08: Time_Series_Moving_Averages_MA_WMA_EMA_EWMA.ipynb

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    "colab": {
      "name": "Time_Series_Moving_Averages.ipynb",
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      "name": "python3",
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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "eUfgI7xiS7cz"
      },
      "source": [
        "Link to video explaining the code - https://www.youtube.com/watch?v=r71hWIUscV4\r\n",
        "\r\n",
        "I have taken the code from @Srivatsan github repo."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CY5G7SE9PLEB"
      },
      "source": [
        "import matplotlib as mpl\n",
        "import matplotlib.pyplot as plt\n",
        "import numpy as np\n",
        "import os\n",
        "from datetime import datetime\n",
        "import pandas as pd\n",
        "\n",
        "mpl.rcParams['figure.figsize'] = (10, 8)\n",
        "mpl.rcParams['axes.grid'] = False\n"
      ],
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pc9-9rleb9_Y"
      },
      "source": [
        "def parse(x):\n",
        "\treturn datetime.strptime(x, '%m/%d/%Y')"
      ],
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WSoh7Ze0P-jd",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "outputId": "ff35249c-e539-4c95-b33c-1bda4febf793"
      },
      "source": [
        "df = pd.read_csv('https://raw.githubusercontent.com/srivatsan88/YouTubeLI/master/dataset/electricity_consumption.csv', parse_dates = ['Bill_Date'],date_parser=parse)\n",
        "df.head()"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "\n",
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              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Bill_Date</th>\n",
              "      <th>On_peak</th>\n",
              "      <th>Off_peak</th>\n",
              "      <th>Usage_charge</th>\n",
              "      <th>Billed_amount</th>\n",
              "      <th>Billing_days</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2016-01-01</td>\n",
              "      <td>365</td>\n",
              "      <td>1423.5</td>\n",
              "      <td>219.0</td>\n",
              "      <td>247.73</td>\n",
              "      <td>31</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2016-02-01</td>\n",
              "      <td>292</td>\n",
              "      <td>1138.8</td>\n",
              "      <td>175.2</td>\n",
              "      <td>234.11</td>\n",
              "      <td>31</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2016-03-01</td>\n",
              "      <td>130</td>\n",
              "      <td>507.0</td>\n",
              "      <td>78.0</td>\n",
              "      <td>123.85</td>\n",
              "      <td>29</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2016-04-01</td>\n",
              "      <td>117</td>\n",
              "      <td>456.3</td>\n",
              "      <td>70.2</td>\n",
              "      <td>111.22</td>\n",
              "      <td>29</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2016-05-01</td>\n",
              "      <td>136</td>\n",
              "      <td>530.4</td>\n",
              "      <td>81.6</td>\n",
              "      <td>118.37</td>\n",
              "      <td>29</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   Bill_Date  On_peak  Off_peak  Usage_charge  Billed_amount  Billing_days\n",
              "0 2016-01-01      365    1423.5         219.0         247.73            31\n",
              "1 2016-02-01      292    1138.8         175.2         234.11            31\n",
              "2 2016-03-01      130     507.0          78.0         123.85            29\n",
              "3 2016-04-01      117     456.3          70.2         111.22            29\n",
              "4 2016-05-01      136     530.4          81.6         118.37            29"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ekRbR-YqwEtA",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "1416b777-c2d8-461e-fc01-89e5e8aa14bf"
      },
      "source": [
        "print (\"Rows     : \" ,df.shape[0])\n",
        "print (\"Columns  : \" ,df.shape[1])\n",
        "print (\"\\nFeatures : \\n\" ,df.columns.tolist())\n",
        "print (\"\\nMissing values :  \", df.isnull().any())\n",
        "print (\"\\nUnique values :  \\n\",df.nunique())"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Rows     :  53\n",
            "Columns  :  6\n",
            "\n",
            "Features : \n",
            " ['Bill_Date', 'On_peak', 'Off_peak', 'Usage_charge', 'Billed_amount', 'Billing_days']\n",
            "\n",
            "Missing values :   Bill_Date        False\n",
            "On_peak          False\n",
            "Off_peak         False\n",
            "Usage_charge     False\n",
            "Billed_amount    False\n",
            "Billing_days     False\n",
            "dtype: bool\n",
            "\n",
            "Unique values :  \n",
            " Bill_Date        53\n",
            "On_peak          51\n",
            "Off_peak         53\n",
            "Usage_charge     53\n",
            "Billed_amount    52\n",
            "Billing_days      9\n",
            "dtype: int64\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bJHsRdAl5C6I"
      },
      "source": [
        "bill_df=df.set_index(\"Bill_Date\")"
      ],
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "A5LxljglE8_x",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 235
        },
        "outputId": "79c36684-5c36-4b34-a4b9-6e383460fc61"
      },
      "source": [
        "bill_df.head()"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "\n",
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              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>On_peak</th>\n",
              "      <th>Off_peak</th>\n",
              "      <th>Usage_charge</th>\n",
              "      <th>Billed_amount</th>\n",
              "      <th>Billing_days</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Bill_Date</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>2016-01-01</th>\n",
              "      <td>365</td>\n",
              "      <td>1423.5</td>\n",
              "      <td>219.0</td>\n",
              "      <td>247.73</td>\n",
              "      <td>31</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-02-01</th>\n",
              "      <td>292</td>\n",
              "      <td>1138.8</td>\n",
              "      <td>175.2</td>\n",
              "      <td>234.11</td>\n",
              "      <td>31</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-03-01</th>\n",
              "      <td>130</td>\n",
              "      <td>507.0</td>\n",
              "      <td>78.0</td>\n",
              "      <td>123.85</td>\n",
              "      <td>29</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-04-01</th>\n",
              "      <td>117</td>\n",
              "      <td>456.3</td>\n",
              "      <td>70.2</td>\n",
              "      <td>111.22</td>\n",
              "      <td>29</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-05-01</th>\n",
              "      <td>136</td>\n",
              "      <td>530.4</td>\n",
              "      <td>81.6</td>\n",
              "      <td>118.37</td>\n",
              "      <td>29</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "            On_peak  Off_peak  Usage_charge  Billed_amount  Billing_days\n",
              "Bill_Date                                                               \n",
              "2016-01-01      365    1423.5         219.0         247.73            31\n",
              "2016-02-01      292    1138.8         175.2         234.11            31\n",
              "2016-03-01      130     507.0          78.0         123.85            29\n",
              "2016-04-01      117     456.3          70.2         111.22            29\n",
              "2016-05-01      136     530.4          81.6         118.37            29"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ajWqia3yGkv8"
      },
      "source": [
        "bill_2018 = bill_df['2016':'2018'][['Billed_amount']]"
      ],
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "PEn1c460HOdL",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "0c24837d-e759-4226-e7e5-20aa98fda735"
      },
      "source": [
        "bill_2018"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Billed_amount</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Bill_Date</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2016-01-01</th>\n",
              "      <td>247.73</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-02-01</th>\n",
              "      <td>234.11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-03-01</th>\n",
              "      <td>123.85</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-04-01</th>\n",
              "      <td>111.22</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-05-01</th>\n",
              "      <td>118.37</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-06-01</th>\n",
              "      <td>77.81</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-07-01</th>\n",
              "      <td>86.67</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-08-01</th>\n",
              "      <td>122.40</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-09-01</th>\n",
              "      <td>223.62</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-10-01</th>\n",
              "      <td>152.54</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-11-01</th>\n",
              "      <td>150.54</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-12-01</th>\n",
              "      <td>244.37</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-01-01</th>\n",
              "      <td>263.64</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-02-01</th>\n",
              "      <td>214.32</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-03-01</th>\n",
              "      <td>151.54</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-04-01</th>\n",
              "      <td>118.79</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-05-01</th>\n",
              "      <td>153.18</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-06-01</th>\n",
              "      <td>212.08</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-07-01</th>\n",
              "      <td>281.19</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-08-01</th>\n",
              "      <td>237.97</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-09-01</th>\n",
              "      <td>284.30</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-10-01</th>\n",
              "      <td>172.69</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-11-01</th>\n",
              "      <td>111.51</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-12-01</th>\n",
              "      <td>151.42</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-01-01</th>\n",
              "      <td>267.32</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-02-01</th>\n",
              "      <td>201.35</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-03-01</th>\n",
              "      <td>202.91</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-04-01</th>\n",
              "      <td>150.86</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-05-01</th>\n",
              "      <td>163.07</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-06-01</th>\n",
              "      <td>219.76</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-07-01</th>\n",
              "      <td>283.98</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-08-01</th>\n",
              "      <td>290.15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-09-01</th>\n",
              "      <td>257.96</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-10-01</th>\n",
              "      <td>327.19</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-11-01</th>\n",
              "      <td>193.49</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-12-01</th>\n",
              "      <td>152.34</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "            Billed_amount\n",
              "Bill_Date                \n",
              "2016-01-01         247.73\n",
              "2016-02-01         234.11\n",
              "2016-03-01         123.85\n",
              "2016-04-01         111.22\n",
              "2016-05-01         118.37\n",
              "2016-06-01          77.81\n",
              "2016-07-01          86.67\n",
              "2016-08-01         122.40\n",
              "2016-09-01         223.62\n",
              "2016-10-01         152.54\n",
              "2016-11-01         150.54\n",
              "2016-12-01         244.37\n",
              "2017-01-01         263.64\n",
              "2017-02-01         214.32\n",
              "2017-03-01         151.54\n",
              "2017-04-01         118.79\n",
              "2017-05-01         153.18\n",
              "2017-06-01         212.08\n",
              "2017-07-01         281.19\n",
              "2017-08-01         237.97\n",
              "2017-09-01         284.30\n",
              "2017-10-01         172.69\n",
              "2017-11-01         111.51\n",
              "2017-12-01         151.42\n",
              "2018-01-01         267.32\n",
              "2018-02-01         201.35\n",
              "2018-03-01         202.91\n",
              "2018-04-01         150.86\n",
              "2018-05-01         163.07\n",
              "2018-06-01         219.76\n",
              "2018-07-01         283.98\n",
              "2018-08-01         290.15\n",
              "2018-09-01         257.96\n",
              "2018-10-01         327.19\n",
              "2018-11-01         193.49\n",
              "2018-12-01         152.34"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "HpS41rSyzH1m"
      },
      "source": [
        "Simple moving average = (t + (t-1) + (t-2) + ... + (t-n)) / n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UBvYPmh1E885",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "dc3b4ac3-7607-437c-ee7d-fe4928af857b"
      },
      "source": [
        "bill_2018['Billed_amount'].rolling(window=3).mean()"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Bill_Date\n",
              "2016-01-01           NaN\n",
              "2016-02-01           NaN\n",
              "2016-03-01    201.896667\n",
              "2016-04-01    156.393333\n",
              "2016-05-01    117.813333\n",
              "2016-06-01    102.466667\n",
              "2016-07-01     94.283333\n",
              "2016-08-01     95.626667\n",
              "2016-09-01    144.230000\n",
              "2016-10-01    166.186667\n",
              "2016-11-01    175.566667\n",
              "2016-12-01    182.483333\n",
              "2017-01-01    219.516667\n",
              "2017-02-01    240.776667\n",
              "2017-03-01    209.833333\n",
              "2017-04-01    161.550000\n",
              "2017-05-01    141.170000\n",
              "2017-06-01    161.350000\n",
              "2017-07-01    215.483333\n",
              "2017-08-01    243.746667\n",
              "2017-09-01    267.820000\n",
              "2017-10-01    231.653333\n",
              "2017-11-01    189.500000\n",
              "2017-12-01    145.206667\n",
              "2018-01-01    176.750000\n",
              "2018-02-01    206.696667\n",
              "2018-03-01    223.860000\n",
              "2018-04-01    185.040000\n",
              "2018-05-01    172.280000\n",
              "2018-06-01    177.896667\n",
              "2018-07-01    222.270000\n",
              "2018-08-01    264.630000\n",
              "2018-09-01    277.363333\n",
              "2018-10-01    291.766667\n",
              "2018-11-01    259.546667\n",
              "2018-12-01    224.340000\n",
              "Name: Billed_amount, dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dz-eNupME86J"
      },
      "source": [
        "bill_2018['ma_rolling_3']=bill_2018['Billed_amount'].rolling(window=3).mean().shift(1)"
      ],
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "T-SphqTYE82u",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "b703c245-e406-4948-9cf2-f93fc5340905"
      },
      "source": [
        "bill_2018"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "    .dataframe tbody tr th {\n",
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              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Billed_amount</th>\n",
              "      <th>ma_rolling_3</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Bill_Date</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2016-01-01</th>\n",
              "      <td>247.73</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-02-01</th>\n",
              "      <td>234.11</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-03-01</th>\n",
              "      <td>123.85</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-04-01</th>\n",
              "      <td>111.22</td>\n",
              "      <td>201.896667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-05-01</th>\n",
              "      <td>118.37</td>\n",
              "      <td>156.393333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-06-01</th>\n",
              "      <td>77.81</td>\n",
              "      <td>117.813333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-07-01</th>\n",
              "      <td>86.67</td>\n",
              "      <td>102.466667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-08-01</th>\n",
              "      <td>122.40</td>\n",
              "      <td>94.283333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-09-01</th>\n",
              "      <td>223.62</td>\n",
              "      <td>95.626667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-10-01</th>\n",
              "      <td>152.54</td>\n",
