442</td>\n",
              "      <td>47.250825</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                           sum      total\n",
              "total daily KW 1000   5515.675  10.290438\n",
              "               1001   5090.375   9.496968\n",
              "               1002   5352.830   9.986623\n",
              "               1003  16305.581  30.420860\n",
              "               1004  25326.442  47.250825"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 32
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-P4H_dW5o8mW"
      },
      "source": [
        "# 3.Clustering"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "pQAoSmEKpCK2"
      },
      "source": [
        "# 4.Justify clustering"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "pQ-SgRXmparw"
      },
      "source": [
        "# 5.Illustrate the difference among clusters"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "necawCTuphgg"
      },
      "source": [
        "# 6.Use ML-Algorithm to predict the total dayily consumption for each cluster in the last 80 days of data"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "vSiv445Fqw8A"
      },
      "source": [
        "# 7.Evaluate results of the prediction model using different measures such as RMSE and MAPE."
      ]
    }
  ]
}