              "      <td>144.230000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-11-01</th>\n",
              "      <td>150.54</td>\n",
              "      <td>166.186667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-12-01</th>\n",
              "      <td>244.37</td>\n",
              "      <td>175.566667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-01-01</th>\n",
              "      <td>263.64</td>\n",
              "      <td>182.483333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-02-01</th>\n",
              "      <td>214.32</td>\n",
              "      <td>219.516667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-03-01</th>\n",
              "      <td>151.54</td>\n",
              "      <td>240.776667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-04-01</th>\n",
              "      <td>118.79</td>\n",
              "      <td>209.833333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-05-01</th>\n",
              "      <td>153.18</td>\n",
              "      <td>161.550000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-06-01</th>\n",
              "      <td>212.08</td>\n",
              "      <td>141.170000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-07-01</th>\n",
              "      <td>281.19</td>\n",
              "      <td>161.350000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-08-01</th>\n",
              "      <td>237.97</td>\n",
              "      <td>215.483333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-09-01</th>\n",
              "      <td>284.30</td>\n",
              "      <td>243.746667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-10-01</th>\n",
              "      <td>172.69</td>\n",
              "      <td>267.820000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-11-01</th>\n",
              "      <td>111.51</td>\n",
              "      <td>231.653333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-12-01</th>\n",
              "      <td>151.42</td>\n",
              "      <td>189.500000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-01-01</th>\n",
              "      <td>267.32</td>\n",
              "      <td>145.206667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-02-01</th>\n",
              "      <td>201.35</td>\n",
              "      <td>176.750000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-03-01</th>\n",
              "      <td>202.91</td>\n",
              "      <td>206.696667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-04-01</th>\n",
              "      <td>150.86</td>\n",
              "      <td>223.860000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-05-01</th>\n",
              "      <td>163.07</td>\n",
              "      <td>185.040000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-06-01</th>\n",
              "      <td>219.76</td>\n",
              "      <td>172.280000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-07-01</th>\n",
              "      <td>283.98</td>\n",
              "      <td>177.896667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-08-01</th>\n",
              "      <td>290.15</td>\n",
              "      <td>222.270000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-09-01</th>\n",
              "      <td>257.96</td>\n",
              "      <td>264.630000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-10-01</th>\n",
              "      <td>327.19</td>\n",
              "      <td>277.363333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-11-01</th>\n",
              "      <td>193.49</td>\n",
              "      <td>291.766667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-12-01</th>\n",
              "      <td>152.34</td>\n",
              "      <td>259.546667</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "            Billed_amount  ma_rolling_3\n",
              "Bill_Date                              \n",
              "2016-01-01         247.73           NaN\n",
              "2016-02-01         234.11           NaN\n",
              "2016-03-01         123.85           NaN\n",
              "2016-04-01         111.22    201.896667\n",
              "2016-05-01         118.37    156.393333\n",
              "2016-06-01          77.81    117.813333\n",
              "2016-07-01          86.67    102.466667\n",
              "2016-08-01         122.40     94.283333\n",
              "2016-09-01         223.62     95.626667\n",
              "2016-10-01         152.54    144.230000\n",
              "2016-11-01         150.54    166.186667\n",
              "2016-12-01         244.37    175.566667\n",
              "2017-01-01         263.64    182.483333\n",
              "2017-02-01         214.32    219.516667\n",
              "2017-03-01         151.54    240.776667\n",
              "2017-04-01         118.79    209.833333\n",
              "2017-05-01         153.18    161.550000\n",
              "2017-06-01         212.08    141.170000\n",
              "2017-07-01         281.19    161.350000\n",
              "2017-08-01         237.97    215.483333\n",
              "2017-09-01         284.30    243.746667\n",
              "2017-10-01         172.69    267.820000\n",
              "2017-11-01         111.51    231.653333\n",
              "2017-12-01         151.42    189.500000\n",
              "2018-01-01         267.32    145.206667\n",
              "2018-02-01         201.35    176.750000\n",
              "2018-03-01         202.91    206.696667\n",
              "2018-04-01         150.86    223.860000\n",
              "2018-05-01         163.07    185.040000\n",
              "2018-06-01         219.76    172.280000\n",
              "2018-07-01         283.98    177.896667\n",
              "2018-08-01         290.15    222.270000\n",
              "2018-09-01         257.96    264.630000\n",
              "2018-10-01         327.19    277.363333\n",
              "2018-11-01         193.49    291.766667\n",
              "2018-12-01         152.34    259.546667"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "paiqHYifM7bO",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 292
        },
        "outputId": "512347eb-a40a-43f1-ecf9-94abe692a764"
      },
      "source": [
        "bill_2018.plot();"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "bxzVBI463G-O"
      },
      "source": [
        "Weighted moving average = (t * weighting factor) + ((t-1) * weighting factor-1) + ((t-n) * weighting factor-n)/n "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3h7wFgM5E8qE"
      },
      "source": [
        "def wma(weights): \n",
        "  def calc(x):\n",
        "    return (weights*x).mean()\n",
        "  return calc"
      ],
      "execution_count": 13,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7Q1-fNJYE8gz",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "494f7146-9d83-49ac-fa10-57ffd7acab85"
      },
      "source": [
        "bill_2018['Billed_amount'].rolling(window=3).apply(wma(np.array([0.5,1,1.5])))"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Bill_Date\n",
              "2016-01-01           NaN\n",
              "2016-02-01           NaN\n",
              "2016-03-01    181.250000\n",
              "2016-04-01    135.911667\n",
              "2016-05-01    116.900000\n",
              "2016-06-01     96.898333\n",
              "2016-07-01     89.000000\n",
              "2016-08-01    103.058333\n",
              "2016-09-01    167.055000\n",
              "2016-10-01    171.210000\n",
              "2016-11-01    163.386667\n",
              "2016-12-01    197.788333\n",
              "2017-01-01    238.366667\n",
              "2017-02-01    235.768333\n",
              "2017-03-01    191.150000\n",
              "2017-04-01    145.628333\n",
              "2017-05-01    141.443333\n",
              "2017-06-01    176.898333\n",
              "2017-07-01    236.818333\n",
              "2017-08-01    248.061667\n",
              "2017-09-01    268.338333\n",
              "2017-10-01    220.773333\n",
              "2017-11-01    160.701667\n",
              "2017-12-01    141.661667\n",
              "2018-01-01    202.718333\n",
              "2018-02-01    215.018333\n",
              "2018-03-01    213.125000\n",
              "2018-04-01    176.625000\n",
              "2018-05-01    165.640000\n",
              "2018-06-01    189.380000\n",
              "2018-07-01    242.421667\n",
              "2018-08-01    276.361667\n",
              "2018-09-01    273.026667\n",
              "2018-10-01    297.940000\n",
              "2018-11-01    248.801667\n",
              "2018-12-01    195.198333\n",
              "Name: Billed_amount, dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "U5ha0--uJ51C"
      },
      "source": [
        "bill_2018['wma_rolling_3']=bill_2018['Billed_amount'].rolling(window=3).apply(wma(np.array([0.5,1,1.5]))).shift(1)"
      ],
      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Nr17yUpGaGOr",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "5ab0bf0f-d3f0-4b42-ad83-e530dd708cd5"
      },
      "source": [
        "bill_2018"
      ],
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Billed_amount</th>\n",
              "      <th>ma_rolling_3</th>\n",
              "      <th>wma_rolling_3</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Bill_Date</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2016-01-01</th>\n",
              "      <td>247.73</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-02-01</th>\n",
              "      <td>234.11</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-03-01</th>\n",
              "      <td>123.85</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-04-01</th>\n",
              "      <td>111.22</td>\n",
              "      <td>201.896667</td>\n",
              "      <td>181.250000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-05-01</th>\n",
              "      <td>118.37</td>\n",
              "      <td>156.393333</td>\n",
              "      <td>135.911667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-06-01</th>\n",
              "      <td>77.81</td>\n",
              "      <td>117.813333</td>\n",
              "      <td>116.900000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-07-01</th>\n",
              "      <td>86.67</td>\n",
              "      <td>102.466667</td>\n",
              "      <td>96.898333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-08-01</th>\n",
              "      <td>122.40</td>\n",
              "      <td>94.283333</td>\n",
              "      <td>89.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-09-01</th>\n",
              "      <td>223.62</td>\n",
              "      <td>95.626667</td>\n",
              "      <td>103.058333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-10-01</th>\n",
              "      <td>152.54</td>\n",
              "      <td>144.230000</td>\n",
              "      <td>167.055000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-11-01</th>\n",
              "      <td>150.54</td>\n",
              "      <td>166.186667</td>\n",
              "      <td>171.210000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-12-01</th>\n",
              "      <td>244.37</td>\n",
              "      <td>175.566667</td>\n",
              "      <td>163.386667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-01-01</th>\n",
              "      <td>263.64</td>\n",
              "      <td>182.483333</td>\n",
              "      <td>197.788333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-02-01</th>\n",
              "      <td>214.32</td>\n",
              "      <td>219.516667</td>\n",
              "      <td>238.366667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-03-01</th>\n",
              "      <td>151.54</td>\n",
              "      <td>240.776667</td>\n",
              "      <td>235.768333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-04-01</th>\n",
              "      <td>118.79</td>\n",
              "      <td>209.833333</td>\n",
              "      <td>191.150000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-05-01</th>\n",
              "      <td>153.18</td>\n",
              "      <td>161.550000</td>\n",
              "      <td>145.628333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-06-01</th>\n",
              "      <td>212.08</td>\n",
              "      <td>141.170000</td>\n",
              "      <td>141.443333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-07-01</th>\n",
              "      <td>281.19</td>\n",
              "      <td>161.350000</td>\n",
              "      <td>176.898333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-08-01</th>\n",
              "      <td>237.97</td>\n",
              "      <td>215.483333</td>\n",
              "      <td>236.818333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-09-01</th>\n",
              "      <td>284.30</td>\n",
              "      <td>243.746667</td>\n",
              "      <td>248.061667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-10-01</th>\n",
              "      <td>172.69</td>\n",
              "      <td>267.820000</td>\n",
              "      <td>268.338333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-11-01</th>\n",
              "      <td>111.51</td>\n",
              "      <td>231.653333</td>\n",
              "      <td>220.773333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-12-01</th>\n",
              "      <td>151.42</td>\n",
              "      <td>189.500000</td>\n",
              "      <td>160.701667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-01-01</th>\n",
              "      <td>267.32</td>\n",
              "      <td>145.206667</td>\n",
              "      <td>141.661667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-02-01</th>\n",
              "      <td>201.35</td>\n",
              "      <td>176.750000</td>\n",
              "      <td>202.718333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-03-01</th>\n",
              "      <td>202.91</td>\n",
              "      <td>206.696667</td>\n",
              "      <td>215.018333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-04-01</th>\n",
              "      <td>150.86</td>\n",
              "      <td>223.860000</td>\n",
              "      <td>213.125000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-05-01</th>\n",
              "      <td>163.07</td>\n",
              "      <td>185.040000</td>\n",
              "      <td>176.625000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-06-01</th>\n",
              "      <td>219.76</td>\n",
              "      <td>172.280000</td>\n",
              "      <td>165.640000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-07-01</th>\n",
              "      <td>283.98</td>\n",
              "      <td>177.896667</td>\n",
              "      <td>189.380000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-08-01</th>\n",
              "      <td>290.15</td>\n",
              "      <td>222.270000</td>\n",
              "      <td>242.421667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-09-01</th>\n",
              "      <td>257.96</td>\n",
              "      <td>264.630000</td>\n",
              "      <td>276.361667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-10-01</th>\n",
              "      <td>327.19</td>\n",
              "      <td>277.363333</td>\n",
              "      <td>273.026667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-11-01</th>\n",
              "      <td>193.49</td>\n",
              "      <td>291.766667</td>\n",
              "      <td>297.940000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-12-01</th>\n",
              "      <td>152.34</td>\n",
              "      <td>259.546667</td>\n",
              "      <td>248.801667</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "            Billed_amount  ma_rolling_3  wma_rolling_3\n",
              "Bill_Date                                             \n",
              "2016-01-01         247.73           NaN            NaN\n",
              "2016-02-01         234.11           NaN            NaN\n",
              "2016-03-01         123.85           NaN            NaN\n",
              "2016-04-01         111.22    201.896667     181.250000\n",
              "2016-05-01         118.37    156.393333     135.911667\n",
              "2016-06-01          77.81    117.813333     116.900000\n",
              "2016-07-01          86.67    102.466667      96.898333\n",
              "2016-08-01         122.40     94.283333      89.000000\n",
              "2016-09-01         223.62     95.626667     103.058333\n",
              "2016-10-01         152.54    144.230000     167.055000\n",
              "2016-11-01         150.54    166.186667     171.210000\n",
              "2016-12-01         244.37    175.566667     163.386667\n",
              "2017-01-01         263.64    182.483333     197.788333\n",
              "2017-02-01         214.32    219.516667     238.366667\n",
              "2017-03-01         151.54    240.776667     235.768333\n",
              "2017-04-01         118.79    209.833333     191.150000\n",
              "2017-05-01         153.18    161.550000     145.628333\n",
              "2017-06-01         212.08    141.170000     141.443333\n",
              "2017-07-01         281.19    161.350000     176.898333\n",
              "2017-08-01         237.97    215.483333     236.818333\n",
              "2017-09-01         284.30    243.746667     248.061667\n",
              "2017-10-01         172.69    267.820000     268.338333\n",
              "2017-11-01         111.51    231.653333     220.773333\n",
              "2017-12-01         151.42    189.500000     160.701667\n",
              "2018-01-01         267.32    145.206667     141.661667\n",
              "2018-02-01         201.35    176.750000     202.718333\n",
              "2018-03-01         202.91    206.696667     215.018333\n",
              "2018-04-01         150.86    223.860000     213.125000\n",
              "2018-05-01         163.07    185.040000     176.625000\n",
              "2018-06-01         219.76    172.280000     165.640000\n",
              "2018-07-01         283.98    177.896667     189.380000\n",
              "2018-08-01         290.15    222.270000     242.421667\n",
              "2018-09-01         257.96    264.630000     276.361667\n",
              "2018-10-01         327.19    277.363333     273.026667\n",
              "2018-11-01         193.49    291.766667     297.940000\n",
              "2018-12-01         152.34    259.546667     248.801667"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DBlVXvBQaGLU",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 309
        },
        "outputId": "8acfc3c2-4874-4690-ccb2-3b4ba9858ce7"
      },
      "source": [
        "bill_2018.plot()"
      ],
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f60ec32ff60>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 17
        },
        {
          "output_type": "display_data",
          "data": {
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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "OjHcOxANyWiM"
      },
      "source": [
        "Exponential moving average = (Close - previous EMA) * (2/(span+1)) + previous EMA\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "q99o4C3Cgmwu",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "e5a89c5c-b8af-4b68-d6aa-7bd1699df418"
      },
      "source": [
        "bill_2018['Billed_amount'].ewm(span=3, adjust=False, min_periods=0).mean()"
      ],
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Bill_Date\n",
              "2016-01-01    247.730000\n",
              "2016-02-01    240.920000\n",
              "2016-03-01    182.385000\n",
              "2016-04-01    146.802500\n",
              "2016-05-01    132.586250\n",
              "2016-06-01    105.198125\n",
              "2016-07-01     95.934063\n",
              "2016-08-01    109.167031\n",
              "2016-09-01    166.393516\n",
              "2016-10-01    159.466758\n",
              "2016-11-01    155.003379\n",
              "2016-12-01    199.686689\n",
              "2017-01-01    231.663345\n",
              "2017-02-01    222.991672\n",
              "2017-03-01    187.265836\n",
              "2017-04-01    153.027918\n",
              "2017-05-01    153.103959\n",
              "2017-06-01    182.591980\n",
              "2017-07-01    231.890990\n",
              "2017-08-01    234.930495\n",
              "2017-09-01    259.615247\n",
              "2017-10-01    216.152624\n",
              "2017-11-01    163.831312\n",
              "2017-12-01    157.625656\n",
              "2018-01-01    212.472828\n",
              "2018-02-01    206.911414\n",
              "2018-03-01    204.910707\n",
              "2018-04-01    177.885353\n",
              "2018-05-01    170.477677\n",
              "2018-06-01    195.118838\n",
              "2018-07-01    239.549419\n",
              "2018-08-01    264.849710\n",
              "2018-09-01    261.404855\n",
              "2018-10-01    294.297427\n",
              "2018-11-01    243.893714\n",
              "2018-12-01    198.116857\n",
              "Name: Billed_amount, dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hCDd1DWeguGC"
      },
      "source": [
        "bill_2018['ewm_window_3']=bill_2018['Billed_amount'].ewm(span=3, adjust=False, min_periods=0).mean().shift(1)"
      ],
      "execution_count": 19,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "kG6ZlZ4UguC7",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "627c14b6-6a89-4e5d-9616-b31c7de700f3"
      },
      "source": [
        "bill_2018"
      ],
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
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              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Billed_amount</th>\n",
              "      <th>ma_rolling_3</th>\n",
              "      <th>wma_rolling_3</th>\n",
              "      <th>ewm_window_3</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Bill_Date</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2016-01-01</th>\n",
              "      <td>247.73</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-02-01</th>\n",
              "      <td>234.11</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>247.730000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-03-01</th>\n",
              "      <td>123.85</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>240.920000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-04-01</th>\n",
              "      <td>111.22</td>\n",
              "      <td>201.896667</td>\n",
              "      <td>181.250000</td>\n",
              "      <td>182.385000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-05-01</th>\n",
              "      <td>118.37</td>\n",
              "      <td>156.393333</td>\n",
              "      <td>135.911667</td>\n",
              "      <td>146.802500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-06-01</th>\n",
              "      <td>77.81</td>\n",
              "      <td>117.813333</td>\n",
              "      <td>116.900000</td>\n",
              "      <td>132.586250</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-07-01</th>\n",
              "      <td>86.67</td>\n",
              "      <td>102.466667</td>\n",
              "      <td>96.898333</td>\n",
              "      <td>105.198125</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-08-01</th>\n",
              "      <td>122.40</td>\n",
              "      <td>94.283333</td>\n",
              "      <td>89.000000</td>\n",
              "      <td>95.934063</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-09-01</th>\n",
              "      <td>223.62</td>\n",
              "      <td>95.626667</td>\n",
              "      <td>103.058333</td>\n",
              "      <td>109.167031</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-10-01</th>\n",
              "      <td>152.54</td>\n",
              "      <td>144.230000</td>\n",
              "      <td>167.055000</td>\n",
              "      <td>166.393516</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-11-01</th>\n",
              "      <td>150.54</td>\n",
              "      <td>166.186667</td>\n",
              "      <td>171.210000</td>\n",
              "      <td>159.466758</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-12-01</th>\n",
              "      <td>244.37</td>\n",
              "      <td>175.566667</td>\n",
              "      <td>163.386667</td>\n",
              "      <td>155.003379</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-01-01</th>\n",
              "      <td>263.64</td>\n",
              "      <td>182.483333</td>\n",
              "      <td>197.788333</td>\n",
              "      <td>199.686689</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-02-01</th>\n",
              "      <td>214.32</td>\n",
              "      <td>219.516667</td>\n",
              "      <td>238.366667</td>\n",
              "      <td>231.663345</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-03-01</th>\n",
              "      <td>151.54</td>\n",
              "      <td>240.776667</td>\n",
              "      <td>235.768333</td>\n",
              "      <td>222.991672</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-04-01</th>\n",
              "      <td>118.79</td>\n",
              "      <td>209.833333</td>\n",
              "      <td>191.150000</td>\n",
              "      <td>187.265836</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-05-01</th>\n",
              "      <td>153.18</td>\n",
              "      <td>161.550000</td>\n",
              "      <td>145.628333</td>\n",
              "      <td>153.027918</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-06-01</th>\n",
              "      <td>212.08</td>\n",
              "      <td>141.170000</td>\n",
              "      <td>141.443333</td>\n",
              "      <td>153.103959</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-07-01</th>\n",
              "      <td>281.19</td>\n",
              "      <td>161.350000</td>\n",
              "      <td>176.898333</td>\n",
              "      <td>182.591980</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-08-01</th>\n",
              "      <td>237.97</td>\n",
              "      <td>215.483333</td>\n",
              "      <td>236.818333</td>\n",
              "      <td>231.890990</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-09-01</th>\n",
              "      <td>284.30</td>\n",
              "      <td>243.746667</td>\n",
              "      <td>248.061667</td>\n",
              "      <td>234.930495</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-10-01</th>\n",
              "      <td>172.69</td>\n",
              "      <td>267.820000</td>\n",
              "      <td>268.338333</td>\n",
              "      <td>259.615247</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-11-01</th>\n",
              "      <td>111.51</td>\n",
              "      <td>231.653333</td>\n",
              "      <td>220.773333</td>\n",
              "      <td>216.152624</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-12-01</th>\n",
              "      <td>151.42</td>\n",
              "      <td>189.500000</td>\n",
              "      <td>160.701667</td>\n",
              "      <td>163.831312</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-01-01</th>\n",
              "      <td>267.32</td>\n",
              "      <td>145.206667</td>\n",
              "      <td>141.661667</td>\n",
              "      <td>157.625656</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-02-01</th>\n",
              "      <td>201.35</td>\n",
              "      <td>176.750000</td>\n",
              "      <td>202.718333</td>\n",
              "      <td>212.472828</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-03-01</th>\n",
              "      <td>202.91</td>\n",
              "      <td>206.696667</td>\n",
              "      <td>215.018333</td>\n",
              "      <td>206.911414</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-04-01</th>\n",
              "      <td>150.86</td>\n",
              "      <td>223.860000</td>\n",
              "      <td>213.125000</td>\n",
              "      <td>204.910707</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-05-01</th>\n",
              "      <td>163.07</td>\n",
              "      <td>185.040000</td>\n",
              "      <td>176.625000</td>\n",
              "      <td>177.885353</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-06-01</th>\n",
              "      <td>219.76</td>\n",
              "      <td>172.280000</td>\n",
              "      <td>165.640000</td>\n",
              "      <td>170.477677</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-07-01</th>\n",
              "      <td>283.98</td>\n",
              "      <td>177.896667</td>\n",
              "      <td>189.380000</td>\n",
              "      <td>195.118838</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-08-01</th>\n",
              "      <td>290.15</td>\n",
              "      <td>222.270000</td>\n",
              "      <td>242.421667</td>\n",
              "      <td>239.549419</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-09-01</th>\n",
              "      <td>257.96</td>\n",
              "      <td>264.630000</td>\n",
              "      <td>276.361667</td>\n",
              "      <td>264.849710</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-10-01</th>\n",
              "      <td>327.19</td>\n",
              "      <td>277.363333</td>\n",
              "      <td>273.026667</td>\n",
              "      <td>261.404855</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-11-01</th>\n",
              "      <td>193.49</td>\n",
              "      <td>291.766667</td>\n",
              "      <td>297.940000</td>\n",
              "      <td>294.297427</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-12-01</th>\n",
              "      <td>152.34</td>\n",
              "      <td>259.546667</td>\n",
              "      <td>248.801667</td>\n",
              "      <td>243.893714</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "            Billed_amount  ma_rolling_3  wma_rolling_3  ewm_window_3\n",
              "Bill_Date                                                           \n",
              "2016-01-01         247.73           NaN            NaN           NaN\n",
              "2016-02-01         234.11           NaN            NaN    247.730000\n",
              "2016-03-01         123.85           NaN            NaN    240.920000\n",
              "2016-04-01         111.22    201.896667     181.250000    182.385000\n",
              "2016-05-01         118.37    156.393333     135.911667    146.802500\n",
              "2016-06-01          77.81    117.813333     116.900000    132.586250\n",
              "2016-07-01          86.67    102.466667      96.898333    105.198125\n",
              "2016-08-01         122.40     94.283333      89.000000     95.934063\n",
              "2016-09-01         223.62     95.626667     103.058333    109.167031\n",
              "2016-10-01         152.54    144.230000     167.055000    166.393516\n",
              "2016-11-01         150.54    166.186667     171.210000    159.466758\n",
              "2016-12-01         244.37    175.566667     163.386667    155.003379\n",
              "2017-01-01         263.64    182.483333     197.788333    199.686689\n",
              "2017-02-01         214.32    219.516667     238.366667    231.663345\n",
              "2017-03-01         151.54    240.776667     235.768333    222.991672\n",
              "2017-04-01         118.79    209.833333     191.150000    187.265836\n",
              "2017-05-01         153.18    161.550000     145.628333    153.027918\n",
              "2017-06-01         212.08    141.170000     141.443333    153.103959\n",
              "2017-07-01         281.19    161.350000     176.898333    182.591980\n",
              "2017-08-01         237.97    215.483333     236.818333    231.890990\n",
              "2017-09-01         284.30    243.746667     248.061667    234.930495\n",
              "2017-10-01         172.69    267.820000     268.338333    259.615247\n",
              "2017-11-01         111.51    231.653333     220.773333    216.152624\n",
              "2017-12-01         151.42    189.500000     160.701667    163.831312\n",
              "2018-01-01         267.32    145.206667     141.661667    157.625656\n",
              "2018-02-01         201.35    176.750000     202.718333    212.472828\n",
              "2018-03-01         202.91    206.696667     215.018333    206.911414\n",
              "2018-04-01         150.86    223.860000     213.125000    204.910707\n",
              "2018-05-01         163.07    185.040000     176.625000    177.885353\n",
              "2018-06-01         219.76    172.280000     165.640000    170.477677\n",
              "2018-07-01         283.98    177.896667     189.380000    195.118838\n",
              "2018-08-01         290.15    222.270000     242.421667    239.549419\n",
              "2018-09-01         257.96    264.630000     276.361667    264.849710\n",
              "2018-10-01         327.19    277.363333     273.026667    261.404855\n",
              "2018-11-01         193.49    291.766667     297.940000    294.297427\n",
              "2018-12-01         152.34    259.546667     248.801667    243.893714"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9VAuv52jgt9K",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 309
        },
        "outputId": "0310956a-2345-4ff2-8e3b-d1918fa8dd07"
      },
      "source": [
        "bill_2018.plot()"
      ],
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f60ebe8aef0>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 21
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "dKpz4jS5ESTR"
      },
      "source": [
        "Exponential Smoothing - "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "p66z2la9Xmqv"
      },
      "source": [
        "![alt text](https://people.duke.edu/~rnau/411avg_files/image028.png)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NvObBoi3_eNz",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "12463df4-be87-4442-f870-89a8f7280ac9"
      },
      "source": [
        "bill_2018['Billed_amount'].ewm(alpha=0.7, adjust=False, min_periods=3).mean()"
      ],
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Bill_Date\n",
              "2016-01-01           NaN\n",
              "2016-02-01           NaN\n",
              "2016-03-01    158.153800\n",
              "2016-04-01    125.300140\n",
              "2016-05-01    120.449042\n",
              "2016-06-01     90.601713\n",
              "2016-07-01     87.849514\n",
              "2016-08-01    112.034854\n",
              "2016-09-01    190.144456\n",
              "2016-10-01    163.821337\n",
              "2016-11-01    154.524401\n",
              "2016-12-01    217.416320\n",
              "2017-01-01    249.772896\n",
              "2017-02-01    224.955869\n",
              "2017-03-01    173.564761\n",
              "2017-04-01    135.222428\n",
              "2017-05-01    147.792728\n",
              "2017-06-01    192.793819\n",
              "2017-07-01    254.671146\n",
              "2017-08-01    242.980344\n",
              "2017-09-01    271.904103\n",
              "2017-10-01    202.454231\n",
              "2017-11-01    138.793269\n",
              "2017-12-01    147.631981\n",
              "2018-01-01    231.413594\n",
              "2018-02-01    210.369078\n",
              "2018-03-01    205.147723\n",
              "2018-04-01    167.146317\n",
              "2018-05-01    164.292895\n",
              "2018-06-01    203.119869\n",
              "2018-07-01    259.721961\n",
              "2018-08-01    281.021588\n",
              "2018-09-01    264.878476\n",
              "2018-10-01    308.496543\n",
              "2018-11-01    227.991963\n",
              "2018-12-01    175.035589\n",
              "Name: Billed_amount, dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QOXhMIhH_eLm"
      },
      "source": [
        "bill_2018['esm_window_3_7']=bill_2018['Billed_amount'].ewm(alpha=0.7, adjust=False,min_periods=3).mean().shift(1)"
      ],
      "execution_count": 23,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LD8mhtOx_eHx",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "79a30910-aeff-4cdb-f083-c964b08d5cd6"
      },
      "source": [
        "bill_2018"
      ],
      "execution_count": 24,
      "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>Billed_amount</th>\n",
              "      <th>ma_rolling_3</th>\n",
              "      <th>wma_rolling_3</th>\n",
              "      <th>ewm_window_3</th>\n",
              "      <th>esm_window_3_7</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Bill_Date</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>2016-01-01</th>\n",
              "      <td>247.73</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-02-01</th>\n",
              "      <td>234.11</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>247.730000</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-03-01</th>\n",
              "      <td>123.85</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>240.920000</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-04-01</th>\n",
              "      <td>111.22</td>\n",
              "      <td>201.896667</td>\n",
              "      <td>181.250000</td>\n",
              "      <td>182.385000</td>\n",
              "      <td>158.153800</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-05-01</th>\n",
              "      <td>118.37</td>\n",
              "      <td>156.393333</td>\n",
              "      <td>135.911667</td>\n",
              "      <td>146.802500</td>\n",
              "      <td>125.300140</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-06-01</th>\n",
              "      <td>77.81</td>\n",
              "      <td>117.813333</td>\n",
              "      <td>116.900000</td>\n",
              "      <td>132.586250</td>\n",
              "      <td>120.449042</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-07-01</th>\n",
              "      <td>86.67</td>\n",
              "      <td>102.466667</td>\n",
              "      <td>96.898333</td>\n",
              "      <td>105.198125</td>\n",
              "      <td>90.601713</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-08-01</th>\n",
              "      <td>122.40</td>\n",
              "      <td>94.283333</td>\n",
              "      <td>89.000000</td>\n",
              "      <td>95.934063</td>\n",
              "      <td>87.849514</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-09-01</th>\n",
              "      <td>223.62</td>\n",
              "      <td>95.626667</td>\n",
              "      <td>103.058333</td>\n",
              "      <td>109.167031</td>\n",
              "      <td>112.034854</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-10-01</th>\n",
              "      <td>152.54</td>\n",
              "      <td>144.230000</td>\n",
              "      <td>167.055000</td>\n",
              "      <td>166.393516</td>\n",
              "      <td>190.144456</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-11-01</th>\n",
              "      <td>150.54</td>\n",
              "      <td>166.186667</td>\n",
              "      <td>171.210000</td>\n",
              "      <td>159.466758</td>\n",
              "      <td>163.821337</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-12-01</th>\n",
              "      <td>244.37</td>\n",
              "      <td>175.566667</td>\n",
              "      <td>163.386667</td>\n",
              "      <td>155.003379</td>\n",
              "      <td>154.524401</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-01-01</th>\n",
              "      <td>263.64</td>\n",
              "      <td>182.483333</td>\n",
              "      <td>197.788333</td>\n",
              "      <td>199.686689</td>\n",
              "      <td>217.416320</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-02-01</th>\n",
              "      <td>214.32</td>\n",
              "      <td>219.516667</td>\n",
              "      <td>238.366667</td>\n",
              "      <td>231.663345</td>\n",
              "      <td>249.772896</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-03-01</th>\n",
              "      <td>151.54</td>\n",
              "      <td>240.776667</td>\n",
              "      <td>235.768333</td>\n",
              "      <td>222.991672</td>\n",
              "      <td>224.955869</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-04-01</th>\n",
              "      <td>118.79</td>\n",
              "      <td>209.833333</td>\n",
              "      <td>191.150000</td>\n",
              "      <td>187.265836</td>\n",
              "      <td>173.564761</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-05-01</th>\n",
              "      <td>153.18</td>\n",
              "      <td>161.550000</td>\n",
              "      <td>145.628333</td>\n",
              "      <td>153.027918</td>\n",
              "      <td>135.222428</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-06-01</th>\n",
              "      <td>212.08</td>\n",
              "      <td>141.170000</td>\n",
              "      <td>141.443333</td>\n",
              "      <td>153.103959</td>\n",
              "      <td>147.792728</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-07-01</th>\n",
              "      <td>281.19</td>\n",
              "      <td>161.350000</td>\n",
              "      <td>176.898333</td>\n",
              "      <td>182.591980</td>\n",
              "      <td>192.793819</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-08-01</th>\n",
              "      <td>237.97</td>\n",
              "      <td>215.483333</td>\n",
              "      <td>236.818333</td>\n",
              "      <td>231.890990</td>\n",
              "      <td>254.671146</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-09-01</th>\n",
              "      <td>284.30</td>\n",
              "      <td>243.746667</td>\n",
              "      <td>248.061667</td>\n",
              "      <td>234.930495</td>\n",
              "      <td>242.980344</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-10-01</th>\n",
              "      <td>172.69</td>\n",
              "      <td>267.820000</td>\n",
              "      <td>268.338333</td>\n",
              "      <td>259.615247</td>\n",
              "      <td>271.904103</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-11-01</th>\n",
              "      <td>111.51</td>\n",
              "      <td>231.653333</td>\n",
              "      <td>220.773333</td>\n",
              "      <td>216.152624</td>\n",
              "      <td>202.454231</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-12-01</th>\n",
              "      <td>151.42</td>\n",
              "      <td>189.500000</td>\n",
              "      <td>160.701667</td>\n",
              "      <td>163.831312</td>\n",
              "      <td>138.793269</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-01-01</th>\n",
              "      <td>267.32</td>\n",
              "      <td>145.206667</td>\n",
              "      <td>141.661667</td>\n",
              "      <td>157.625656</td>\n",
              "      <td>147.631981</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-02-01</th>\n",
              "      <td>201.35</td>\n",
              "      <td>176.750000</td>\n",
              "      <td>202.718333</td>\n",
              "      <td>212.472828</td>\n",
              "      <td>231.413594</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-03-01</th>\n",
              "      <td>202.91</td>\n",
              "      <td>206.696667</td>\n",
              "      <td>215.018333</td>\n",
              "      <td>206.911414</td>\n",
              "      <td>210.369078</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-04-01</th>\n",
              "      <td>150.86</td>\n",
              "      <td>223.860000</td>\n",
              "      <td>213.125000</td>\n",
              "      <td>204.910707</td>\n",
              "      <td>205.147723</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-05-01</th>\n",
              "      <td>163.07</td>\n",
              "      <td>185.040000</td>\n",
              "      <td>176.625000</td>\n",
              "      <td>177.885353</td>\n",
              "      <td>167.146317</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-06-01</th>\n",
              "      <td>219.76</td>\n",
              "      <td>172.280000</td>\n",
              "      <td>165.640000</td>\n",
              "      <td>170.477677</td>\n",
              "      <td>164.292895</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-07-01</th>\n",
              "      <td>283.98</td>\n",
              "      <td>177.896667</td>\n",
              "      <td>189.380000</td>\n",
              "      <td>195.118838</td>\n",
              "      <td>203.119869</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-08-01</th>\n",
              "      <td>290.15</td>\n",
              "      <td>222.270000</td>\n",
              "      <td>242.421667</td>\n",
              "      <td>239.549419</td>\n",
              "      <td>259.721961</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-09-01</th>\n",
              "      <td>257.96</td>\n",
              "      <td>264.630000</td>\n",
              "      <td>276.361667</td>\n",
              "      <td>264.849710</td>\n",
              "      <td>281.021588</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-10-01</th>\n",
              "      <td>327.19</td>\n",
              "      <td>277.363333</td>\n",
              "      <td>273.026667</td>\n",
              "      <td>261.404855</td>\n",
              "      <td>264.878476</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-11-01</th>\n",
              "      <td>193.49</td>\n",
              "      <td>291.766667</td>\n",
              "      <td>297.940000</td>\n",
              "      <td>294.297427</td>\n",
              "      <td>308.496543</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-12-01</th>\n",
              "      <td>152.34</td>\n",
              "      <td>259.546667</td>\n",
              "      <td>248.801667</td>\n",
              "      <td>243.893714</td>\n",
              "      <td>227.991963</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "            Billed_amount  ma_rolling_3  ...  ewm_window_3  esm_window_3_7\n",
              "Bill_Date                                ...                              \n",
              "2016-01-01         247.73           NaN  ...           NaN             NaN\n",
              "2016-02-01         234.11           NaN  ...    247.730000             NaN\n",
              "2016-03-01         123.85           NaN  ...    240.920000             NaN\n",
              "2016-04-01         111.22    201.896667  ...    182.385000      158.153800\n",
              "2016-05-01         118.37    156.393333  ...    146.802500      125.300140\n",
              "2016-06-01          77.81    117.813333  ...    132.586250      120.449042\n",
              "2016-07-01          86.67    102.466667  ...    105.198125       90.601713\n",
              "2016-08-01         122.40     94.283333  ...     95.934063       87.849514\n",
              "2016-09-01         223.62     95.626667  ...    109.167031      112.034854\n",
              "2016-10-01         152.54    144.230000  ...    166.393516      190.144456\n",
              "2016-11-01         150.54    166.186667  ...    159.466758      163.821337\n",
              "2016-12-01         244.37    175.566667  ...    155.003379      154.524401\n",
              "2017-01-01         263.64    182.483333  ...    199.686689      217.416320\n",
              "2017-02-01         214.32    219.516667  ...    231.663345      249.772896\n",
              "2017-03-01         151.54    240.776667  ...    222.991672      224.955869\n",
              "2017-04-01         118.79    209.833333  ...    187.265836      173.564761\n",
              "2017-05-01         153.18    161.550000  ...    153.027918      135.222428\n",
              "2017-06-01         212.08    141.170000  ...    153.103959      147.792728\n",
              "2017-07-01         281.19    161.350000  ...    182.591980      192.793819\n",
              "2017-08-01         237.97    215.483333  ...    231.890990      254.671146\n",
              "2017-09-01         284.30    243.746667  ...    234.930495      242.980344\n",
              "2017-10-01         172.69    267.820000  ...    259.615247      271.904103\n",
              "2017-11-01         111.51    231.653333  ...    216.152624      202.454231\n",
              "2017-12-01         151.42    189.500000  ...    163.831312      138.793269\n",
              "2018-01-01         267.32    145.206667  ...    157.625656      147.631981\n",
              "2018-02-01         201.35    176.750000  ...    212.472828      231.413594\n",
              "2018-03-01         202.91    206.696667  ...    206.911414      210.369078\n",
              "2018-04-01         150.86    223.860000  ...    204.910707      205.147723\n",
              "2018-05-01         163.07    185.040000  ...    177.885353      167.146317\n",
              "2018-06-01         219.76    172.280000  ...    170.477677      164.292895\n",
              "2018-07-01         283.98    177.896667  ...    195.118838      203.119869\n",
              "2018-08-01         290.15    222.270000  ...    239.549419      259.721961\n",
              "2018-09-01         257.96    264.630000  ...    264.849710      281.021588\n",
              "2018-10-01         327.19    277.363333  ...    261.404855      264.878476\n",
              "2018-11-01         193.49    291.766667  ...    294.297427      308.496543\n",
              "2018-12-01         152.34    259.546667  ...    243.893714      227.991963\n",
              "\n",
              "[36 rows x 5 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "e5mQAAKx_eFY",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 309
        },
        "outputId": "ebd7653d-3278-42b1-ae8c-ea90e2857719"
      },
      "source": [
        "bill_2018[['Billed_amount','esm_window_3_7']].plot()"
      ],
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f60eaad2a90>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 25
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "b8rRNAbrfcWu",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 309
        },
        "outputId": "691ed98b-bb39-44d5-a849-8246d0d80ed1"
      },
      "source": [
        "bill_2018.plot()"
      ],
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f60eaa8cda0>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 26
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "uCttA7EM_eCg",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "75ede26a-f734-4f00-e592-20721c0d6b67"
      },
      "source": [
        "bill_2018['Billed_amount'].ewm(alpha=0.3, adjust=False, min_periods=3).mean()"
      ],
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Bill_Date\n",
              "2016-01-01           NaN\n",
              "2016-02-01           NaN\n",
              "2016-03-01    207.705800\n",
              "2016-04-01    178.760060\n",
              "2016-05-01    160.643042\n",
              "2016-06-01    135.793129\n",
              "2016-07-01    121.056191\n",
              "2016-08-01    121.459333\n",
              "2016-09-01    152.107533\n",
              "2016-10-01    152.237273\n",
              "2016-11-01    151.728091\n",
              "2016-12-01    179.520664\n",
              "2017-01-01    204.756465\n",
              "2017-02-01    207.625525\n",
              "2017-03-01    190.799868\n",
              "2017-04-01    169.196907\n",
              "2017-05-01    164.391835\n",
              "2017-06-01    178.698285\n",
              "2017-07-01    209.445799\n",
              "2017-08-01    218.003059\n",
              "2017-09-01    237.892142\n",
              "2017-10-01    218.331499\n",
              "2017-11-01    186.285049\n",
              "2017-12-01    175.825535\n",
              "2018-01-01    203.273874\n",
              "2018-02-01    202.696712\n",
              "2018-03-01    202.760698\n",
              "2018-04-01    187.190489\n",
              "2018-05-01    179.954342\n",
              "2018-06-01    191.896040\n",
              "2018-07-01    219.521228\n",
              "2018-08-01    240.709859\n",
              "2018-09-01    245.884902\n",
              "2018-10-01    270.276431\n",
              "2018-11-01    247.240502\n",
              "2018-12-01    218.770351\n",
              "Name: Billed_amount, dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rNmsEDBw_d_s"
      },
      "source": [
        "bill_2018['esm_window_3_3']=bill_2018['Billed_amount'].ewm(alpha=0.3, adjust=False,min_periods=3).mean().shift(1)"
      ],
      "execution_count": 28,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vyFxXg_U_d8q",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "471761d7-8a6c-4326-8e4f-0d835191f74a"
      },
      "source": [
        "bill_2018"
      ],
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Billed_amount</th>\n",
              "      <th>ma_rolling_3</th>\n",
              "      <th>wma_rolling_3</th>\n",
              "      <th>ewm_window_3</th>\n",
              "      <th>esm_window_3_7</th>\n",
              "      <th>esm_window_3_3</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Bill_Date</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>2016-01-01</th>\n",
              "      <td>247.73</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-02-01</th>\n",
              "      <td>234.11</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>247.730000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-03-01</th>\n",
              "      <td>123.85</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>240.920000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-04-01</th>\n",
              "      <td>111.22</td>\n",
              "      <td>201.896667</td>\n",
              "      <td>181.250000</td>\n",
              "      <td>182.385000</td>\n",
              "      <td>158.153800</td>\n",
              "      <td>207.705800</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-05-01</th>\n",
              "      <td>118.37</td>\n",
              "      <td>156.393333</td>\n",
              "      <td>135.911667</td>\n",
              "      <td>146.802500</td>\n",
              "      <td>125.300140</td>\n",
              "      <td>178.760060</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-06-01</th>\n",
              "      <td>77.81</td>\n",
              "      <td>117.813333</td>\n",
              "      <td>116.900000</td>\n",
              "      <td>132.586250</td>\n",
              "      <td>120.449042</td>\n",
              "      <td>160.643042</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-07-01</th>\n",
              "      <td>86.67</td>\n",
              "      <td>102.466667</td>\n",
              "      <td>96.898333</td>\n",
              "      <td>105.198125</td>\n",
              "      <td>90.601713</td>\n",
              "      <td>135.793129</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-08-01</th>\n",
              "      <td>122.40</td>\n",
              "      <td>94.283333</td>\n",
              "      <td>89.000000</td>\n",
              "      <td>95.934063</td>\n",
              "      <td>87.849514</td>\n",
              "      <td>121.056191</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-09-01</th>\n",
              "      <td>223.62</td>\n",
              "      <td>95.626667</td>\n",
              "      <td>103.058333</td>\n",
              "      <td>109.167031</td>\n",
              "      <td>112.034854</td>\n",
              "      <td>121.459333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-10-01</th>\n",
              "      <td>152.54</td>\n",
              "      <td>144.230000</td>\n",
              "      <td>167.055000</td>\n",
              "      <td>166.393516</td>\n",
              "      <td>190.144456</td>\n",
              "      <td>152.107533</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-11-01</th>\n",
              "      <td>150.54</td>\n",
              "      <td>166.186667</td>\n",
              "      <td>171.210000</td>\n",
              "      <td>159.466758</td>\n",
              "      <td>163.821337</td>\n",
              "      <td>152.237273</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-12-01</th>\n",
              "      <td>244.37</td>\n",
              "      <td>175.566667</td>\n",
              "      <td>163.386667</td>\n",
              "      <td>155.003379</td>\n",
              "      <td>154.524401</td>\n",
              "      <td>151.728091</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-01-01</th>\n",
              "      <td>263.64</td>\n",
              "      <td>182.483333</td>\n",
              "      <td>197.788333</td>\n",
              "      <td>199.686689</td>\n",
              "      <td>217.416320</td>\n",
              "      <td>179.520664</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-02-01</th>\n",
              "      <td>214.32</td>\n",
              "      <td>219.516667</td>\n",
              "      <td>238.366667</td>\n",
              "      <td>231.663345</td>\n",
              "      <td>249.772896</td>\n",
              "      <td>204.756465</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-03-01</th>\n",
              "      <td>151.54</td>\n",
              "      <td>240.776667</td>\n",
              "      <td>235.768333</td>\n",
              "      <td>222.991672</td>\n",
              "      <td>224.955869</td>\n",
              "      <td>207.625525</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-04-01</th>\n",
              "      <td>118.79</td>\n",
              "      <td>209.833333</td>\n",
              "      <td>191.150000</td>\n",
              "      <td>187.265836</td>\n",
              "      <td>173.564761</td>\n",
              "      <td>190.799868</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-05-01</th>\n",
              "      <td>153.18</td>\n",
              "      <td>161.550000</td>\n",
              "      <td>145.628333</td>\n",
              "      <td>153.027918</td>\n",
              "      <td>135.222428</td>\n",
              "      <td>169.196907</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-06-01</th>\n",
              "      <td>212.08</td>\n",
              "      <td>141.170000</td>\n",
              "      <td>141.443333</td>\n",
              "      <td>153.103959</td>\n",
              "      <td>147.792728</td>\n",
              "      <td>164.391835</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-07-01</th>\n",
              "      <td>281.19</td>\n",
              "      <td>161.350000</td>\n",
              "      <td>176.898333</td>\n",
              "      <td>182.591980</td>\n",
              "      <td>192.793819</td>\n",
              "      <td>178.698285</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-08-01</th>\n",
              "      <td>237.97</td>\n",
              "      <td>215.483333</td>\n",
              "      <td>236.818333</td>\n",
              "      <td>231.890990</td>\n",
              "      <td>254.671146</td>\n",
              "      <td>209.445799</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-09-01</th>\n",
              "      <td>284.30</td>\n",
              "      <td>243.746667</td>\n",
              "      <td>248.061667</td>\n",
              "      <td>234.930495</td>\n",
              "      <td>242.980344</td>\n",
              "      <td>218.003059</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-10-01</th>\n",
              "      <td>172.69</td>\n",
              "      <td>267.820000</td>\n",
              "      <td>268.338333</td>\n",
              "      <td>259.615247</td>\n",
              "      <td>271.904103</td>\n",
              "      <td>237.892142</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-11-01</th>\n",
              "      <td>111.51</td>\n",
              "      <td>231.653333</td>\n",
              "      <td>220.773333</td>\n",
              "      <td>216.152624</td>\n",
              "      <td>202.454231</td>\n",
              "      <td>218.331499</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-12-01</th>\n",
              "      <td>151.42</td>\n",
              "      <td>189.500000</td>\n",
              "      <td>160.701667</td>\n",
              "      <td>163.831312</td>\n",
              "      <td>138.793269</td>\n",
              "      <td>186.285049</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-01-01</th>\n",
              "      <td>267.32</td>\n",
              "      <td>145.206667</td>\n",
              "      <td>141.661667</td>\n",
              "      <td>157.625656</td>\n",
              "      <td>147.631981</td>\n",
              "      <td>175.825535</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-02-01</th>\n",
              "      <td>201.35</td>\n",
              "      <td>176.750000</td>\n",
              "      <td>202.718333</td>\n",
              "      <td>212.472828</td>\n",
              "      <td>231.413594</td>\n",
              "      <td>203.273874</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-03-01</th>\n",
              "      <td>202.91</td>\n",
              "      <td>206.696667</td>\n",
              "      <td>215.018333</td>\n",
              "      <td>206.911414</td>\n",
              "      <td>210.369078</td>\n",
              "      <td>202.696712</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-04-01</th>\n",
              "      <td>150.86</td>\n",
              "      <td>223.860000</td>\n",
              "      <td>213.125000</td>\n",
              "      <td>204.910707</td>\n",
              "      <td>205.147723</td>\n",
              "      <td>202.760698</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-05-01</th>\n",
              "      <td>163.07</td>\n",
              "      <td>185.040000</td>\n",
              "      <td>176.625000</td>\n",
              "      <td>177.885353</td>\n",
              "      <td>167.146317</td>\n",
              "      <td>187.190489</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-06-01</th>\n",
              "      <td>219.76</td>\n",
              "      <td>172.280000</td>\n",
              "      <td>165.640000</td>\n",
              "      <td>170.477677</td>\n",
              "      <td>164.292895</td>\n",
              "      <td>179.954342</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-07-01</th>\n",
              "      <td>283.98</td>\n",
              "      <td>177.896667</td>\n",
              "      <td>189.380000</td>\n",
              "      <td>195.118838</td>\n",
              "      <td>203.119869</td>\n",
              "      <td>191.896040</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-08-01</th>\n",
              "      <td>290.15</td>\n",
              "      <td>222.270000</td>\n",
              "      <td>242.421667</td>\n",
              "      <td>239.549419</td>\n",
              "      <td>259.721961</td>\n",
              "      <td>219.521228</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-09-01</th>\n",
              "      <td>257.96</td>\n",
              "      <td>264.630000</td>\n",
              "      <td>276.361667</td>\n",
              "      <td>264.849710</td>\n",
              "      <td>281.021588</td>\n",
              "      <td>240.709859</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-10-01</th>\n",
              "      <td>327.19</td>\n",
              "      <td>277.363333</td>\n",
              "      <td>273.026667</td>\n",
              "      <td>261.404855</td>\n",
              "      <td>264.878476</td>\n",
              "      <td>245.884902</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-11-01</th>\n",
              "      <td>193.49</td>\n",
              "      <td>291.766667</td>\n",
              "      <td>297.940000</td>\n",
              "      <td>294.297427</td>\n",
              "      <td>308.496543</td>\n",
              "      <td>270.276431</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-12-01</th>\n",
              "      <td>152.34</td>\n",
              "      <td>259.546667</td>\n",
              "      <td>248.801667</td>\n",
              "      <td>243.893714</td>\n",
              "      <td>227.991963</td>\n",
              "      <td>247.240502</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "            Billed_amount  ma_rolling_3  ...  esm_window_3_7  esm_window_3_3\n",
              "Bill_Date                                ...                                \n",
              "2016-01-01         247.73           NaN  ...             NaN             NaN\n",
              "2016-02-01         234.11           NaN  ...             NaN             NaN\n",
              "2016-03-01         123.85           NaN  ...             NaN             NaN\n",
              "2016-04-01         111.22    201.896667  ...      158.153800      207.705800\n",
              "2016-05-01         118.37    156.393333  ...      125.300140      178.760060\n",
              "2016-06-01          77.81    117.813333  ...      120.449042      160.643042\n",
              "2016-07-01          86.67    102.466667  ...       90.601713      135.793129\n",
              "2016-08-01         122.40     94.283333  ...       87.849514      121.056191\n",
              "2016-09-01         223.62     95.626667  ...      112.034854      121.459333\n",
              "2016-10-01         152.54    144.230000  ...      190.144456      152.107533\n",
              "2016-11-01         150.54    166.186667  ...      163.821337      152.237273\n",
              "2016-12-01         244.37    175.566667  ...      154.524401      151.728091\n",
              "2017-01-01         263.64    182.483333  ...      217.416320      179.520664\n",
              "2017-02-01         214.32    219.516667  ...      249.772896      204.756465\n",
              "2017-03-01         151.54    240.776667  ...      224.955869      207.625525\n",
              "2017-04-01         118.79    209.833333  ...      173.564761      190.799868\n",
              "2017-05-01         153.18    161.550000  ...      135.222428      169.196907\n",
              "2017-06-01         212.08    141.170000  ...      147.792728      164.391835\n",
              "2017-07-01         281.19    161.350000  ...      192.793819      178.698285\n",
              "2017-08-01         237.97    215.483333  ...      254.671146      209.445799\n",
              "2017-09-01         284.30    243.746667  ...      242.980344      218.003059\n",
              "2017-10-01         172.69    267.820000  ...      271.904103      237.892142\n",
              "2017-11-01         111.51    231.653333  ...      202.454231      218.331499\n",
              "2017-12-01         151.42    189.500000  ...      138.793269      186.285049\n",
              "2018-01-01         267.32    145.206667  ...      147.631981      175.825535\n",
              "2018-02-01         201.35    176.750000  ...      231.413594      203.273874\n",
              "2018-03-01         202.91    206.696667  ...      210.369078      202.696712\n",
              "2018-04-01         150.86    223.860000  ...      205.147723      202.760698\n",
              "2018-05-01         163.07    185.040000  ...      167.146317      187.190489\n",
              "2018-06-01         219.76    172.280000  ...      164.292895      179.954342\n",
              "2018-07-01         283.98    177.896667  ...      203.119869      191.896040\n",
              "2018-08-01         290.15    222.270000  ...      259.721961      219.521228\n",
              "2018-09-01         257.96    264.630000  ...      281.021588      240.709859\n",
              "2018-10-01         327.19    277.363333  ...      264.878476      245.884902\n",
              "2018-11-01         193.49    291.766667  ...      308.496543      270.276431\n",
              "2018-12-01         152.34    259.546667  ...      227.991963      247.240502\n",
              "\n",
              "[36 rows x 6 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "i5K4-vwa_d5s",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 309
        },
        "outputId": "7ea074a2-7249-473a-d18e-1f32b6c3f16c"
      },
      "source": [
        "bill_2018[['Billed_amount','esm_window_3_3']].plot()"
      ],
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f60ea8aa358>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 30
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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vtrPDF2IJhLIaZ4+G++EkW6Ra93AmVSPWczeZTDQ2NpKUlKS2rR+liKJIY2MjJpNppLeiotKHiuZ2nlm6mw82VuDxiuxvaOOlq/rNW/ZLQ2snDa1dfQTDetPTpRrGuHvEGvfs7GwqKiqI1AYnFWUwmUxkZx9ZKqaiMhLUtLh4Ztku3ttQjoDAlcePor3LzUebKmls7STJbBx6EWCnX3ZgAOOe0iMeFr5a94g17v7OTRUVFZVwU+d08fx3e3h73UG8XpFLZ+dw26KxZMbHUFbj5P2iCj4pruLak+TZpB1DGPekuPDry0SscVdRUVEJN01tXby4fA9vfL+fbo/Ij6dnccep4/okOcenW5iSbePDjRWyjfvOWieJcYaexOnhGHQabDHhlSCI6ISqisrRzJ76VmY//A176luHPlhFcZbuqGX+/y3lpZV7OWtyBt/cfTKPXTK13+qVi2dmU1rtYFtVi6y1d9Q4yU8zD5ovTDYbwjpuTzXuKiojxNeltdQ7O9laKc9gqCjLO+vKscbo+fquBTxx2TTykuMGPPZHUzIxaDUs2Vg54DF+vF6RXbVOJqRbBz1OGpStGncVlYigpb2bN9bsx+sNvYRz9e4GAKpbXCGvpRI426sdzM5NZGxq/3Hx3iTEGThtUiofF1fS5R58SE2lvYO2Ls+A8XY/yRZjWBOqqnFXUQmAJZsqePDTbazf3xTSOp1uDxt8a9Soxn3Ysbd3UWnvYFLm4N51by6emU1TWxffldUNepw/mTpQjbufFLMxrKWQqnFXUQkA/2SdFTtDK9H94aAdV7fkAarGffgprZaakiZlyDfuC8alkGw28uHGikGP21nrN+7mQY9LNhtwdrpxdYdncLxq3FVUAqDM94u7PETjvmZPIxoBpmbbqHaoxn24Ka3yGfcAPHedVsOPZ2SxdEcdjYPEynfUOMmKj8Fi0g+6XrjH7anGXUVFJl6vyM5aJ0adhm1VjpAqHdbsbqAwO55xaRZqVc992CmtdpBmNfYYWLlcNCMbt1fkk+KqAY/ZWePsMxB7IMLdyKQadxUVmVQ0d9De5ekZvrByV3Dee1unm+JyOyeOSSLDZqLO6cLtGTxJp6IspVWOgEIyfnrXvPdHl9vLnvrWIZOpEH4JAtW4q6jIxC8e9eMZWSTFGYKOu6/f34TbK3LCmGTSrCa8YngFpFT60un2sLuuNaCQTG8Gq3nf29CK2yvKM+4WNSyjohIR+BNl49OtzB+XzIpdDUGVRK7Z3YBBp2FWbgIZNkk0TU2qDh+7aiUDPCnDFtT5g9W8lw0hO9CbpDifMqTquauojCw7apzkJMZgNuo4eXwKTW1dbKsKXAp29e5GZh6XgEmvJV017sNOMMnU3gxW815W40SnERidPHilDIBJr8Vi0qmeu4rKSNN7kv38cSkArAgw7t7c1kVptYMTxkjTt9KtknFXG5mGj9JqB7EGLaNCGJLhr3lfdljN+85aJ6NT4jDo5JnWFHM/jUxVP8CLC8BeHvT+QDXuKiqy6HR72NfQ1vO4nWw2UpBpZXlZYMb9+72NAJwwNhmAxDgDBq2GWrUcctgorXIwMcPa74QkuQxU876jxsn4IWQHepNsNh6Zb/nmD1BdAt89GvT+QDXuKiqy2Fvf5kuUHfrFPTk/hU0Hm3G4umWvs3p3A2ajjqnZUrxXEATSbaaI89w/Ka7kQGPbSG9DcbxekdLq4CpleuOveV+2o64nrNLa6aaiuYPxQzQv9SbZYugblilfD3uXgS0HSt6B+p1B71E17ioqMvAnynrXLy/IT8HtFVmzu1H2Omv2NDInLxGd9tCvXrrNFFEx926Pl7veK+aF5XtHeiuKU9HcQWunO+h4e28Or3nvnXCXS/LhEgTL/w9ik+Dnn4M+FpY9FPT+VOOuoiKDsloneq3QRzlwxnEJmI062XH3KnsH+xraeuLtftKtJmoiKCxT5+zEKxLU3NBIp7RaKl8sUMC4H17z3p8DMBQpZiMOl5tOtwcqNsLub+CE2yFhFMy7FUo/kWLwQaAadxXF+KS4kv9srRnpbYSFshonY1LM6Ht53AadhnljklheVi9r0PeaPZKHf6Iv3u4nw+e5R8qwcH/8v6zGqYj6ZSRRWuVAqxGGFPWSy8Uzs9nuq3kvq3ESa9CSFR8j+3x/rXtjaxcsfxRiEmH2DdKb826FmARYGpz3rhp3FUXYWevknvdLePTL7SO9lbBQVuPst3b55PwUKu0d7G0YOj69ZncDiXGGnoobP+k2E10eL01t4ZN/DQS/HEJ7l4cDTe0jvBtlKa12MCYlDpNeq8h6/pr3DzdWUFbjJD/NElCi1t+l2rZvA+z6r2TQjb6YvckGJ90lefP7Vwe8N9W4q4SM1yvy24+24PaK7G9sP+oqP5yubirtHf16eyfnSyWRQ1XNiKLImj2NzBuTdMQvv78cMlJCM733sb366ArNbAtSdmAg/DXvnxRXsaPGEVBIBiRlSID4DU+AKR7m3Nj3gDk3giUDlv4vBPhkpxp3lZB5d0M5RQeauWreKADW7pWfYIwG/Imy/n5xcxJjGZ0cN2TcfW9DGzUO1xHxdiDiGplqHZ3otQIa4egy7k1tXVS3uBRJpvbGX/Pe3N4dcLgn2WykQNhPStVSmHcbmA7bmz4GFvwKDn4vefABoBp3lZCoc7p49MvtzM1L5IFzJ2E26li/L7RBFpHGUJPsF+SnsHZv46C63Gt8U5dOHJN8xHsZNilGGynlkLUOF6kWE6NTzEeVcd/eo+EenOzAQPhr3iGwZCpIypB36D7CpbPA3Bv7P2j6lZCQC9/+EbzyBeZU464SEg99th1Xt5c//bgQnVbSS1l3lBn3shonZqNuwETZyfkpuLq9PZOV+mPNnkay4mMYlXRkV2Sy2YBGiBzPvabFRbrNxMQMK9urnSO9HcXwyw5MzFAmmepHp9Vw0YwsNII8TZnemBpLOVNbxPcpl0ox9n4vYICFv4WazVD6sey1VeOuEjTLd9bzaUkVtywaw5gUKQk0Ny+J3XWtYR38O9yUDTHJfu7oRAxazYBxd69X5Pu9Ury9vzV0Wg2plsgph6x1uki3mpiYYaHS3kFLh/wmrUimtNpButVEUoAa7nL45Wn5fHDTCYGvvfzPtBLLF7EXDH5c4cWQMhGWPQwet6ylVeOuEhQdXR7u/3gLo5PjuHnhmJ7X5+QlArDhKPHeRVGkrHbwlvJYg445eYkDxt1Lqx3Y27s5ceyR8XY/kdTIVNviItVqZKIv8bjjKAnNlFY5FI+3+4kxaJk5KiGwk2q3wfZP+SLuAso7Bp/ahEYLp9wPjbuh5J+ylh/SuAuCkCMIwjJBEEoFQdgmCMKdvtd/LwhCpSAIxb4/Z/c65zeCIOwWBKFMEIQzZe1EJap4aukuyps6ePjCQoy6Q2VlhVk2YvTaoyY0U+fsxN7ePWRL+YL8ZHbWtlJl7zjivdW+ePsJ/cTb/aRbTVS3HHnucON0ddPW5ZE8d98N7WiIu7u6Peyub1WkeUkxlv8ZDBbWplwqbxrThHMgc4akOeMe+slYjufuBu4RRXEScDxwqyAIk3zvPSGK4jTfny8AfO9dDhQAi4HnBEFQpqhUJSLYUePg5RV7uWRmNvMOq/4w6DTMGBV/1Bj3Q/rcgxuFk/NTgf6nM63Z08iYlDjSfCWP/ZFuM1HrGPlQln8P6TYTaVYjCbH6oyLuvqu2FY9XVLQMMiTqtkvdp3N/QVx8irwwpiDAqQ+AowKKXhvy8CGNuyiK1aIobvJ97QS2A1mDnHI+8K4oip2iKO4DdgNzht65SjTgr2m3xuj57dkT+z1mbl4SO2octLRHf6xWbkt5fpqZdKuJFTsb+rze5fayfl/TEV2ph5NhM9Ha6cYZgAhZOPD3KKRaTAiCICVVjwIZAr/sQLjCMgGz4jEwxMG8W0k2G7G3d9MtZ9TimEWQtwBW/gU6Wwc9NKCYuyAIucB0YJ3vpdsEQdgsCMKrgiD4A05ZQG8h4goGvxmoRBH/3HCQTQft/L+zJ5LgmyRzOHPzEhFFaZxctLOjxkmqxTjg9+pHEAQW5Cezcld9n3moxeV2Oro9g4ZkIHJq3f3X9+9nYoaVshonniiXISitcmA26shJCF7DXTHqy2DrRzDnBohNJNkifbYa5Q7KPuUBaKuHdS8Mephs4y4IghlYAvxSFEUH8DwwBpgGVAN/lbuWb70bBUEoEgShqLa+YegTVEacOoeLR7/cwQljkvjxjIHv11Nz4jHoNKzfF/3NTDtr+5cd6I8F+Sk4XG5KKg7N1lyzpwFBgONHJw56bqR0qdY6peunWaWqj4kZVjrdXvbJkFeIZLZVOZiYEZg0QNhY8RdJ8XHe7cAhCQLZ4/ZyZsP4s2H1U4MeJsu4C4KgRzLsb4ui+BGAKIq1oih6RFH0Ai9zKPRSCeT0Oj3b91ofRFF8SRTFWaIozmpyG6jsJxGlEln88bNSOt1eHrpg8oBlgSCND5uWE/1xd49XlIy7zK7Dk8YmoxGkElE/a3Y3MjnTRnzs4J5/pDQy1ba4sJh0xBp0wKGa8GhOqnq9ItsV0HBXhIbdsPVDmHM9xEn5Kr9xD6h8eNH/g87BfyZyqmUE4BVguyiKj/d6PaPXYRcCW31ffwpcLgiCURCEPGAcsH6wa3hF+Pmr64+KGO3RyrKyOj7bXM1ti8YyOmXoYQTH5yWytbJlxGPIoXCgsY1Ot1e25x4fa2BqTjwrfMa9vcvND+XNnDBICaSfVJ+nPOJhGYer5ykCYGyqGZ1GiGrjfrCpnbYuz8jH29sa4b/3g87U47WDJPsLHDmRaTDSJ0u174Mgx3M/EbgSOOWwssc/C4KwRRCEzcAi4C4AURS3Ae8DpcB/gFtFURy4LxsYlRTL/sY2bnyrSNI1VokoOro8/O7jrYxNNfOLk0fLOmdOXhJeETYeaA7z7sJHIJPs/Zycn0JJhZ3mti7W72ui2yMOGW8H6WknMc4w8mEZR2dPvB3AqNMyJsplCErDJDsgm+oS+PhWeHwi7PwS5t8D5pSet/0x94Ab/y54ftC3dUOdL4riKqC/Z/AvBjnnYeDhodb2Yzbq+N0lU7nz3WLufr+Epy+fHhmxMRUAvtleS0VzB29dN6dPTftgzBgVj04jsG5fEwvHp4Z5h+GhrNaJIMC4VPnGfUF+Cn/7ZherdjewtbIFvVZgdq685pZ068g3MtU6XIxJ6XszmphhYe3e6A2x+TXcxwUw/i5kPG7Y8W9Y9xIcXCPF2Kf/TFJ5TJ3Q59BYg45Yg5YGZ4CSz9rBG5+GNO7DxfnTsqhpcfHIlzvIsJq4/9xJQ5+kMiz4Z2nOGjV4UrA3sQYdhdk21kWxQmRZjZPcpDhiDPLbNKZmx2OL0bN8Zz07ahxMPy6hJ349FCM9S9XjFalzdpJu69tCPzHDysfFVTS3dQ1ZNRSJlFY7GJdqVkzDfVDaGmHT67DhFXBUSoJfZ/4Jpv0UYuIHPC3ZbFRcsiNijDvAjQtGU2Xv4O+r9pERH8N1J+WN9JZUgPKmDpLNxoCMHEj17n9fuZeOLk/A50YCfk2ZQNBqBE4al8y322uxd3Rz56njZJ+bbjNRXG4PdJuK0djWiccr9om5Az0yBNtrHLJCTJFGaZWjX6llRWmtg2/+AFs+AE8njF4E5/wVxp0hSQcMQYpFeeMeUdoygiDwwI8KOLMgjYc+L+XzzdUjvSUVoLy5nZxE+aPD/MwdnYjbK7LpYPTF3V3dHvY3tgU07NjPyfkpNLd3I4pHjtQbjAyriaa2rkGlg8NJbYtkXFIHMu5R2Kna2NpJjUN5Dfcj+OwuybBP/xncsg6u+hjGnyXLsIOkDHpUG3eQPJ8nL5/OzOMSuOu94qh+rD9aKG9uD6r5Y9aoBDQCUfkz3F3XilcMXJ8bJH1vgFiDlqnZAz+KH06aL5F5xCSrbhd0hP8G6b/u4Z57isVIstkQlUlV/w0prGWQe5fDjs9g4X1w7uNHxNTlIIVllB2zGHHGHaTKgZevmkV2Ygw3vFnErtro8xiOFtweL1V2V1Ceu8WkpyDTFpX17v4BHcEMUk63mZiabWP+uGQMOvm/Yhn9dal6vfDmefDcCeAKr3H1V+r0rpbxI2m7R59x98sOTAyXcfd64EDK5nUAACAASURBVKvfgu04OP7WoJdJNhtpauuSJ0Egk4g07iDNJnzjmjkY9Vp+/tqGo24uZ7RQ3eLC4xWDbtuem5fID+X2EQs1BMvOWicGnYbcfoZryOHN6+by+KXTAjqnx7j3/qz/8CaUrwNnlaTlHUZqHS40AiT1kzSdmGFlV22rosZnOCitcpBpM4UvEfzDP6B2K5zxR9APLAw3FMkWKYmt5JD0iDXuIM2nfO3ns7G3d3H1q+ujuiEmWqloljqHcxKDM3Jz8hLpcnvZ3KslPxrYUeNkXKoZnTa4XxFbjJ44Y2D1Cn7VyJ6KmbZG+Ob3MOpEmHUdrH8Jqn4Iaj9yqHW4SLEY+/2eJ2ZY6PJEnwzBtjBquONySIOrj5sHk4YYtjEEKb5B2bIlCGQQ0cYdYHKWjed/NpOyWievrd4/0ts55ihvbgcI2nP3D++Itrh7WY0j4JFpoWIx6TEbdYfCMt88CJ1OOPsvktRrbLKUuPOG5ymoxtF5RLzdz6GkavSEZlzdHvbUt4Yv3r7yr5KA15l/kuR4QyAoCYIhiHjjDlJjSIbVxIHG9pHeyjFHRVM7GgEy4oN75IyPNTAh3RJVcXd7exe1jk7ZmjJK0jORqXw9/PAWHH8zpE2SaqQXPyJ57kWvhuXa0gSm/n/OY1LM6LVCT7dnNFBW48Qrhknmt2kfrH0Opl4BWTNCXu6QcT9GwjK9SbeZqHGo4mLDTXlzBxm2GPRBhidAirtvPNAcNfHaYGQHlCLDZqK2pQ0+uxssmXDyrw+9OfkiGL0Qvv0jOGsVv7Z/dmp/6LUaxqZaoqoc0n8jKsgMg+zA1w+ARic9USmAP+Z+zHnuIKnmjbRi3rFIeVM72QmBV8r0Zu7oJDq6PWypjI64e1mtf0DH8AtNpVlNzG/+GGq3SJ66sVcTlSDAOY9LI9a++q2i13V1e7C3d/dbKeNnYoYlqsIypVUOLEZdyJ/fI9i/GrZ/CifdDdaMoY+XQZxBi0mvoeFYirn78T+uimJ0Dw2INqQGptAGHMzO9cfdoyM0s6PGidWk69E0H07GxrRyg/sdvKNPgUnnH3lA0hiYf7ckG7tnqWLXPTSBaeDveVKGlXpnp+LNNuGitNrBxEzroPLUAeP1wH9+DdZsOOE2xZYVBEHxLtWoMe4ZNhPtXR4cLvdIb+WYwdXtodbRGfL0mhSLkTEpcVEzvGNnjZMJ6QobBZmcWfkMBrppWPDQwEm6E38JiWPg83ukBicF6D07dSD8SdUdURCaCZuGe8k/oWYznP4H0Cv7RKB0I1PUGPdIGUN2LOEfoBJMA9PhzB2dRNH+5ogf1yaKImUBTF9SlH0ryKv+ghc8P6JSkznwcXqTpFvStBdWPaHIpf219YMN8Y6mipkDTe20K63h3umU8h3Zs6X8h8IoLR4WNcbd3+BR3aImVYeL8iZfGWSIYRmQkqrOTjelVZFtGKpaXDhdbvKH27i7u+Dze+my5PCc+/yhnZgxi6DwElj1uDTdJ0RqW4Y27olxBtKsxqgw7v7PmaKe+6onoLUWFj8aculjfySbjcdWnbufdN8YsmPdc/d4RX7697UsK6sL+7XK/Q1MCgwV7ql3j/DQzM4afzJ1mI372mehoYzO0x+lE4O84oEzHgZdDHx+N4SYi6p1uIjRa7GaBm+8mpBujYpyyNLqFnRKarjbD8KaZ6DwUsiepcyah5FiNtDU3tVnwHooRI1xT7UYEYSRnzE50tQ6XKze3ch/tylfCnc4FU3tGHSaQZNscsmwxXBcYmzE17uHoikTNPZyWP5nGH8O5sJzMOg08uQ2LGlw2gOwbzls+TCkLdQ4XKRZjUPmGSZmWNlT30qXO7LLWrdVORibapY9XGZIvn4QBA2c9qAy6/VDssWIKEJTuzJx96gx7nqthhSz8Zj33Kt8cfCdwyCmVt7cTnZ8jGJTsebmJbJhfxPeCI67l9VIWiS2mMGn3CjKV7+RPO+zHkUQBNKtAQztmHkNZM6Q1ghBObLW4Ro0JONnYoaFbo/I7rrWoK81HJQqKTtwcC1s+whOvBNs2cqs2Q89jUyBTmQagKgx7iDF3auO8Zh7ZS/jHu6y0PKmDrIViLf7mTs6CXt7NzvrIrfaoqy2dXjj7bu+hu3/hgX3QvxxQK8uVTlotHDuE9DeCN/+b9DbOHx26kD4Y9g7aiI3NNPQ2kmds1OZ5iVRhP/8RmooO/GO0NcbBKUlCKLKuAf0oT9K8Rt3p8sd9mHKko67cuVec/Miu9692+NlT13r8FXKuBzwxa8gaRyccHvPy+lWU2A/28xpMOcXkixB5aaAtyGKoi8sM7Rxz0uOw6DTRHRSdXOFNM1qshKe+97voGoTLPoNGOJCX28Qks1BDsoegKgy7hm2GNW4Nx96ctlZG75HY6erG3t7tyKVMn6yE2LItJkiNqm6v6GNLo93eJKpB9fBCyeB/YBU1qg7lNfICKZhb9FvwWiB9S8HvBV7ezddbq8s467TahifFtkyBMXlLWgEKMxWwHNf+zzEpcCUy0JfawhSFJYgiCrjnm4z4ex0H9PSv1X2DrLiJW/aX9kRDioUrJTxIwgCc0cnsX5fU0R2Gg9LMtXjhmWPwGuLARGu+RJGn9znkHSbiS6PNzBtb5MVCi6E0k+gM7Cbfq2z/wlMAzEhXZIhiMSfIUBxuZ38NIvsweQD0rAbdn0lyS3rwt+tbDbqMOo0ijUyRZVxzxhoDNkxRKW9g4JMK8lmY1iTqv4ad6V1OebkJdLQ2sWe+sjTBd9Z60SrERibqlD53OE07ZWM+vJHpZK6m1bBcccfcZjfyAYcdpv2U+hug9KPAzqtpqfGXZ4Bm5hhpbGtS9GabKUQRZGScjvTj5M/3nBA1r8IWgPMujb0tWQgCILUyKTQ/2tUGff0w4cZHGOIokhlcweZ8THkp5nZGcaKhfIQh3QMxOzcBICIHJq9o8ZJXnKccuVzfkQRfngbXpgP9Tvholfgxy+Cqf+wQdDd2DlzIGksFL8T0Gm1MrpTe9PTqRrGJ8dg2d/YTktHd0Cza/ulwy79zCZfLJWcDhPJFiP1x2JYJsPXyHSsGndHh5u2Lg/ZCTHkp1nYVesMW1lheVM7cQYtCbHKlgTmJZuJ0WsjslO1rMapvIZ7exN88HP45BbImAo3r4bCiwc9JejPuSDAtCvgwGrpKUEmfl2ZVJme+6QIliEoKZeSqdNC9dx/eEt6Cjr+JgV2JZ8Us0GxJ6KoMu7+D9+xmlStsEuhEslzt9De5empnlH8Wj41SKXFs7QagYkZFrZVRZb8b0tHNweb2pXVItm3Ap4/EXZ8Bqc+CFf/G+Jzhjwt2WxAIwQZfpxyudRsU/xP2afUOFwkxhlkP7HYYvVk2kwRadyLy+3EGrSMSw3hJu1xw7qXYNRJ0g15GFFSPCyqjLtJryUpTmZr9lFIlV36vrPiYxifLsWFwxV3L2/qIFvBZGpvCjJtlFY5IqqZaatPa36KEhUWAKufhDfOA0MsXP+NJNOrkWc8dVoNqZYAGpl6Y8uC0Ysk9UKvvC7S2hZ5ZZC9mZhhjVjjXphlQxtK413Z59ByUJqCNcwkm400tXUqIrAXVcYd/LXuIXqrlZuCqgceaSqbD3nuY32eSTjKIUVR9Om4KzzkwMfkLCttXR4ONA0yNrGlAhxVYbl+f/gHeBdmKWDcO5ph2Z8g/0z4xQrInB7wEiH1dEy7AlrKYf8KWYdLE5gCqwaZkGFhT30bru7wzHMNhk63h9IqB9NyQgzJrH0e4kfB+LOU2VgAJJsNeEVoVkCCIOqMe4YtSI/Gj9cD710J3/5BuU0NE1UtLgw6DclmA7YYPRk2U1g896a2Ltq7PIqWQfbG3znYE5rxeqFuu9SEs+QGeGIyPFEAz82Dlsqw7OFwNlfYGZUUS3ysQYHFPgC3S6o9D7LxJeBGpt5MOAeMNtmJ1ZqWzqA8d483smQIdlQ76fJ4QzPuVT/Awe9h7i9kP2kpiZLj9qLOuEuzVEMw7hotzLpG6jxr2KXYvoaDymapxt0fBx+XZgmLcQ9XpYyfcclGZmr3EFv0HPzzJ/DYGHjuePjsLunnkjUDTvsDeLrhX7+QbshhZnNFizJeuyjCpjekWG0I8dqQPHd9DBReBKWfgmvw3Ea3x0tjW3DGHSIrqVrsS6ZODcW4r30BDGaY/jOFdhUYSurLRJ1xz7DFYG/vpqMrhF/4GVeBRg8b/q7cxoaByl4NTADj08zsrmtVfADGIR33MIRlGvdgfHISS/S/45SDT0P9Dhh/Npz/LNy+Ce7dCZe+CSf9Es7+M+xfKcWvw0hjayeV9g5l4u1Vm6B2K8y4OqRlMmwmWkNp2Jv2U3B3wLbBa97rnZ2I4uATmPojNykOk14TUZ2qJeV2Ui3Gnn6YgHHWwNYlkmEfoEw13CjZpTpkC5cgCDnAm0AaIAIviaL4pCAIicB7QC6wH7hUFMVmQXIrnwTOBtqBn4uiqFiAu3eDR15ykFoP5lQouEB6bD3ld32HEEcwlfYOFo1P6fn3uDQLnW4vB5vag/+/6IdyX2w/LGGZlX+Frnb+kf0gb1Vl85/bLxm4ImfaT2H3N7DsYamLM2um8vsBNvckUxVofNn4Buhjhyx3HIr0Xg17FlMQ5ahZMyE5H4rfhpkD32gOTWAKLOau1Qicm1TNpVv+F5qSJG/XYAZDHKIhDpcQQ7PbQGOXnvouHeMy4snxOyai16c/L/b92mSTbvRBhkOKy+1MzYkPvsJrwyvgdcOcG4M7XwGUFA+T05/rBu4RRXGTIAgWYKMgCF8DPwe+FUXxUUEQfg38GrgPOAsY5/szF3je97ciZMQfmsgUkkGbfQNs+UD6M+sahXYXPjrdHuqdnWTFHzK4/prsMl/zjVKUN3WQGGcgzhhi+/bh2A/C5vdg9vW4rRdStrt0cDVCQZAUDyuKYMn1UnLSqLw0wObyFgQBJocalulslTy/ggtD9vx6N+yNDaasTxCkm+M3D0pt9Mlj+z1MzgSmgbjB8y4ZXfuobdYjdlaj6W5D72nH6O0gVugkBugZFlgqc9GT7oLTfh/wXlrau9nb0MZFM4OU5O12QdErUhI1aUxwayiA1aTDoNUo0sg05G+vKIrVQLXva6cgCNuBLOB8YKHvsDeA75CM+/nAm6IkPLFWEIR4QRAyfOuETIZSE5ly5kBaoRSamfnzsIzNUpJqXxlkZvyhX0J/m/yuWieLJ6crdq0KhdUge1j9FCDACbdT0CzdpLZVtQweEohJgB+/BK+fA1/eBxc8p/i2tlTaGZNixhzqzWzbR9DVKoX9QkSRhr0pl0mFAyXvwKkP9HuIv5Zerq5MD/VljHeu4y/dl/BMzYWY9BpyEmLJSYwlJyGG4xKMHGcROM7s4d8bdrF8Rw0f3XIiep0OEKTfN0GQavL9/17xmDTKLnu2lBQOgBKfEmTQydQtH0iyySNQ/tgbSYJAmUamgD7NgiDkAtOBdUBaL4NdgxS2Acnwl/c6rcL3miLGXTEJAkGAOdfDv++UxPhHzVNgd+HDP6Qjq5fRjTPqyEmMoUzhpGp5U7syWti9cdbCpjdh6uVgy2aiyY0gwNZKB6dOHKK9e9QJMP9eWPFnGHuq4sOJN1e0cNLY5NAX2vQmJI+HnNAfVP0Ne7WhfM6tGTD2NKmhadH/6zfcUePoRK8VSAi0Smjt84g6E+de+VuuSs0kxTzwFKed7Rae2fwD290ZTEkfxPie9RjUbIF/3Qw3LgvIgy4ptyMEqwQpirDuBUibDLnzAz9fYZItyjQyyU6oCoJgBpYAvxRFsU+K3OelB5TVEwThRkEQigRBKKqvr5d9XoxBS3ysXpku1cJLpJKxDYHLpA43FX7jHt/Xo85PtbBLwVp3r1ek0t5BttLJ1LXPgrdbeuxGUsDLTYqT36l68n2SR/fvu6TwjkLUtLioc3aGnkytLYWKDZLXrsBToEmvJTHOQHWoInnTrgBnlVSF1A91DhepFlNg07bam6DkXYQplzJhzGhSLaZB49yzfHpCRfuH0BPSm+CSN0Cjgfevgq5B+iAOo7hcevqyBpOf2L9SSoLPvSkinuCVEg+TZdwFQdAjGfa3RVH8yPdyrSAIGb73MwD/xOZKoHePdbbvtT6IoviSKIqzRFGclZKScvjbgxLQGLLBMMTB9J9KJWPO8M8kDYUqeweCcGRVw7g0C3sbWulWaKhurdNFt0dUNpna0Swlqwou7OONFWRa2SZXY0argx+/LCXgltwgtYgrgH+wQ2GoydRNb0oVWFMvV2BXEulWBYbT5J8FpngpsdoPNQ5XwJUyFL0qVeIcf4uswzNsMWTFx7DxgAyxuIRR8OO/Q+022YO/RVGkpMIefEhm7fMQmyQ5exFAstkwPHXuvuqXV4Dtoig+3uutTwF/Gv5q4JNer18lSBwPtCgVb/eTYTNR41BIU2XWdZJHuelNZdYLE5XNHaSYjUfof4xPN9PtEdnfoIyEbnlTGGrc170kxaJPurvPywWZNirtHdjlduMl5kmDLcrXSlU3CrC5ogWtRqAgFE2ZbhdsfhcmngtxCoR3fGQoMXlMb5KM1vbPJKXDw/APxpaNu0vKU41eBKkTZZ82KzeBDftl6viPOw0W/lqSUNj42pCHVzR30NDaFVx9e+MeKPtSsgP6IEsoFSbZbKSxrStkeQ45nvuJwJXAKYIgFPv+nA08CpwuCMIu4DTfvwG+APYCu4GXAXm39wBIV3IiU/JY6YO68TXFvMFwUNXS0Sfe7mecwjIEPTXuSiVUO1th3fOQvxjSJ/d5y29QA1KInHqZpIW+/P+kaUYhsrmyhfw0CyZ9CN2IOz6Tnk4USKT2Ji3Uhj0/064AT6eU8D2MOkeADUylH4OzGubdGtAWZo1KoM7Z2TMEZkgW/I+UL/jyPqjcOOih/mTq9GCM+/qXQKOD2dcFfm6YSDYb8XhF7B2hDSUa0riLorhKFEVBFMUpoihO8/35QhTFRlEUTxVFcZwoiqeJotjkO14URfFWURTHiKJYKIpiUUg77IcMm4mG1i463Qp1Ls65ARyVUPaFMuuFAb+O++GMTTWjEVAsqVre3I4g0O+NJCg2viYZvvn3HvGW37jLDs34OecvkkDWR9cP2YE5GKIosrnCztRQ4+2b3pCGW+ctDG2dw8iwmmhq6wpdvyVzOqROkvTJe9Ha6aa10y3fuIsirH1Oqp8fc2pAW5g5SpqfW3RA5vxcjUYKw5nT4f2roW3g0YzFB+0YdZrAZ9+6WuCHf0gJeoty1Wah4m9kqg5RQyvqOlThUNy5zqHQJJhxZ4I1O2I7Vr1ekaoWF9n9GHeTXsuopDh2KWXcmzpIs5iUGVjR7YI1z0gVCDmzj3g7yWwk3Wpia6DyvyabNPCipRI+vyfo7VU0d2Bv7w5t1mbTXknad/pVkkFSEMU+536d98oiqC/redn/9Cu7DPLgWkl7Ze5NAX+v49MtWIw6NgyVVO1NbCJc+ga01ko38gFkKEoq7EzOsqHXBvj///1zUrhwmDXbh8I/Rer7PaHNGo5K4+5vL1ZM+lerkxqZ9i2XJuVEGA1tnXS5vf167gD5aWZFPXfFZAeK34bWGlhwpNfuZ3JWAEnV3uTMkeKyWz6ArUeGG+Tgf5wPaWrPprekWu3pPw1+jQFItx1q2AuZwktB0PZJrNYFOIGJtc9JydmpPwn48lqNwPRRCWwMxLiDpDN01p9hz1JY/ucj3u72eNlS2RL4z3DtC9K4w4ILg1LtDCfZCbHkp5n5dnvd0AcPQpQbdwUHVcy4OmL1ZnrruPdHfpqFA43tisivVjS1K1Mp43HD6r9JbfB5Jw942KRMG3vrW4PTCpp/D6RPga8fgO7APwtbKlowaDXBD8T2dEvGctwZYM0c+vgA8X/OFYm7W9KkfZa815NbCkh6oHm/lFuYdY2kUR8Es0YlsLPOSUt7gLHkmT+HqVdIeZZdX/d5a2etE1e3N7DJS98/B/+5DyacCxe+FNheholFE1LZsL8JR7DaQkSpcU9Xqku1N+YUSW+m5J8BT48PN5W+JNTAnrsFj1dkb4hDp7vcXqodLrKVqJTZukSqR59/76C1wwWZVrwibK8JwnvXaOHMhyXt8rXPB3x6SYWdiZlWDLogfw12/VcKGYQoEjYQin/Op10hPUntWSqt6+9OlVMKuf5l6Qll9g1BX35WboIkmhno/FxBkKqk0iZLMhTNB3re8itBTpPrua95Gr76DUw8Dy55HXQKSDyHgVPGp+L2iqza1RD0GlFp3M1GHRajTvmJTLNvgE4HbHlf2XVDpL/u1N74Pc9ddaGFZqrsHYiiApUyXi+selxK4uUvHvTQoJOqfvIWSLXcKx+HVvnNcF6vyNZKB1NC0ZPZ+IaU8Bt3RvBrDILZqMOs5Oc8fzHEJELxPwAplm8x6Yg1DNGo3umUSoUnXSAlsoNkWk48Wo0gP6naG0OsFH8XRXjjXNj5FSB1pibGGeSFElc/Cf+9X/o+Ln4VtMrOB1aSmaMSsJp0LN0RfGgmKo07hKh3PRA5cyC9ENb/XVbzxHBRae/AbNRhNfX/S5iXHIdOI1AW4jT6HjXIUD33ss8lKd+T7h4y8ZYVH4MtRs+2yhBmqp7+R+huh+8ekX3KvsY2WjvdwXemtlTC7q+lWLtWYYG1Xij6OdcZJO+99FNY8zQ19g558fYf/iE5PTKblgYi1qCjINM6dKfqQCSNgZ99CDoTvHMpvHM5NQd2MDXbNrQS5MrHpfDd5IukZHwEG3aQRi2ePD6V78rqgq53j2rjHnJr9uEIAsy+Huq2SdNYIgS/jvtAH2CDTkNeclzIte6KNDCJIqz4CyTkScmqIRAEIfikqp+UfJh1LWx8vU81yGD4O1ODlvktflvqlg3zUIcMpWrd/ZxyP0w6H/57P+dXPU6mZQgj5/VIuis5cyE7dMnlWaMSKS630+UOsqM6Zw7ctBpO/yPivhW85LiVG8UPpcqsgVjxmCSgVniJFGMP481YSU6ZkEJDaxdbgnR8ota4ZygxS7U//Hoz6yNHb6ayuf8Gpt7kKzCVqby5HZ1GCFwhsDd7lkJ1sTRsQ+YvUUGmjbIaZ2gSCgt/LclJ/Pd3sg7fXNFCjF7LmJQgpJK9XqlKJu9kSBwd+PkBkKaEBEFv9DFw8Wtwwh2c5fqcX7f8YfAcU9mXUjI1RK/dz6zcBDrdXvmaQv2hM8CJd7LxR1/xtXcm8w6+CM/N7QnV9GH5n2HpQzDlcrjwxagx7AAn56ciCAQdmola455ui6HO2amYpkoPfr2Z7ZGjN1PV0tFH6rc/8tMslDe3094VfJdteVM7mfExoU2OX/lXsGQGVC5XkGmly+MNbR5nXLJUPbPrqwFFsnqzuaKFyVlWdIHWRgPs+w5aDirekdofGTYTdU4XbiU/5xoN3tP+yO/c1zKhdT28dhY4BlAIWfs82I6TKksUYNYoSURMls7MEKxviuH27jtovWwJaA09oRqa90sHfPeoNOhl6hWSVPQIzEQNhcQ4A9Nz4llWdowZ9wybCVFEEd3jI5h1nTSRZdMbyq8dIG2dbuzt3X2GdPRHfpoZUSQkA1ne3BFajfuB7+HAajjhdtDJ1ysJOanqZ+5NkiH66v5B5666PZLnWJgVZEhm4xuSzvzEHwW5Ufmk20x4RRSRgO1NQ1snb7lPY9mMpyR9lb+fJol19aa6BA6sgrk3KubxplpNHJcYy4b9QSRVD6Ok3E5uUizmiaf1hGrYtwKenQvvXCblYKb9DM5/JuoMu59TJqSyuaKFOmfgT29Ra9zTlW5k6o1fb6Zo5PVm/JUyQ3ru6aFrzFQ2h1jjvuoJSV1vkLFu/ZGXbCZGr2VrKElVkISfTnsQardIJa0DsKuuFVe3l6k5QSRT2xpgx+fSk0kAN7BgOTS/QNkQpL/r1T3mdLj2SxA98MqZPWWSgOS16+Ng+pWKXnvWqAQ2HmiWJyI2CMXlvZQgfaEabtsgjerb+R/pyeq8p6PWsINU7w7wXZn8SjA/UWvcexo8wmHcAeb+QtLBXv9ieNaXiV/HPXuImPuoxFgMWk3QMgTtXW4aWruCT6Y27JJCIrNvkEJbAaDVCEzMsAQmIDYQky+CrFnw7f9CV/91/1sqpJtIYaBlkKIoCVl5u8NW23446WH6nNf0Hq+XMRWu/0bSx3n7Eimf4KyBLR9KCeMYBWbL9mJmbgINrV0caJSv1344NS0uah2dRypB2rLgktfgrlL40VOKS0IMN5MyrKRbTSwLIu4etd95htU/hiwMSVWQaoLHnSkZicY94bmGDA557oMbd51Ww5jU4GUI/Gp9Q91EBmTdi1Lcc9a1QZ1ekGmjtNoRsswpggBn/klq1lnzdL+HlFTYsZikYSEBsfzPsPVDaWRd6oTQ9imTnrGSCleG1Rw+Xs+WDdf+R+ob+PQ2+MdFUmhy7i8UvS7A7FxJRCyU0ExxuRSzH1Dm15YVEYM3QkUQBBZNSGHlroaAK4yi1rhbY3TE6LXh89wFAX70pPS498mtUoXECFDZ3IFOI5BqGbqCJT/NHPRUph6p32A89w47FL/jU9cbYmTeABRkWmntdHOwKXhvrofj5krlfquf7DdRuKWyhcIsW2DTh7Z8CN/9SQrHHKZLH04SYvUYdBrFP+d1DhcaQRoM0YPJCle8L4UzareGbVj02BQzVpMupKRqcXkLeq3ApIwQdPijhEXjU2ntdFMU4M0wao27IAhkhKPWvTfWDFj8qFTzPkLhmSp7B+k2k6wKlvw0C5X2DpxB6FEc0nEPwrj/8A/obpMSmkHin9kaclLVz2m/l7Rflj3U5+VOt4ft1Y7A6tvLN8DHt8Bx86Qb/jB6hIIgKDd5rBc1DhfJZuOR1UJavRTOuOxtOPcJRa/pR6MRmDkqIWTPfWKGNTQd/ijhxLHJGLSagEsio9a4Q5i6VA9n6k+k8Mw3fxiR8Iy/gUkOh2QIAvfey5s7iNFr+3pycvB68k1MjwAAIABJREFUpBvfcfMgc1rA1/WTn25GpxECl/8diMTRUkjhh7elocs+pHp6UX5nqv0gvPsT6UZ/2dvDkkQ9nHSlG5mQBmMPqCkjCNJUqTBqnM/KTWRPfRvNbYFXAXm8IlsqWoIfqxdlxBl1zB2dyNIASyJV4z4UggA/+psUTx6B8EyV3SXbuI/3GfedQcgQlDe1k50wcBfsgJR9KRnAELx2AKNOy7g0i3KeO0hSwzHxkp6IrzKjxJdMlWXcO51S3bS7SwpXxCUpt7cAyEmIZZ9CYxT91DlcgU1gUphQ6t1317XS1uUJTao5yjhlQip769sCGqcZ1cY9w2ai1uHCE2oSbiismXDW8Idn3B4vNQ6X7KlI2QkxxOi1QZVDSjXuQYRk1r0AthxFmlwKMq2UVrWEXCLXQ0wCnHyf1NTkk4rdUiEJTQ15w/R64MPrJI2cS16DlPHK7CkICjKt1Ds7e/TXlSDg2akKMzUnHr1WYEMQImIlfiXIQGR+o5xTfCWRgYRmotq4p9ticHtFGhWYFD4kIxCeqfHduIaqlPGj0QiMTTUHLEMgiqJPxz3ASpnqzbB/pTSmUIEml4JMKw2tXdQp2Zg26zopRPPFPbB1CdvLG5giR2jqv7+TSjvP/jOMDWyknNL4J0UFqzFyOK5uD/b27tBkJkLEpNcyOcsW+PAO4IdyqdopL9BqpyhmVFIcY1LiAupWjWrjnmENYyPT4fQJz9w2LOGZoYZ09EcwGjMtHd04O91kB5pMXfci6GMVa8M/lFRVKO4OUrXTec9IX394La/br+a27jegYffA5xS9CmuflUJNs69Xbi9BMinDiiDA1kplQlb+BqaRDMuAFJrZXNES8JCZEl/zUkDVTkcBp0xIZd3eJto65TVWRrVxD2uXan9YM2HxI3BwjTQ1PcxU2qUKFrmeO0jlkHXOTuzt8hNVh9QgA/Dc2xqkEXdTL5fCHwowySdDoJQR6yH3RLijhJ1nvME670RmVL8Lz8yE18+VShx7KwruWQaf3wtjT4czHlZ2H0ESZ9QxOjlOMc+9JtDxemFi5qhEujzegDqTO7o8lNU6j6l4u59FE1Lp8nhZtVveAI+oNu6HulTD1MjUH9OukIYzfPP7sIdngvLcg5Ah8Ou4B+S5F70Gns6QE6m9MRt15CXHKeu5+9FoWOWdyi3dv6Txxh/g1AelCU5LroPHJ8B/fgs7/wsfXA3J+b5hDpGjIDg5y6bY/0tAE5jCyKxcySkoCiCpurWqBY9XPGYqZXozOzcRi1Enu1s1qo17YpwBg1YT3lr3w/E3Nw1DeKaiuYPEOAMxBvm1vP5yyEA6VQNuYHJ3SbNmx5yqeKJxUmaI2u6DsKWyhTSrkZSM42D+3XD7D3Dlx5J07/oX4Z1LpDm6V7wnNfREEIVZNqpbXDQokF8KeDB2mEg2G8lLjgtoeEfxQd9Q82PQuOu1GubnJ7OsrE5W0UFUG3dBEKShHfZhNO4wbOGZqgBq3P1k2kyYjbqANGbKm9uxmnTYYmROpyn9RGrvP/7mgPYmh4JMKxXNHYEPUZZBSYW9b/OSRgNjFknj2+7eDov/D676GBJGKX7tUPHnI0IWV0PSZTHpNQNO9hpOZo5KYOOBJlnGqtvj5evSWrLiY0ixjFylz0iyaHwqtY5OWQ5QVBt3GKZa9/4YhvBMpX1oHffDEQSBcWnmgEbulTcFWAa57nlIGit57grTk1StVjY043R1s7e+beCZqeZUOP4macxiBFKQ5c9HKGDcHS7SrabAexrCwOzcBJrbu9kzxHD3bo+XO9/9gfX7m7hlkfKSCNHCwvFSSaSc0EzUG3dJgmAYY+5+eodnPr9H8eVFUfR57oHXno9PswTUpVoRiNRv+Qao3CjF2sOguOfXdldEIbIX/mTklCh9nLea9OQmxSqSbK5zdI54SMbPzFGSiNjGQerd3R4vv3yvmC+21HD/ORP56dzIe7IaLlIsRqZm22R1q0a9cU+3maht6QxdTTAYrJlw8q9g7zI4uE7Rpe3t3bR3eQL23AHGpVloauuSFZ8VRZGKQIZ0rH1OGkMYwKSlQEg2G0m3mhTxUHsTtMxvBDE5y6ZIxUzNCHen9mZMShwJsXo2DBB3d3u83P1+CZ9vrua3Z0/g+vnhHWsYDSyakEpxuX3I/p6oN+4ZVhNdHi9NAZT+Kcqsa6UBFSseU3TZSpk67v0RiAxBvbOTTrdXXlimpVKKt8+4EozmgPcll4IwJFU3V7SQkxhDYlyA2jkRxOQsG5X2jqD0WPyIoiiFZUa4UsaPIAjMHJXYrwyBxyty7wclfFpSxX2LJ3DjgmM3HNObUyakIoqwfOfgAzyi3rin+/WuRyLuDtJginm3wu6voeoHxZatlKnj3h/5aZLhldPM5C+DlBWW2fB3QIQ5Nwa8p0AoyLSyp76Vjq7AmlsGY3OlnSnBjtWLEPxPHaGIq7V0dNPl9pIaQQnJWbkJ7Gto6/Ok6fGK/OrDEj4uruJXZ47n5oWqYfczOdNGstk4pBRB1Bv3jOFuZOqP2TeAyQYr/qLYkv4hHYFWy4AUl4uP1VMmo9ZddgNTdwdsfF0aYRbmapJJmTa8IuyoUcZ7b27rorypQ74SZIRSoECTV6TUuPfGLyLmL4n0ekXuW7KZjzZVcvfp+dy6aOxIbi/i0GgEFo1PYcXR7rmPSCPT4ZisUoJxx2dHDhkOksrmDkx6TVBhBEEQyE+1yCqH9Ne4D9nAtPl96GgKS/nj4UzOUmhgto/Nvjh1YZQb9/hYAzmJMSHlI2p90gMjqStzOIXZNgw6DRsPNOH1ivzmoy18uLGCO08dxx2njhvp7UUkp0xIxeEaXIZgyEJXQRBeBc4F6kRRnOx77ffADYD/1vFbURS/8L33G+A6wAPcIYriV8F+A3JIMhvRaYSR9dxBMu7fPwsr/yp1N4ZIVUsHmfFBSPD6mJBiZHfJKpb+p5psm4mseANxOkEahCx6JdVD0UPC/r1cFNuO6WCMNAxZHyOFmvSxYIiVXtNoJfXHtEIYdWLI39tQZMXHYIvRK9aRufFAM4IgxayjncmZtpDCMrUtkdHA1BujTsuULBvr9zfz/z7eyntF5dx+ylh+eZpq2AfipHHJ6LWD2wY5XQyvA88Abx72+hOiKPaJQwiCMAm4HCgAMoFvBEHIF0VRueDpYWg1AmnWEap1701soiQytfpJWPgbSA7tg1nZHHgDU29+7lnCaM0zsHbw437m+8Nbgxyk0UtDoc9/dlimEAmCQEGmVZHKEFEU+XxzFbNzE7GaZDZpRTCTs2x8ubWGlo5u+U1nvfCHZVJHUO63P2bmJvDi8r2UlNu5ZeEY7j49PyLq8CMVi0nPnLxEBpG/G9q4i6K4QhCEXJnXPB94VxTFTmCfIAi7gTnA9zLPD4p0m/JjyIJi3m2SUuLKx+HC50NaqtLuYmKw8yE9bkaXL0EcdSJ1M/5/e3ceX2V9J3r8880eQgiBLJAEZAsJEFYRUVFZtLhVFLs5LjDT1ulte6d1bmvX17xmbl+dOvfa26nTqbduI3ZaO1W5imCtAoPVqVVZw5KwWiQLWSAJCdlzvveP5wkeIZCck3NyTp7zfb9evDh5znN+5xt+4ZvnfJ/f8iAnGjs40djBh6fbON7QwfGGDtq6FR9x9BDHjUWZPLRsgrNVXlcbdLY6jztbna+7zkJ8Msz+zKC+p0BcPXUsj7x+iIqG1sBXq/RzoPoMR+vO8ldLJocwusjp/fSxv6qJq6dmBfz6XR82cNnYESQnRNf2dNdOy+YXbx7jr6+fwjdXFlliH4BHPj2XX3/x4s8PZv7xV0XkfmA78D9UtQHI5+PXihXusQuIyAPAAwATJ04cRBhOcg/1pJegjMyGy9c6SxIs/RZkTgqqmfauHupbOoIaKQM4I3eaq5Fb/je5M24kF1jo97TPp1Q2tnG4tpljdWdZWpQNOenBvVeYrJqXzyOvH+KlXZV8dXnwn4I27K4iIU64pWR8CKOLnJK8j2aqBprcWzu7+a+jp7g3CicBLSnM4u1vLSN/EKXIWDM+49L5Idgbqo8BU4F5QDXw40AbUNXHVXWhqi7Mzs4OMgzH+FEpVDe1hW4Hn8G45m+cGvXb/xx0E72fQoIuy+x8FtJyYPpNfT4dFydMGDOC5cW5fOHaKUyLssQOziJmi6eM4cWdlUH3q8+nbNhTxfXTs8kcxuPb/Y0dmUxeRkpQI2beOlxPZ7ePG2bkhCGywSvIHGGJPYSCSu6qWqOqParqA57AKb0AVAIT/E4tcI+F1biMFNq7fDS1hX6xqYCNyoP598LuXzmTfoJQ2RD8GHfOVMOh38P8e5yd7Iex1QsK+KD+LLvcbdUC9f6fT1Pd1M7t8/JCHFlkleRnBDViZktZDekpCVwxeUwYojLRJqjkLiL+n3HvBPa5jzcAnxORZBGZDBQC7w0uxP71fjyJiro7wDVfd0ak/PHRoF5eNYjZqez+d2dEzPz7gnrvaHJzyThSEuNYv7MiqNdv2FNFamI8N8zIDXFkkVWSn8Gx+rM0tw/8YsbnU7aW17K0KIfE+GE/AtoMQL+9LCLP4dwQLRKRChH5PPC/RGSviJQCy4AHAVR1P/Bb4ADwGvCVcI6U6TXu3Fj3KEnumZfBnM85k35aBr7nYa+KxjZEghiu5vPBzl/CpGth7PCf0ZeekshNs8bxyp5qOroD+zHq7PaxaW81N87MJS058kvbhlLvTNVA7jPtrmikvqUzaksyJvT6Te6qereqjlfVRFUtUNWnVPU+VZ2tqnNU9XZVrfY7/4eqOlVVi1T1d+EN3xEVs1TPt+RB6OmEP/5LwC+tamwjNz2FpIQAr7A+2AaNx52buh6xekEBTW1dbC0L7Jfk20fqaGztYpXHSjLgt/xvAMl984Ea4uOEpdMtuccKT3w+y05PJk4iPEv1fFnTYNZqeP8paL34cqZ9qWwIfB13wLmRmpoJxbcF/toodc20LHJHJfPizsDuX7y8u4rRIxK5tnBwN+ujUU56CrmjkgOqu28pq+WKSZlkjBje92HMwHkiuSfGx5GdnhxdV+4A133DGSP+p8DGvFc1tZEf6Njus/VQttFZijcxemYfDlZ8nHDH/Hy2Haztd4nTXq2d3by+v4ZbZo8P/NPPMFGSN/CbqidOt3Kwptlz9x7MpXnmJ39cRuq52XdRI2cGzPikM7GpfWD/EX0+pbqxPfBhkHuec2aRLrg/iECj2+r5BXS7wxoH4o0DNbR19XD7XO+VZHqV5GdwtK6F1s5Lry8CsLmsBsCSe4zxTHJ3xrpHWXIHuPYb0NE04L1W61s66OzxkR9IWUYVdqyDgkXOLxSPKRqXTkn+KNYPsDSzYXcV40alsGiSd4f8leQ7K2eWVfdfd99SVsvU7DQmZaUNQWQmWngmuUdsL9X+5M2DwpXwzs+ho/8leCt6l/oNZBjkh+/AqcNw+Zpgo4x6q+cXsLeyqd816hvOdvLmoTpun5dHXJx3J8T0jpjp3WHqYs60d/GnY6e4YaZdtccazyT38RkptHR0BzT2d8hc901nudzff8e5yr6EqmA26dj5LCSPgll3DibKqHb7vDwS4oQX+xnz/rt9J+n2qadLMgC5o5LJGpnE3n5mqv7hUB3dPrWSTAzyTHKPurHu/iZc4ZRndj4L7z1xyVN7Z6cOuObe1gj7X4LZn3KW6vWorJHJLC3K5qVdlfRcYr/cl3dXMjU77dzGFl4lIpTkZ/S7LPKWsloyRySyYGLmEEVmooVnknvUzVI937LvObsYvfZtOLbtoqdVNbaRnpJA+kCXp937PHS3wQLvlmR6rV5QQM2ZDv7rSH2fz1c1tvHen0+zal5+TKxRUpKXweHaFtq7+p7g1d3jY2t5LcuKc4j3cInK9M1DyT2Kr9wB4uLgzl9A1nR4fi2cPtbnaZWNAazj3nsjddwcp7bvcStm5DAqJeGiyxFsLK1CFc+XZHqV5GfQ49OL3lTdcbyBprYuK8nEKM8k996p+lF75Q7Odnx3/9p5/Nzd0H7hf8qKQDbpqNoJNXs9fSPVX3JCPJ+cm8dr+0/S0nHhEMCXd1cxtyAjZkaF9G5HeLHx7lvKa0mKj+O66d6byGX655nknpQQR9bIZE6eiaJZqn0ZMwU+/QzUH4b1Dzjrwfipamwb+EiZHeuc7fBmfzr0cUap1QsKaO/y8ere6o8dP1Lbwv6qM9w+r8/tAzwpf3QqmSMSL7r87+YDNVw5ZQwjPba2jhkYzyR3cEozUX3l3mvKUrjpYTj0O/jPH5473NzexZn27oGNlOlogX0vOiNkUob/3qADtWDiaCZnpV1QmtmwpwoR+OQcb2zKMRC9N1X72o7waF0Lx+rPcqMNgYxZnkruUTvWvS+LvujMJn3rESdJA1WNAWzSsX89dLbExI1UfyLC6vn5/OnYaSoaWgFnn9QNuyu5eupYcqJo4+ehUJKfwaGa5gtWzdzizkpdXmwLhcUqTyX3YXPlDs5G07f8GCZeBS99Bap2U9noJKsBXbnvWAfZxTBhUf/neswd853Sy/9zZ6yWVjTx51OtrJobOyWZXiV5GXT7lIMnPz65a3NZLTPGjxrU/rNmePNUch+XkUJTWxeVjVFed++VkASf+SWMGAu/+QtO1TjJqt9NOmr2Q+V258o/Bob8nW/CmBFcOXkM63c5W/C9vLuKpPg4VpaMi3RoQ653pqp/3b3hbCc7jjfY2u0xzlPJ/RMzcxmZnMB9T71L/QBXEIy4kdnOCJrW01z1/tdIi+8me2TypV+zYx3EJzkbgsSouy53tuDbcbyBV0qrWFqUTUZq7C1nO2FMKqNSEj5Wd992qJYen7LChkDGNE/dRp+Wk87Ta6/g/qff5d4n3+U3Dyxm9IhhsDHy+Llw52MUPL+W51N/RNwLL0JXO3T7/fH/+mw9zLoD0sZGOvKIublkHH/38j6+/9I+6po7WBVDo2T89TVTdXNZLdnpyczJj50b7eZCnrpyB1g0eQxP3L+QY3VnWfP0e9G51kwfToxfyQ+67iE/oRlqy6HlpJPIE1Jg5DjIKYaJi2H6TbDoAWfGawxLT0lk5axxlJ9sJi0pnhUxXIIoyc+gvLqZzm4fnd0+3jxYx4riHE8vnGb656kr917XFmbzr/cs4L/9+w4+/8x21v3VIlKT4gNqo/ZMO9sO1XHXgoIhmbr96t5qnuq5lTVffISMsXYTbCDuWlDAy7urWFkyjpTEwPrXS0ryM+js8XG4tpmGs120dHTbrFTjvSv3XjfOzOUnn53H9uOneeCX2we8wXJnt4/H/3CUZY9s46EXSnnjwMkwR+rYtLeauQUZTLTEPmDXTMvir6+fwpeXDv/NwAejJO+jmaqby2pITojjmmlZEY7KRJpnkzvAJ+fm8fBdc3jrcD1f/fUuunp8lzz/rcN13PzTP/CPr5azeMpY0lMS2Foe2MbMwTh+6iylFU3cGkMTcEIhPk74zs0zmJaTHulQImrS2DRGJjs3VTeX1bBkWlbAn1SN93g6uQN8ZuEE/ueqWbxxoIa//e2ePpeLrWho5Uu/3MF9T71Ht095as1Cnlp7BUuLcthaXofvEkvMhsImdyr9LbMtuZvAxcUJM/NG8dq+k1Q0tNnGHAbwaM39fPdfNYnWzh4e/l05qYlxPLx6DnFxQntXD7948xg/33YEEfjmyiI+v2TyufrtiuIcXtlTRWllE/MmjA5bfBv3VDN/4mibcGKCNjs/g/c+OA04P7fGxERyB/jS9VNp7ejm0a1HSE2M55ppWfxg0wFOnG7j1tnj+e6tMy6Y9n/99GziBLaW1YQtuR+ra+FA9Rm+f6v39j41Q6d3hci5BRkxtwSD6VvMJHeAB2+cTmtnD0++/QHr3jlOYc5Ifv2FK7n6IjefMtOSuPyyTLaU1/K3nygKS0y9qxtavd0MxpwC5+LDJi6ZXjGV3EWE7906g8y0JEYkxXPv4stIjL/0bYflxbn802vlnGxqP7eVXyhtLK1m4WWZ53aSMiYYU7NH8ov7LmeJjZIxLs/fUD2fiPCVZdP4y2sm95vYgXOTY8IxauZIbTPlJ5u5za7aTQisnDWONFu73bhiLrkHqjBnJAWZqWwtrwl52xtLqxGBm22UjDEmxCy590NEuGFGLm8fqb/oRsTB2lRazaJJY85tEWiMMaFiyX0Alhfn0N7l449H60PW5sGTzRyubbGSjDEmLPpN7iLytIjUisg+v2NjROQNETns/p3pHhcReVREjohIqYgsCGfwQ+XKKWMYkRTPlrLQ1d03lVYRJ3BTiSV3Y0zoDeTK/RngpvOOfRvYoqqFwBb3a4CbgUL3zwPAY6EJM7KSE+K5tjCLreW1qA5+tqqqsrG0msVTxpKd3s/a7cYYE4R+k7uq/gE4fd7hVcA69/E64A6/48+q40/AaBHxxKXpiuJcqpvaKatu7v/kfpRVN3Os/iy3zckLQWTGGHOhYGvuuapa7T4+CfTOnMgHTvidV+EeG/aWFmcDhGTUzMbSKuLjhJWzbMKJMSY8Bn1DVZ06RcC1ChF5QES2i8j2urq6wYYRdjnpKcwtyGDzIOvuqsqmvdVcPXUsY/vbTs8YY4IUbHKv6S23uH/3ZrxKYILfeQXusQuo6uOqulBVF2ZnZwcZxtBaMSOXPRWN1DUHvz/rvsozHD/VaqNkjDFhFWxy3wCscR+vAV72O36/O2pmMdDkV74Z9pYX56AK2w4Gf/W+cW8VCXHCylnjQhiZMcZ83ECGQj4HvAMUiUiFiHweeBi4UUQOAze4XwO8ChwDjgBPAF8OS9QRMitvFLmjkoNeikBV2VRazZLCrOGxcbcxZtjqdyEKVb37Ik+t6ONcBb4y2KCilYiwvDiXDbsr6ez2kZQQ2AefPRVNVDS08bUVhWGK0BhjHDZDNUArinM429lzbmOEQGwqrSIxXviElWSMMWFmyT1A10zLIjkhjs1lgQ2J9Pmcksx1hdlkpCaGKTpjjHFYcg9QalI8V08dy5bymoBmq+460UhVUzu3zbVRMsaY8LPkHoQVM3I5cbqNo3UtA37NxtIqkhLiuMF2yjHGDAFL7kFY7m5APNCFxHp8yqt7q1k6PZv0FCvJGGPCz5J7EPJGpzJj/Ci2DGBIZO2Zdu5/+l1qznRw53xPrMRgjBkGLLkHaUVxDjuON9DY2nnRc7YdrOXmn77FjuMN/NNds7mpxEbJGGOGhiX3IC2fkUOPT3nz0IXr4nR2+/jRq2Ws/bf3yU5P5pWvLuGzV0xERCIQqTEmFtluukGaWzCasWlJbCmrZdW8j8otH55q5b//Zhd7TjRy7+KJfP/WmaQkxkcwUmNMLLLkHqT4OGFpUQ5vHDhJd4+PhPg4XtlTxXfX7wWBx+5ZYBtfG2MixpL7INwwI4cXd1bw9pF6fr//JM+9d4IFE0fz08/NZ8KYEZEOzxgTwyy5D8KSwiwS44UvPrudbp/y5aVTefDG6STG260MY0xkWXIfhPSURJYV5bDzw0Z+8tm5XFs4PNalN8Z4nyX3QXr07vmIOJtoG2NMtLDkPkg2EsYYE42sOGyMMR5kyd0YYzzIkrsxxniQJXdjjPEgS+7GGONBltyNMcaDLLkbY4wHSSD7gIYtCJFm4OAATs0AmkJwTiTaisR7RqKtLKB+iN9zOLcVifcMZV9G6/cYifeMRFuFqprR5zOqGvE/wPYBnvd4KM6JRFvDPf4A2vJ8X8bQz0W/fRmt32OU/7sOSVvDrSzzSojOiURbkXjPSLQ1UNEav/1cBCZav8dIvGdUtRUtZZntqrow0nGYwbO+9A7ry+EtWq7cH490ACZkrC+9w/pyGIuKK3djjDGhFS1X7p4jIi39PL9NROwj7zBgfekdsdSXltyNMcaDhjS59/db02tEZKmIbPT7+mcisjaCIYWM9aX15XDl5b70Z1fuxhjjQUOe3EVkpIhsEZGdIrJXRFa5xyeJSJmIPCEi+0XkdRFJHer4zMBZX3qH9aX3ROLKvR24U1UXAMuAH4uIuM8VAv+qqrOARuCuCMQXSt18/N84JVKBhIn1pXdYX3pMJJK7AP8oIqXAZiAfyHWf+0BVd7uPdwCThj68kDoOzBSRZBEZDayIdEAhZn3pHdaXHhOJDbLvAbKBy1W1S0T+zEe/OTv8zusBhuXHPxFJADpU9YSI/BbYB3wA7IpsZCFnfekd1pceE4nkngHUuj9Ay4DLIhBDuM0CjgKo6kPAQ+efoKpLhzimcLC+xPpyGImVvgSGMLn3/tYEfgW8IiJ7ge1A+VDFMBRE5EvA3wBfj3Qs4WJ96R3Wl941ZMsPiMhc4AlVXTQkb2jCxvrSO6wvvWtIbqi6vzWfA74/FO9nwsf60jusL73NFg4zxhgPCsuVu4hMEJH/FJED7sSHr7nHx4jIGyJy2P070z1eLCLviEiHiHzjvLZGi8gLIlLuTqa4Khwxm76Fqi9FpEhEdvv9OSMiMVP/jAYh/n/5oNvGPhF5TkQ8OVZ8OAvLlbuIjAfGq+pOEUnHGRt7B7AWOK2qD4vIt4FMVf2WiOTg3J2/A2hQ1Uf82loHvKWqT4pIEjBCVRtDHrTpUyj70q/NeKASuFJVjw/V9xLrQtWXIpIPvA3MVNU2d1jhq6r6zNB/V+ZiwnLlrqrVqrrTfdwMlOFMilgFrHNPW4fzQ4Oq1qrq+0CXfzsikgFcBzzlntdpiX1ohaovz7MCOGqJfWiFuC8TgFR3tM0IoCrM4ZsAhf2GqohMAuYD7wK5qlrtPnWSj2bAXcxkoA74NxHZJSJPikhauGI1lzbIvvT3OZwbeSZCBtOXqloJPAJ8CFQDTar6etiCNUEJa3IXkZHAi8DXVfWM/3Pq1IP6qwklAAuAx1R1PnAW+HY4YjWXFoK+7G0nCbgdeD7kQZoBGWxfujX5VTgXX3lAmojcG6ZwTZDCltxFJBHnB+hXqrrePVzj1v1663+1/TRTAVSo6rvu1y/gJHumGO2/AAAC8UlEQVQzhELUl71uBnaqak3oIzX9CVFf3oCz3kydqnYB64GrwxWzCU64RssITp28TFX/j99TG4A17uM1wMuXakdVTwInRKTIPbQCOBDicM0lhKov/dyNlWQiIoR9+SGwWERGuG2uwKnfmygSrtEyS4C3gL2Azz38XZz63m+BiTgrs31GVU+LyDicKc+j3PNbcO7EnxGRecCTQBJwDPhLVW0IedCmTyHuyzScxDBFVZuG9jsxIe7LfwA+i7N87i7gC6rqv8CYiTCbxGSMMR5k2+wZY4wHWXI3xhgPsuRujDEeZMndGGM8yJK7McZ4kCV3Y4zxIEvuxjNEpMddTniPiOwUkavd43ki8oL7eKmIbHQfrxWRn12ivb8XkUq3zcMisl5EZg4gjrUikheq78uYYFhyN17SpqrzVHUu8B3gRwCqWqWqnwqyzZ+4bRYC/wFsFZHsfl6zFmfNFWMixpK78apRQAM4KyCKyL7BNqiq/wG8DvyF2+7ficj77oYVj4vjU8BC4FfuFX+qiFwuIm+KyA4R+X3vOi7GhJMld+MlqW5CLcdZsuIHYXiPnUCx+/hnqnqFqpYAqcBtqvoCzpT9e1R1Hs70/H8BPqWqlwNPAz8MQ1zGfExCpAMwJoTa3ISKONsxPisiJSF+D/F7vExEHsLZrGIMsB945bzzi4AS4A1njS3icdZANyasLLkbT1LVd0QkC+ivPh6o+cB2d8/QnwMLVfWEiPw90Nc+ogLsV1Xb+9cMKSvLGE8SkWKcq+RTIWzzLuATOEsW9ybyenfzC/8bts1Auvv4IJDtfpJARBJFZFaoYjLmYuzK3XhJqojsdh8LsEZVe9xySLAedHcZSgP2ActVtQ5ARJ5wj50E3vd7zTPA/xWRNuAqnMT/qLsncALwzzglHGPCxpb8NcYYD7KyjDHGeJCVZUzME5HvAZ8+7/DzqmpDFs2wZWUZY4zxICvLGGOMB1lyN8YYD7LkbowxHmTJ3RhjPMiSuzHGeND/B2Rxxjrj/MbpAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-71-HtqP_d3I",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 309
        },
        "outputId": "f5a9908c-3509-4249-e823-d9baca0bf1d0"
      },
      "source": [
        "bill_2018[['Billed_amount','esm_window_3_7', 'esm_window_3_3']].plot()"
      ],
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f60ea932c50>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 31
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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zuest5nvvvec2ZKOgcDaTV96Er4+a4aF+3Z4LN+hobrPS2mbFV6uWUiANURDVqbI8PAmObgabFVTy2nt2RqlQHSCGkmZ7amqqR2vtyegrKPycyaswMibKgErVPTEiolOue3ywDgq+gzGXQuckirAksLZB/UkITfT4+oq2jIKCgkIPnKhp5t+bcsi1h1g8Ia+8sUPD/XTCA6Rc96omM5RlQGutlALZmbAk6Xsv1SEVz11BQUHhNIrrWnhh61HW7CvGahMprG7mtRuc9qF2SnWTmeqmti6CYZ3pqFJtNEONPd4+6oKug8I65bqP/oXHr0Ex7goKCgp2yhtMvPDdET7eW4SAwPUzR9DSZmHd/hJqmsyEGXTuJwHyHbIDPRj3iA7xsDY4uhViJnWvRPUPB12QJEPQCxTjrqCg8LOnstHEy98X8MHuk9hsIldPj+eeC5KIDfYlr7yR1enFbMgo5ebz5MW+c90Y9zB/ybgb62ugeA+ce1/3QYIgbar2MmNGibkPAYainjvA/PnzmTRpEikpKdxxxx1YrVavr0lBoS/UNrexYlMOc5/8jnd3nWDRpFi+++M8/r04ldhgX0Ay0BPjgvhkX7HsefMrGgn113ZsnJ6OVqMiyNeHwPJdYLN0TYHsTFhSr3XdFeM+BNi0aRPBwcFnehkdeu4ZGRns3r2bJ554gtLS0h7Hr169mszMTA4fPkxVVRVr1qwZwNUOfgqqmpj++LcUVDW5H6zgdbbmVjDnP1t5bfsxLpsQw7e/P5+nfjWJeCepi0unxpFdZiSrtEHW3LnljYyJMriUEAk3aImr2QlaA8R1yyqXCEsCYzG0tci6bmeGRFjmP3v+Q25trlfnHBc6jofOecjtOEXP/RSe6rkHBkoypxaLhba2NkXy9zQ2Z1dQ1WjmcEkDoyIMZ3o5Pzs+3F1EoK8PG+6ZTVKk8/CJgysmxrL88xzW7ishJTbI5VibTeRIRSO/mhbvcly4v5axVXshaS5otM4HOTJmao9BtGd344rn7gJFz707nuq5X3rppURGRhIQEMDSpUtdjh0KNLS0887OQmy23itYO9hxtBqAsgZTn+dS8JycMiPTE0LdGnaAEH8tvxgfyfqMEtosTpwak1HKVQdK6ltpbrP2GG93kKyvIcpaDqMu7HlQRzqk55uqQ8Jzl+Nh9weKnnt3PNVz//rrrzGZTPzmN79h69atXHzxxT3/wocAa/cX88/PsxkbHcDMkb2vLDZbrOwtrAWkDA2FgaW+pY2S+launzVC9jlLp8ax6VA53+dVcklKdNcnP7sPsj6Fxa+S6yOlNPaU4+5guvWA9MClcberQ/ZiU1Xx3F0gKnruPSJXzx1Ar9ezaNEiNmzY0Ku1DiYcnXW25fetB8GBk/WY2iUPUDHuA092mVSUND4m0M3IU8wdHUG4Qdd9Y/XkT5Jh1wbA5w9SdewgAGOiXIfaxjfv4YQtElNgQs+DtP4QOKxXhUyKcXeBoufeFU/03JuamigrKwOkmPsXX3zBuHF9bgNwxsmrkIz7D3007jsLalAJMCkuiDKjYtwHmuxSu3GPlW/cNWoVS6YMY2tuJTUOuV6bDb76CwTEwO9+AB8/5h38EyODVATofXqezNJGXMM+ttkmOm+315mwUb3SdVeMuws667lPnDiRiy++mMLCQubNm0daWhrXXXed1/Tcy8rKmDVrFlFRUb3Wc7/77rtJS0tzSDUDkp67zWYjNTWVZcuWddNzj4yM9EjPfcaMGUyaNInzzz/fpZ57c3MzV155JRMnTiQtLY3IyEjuuOMOj17TYMNmE8mvaESnUZFVaqSq0c0/pQt2Hq0mNS6Y0VEBVCie+4CTXWYkKlDXUSkql19OicNiE9mQYc8SO7QGSvfDRY9JRnjJq8S2Hef/+bzjeqKi3fhYW+zG3Umj7M6Eje5VP1VB9PCE/mDatGlienp6l2M5OTlOwxIKZx9D5W99sqaFuU99x29mDOeD3Sd5+upJLJnSvRGDO5rNFib94xtunzsStUrgxe+Okr/8MjRqxdcaKOY/u42YID1v3dRDCqILrnzhRyxWkU13ToUXpoF/BNz2HahUtFls/O8fN3GXej0seR0mXu18km//gbhjJamtr/DsDXP5xXgXfYh3vQRf/wX+VNCtilUQhH2iKDrVRVDeTQoKMnGIRy2ZMowwf22v4+57Cmux2ETOHRVOVKAem0j3rjwK/YbZYuVoZZNHIZnOOHLeK79+CowlMH8FqCRTeqy6if+2/5LqsKnw2QM9h1MKttAWO40m/GSEZRwZM55tqg6JbJmzAUXPfeiTX+EoKQ9kzuhwth2pxmYTnUq6umLn0Wq0GhXTEkIwW6Sq3fIGEzFBvs5PaG8Fazvoe2eMFLpypKIJi01kfIzrfPWeuGJiLK9/voPgAy9B8pUw4tyO5/LKG7Gipv6ylwlfOx9W3wi3bQGfTn/bpiooy0R1/t+gAPfhvfBOxn34TNnrVIz7AKHouQ99cssbiQ/1xaDTcP7YCNZnlJJVaiQ1zjMjseNoDVOHh6D3URMdpAfcZMx8cgs0lcNtW/uyfAU7vdlM7UyIv5YnQzdAo4W2C/9B5/KjvPJGNCqB4QmjYclr8MFS+OphuOK5U4OOSfnwPmN+QcAPVe49d0c/VQ83VQd1WGYw7Aco9C9D6W/cuZP9nNERAGw74llopq65jewyI+eOku7WogMl495jIVPtMcjbBGWZYFFCN94gu8yIn1bNCCcyA7IoPcCsxq950zKf7yq7zpFf0cjICH+0GhWMvhhmPwD73oZDn5wadHQL+IVBTBoRBl23DdWsmiyu/uxqypqkbDPUGggd6XFYZtAad71eT01NzZD651fwDFEUqampQa/Xn+mluMVssXK8urmj6jDcoCMlNpAf8jwz7ruOSZXK5yZJG2Oh/lq0ahUVPaVD7n0DECVxqV6kwyl0J7vUSHJMoMfhNEDKWPnqr4h+4Xyku7pbzntueSNjozvdEVz4CMTPhM/ulwTAbDapX+rIC0ClItyg67bf8ty+58ipzeGlzJdOHQxL8jjXfdCGZeLi4iguLqaqqm/5xAqDG71eT1yc5xknA82xqmYsNrHLP+75YyJ4bdsxjKZ2Al3lNHdix9FqDDoNk+yhHEEQiA7SO/fc21rgwPsQOR4qs6Eyx2N9kd6yIaOEtPhgRoT5D8j1BgqbTSS7zMjiycN6N0HORji5E2HhM1xaOYY3fzxOdZOZcIOOJrOF4rpWrpneSVNG7QNL34BXzoM1v4UrnoXmyg4VyPAAbYc8MEBGZQa7ynYR4x/DxoKN3DThJkYGjZTSLI9+61E/1UFr3B2VmwoKgwFHZeq4Tnohc8dE8NL3Bew8WsP8CdE9ndqFnQU1nJMY2iXtMTpI7zzmfngtmOrhV2/BB7+CyiwGovd8u9XGgx9nsGz6cFYsObs2xYvrWmkyW3oXb7eYYfNj0oft5Bv4ZVUrr207xoaMUm45L7HLhnsXguJg8avw4dWw6jfSMbvkQLhBR3VjdcfQVw6+QoguhLfmv8WSDUt44cALPD3vaQgfDVYzNBRBSIKs5Q7asIyCwmAir6IRH7VAYvgpT3bK8BAMOo3suHtpfSvHq5s74u0OogP1lJ8elhFF2Ps6RCRLt/DhYyTPfQCobDRjE+lV39DBTnaZJNmb0hvjvvsVqCuESx8HtaabzrszB6CDMZdKDTmayiEyBQIkZyDCoMNosmC2WDlUdYgdJTu4MeVGhhmGcUPKDWw+sZmsmqxT6ZAeaLsrxl3Ba2zIKOGrw+Vnehn9Ql55I6MiDPh08ri1GhWzRoXxQ16VrL2hnQVSvH12UtdClBi7595ljpJ90ibq9FukjjyRyVCR7Z0X4wZH/D+vvNEr6peDiexSI2qV4FbUqxtNVbDt/2D0pV2EvpZOjSPHrvOeV96In1bNsOAeUlovegzGL4JzTulRhdvb7dU0tfFy5ssE64K5dty1ANww/gaCdEE8f+D5XuW6K8ZdwSvkVzTyh9WZPPHlwHiXA01eeaNTCdfzx0RQUt/Ksepmt3PsPFpNqL+2I+PGQXSQnjarjdrmTlkTe16XhKgmXSP9HDkeGk5K0rL9jEMOoaXNyolaz5tEDGayy4yMivBH7yMvbt3B9/+G9ha4pGtfhismxqJVq/hkXzF55Y2MiQroeaNW7QNXvwvTbu445JA/2FOayfaS7dww/gb8fKQMnABtALdMuIUdJTtIbzph76eqGHeFAcRmE/nrukNYbCKFNS09Z34MURpN7ZTUtzr19s4fI6VEusuaEUWRnQU1zBoV1u2f35EO2RGaaa6GrHWSYdfZrxk5XvpeldeHVyKPziGinLKzKzSTVWr0SAkSkO6Y9r0N026BiDFdnnLovG/IKCW33Og8JOOCcIOUJf/xkTcJ1AZ2eO0Orh13LZG+kTx/4AXEsJEe6borxl2hz6zaW0T6iTpusGtj/3TMeWOSoYpjo8zZP258qB8jw/3dxt2PVTdTbjR1i7cD3QuZ9r8L1jYpJOMg0q69U5nVi1fgGRVGMz5qAZVwdhn32uY2yhpMnm+mfvMI6AJh3sNOn146NY7a5jbqWto9DveEG3SodCUcrt/FDeNvwKDtKhOs1+j53aTfsb9yPz8GR3iUDqkYd4U+Udlo4okvc5iRGMpjC8dj0GnYc7z2TC/Lq7jrZD93TAQ/HavB1N5zA/Cd9q5Ls0eFd3vOITtQ1mCSUt3S34KEOacMOkDwCPDxH5BN1QqjicgAPSMjDGeVcc/p0HD3oKK4sQIKtsCse8Av1OkQh8479LCZ6oKIAB3aiC1oBX9+nfxrp2MWJy0mzhDH89ZKbA1FkhyFDBTjrtAnln+eg6ndxr+XpKJRS3opu88y455X3ohBp+lxo+z8MRGY2m0dnZWcsbOghmHBvowI614VGW7QohLsnvuRb6TY+vRbuw5SqSByHFT0v+de3mAiOkhPckwgOWWN7k8YIjhkB5JjPDDAJfuk74k99znQqFX8csowVELPDkBPnGg8ik9ANqN0lxGgdX6uj9qHu9LuIqetlm/8/WR774pxV+g1P+RXsTGzlLsuGNXR4HlGYhhHK5vc62UMIfLcdLKfMTIUrVrVY9zdZhPZdUyKtzubQ6NWERlgT4fc87rU+GHcgu4TRY4fGM+90UR0oJ7kmABK6ltpaG3v92sOBNllRqID9YR5ouFekg4qDcRMdDnsgV+MYc0d53o2N/DqwVcRbL6EWly02gMuT7ycJP84XgwOwlItb99FMe4KvaK1zcoj6w8xMtyfO+eN6jh+TqJ067r3LPHeRVEkr6Kxe2FKJ/y0Gs5JDO0ady/cIbVfQzIq9S3tzE7qWf0zOkiPWF0ghQCm3iRlVpxO5HhoqYamyl6/HjlUNJiIDNSRbN94zD1LQjPZpUbP4+3F6RCV0lXV0Qm+WjVTR4R4NHV+XT6bT2wm1Hoh9c2u60nVKjX3TLmXQq0Pn534Wtb8bo27IAjxgiB8JwhCtiAIWYIg3G8//v8EQSgRBCHD/nV5p3P+IgjCUUEQ8gRBuFTWShSGFCu3HqGotpXHF6ei05xKK0sdFoSvj/qsCc1UNpqpb2lnrJt+mHPHhJNf0URpvT0euv4OeHsBHF7HDnu8/Vwn8XYH0YF6Ztaul7zEqTc6HxRlz5ip7L9890ZTO81tVslzt3+gnQ1xd1O7laNVTZ4VL9lsUHoAhsnrK+wpr2a+ir+PP6O0l7nvxgRcmHgZEywiL9Xso83qfrwcz90C/EEUxfHATOBuQRDs7zKeEUUxzf61CcD+3DVACjAfeEkQBA+TShUGM7nlRl7fdoxfTY1j1mnZH1qNiikjgs8a455X3kNJ+WmcPyYSgO1HqqClFupPgloHa2+Bg6sYFeFPVGDPAmnxAXBJ27eQfEVH9WI3HOmQ/VjMVGGUwmnRQXqiAnWE+PmcFXH3IxVNWG2iZ2mQNUfAbIRhThsd9YmjdUfZfGIzvx73a2IDw2SFMQVB4D5NNOViG2vy17gd79a4i6JYJorifvvjRiAHcKW6swhYJYqiWRTF48BRwPNeVgqDEkdOe6CvD3+93HlrvBmJYeSWG2loGfqxWpcl5Z0YE2UgOlDPtvxqKD8oHVzyGrYR53Fb9VPcG7zT5SCcJQsAACAASURBVPmzW78nSGimZdJNPQ8yRIJfeL967o4ahcgAPYIgSJuqZ4EMgUN2wKOwjGMztR8899cOvoavxpcbxt9AuEFHfUs77Vab2/NmhaUyw2zhtYOv0dLuusDMo5i7IAgJwGTA0Z3hHkEQDgqC8KYgCI6A0zCgqNNpxbj+MFAYQny09yT7T9bzt8uTCfHXOh0zIzEUUZTayXWjrRm+/lu/x429RW55I5EBuh5fqwNBEJg7JpztR6qwltgbnQyfxb7Zr7LNNpGriv4jbZY6QxRJK19Dri2eksDJrhcUmdyvxt2Ra+/IvU+OCZS6Cw1xGYLsUiMGnYb4EA803IvTpfz28DHux3rAsfpjfFX4FdeOu5ZgfTDhAdJ7q0ZGaIaw0dxbU02tqZYPcj5wOVS2cRcEwQCsBR4QRdEIvAyMAtKAMuC/cueyz3e7IAjpgiCkV1RVuz9B4YxTaTTxxJe5nDsqjCVTev68nhQfjFajYs9xJ8VMB1fDrhfgh//040q9R36Fc9kBZ8wdE4HRZKHhWDoExYN/GDtONPE7y+9pT5oPm/4IO1/ofmLxXoIbcnjPejHl7lquRaVAZa4UD+4HKhol4x4VKGV9JMcEYrbYOC5DXmEwk1VqJDnGhTSAM0rSIXZyR39Ub/HaodfQa/TcmCLtrThy5N222wMIS2KSuY154ZN46/BbLofKWrUgCD5Ihv0DURTXAYiiWCGKolUURRvwOqdCLyVAJ0Fj4uzHuiCK4muiKE4TRXFarUVLSb28xHyFM8c/P8/GbLGx/KoJPaYFAuh91KTF9xB3z/xI+r7/PTCW9dNKvYPVJkrGXWbV4XlJ4agEJMGvmEkA7Dxaw5jYcHyufR/GXwXf/A22PdX1xL3/w+ZjYL11ds8dmRxEJkN7M9Sf6MUrck9Fg4kAvQY/rZS94cgJH8qbqjabSE6Zh7ID7a1STYGXQzKFDYV8efxLrhl3DSF6KdjhMO6y0oft/VTvCZlCU3uTy6FysmUE4A0gRxTFpzsdj+k0bDFw2P54I3CNIAg6QRASgdHAHlfXsInw2zf3nBUx2rOV7/Iq+fxgGfdckMTICNeZIwAzE0M5XNJAo6nT37T6KBTtloSTbBbY+Xw/rrjvnKhpxmyxyfbcg/20zBymJdR0EmIm0dJm4UBRHecmhUmpjb98AyYug63LpS9RlNQGsz7FNulamvF13UsVJLlY6Ld893KjqUPrBiAp0oBGJQxp436ytoXmNqtn8fayg9J7NM57m6l1pjr+m/5fdGodN44/lREV4fDc5Rh3ez/VsS1GLku8zOVQOZ77bOB64MLT0h6fFAThkCAIB4ELgAcBRFHMAlYD2cBXwN2iKPZclw2MCPOjsKaZ299L7+gGrzB4aG2z8uj6wyRFGvjd+SNlnXNOYhg2EfadqDt1MPMjEFRw/kMw8WpIf1MSyRqk5LmRHXDGVTHS3UpjyHj2HK+l3SqeSoFUa+Cql2Hy9ZL3vvkxOCDpyGhm3Eaov7a7rvvpRI6TvveTxkyF0dwRbwfQadSMGuIyBNm9kR3w4mZqTk0Oj+54lF+s+QXfF3/Pbam3EeZ7KsvMEXOX5bmrNRCaCNVHWH7ecpdD3XZiEkXxR8DZPfgmF+c8Djzubm4HBp2GR381iftXZfD71Zk8f83k3vU3VOgXvs2poLiulfduOadLTrsrpowIRqMS2H28lnljI6UYceYqSQs7IBrO+730864X4Bf/r1/X31vyKhoRBBgdKd+4z/KTGjfsao1jX3ENPmqB6QmdiltUarhiJWh0sHOl1NU+cS5EjCU6sNK9564LgODh/ea5VxhNjIromo+fHBPAT8eGbmqrQ8N9tJtahS6UpENgXM9pqW6w2CxsObmFD3M+ZH/lfnw1viwevZhrx13LqOBRXcb6aTX4adVUN8rYUAUIGw01BfioXLd2HDRt9halDaO8wcSKL3OJCdTzyMLx7k9SGBBO1EibadNGOBdOcoafVkNqXBC7HQqRhdvAWAyX/FP6OWIMpCyWMkjOva9HUaYzSV55Iwlh/vhq5ZdpDGvNp4pgvjkpkFtezeThIR3x6w5UKrj8/6Q8+J9ehBl3AvTcS/V0Isf3S6671SZS2WgmOqhrCX1yTCDrM0qpa25zmzU0GMkuMzI60uCZhnvJPhg2xeNr1ZnqWHtkLatyV1HRUkGcIY4/TfsTV42+ikBtz2GhcINOvmRH536qLhhU8gO3zx3JjbNG8L8fj/PGj8fP9HIU7BTVthJu0Hlk5EDKdz9Y3EBrmxUyPpSaDYztpJky94/Q1gS7X/Xyir2DQ1PGE1TlB6nwH8uWnAqySo1OJX4BqbvSpY/Dg1kwTirujg7Sy9PCjxwvFdhYZHp6MqlpNmO1iV1i7kCHDMFQzXfP9lTDvblaaqfnQby9urW6I/Ty3P7nGBk0kucvfJ7PF3/ODSk3uDTsIKlDyjfuSaf6qbpgUBl3QRB47IoULk2JYvkX2XxxcHBnU/xcKKprIT7UtbaGM2aMDMViE8k8ehKyN8KEJeDTyXBEpcC4hbD75QHpMOQJpnYrhTXNbitTu9DWAlW5qGLTqGtpRxS7t9TrgiBIzZPtxATqqW1ucykdDEjG3WbxqHGDHCoaJOMS2ZNxH4KVqjVNZsqNHmq4d8Tb5Rv3f+36F5uObWLx6MWsX7Se1y55jXnx81Cr5DlE4QatfOMePlr67qYr06Ay7gBqlcBz10xm6vAQHvw449RtvcIZo6iuxbPiDzvTRoSgEqBh3ydgaYU0J3rVc/8IpgapGfQg4mhlEzbRQ33uymwQbcSMmwmAn1bNpLhg2adH2TcyT/fezVYzDeaGTgMdGjPejbs7rnu65x4RoCPcoB2Sm6qODySPPPeSfdLGvz2d1R27y3aztWgrd6bdySMzH+kWU5eDFJaRG3OX1yx70Bl3kPKkX79hGnGhvtz2bjpHKoaex3C2YLHaKK039cpzD9D7kBIbRHzRBukNGTe9+6DYyZB0Mex6UapeHSQ4GnR41FmnTKpMDRk1jUlxQcwZHY5WI/9fLOb0jkyATbRx69e3smTjEpra7HnNYaMlgTEvV6o6MnU6Z8s4kLTdh55xd8gOJHti3IvTpbsjnfuQnNVm5cm9TxLrH8v146/v7TIJN+iobW6TJUGAf4SsfqqD0riD1JvwnZvOQeej5rdv7T3r+nIOFcoaTFhtYq88d4BLY1sZ33aI9tRrpDCEM+b+CVpqpA5Eg4T8ika0GhUJTppr9EjZQfANgaB43r1lBk9fnebRNTuMe6f3+roj68ioyqCypZIXMuzVrRqtZOC9vKlaYTShEiDMyaZpckwgRyqa5BmfQUR2qZHYIL38jWBR9Ggzdf3R9eTX5fP7ab9Hp/ZMy70z4QHSuV2apPeEIEibqkPVuIPUn/Kt306nvqWNG9/c07UgRmFAKK6TKofjQ3tn3C+zfo9NFMgKd1FwMXyGlA64cyW0D44P8dzyRkZHGtCoPfgXcVSmCgJBvj746zxLRnOoRjoyZupMdTy7/1mmRk1l2dhlfJT7EVk19vz2ftCYqTCaiAjQOX3NyTEBtFmHngxBlqca7rXHwFQvK97e1NbEygMrmRI5hUtGXNKHVUKEvVG2LAkCkO6Eh7JxB5gwLIiXr5tKXkUjb+0oPNPL+dlRVCcpz/XKc7fZSCjZyA5bCtsr3Hg1c/8ETRVw4L1erNL75JUbPWuZZmmTjG206449rgjQ+2DQaTrCMs/uf5bmtmb+NuNv3DflPkJ0Ifxr17+w2qxS3L3+BJi9F7IsN5q7xdsdnNpUHTqhGVO7lYKqJs/i7cXp0ncZxUuvH3qdWlMtf57+Z5dyHHLwSIIApE3VoZQt0xNzx0QQE6jnRI1riUsF71Nc24JKgJjgnrXIe+TkTtQNJ9kZcKl7ffeEORA/E3581uspfp5S39JGhdEsW1MGgKpcsLbJ3oTrieggPeUNJjIqM1h3ZB3Xjb+O0SGjCdQG8ufpfyarJkvS8nZou1fJa7kmB6kDk/O/86gIAz5qoaPaswPr4L2bzitvxCb2QubXx79rc3InFDUW8V72e1w56kpSwlP6uNLOxl3upqr7TdshYdzB/qY3KuJiA01RXSsxQb74eBKecJDxIWgDaB99OftO1LmO1wqC5L0bi+Hgqt4v2Av0RnaAskzpe4xncfbTiQnSU2psZvlPy4n0i+TOSXd2PHdZ4mXMjJnJc/ufozrQXjnpxYbZjt6pzvBRq0iKDOiaDpm9Ef6TKLth80Dj+CBKifVEdsChBOk6hfGZfc+gUWm4f8r9fVliB46Yu/xc99FuhwwZ4x4T5Cuvek/BqxTVthAX4nmmDOYmyFoPKYuYkjSM1nYrh0oaXJ+TdJH0j7X9v2C19G7BXiCvwtGgwxOhqUzQGiBUnvZOT0QF6imxfEteXR4PTX8IP59T4TBBEHhk5iO0Wdt48sjH4OPntXRIU7uV+pZ2p5kyDpJjArqGZYr3QlsjfPOIV9bgbbJLjQToNPLfvxYzlB9yu5maXp7O5hObuWXCLUT6RXphpeCvVaP3UVEtN+Yu4302ZIy743ZVFId204ChhlTA1It4e85nkjRt2m+YniBJC+x2p0/i8N7rCuHwWs+v6SVyyxsJ1Gs6NM1lUZYpxdv7qP0dZGjFHLCJWTGzuHjExd2eHxE4gltTb+XLwi/ZGTnSawJipzow9fyax8cEUtVoPuVd1h6TvudtgoLvvLIOb5JdZiQ5NlB+PLz8sBRac1GZ6kh9jPaP7tBj9waCIHhWpaozQECsyyFDxrjHBOlpabNiNJ05j+7nhqndSoXR3LvN1MwPISQBhs8iIkDHqAh/5807TmfMZRA1Abb/n1vtjP4iv7yRcdEeGAWbVfL4+hhvBzhseh8EC7en/KHH69+cejMjAkfwuL4Ns5c89869U3vCsama6wjN1BTAqIsgeAR8/dczerd1Or3ScJehBLmxYCM5tTk8OOVB9Jpe7EO5wKNCJujQdu+JIWPco50UeCj0L44GKh4XMNWfhOPbYdKvO3LbZ4wMI72wzn27NpUK5vwBqvMhZ2Nvlt0nRFEkz4PuSwBUH5EqcPto3PeU7SHb+ANtNeejtvZ8u69T6/jbjL9x0mbiDZ82SRO+jzhy61018e6SMWOzQd1xaePxkn9JmUL73+7zOrzFidoWWjzVcC9JB0M0BDrvMtbc3szKAyuZGDHRrZZ6b/BIPAwk+WgXDBnj7ijwKGtQNlUHiqJaexqkp2GZzI8BESZd03FoRmIojWYL2aUyUunGL5L6Vu54zrPreoHSBhONJgtjerWZ2nvj3m5t5/HdjxPpG0NbzQVunZhZsbO4PGIq/wsOpLCw7yGRigb3xj3UX0tUoE4y7sYSsJikrI3kK2HEebD1cWit6/H8gcTxPvM4DXLY1B6L7d449AbVrdU8NP2hPqc+OiPcoJOf5w5ddImcMWSMe3SQ5D3+3D13q03kN//7ie/y+r/BdJGjgMmTsIwoSiGZhDkQMqLj8DmJ9ri7nNCMSi018yg9AC0DqyOeX+7YTPXQuGv0fWqk/G72uxxrOMaDk/8Moo+s5IE/TX8IvU1kec5bfd6LqjCa8PVRE6h3XXg1LjpQykKptWfIhI6SjOH8FZJh/+HJPq3DW2SXNaDxRMO9pVZ6TXHOQzKlTaW8k/UOC0YuYGJE72sZXBFh0FLb0obFS1XAQ8a4RwboEAR+9hkzFUYTO47W8E1WRb9fq7i2Ba1G5XKTrRtFu6WNtknXdjkcE+TL8FA/9/nuDobPss/nskOj1+mdpkymtE+g7l17hLKmMl49+CoXxF/AgqSL0GpUsuQ2wsPHcX9zO7tbitl0vMfeObIoN5qICtS59UiTYwIpqGrCUmU37o5865iJMOUG2PMaVOX3aS3eIKvUSFKkQXZzGUr3S997iLc/s+8ZVIKKB6Y84KUVdic8QIcoQm2Ld+o8hoxx91GriDDofvaee6k9Dp4/AGJqRXUtxAX7etYVK+NDqQhk/KJuT81IDGVvYS02d3F3gNgpUpeik7s8WHHfySuXtEiCfF13uenAZoPyg30KyTy590lEUeThcx5GEASiA2U27RAElgaMZoJNw5N7n+yqHOkhFUaTy5CMg+SYANqtIg0ludLdSueMjQsfldIzB0FqZLansgMl+wFBet+dxoHKA3xV+BU3TbiJaP/edWaSQ0chk9yOTG4YMsYd7AUeP/OYe0kn497faaFFta3EeRJvb2+FrE9h/JVOFfVmjAyjvqWd/EoZH0xaP4hNg5M/ebDivpNX0eRZvL2+EMzGXhv37cXb+fbkt9w+8XZiDZKhdKT9ykEdmcKj1TXUm+t5/kDvG46f3ju1JxwxbHPlESnXunPqpyFCSmU98rXUKegMUd1kprLR7FnxUnE6RIwFfdcPBFEUeXLPk0T6RfLblN96d6Gn4bEEgRuGlHH35E1/tuIw7o0mi/tmyn1E0nH3IFMm9wvJ0DnTbUfy3EFGvruD4TOl2+UBEhNrt9ooqGzqZWWq58a9qa2JFXtWkBCY0CVnOjpQL/9vG5nM+OYGfp24kNV5q8mq9jzvXRRFe1jGvXFPDPdHq1HhU3/ceSHNjN9BSCJ89dczJk1wsLgegAlyPfcOJcjuIZmfyn7icM1h7k67u0tBWX8QbvCgUbYMhpRxjwnyVYx73ak7l/yKpn67TqOpnfqWds8yZQ6uhqB4KXPCCXEhvsQG6eVtqoIUd7e2SRurA0BhdTNtVpvnm6kqH7daJKeTUZnB0s+WUtJUwiMzH0GrPiVJG+NJwV6UpGtyd+g0/H38+TD3Q4/WAVDf0k6bxSbLuGvUKpIj/Qg2lTg37hqd1D6wOg/S3/R4Ld4go6gBlQCpcTI99/oT0FLt1Li/n/M+ofpQFo5c6OVVdifCUwkCNwwp4x4dpKfRbPlZS/+W1rcyLFjyph2ZHf1BsaeZMqIolaOPnNdjlaYgCMwYGcae47XyDFe81NFooOLuvd5MjUyWjJoMLDYLL2W8xI1fSZ762/PfZkbMjC5jooP0tFlt8rS9I8YBYKgp4NKES9l8YjMt7Z4J7FU0Ou/A1BMzwlrxoR0xtAfxqrGXQ+L58N2/BzzbCSCjqJ4xUQHdG5P3RA9KkIUNhWwr3sayscu6fPj2FwadBp1G5VkhkwuGlHGP6aEN2c+JkvpWUmIDCTfo+nVT1ZHjLluXw1gCrbVuwxPnJIZS3dRGQZUMXXD/MAgfO2Bx9/yKRtQqgaRImelzonhKw10GRcYibvzqRl7OfJkFiQtYc8UaJkdO7jbOYWRlhWb0gRA0HCpzuCrpKlotrXxd+LW89dsp78hxl/cBNcUgGex633jnAxypkWYjfP+ER2vpK6IokllUz+Th8tsbUrJf2hyO6qru+GHuh/iofLh67NVeXqVzBEGQCpk8yXV3wZAy7tGnNTP4uSGKIiV1rcQG+zImykB+Zf+FZYo8bdJRdlD67kbPfHpCCAD7T8osdhk+E4p+krJS+pnc8kYSw/3lp88ZS6QOUm6MuyiKrD+6nqWfLeV4/XGenPsk/57zbwK0zu8QPK7GtjfumBQxiYTABDYUbJB3np0KGdWpnRnjI9VY5La7EM2KSoGpN8He/0Flrkfr6QuFNS00tLZ71LuWknTpb6g+lSFlbDOy/uh6Lku8jHBfF03OvUx4gI6qn2NYJsZeyPRzNe7GVgvNbVbiQnwZExXAkYpGeWmFvaCotgV/rZoQP5kpgeUHAaGb93M6ieEGfH3U8ipVQYq7mxqgyrvNoJ2RV97omYa7DJnfBnMDf/zhjzy641GSw5JZe+Vat6XrHr/Po8ZDdT6CtZ1FSYvYV7GPIqPrRg6dcejKRMr03IfZymgRdWTWu7mru+CvklLm13+V7nIGgMwiaTM1Ta7nbm2X/o6ndV769MintFpauS75Om8v0SURBq1nVaouGFLG3fHm+7luqhbXS6ESyXMPoKXN2pE94/Vr2dUgZZdZlx2UWn+5aSqsVgkkxwSQVSozJ3v4wMTdG1rbOVnb4lludFkmCKoeP9D2lO1hycYlbD25lfun3M8bl7xBjCHG7bThBi0qwYPwY+R4sFmgtoCFIxeiElQeee/lRhOh/lrZdyw6YyElqmhy3O35+IfDvIegYAsc+mRADHxGUT1+WjWjI2V+SFdkSTIKnSpTLTYLH+Z8yLSoaSSHebZR3lc8Fg9zwZAy7nofNWH+2p+t515aL73uYcG+jI2WjGh/xd2LaluJ80R2wINCnpTYILJLjfLuOkISJDGnfo67H7ZrzU+Um2EBknEPHyPl5J/GW4ff4tZvbsVP48f7C97n1tRbUbtpAOFAo1YRGSCzkAlOdWWqyCLaP5pZMbPYWLARmygvlFXRIC8NsoOaAhp8h8truTf9Nml9626F1+ZB5ipJN72fyCiqJ3VYEGq5hXcl3TdTvyv6jtLmUq4bP7BeO0jGvbbZ7F5gTwZDyriDI9e9b95qVnVWr/KBzzQldac89yS7Z9If6ZCiKNp13GVuprbUSv0cY+RpbkwYFkhzm5UTtT1ndZQ3l1PRXCFtzg2f2e/G/WCxZNxTh3lo3J18oDWYG3gx40Xmxs3l44UfkxLmeRs2j2o6wkeDoO5o3LEoaRFlzWXsKZcn3SB1YJIpMWG1QF0hluBECqqaMbW7kWXWaOHWb2HBf6G9BT79HTwzAb5bAY3eldAwW6xklxpJi/dwM9UvXJIttvN+9vsMMwxjXtw8r65PDuEGLTYR6rwgQTDkjHtMkAcejROsNisPfP8Az+5/1ourGhhKG0xoNSrCDVqCfH2ICdL3i+de29xGS5tVfhqkI/Ysszm0o3LQEZqxiTaO1h1ldd5qHt7+MJd8cgkXf3IxSzYuoby5XIq7NxRBvfw4sqccLK5nRJgfwX4yU94aK6CxzKlx/+LYF5it5j4VvnhUyKTRSQa+MhuAC+IvIMAngA1H5YVmyhvM8j33hiKwteMbPRqrTeSonE19rT9MvxXu2g3XrZMqj394Ap5JgXW/81odQ25ZI21Wm2fG/TQlyKyaLPZX7ufX434t+07Lm3jcbs8FQ864S71Ue2/c1So1V4+5mp/KfuJ4w3Evrqz/KamTctwdcfDRUQH9Ytw9zpQpt2fKyAzLJEbo8PErYvWR97l3672c//H5LN64mH/99C9+Kv2JCeETeHDqg7Tb2vnrj3/FGn+OfWG7PX0psjlY3OCZ197DaxZFkbVH1pIcmtyneK3H1dj2jBkAvUbPZYmX8e2Jb2lsc/3+aLfaqGn2wLjb1SDDR0ihIFmhGQcqldRK8Tdr4J59MO1myP1cCte8cYnUk7UPZNg3UyfJNe6mBqlvQKfOSx9kf4Cfxo/Foxf3aS29xZv6MkPOuMcE+VLf0k5rW++79CwevRiNSsPHeR97cWX9T0mnAiaAsVEGjlY2eSU+15lTOu4ywzJlByEwDvxC3Q49YTzBZesuQT/iRQ40vcex+mPMi5/HP8/9J18s/oLvrv6Op+c9zc0TbuYv5/yFveV7eas6Xcq66KdN1ZomMyX1rZ7H2wGiU7sczqrJIr8un6VjlvZpTTFBepo8KdiLTJHaE5olT3pR0iJMVhPfFH7j8rSqRjOi6LoDUxdqpNZ60Qkp6H1UXRtme0J4Elz+JPw+Gy5dAU0VsPp6OL6td/MhZcpEBug66mHcUnoAEDt6pla1VPFl4ZcsHr24xzTV/sabVapuS7gEQYgH3gWiABF4TRTF5wRBCAU+BhKAQuBqURTrBMmtfA64HGgBfiuK4v4+r9RO5wKPxHD/Xs0R7hvOJSMuYcPRDdw3+b5+14zwFiX1rVwwNqLj59FRAZgtNk7WtvT6d+GMIntsX3ZYpvyg7Hj76wdfp9XSyiTtPWQfC+fzvy7pMSPnqqSr2FG6gxczX2Zm3EQm9FPc/WDHZqoHt/NlmVL5vb7rB8In+Z/gq/Htc6ee6E4FewF6GemoDvmDqjyIm0pqeCqJQYmsP7qeX475ZY+nnerAJDPmXlsAWgPqwGhGxNbwRfVrnPw6DF8fX/x9/PHT+OGr8UUl6mlr96HVrKbZpGZcdDBxIb6IoogNW0eFsk20IUbEIl76NwK/+BPzDn+KOnGuvLWcRkZRPZPig+VneDkqU+1KkB/nfYzVZuXX45xrIw0E3hQPk1OfawH+IIrifkEQAoB9giBsBn4LbBFF8QlBEB4GHgYeAi4DRtu/ZgAv2797hZjgUx2Z+mLQrh13LZuOb+KL41/wqzG/8tby+g2zxUpVo5lhwacMriMnO89efOMtimpbCfXX4q+T8fZoa5bazKUscTu0tKmUL459wbJxy4huv4QfM7NdqhEKgsCjMx/lYNVBHjI3sLoyB//WevD1wAjL4GBRA4IAEzzdTB3WVR62pb2FL49/ySUjLumz59e5YC9JTlqfw7hXHIa4qQiCwFVJV/HMvmcobCgkISjB6WlyOjB1oaYAQhNBEGgP+JKWtmKK6n1oaS+n1dpKu60VGyZQdb3j+EZOJ8DwQG4p/poHbDaPG403tLRzrLqZX0513Z2oC8e+lzJ5/EIxW82szlvN+fHnMzxwuEfX9iaBeg1atcorhUxu/3tFUSwDyuyPGwVByAGGAYuAefZh7wDfIxn3RcC7ovTR/JMgCMGCIMTY5+kzMV7qyDQpYhJjQ8ayKncVS0cv7Ze2Wd6kzJ4GGRt86p/QUSZ/pKKR+RO8pzNd7IkaZEUWIMry3N86/BYI8NuU31JUJW1cZpU2uAwJBOmCWDFnBTd/dRMrwoJZXrwXRl8sb20yOVRSz6gIAwY5H2YgdRyqPwHTbupy+KvCr2ixtLj0lOXicSFTSCJoAyTjbmfhyIU8t/85NhZs5L4p9zk9zZFLL1dXhtpjEJ3KsfpjVFkPYq65mLz8i9D7qIgP8SM+1I/4EF+GheiIDFITFiDy8b4jbM2t4NO7Z6NVqxEQUAkqBAQEwf6FwGvfP8wbHGBi3ldwSgAAIABJREFUxv+4cMrt8tZjJ9OuBCl7M7WlFk7sgPN+D8CmY5uoM9dxffL1Hl3X20gSBN4pZPKodYwgCAnAZGA3ENXJYJcjhW1AMvyd0xqK7ce8Yty9JUEgCALXjLuGf+z6BwcqDzAlqrtI/2DC0aRjWCej66/TEB/qS56XN1WLalvka2HLlLytbq1m3ZF1XDnqSqL9ozFoLAgCHC4xclFylMtzp0ZN5baUm3g1603Oy/mY+V427geLGzgvyYMS8zLnm6lrj6xlZNBI0iJ6rliVi6Ngr0Lu+1ylgugJp9YGRPpFMjt2NhsKNnB32t1Osz/KjWZ81AIhcrKErBbpQy3lKt7PeR+dWsdrv7qPUWHRRBh67uJU3+jL5/sOYG4JZ6yL0Ndf5j1F7odzeeTwy6xKmu+RB51ZVI/giRJk/tcg2mDcAkRR5P2c9xkTMobp0dNlX7O/CA/wTiGT7HsfQRAMwFrgAVEUu2yR2710j3b1BEG4XRCEdEEQ0quq5Hdv99WqCfbz8UqV6uWJlxPgE8Cq3FV9nqu/KXYY9+CuHvWYyACOeDHX3WYTKalvJU72Zmom+Ib22DHewbvZ72IRLdw84WZAUsBLCPOXXal6x5R7mWjT8M/aPZQ2lcpbmwzKG0xUNpp7uZl6yrgfqTvCwaqDLBnd8x6CJ+h91IT6aynzJDMsOlXy3Dvp8CxKWkRlSyW7y5xnGlUaTUQG6OV126o/ATYL9YGxfFbwGQtHLmRWQgKRAXqXr3maXU8ovdC1npDOEMV/9WNQWS08+P2DtFrk17NkFEl3X4Fy9idAytIJiIXYyewt30t+XT7XJV83KO7gvSUeJsu4C4Lgg2TYPxBFcZ39cIUgCDH252MAR8fmEqCzXFyc/VgXRFF8TRTFaaIoTouIiDj9aZfIbkPmBj8fPxYlLWLzyc1Ut1b3eb7+pLS+FUHontUwOiqAY9VNtHupqW5Fo4l2q+j5ZqqLf4oGcwMf537MpSMuZUTgqWKRlNhAsmRqzGhUGp6IPB+baOXhbX/GYrPIW58bHI0dUj3dTA2Kl1Qr7aw7sg6NSsMVo67wyrrAnuvuyfs8eiK0NUHdqRTfefHzCNQGsv7oeqenlBtN8jNlaqVMmTWtJzBZTbJ1V2KCfBkW7Mu+E+7F4oaNX8wTlZUcqTvC8p+Wy5KGFkWRzOJ6+SGZ9lYo2ArjLgdB4L2c9wjRhXD5yMvlnd/PhBu0A5Pnbs9+eQPIEUXx6U5PbQQc7WNuBDZ0On6DIDETaPBWvN1BTJCecqN3NFWWjV2GxWZhbf5ar8zXX5TUtRJh0HXT/xgbbaDdKlJYLUNCVwZFtR7kuFvbpapIN8VLH+Z+SIulhVtSb+lyPCU2iJL6VuplVuPFj7yIv1XXcqAqk9cPvS7rHHccLG5ArRJI8VRTplNIxmw189mxz7ho+EWE6t2ng8olxtNcd0dapuPOAtCpdVyeeDlbTm7B2Nb9g9TRGFsWNQW0A6vKtjMrZhZJIUmylzYtIYS9hTJ0/Mcu4LxWM3cGpbKxYCNr8te4nbu4rpXqpjb5+e3HvpeqZcct4KTxJD8U/cDVY69Gp/agEXw/Em7QUdPc1mdRQDme+2zgeuBCQRAy7F+XA08AFwuCcAT4hf1ngE3AMeAo8DpwV59W6IRoL3ZkSghKYFbMLNbkr/GaN9gflDa0dom3OxjtZRmCjhx3ORuqVblSpyQX8faW9hY+yPmA8+POZ2zo2C7POQyqbIXI+Jlc0dzCAsMoXs18lYzKDHnnueBgSQNjogLQ+8isRjQ3Qs3RLq95y4ktNJgbWDLafcaQJ0R5WrAXmQwqDZQf6nL4qqSraLO18dXxr7qdUmn0rIDp66AwKk01XD/es43HaSNCqGw0dzSB6ZGAKIifwe/KC5k9bDZP7HmCw9WHXZ7i2EydLNe4534OukAYcR4f5n6IWqVm2dhl8s4dAMINOqw2kfrWvjUlcmvcRVH8URRFQRTFiaIoptm/NomiWCOK4kWiKI4WRfEXoijW2seLoijeLYriKFEUU0VRTO/TCp0QE6SnuqkNs6X3hUyduWbcNVS0VPB90fdema8/cOi4n05SpAGVgNc2VYvqWhAEnH6QdEOGhvua/DU0mBu4beJt3Z5zGHe5oRkMERCWxN9MPkT7R/Pw9ofdVmC6QhRFDhbXM8mTeHv5YaTsoFPGfd2RdQwzDGNmzMxer8UZMYF6apvb3Ou3ONDopM5M5Qe7HB4fNp6k4KRucgRNZgtNZots4y5WH+X94EASgxKZPWy2vDXZmTpCuqNJPyGjM1PyQlTlh3ki9S4i/n97Zx4fZXX9//edJXsy2fewQxIIhE0UAdlU3ECUtmpp3bdWrbXaajf9tr8u1lJbra3WfddaUETADRTBVpE1YUkgEJasJCH7vsz9/fHMJBOyzDOTyTbc9+uVVybPPHOfO7kzZ86ce87n+Efxky0/oaKx55DO3pOV+JoM+nrfWtvg0Ecw/mJqrE28l/Mel466lKgA10LD/Ym9kKmojxpaw65CFTriziXVnlGXuyDxAmIDY3n70NDcWLVaJYVVjSR2Y9z9zEZGRgSS4ynjXt5ATLCfPvnX4kwwB0BE9+3WmtqaeOXAK8yKnUV6VFfvPiLIl9gQP/brlf8FGHEewfk7eHTuHymuK+Z3X/9O/2PPIL+igcr6Fv0ZFgD5NjEum4Z7XnUe24u3c9W4qzAIz76d3Hqdx07p4rnbc94zyzLJrcxtP27/9qs3DXJP9VEOGNr4Xur3XH6uybHBBPua2OFkUxWAFK1faWjuNh5f8DhlDWU8tO0h2qzdf8hl5FeSlmDBbNQxp7xvtH6pKZfx2sHXqG+tZ+XEla48lX7H3kXqq6M6ew33wLA07vbyYk9J/5oMJr4z4TtsL9pOblWu8wcMMGV1TTS3Wrv13AEmxAR19dwbq91SUnRJDbIoA2LSoAeBpfePvE9pQ2m3XrudtAT9m6oAjDgfGiqYKvy5M/1ONh7byEfHu4Yb9GD/Ou9S156jn0NUqhY+AN498i4GYWD5uOVuzaE3Yi0dBXv6HzRZK+U/Q3Hx8jGXYxRG1h7t2FgtcaUDU2szrxvqCDH4uLVpbDQIpo0MY5ce4x4+WntdZX3ApMhJ/Pzcn/O/wv/xr8x/dTm1pc3KvoIq/Wt4aAMYzLxhreTpjKdZMmqJW6qd/UliWAATYoLYnFXi/OReGObG3XONKq4ef7WmN5M99PRmHHXcu2NCTDAnTtd3/vq+4zl4cYktjKCf/PJ6fZkyVqvmIfYQb2+1tvLi/heZHDmZc2N7LlCeGG8ht7RWv1aQQ/OO2ybfRmp4Ko/vfJzGVtc/6PflV+FjNOhviN3SqOnbjF2o/WltYe2RtcxLmEdMYO+5+u5gf527FHe3F5Od4b1H+kcyL2Ee64+ub99bckV6IL9wB5sD/Pl25Az8TTo//M9g5sgwDpfUUFWvI5aculRzTmpL+Nb4b7Fs7DKeyXiGbfnbOp12+FQNjS1WfZ2XpITsDbw2agqP7vkbi0cs5o9z/+jWc+lvFqZEs+N4OdV6tYW6YVga91gPVak6EuEfwcUjL2bd0XUud4/vbwpsm1A9e+7BtFkluY5Np23a3vzv77qv09xqpai6kUQ9mTIVx7S0ux4qUz889iEFtQXcNvm2XnOHJ8WHYJWQVazTew8fA4HRcPIrjAYjD8x8gKK6Il7Pel3f4x3IyK8kNT4EH5POt0He11rXnjELANiWv42yhjJWjO97RWp3uPU6j0nTfhdndLnrynFXUtpQyv8K/6edYq9O1ZEK+Vb2mxiAa8e6r5Y4c1QYUursn5tyBSDh0EaEEPzqvF8xIWwCD217iILajsxquxLkVD2ee+khXmkt5TFZykUjL+LP8/+M2agzL36AWZQcTatV8mWO+ynaw9K4B/maCPY1ebwj03Up11HbUsv63PUeHbevdFed6ojd88wpcQjNlB3Wfu9fDVX5uq8jpc5MmV403K3Sygv7XmBc6DjmJ83vdRiXN1Xbm3doCpGz4maxIHEBz+97ntMN+mOUVqtkf0E1U1zRkzn6ORjMMFLbTFyTs4Yo/yjmJc7TP4YLBPmaCHL1de4fqjWeOMNzB5ifOJ9Q39D2nPeS6iaC/UwE+PReqF7XUse7p77morp6YhPcr+CcmhSK0SD0barGTNK6cGV9AIC/yZ/HFzyOlJJbPr6FrfmaemRGXiXhgT66Qokvff0oqyLCuDjhAv50wZ8wG4amYQeYMTKMED8Tn2W7H5oZlsYd3NC71kF6VDop4Sm8fehtXcUTA0VBZQNBviZC/Lp/E46ODMRkEByy97SUEsqOQPLl2u2vn9Z1nXY1SD2ee3GmlnZnF6xy4POTn3O06ii3Tr7V6cZbQqg/Fn8zBwpc2VSdDZUnoUrz4O6beR+NrY08naHveQIcO11HbVOra5WpuZ9D0izwDaK4rpgvC75k+bjlmAwuqXi4hFuv89jJnWQI7JiNZpaNXcamE5t45cArFFU26Iq3v5fzHrXWZr7fICEgwun5PRHgY2JSfIjTSlVA+xBPXQq5X2i668CIkBH888J/4mP04a7Nd3HP5nvYWXCE9ESL08rS5/c9z+MVu7i0zZc/LXpiSBt20Fotzk+OZsuhErfz3Ye1cXepNFsHQgiuSb6GnIocdpd4TKW4z9h13Ht6AfuYDIyODOzIda8uhJY6LTactgJ2vQwNlU6v41IBU1GmtrFo6hyvlVLy7L5nSQpOYsmoJU6HEUK4salqi7vnaRvGYyxj+PaEb7P68OpO2SC9Ya9M1S3zW3dae85jFgCw9sharNLKVeP6t6lDnDvNaeLStWrSpq4ZVPdMu4eLRl7Eqp2r2N/8EjEhvRu5Nmsbb2S9wVT8mBwystdKZD3MHBnO3rxKmlt1VFSnLAVrC+R82n5oavRU1ixdw09m/ITtxdspCfkdVsunNLX1nFH0bOazPLH7CS6rreMP467p1w9jT7IoJYqy2mb2ueL4ODBsjXucB3qpdsdQ1JspqOi+gMmRCY5dmU7naL8jJ8CcH2mx8Z0vOr1OXkU9JoNwnhonZY8a7l8VfsXB0we5Oe1m3W+iSfEWDhXX6JdQiJ0C5sBO2UA/mPoD/E3+/GXXX3QNkZlfhb/ZyNgonVLJx74AJIxZiFVaeS/nPc6NO5ekkCSnD+0LMa5KEICtUlXaFDs742fy48/z/8xNk26i2ryVQt9/9rrHtCV/C/m1+Xy/thHCu095dYWZo8JoarXq0xRKPAeCYiCrc4cms9HMTWk38ci0V2itmcjumrdZvnZ5e6jGkWcynuHve/7OUksKfyg9jSnFc/IQ/c38CdEIgduhmWFr3GMt/pTUNHlMU8WOXW9m04lNQ0ZvprCqoZPUb3dMiAkmr6Ke+uZWTV8dNOMeOxnGLITtzzjtOp9XXk98qL/zzvE1xVBX2m28/dl9zxIdEM2ysct6H8OBSfEhNLdZ9fXjBDCatNZoDp2Zwv3CuW3KbWzN38rXRc5TQDPzq0hLCMGkJzcatJCMrwXip/F10dcU1hX220aqI3EWP0pqGml15XUe233GjB2DMPDj6ffRXHwVp62Z3PjRjZTUd29AXj/4OvGBcSwqy++xnsEVZo7URMT06MxgMEDyZZCzSdODOYMTJWYaC7/LXy94GrPR3B6qya/R9pie3vs0/9j7D5aNXcb/q27FGD4WopK7jDNUCQ/0YVpSKJ8fOsuMe5zFDynxiO7xmVyTfA2tspXVh1d7fGxXqWtqpbK+pVOTju6YEBOElGgGsixHa0sXbNN4n3Ovlvuc2XuaZ15Fg74c93aZ387Gffep3ew6tYsbJ92Ij1Fno2nc2FQFLe5+6kB7PBZgZepK4gPjWbVjVY8FLwCtbZrnODlBZ0hGSji6BUbPA6OJNYfXYPG1sHjEYv3zdZNYix9WiWsSsCHxmlJnUdeMGTtldU00VZzL1fEPc7z6OCs3ruRwxeFO52SdzmLnqZ18N+kiTNLqEc89OsSPEeEB7DiuY1MVtLh7S52mB3MGGXmVjIoI4MLRczuFapa/v5y7N9/NPzP+yfJxy/nt9PsxHt8GKZf3Oaw00CxKiSYzv4qSGtdD0MPWuMd6uJDJkaGkN2PPlHHqucc6aMyUHYbI8R0v5DELNA/+f3/vJAd7JgUVOnPc7eXtZ/QPfWH/C4T5hrns0Y6ODMLfbGS/S5uq52l63Pk72g/5Gn358Ywfc6jiEOuO9txsOaeklsYWK+lJOjdTy3Oh6iSMWUB5Yzmf5X3G0jFLXfoAc5eO/gUuhCCF0D54e/DcoaPqdXb8XF655BWsVivXf3h9e5okwOtZr+Nv8ueqIJtR94DnDpr3vutEhb6khVHztG9MWV0z2PbmdShB2kM165avY2HSQr7I/4IV41fwm/N/gzH3cy12n3K5R+Y/kCxMiQZgyyH9suh2hq1xby/w6AfjDvDd1O9SUl/Cm1lv9sv4erHruCc6ibmPDA/Ax2jQZAhOH4GI8R13CgHn36sZ/ZyPu318fXMrZbXNOjdTMzQvzrej+OdY1TG25m/l2pRrXe5JazQIUuOC9QuIgRaPFcYuVbiXjLqEKZFT+Puev/cYS96Xr32ITNabBmnzGuXoBTz6zaO0Wlv73ABbL7Huvs5jJ0PJQU25sxuKHdrrpUak8sblbxAfFM9dm+7ivZz3KK0vZeOxjVw17ipCqmz6+eFj3H4ejswYFUZZbTMnTuuoJzH5wIQlcGij1izEYf6nqpu6KEHGBsby5/l/5tNvfcojsx/RsrWyN0BglPaaGWZMjAshNsSPz92Iuw9f4x5ib0Pm+U1V0HKCL0i8gL/v+Tsnqk/0yzX00OG5927cTUYDY6ODOFZUAlV5WrzdkUnLwTIC/vtEt4+3q/U5+xABut1MfTPrTcwGM99J/o7zx3fDpHgLB4uq9ad9+QZpczjxVafDQgh+es5PKW0o5ZUDr3T70Iz8SoL9tGYhusj9HCxJPFOwiQ+Pfci90+9lbKhnvFhntLeVdDVjJjZdU+wsPdTt3cVntNeLDYzl1UteZVbcLB7+38PcuelO2qxtrExdqTXF9guFAM/IGZ8zShvHpdBMQzmc7PhWsTdPi9n3JPMbGxirZZe1NmvZNhMu6VEmYygjhGBhShTbcsr0ZRg5MGyNe4i/CX+zsd88dyEEj8x+BLPRzMP/fRir9OzGrV4KKhowGQTRwc7zkSfEBNF86oj2R+QZWttGM8z+obYJmfdNl8e2S/0689wbKrQcc4fN1Ormat4/+j6Xjr6USH8X2tU5MCk+hNqmVk6Wu1AdPGI2FOzU3sAOTI2eykUjL+KlAy91u1G4r6CKyQkWfd2HrG1wbCsfJk7knxn/ZNnYZdySdovzx3mIsAAzPiaD66/zHmQI7JRUN2IQWmMIO0E+QTy1+ClWjF/B4YrDHc2iTx/1WEgGYFxUECF+Jn2bqgDjFoPJr1NoZm9eFWajYGKcEx3+49ugqbpdjGw4sjA5mtqmVnbq/TC0MWyNuxCCuH7IdXckOiCaB895kN0luwctPFNY2UCsxc95BgtaxkxwrS3P+0zPHWDa9zUPrBvvvUPH3YlxtxsLB8/9vZz3aGht0Lw8N7H3bHU53721sduNw/um30eLtYWn9jzV6XhTaxtZRdX689sL95IhG/hVw2GmR0/nkdmPDGgrNiGEe53HIsaByb+L/K+d4upGIoN8u2QLmQ1mHpn9CH9b+DcePu9h7WB5rkc2U+0YDIIZI8P0e+4+gTB2sabDbovT782rIDUuxLkOf/YGTbl0TO+V0kOZOeMi8TEaXE6JHLbGHfqnSvVMlo1dxgWJF/DE7icGJTxjL2DSw4SYYMYaCpGI7uOjvkFwzq3aC77sSKe78ioa8DcbO3ly3dKu4a4JhrVZ23gr+y2mR09nYsREXfPsdu6xQZgMwkX539na7+Nd85uTQpL4bsp3WXtkLYfKO0ITWj691F2ZWnhoHT+KiSI6IIa/LfzbgGyinkmsO4VMBqNWwt+D515c3dSjpowQgsUjFmsa5y2NmnyFBz13gJmjwjlaWkdFnc4soNQroLoACnfTZpXsy69y3lbPaoVDH2qev9k9sbOhQKCviXPHhPOZiymRyrg7QQjBw+c9jNkwOOGZwspG3cY9OSaYMaKIOv/4nl/M594BRh/4qrNHm1deT2JYz1Ww7RRlQHCc1jgDrciloLagT147gK/JyPiYYNc896BoiJ8G2Ru7vfv2KbcT4hvCqp2r2jMzMmybqXqMe11LHXfnfUCLwcg/LnyaML8w/XPzIElhARxzp41i7GTNc+8mK6WkulGf1G/FMUB61HMHF/PdQYuZCyNkredISS11zW3OZX6L9kBN4bAOydhZlBJNbmmdS+00h7Vxj7P4caq6kbY+9hp0RkxgDA/OGvjwTGubleLqRn1dkdA2Q8cZiigyj+j5pKBomHod7H0Tajs8AS3HXWcapIPM7xtZbxAXGMeiEYt0zbE3JsWHcLCwyjVdn5QrtLh7dWGXuyy+Fu6ccidfF33NtgJNKnZfviY05ewDs83axs+23E8uzayKOJ8xoZ7JFHGHSfEhlNY0teuv6yZuilYHUHmyy126e6eePqr9jvDs809PCsVsFOzQIyIG2mbuqLmQvZ4MuxKkM5nf7I3aB8L4i/s428FnkS0l0pXQzLA27rEWf1qtktMe6BTuDMfwzMnqrm+W/qDY9sHlLFPGjgHJGFHEEWts7yfOvkfLpPjmWUDTg9F03J1cp7leS6e0baZml2ezo3gH16Vc5xG9jknxIZTVNlPiSmGa3SvL3tDt3dckX8OI4BH8Yfsf+OjYR2TklzFFh9DUX3b9ha2F/+Xnpys4f+Lg9te0d4pyWWOkvVK1c9y9saWNyvoWfR2Yym3G3UNpkHb8zEbSEiz6mnfYSV0KZYfJz9lLsJ+J0c6ynbI3wMjzPZblM5iMjAhkbFSgS9Wqw9q4x4X0XyHTmTiGZ379318PSHjGWZOOLlQX4EcTe+ujez8vcpxW0PHNc9BUS1VDCzVNrSQ620wtOagVDtk2U9/IegN/k7/HGkN3bKq6YMSikrXNwx6Mu9lo5jfn/waAn279KQXBv6Qp+H2OVx3vcch3Dr3DawdfY6X/aK6pb+mI7Q8SE+NCEAL2F7gQsgKIngjC0CXubi9g0hWWKc/Vql39PR+SmjkyjMz8Kv09Ym1FSBEnP2ZqUmjv2U6nj0Jp1rAsXOqJRSnRbM8tp65JX2HlsDbu/Vml2h0xgTH8bNbP2F2ym7ey3+r36xVUahksej13u2BYRmMUlfVONqrm3AuNlbDndQc1SCfXcdBwL28sZ2PuRpaOWYrF1wXZ3F6YaJMhcMmICaG9gY9v09I0u2Fm7Ew2Xr2RB6asorV+NAfrN7B07VJu/vhmNuZu7KQo+FXhV/xh+x+YmzCXB8pKtYycQd6MC/Q1MSYy0HXP3SdAK2Y7Q/632JX2eh5Og3Rkxshwmtus+iuTQ+JpS5zFDY2v8deyO+CDH0PGv7sNO3HItg+TfJnnJjzILEyJprnNypdH9GleDWvj3lGl2j+FTN1x5dgrmZcwj7/t+lu/h2dc9txtgmFHrfEd8r89kTQLks6Dr/9B/mnNmDr13IsztVTK0BH859B/aLY293kj1ZEgXxOjIwNd89zBJg3b2kka9kwMwkBb3QQaC77H25es597p91JUW8SD2x5k8X8W89iOx9iav5X7v7if0ZbR/Hn6TzGVHGxvqTfYpCVYXP+/QLcyBK50YPJ0GqQjM0dp3wZ26t1UBfbNfoLHWr4DlkTYvwbeux3+NhkenwSrb4Edz2uaQ9kbIGYyhI3sl7kPBueMCifY16S7WnVYG/fwQB98jIZ+zXU/k/bipgEIz+RXNBAe6IO/j87KurIcrD7BlGLp2jC7O+b8CCpP4pe1BtBRwFSUCbGTabG28u9D/2ZO/ByPbzROjHdR2x0gYQYExbZ37emJfQVVxIT4khqdyK2Tb2XD1Rt49qJnOTf2XN7Keou7Nt+F2WDmqcVPEZS/U3vQmAVuPQ9PMznBQlFVI2Wu7i/FTobqfKjv2LjU3Ri7uV5LP+wnzz0yyJfRkYH6mnfY2HHaj3+2LUeuXAMPHoc7tsGlf4akc+D4l7Dhfnj6fK1Yz4tCMgBmo4F5EyL5/FCJrqSDYW3chRBa047KgTPuMHDhmUIXctwBKDuMiJpAkK9Z05hxxoRLIS6dC7J/yz1+G7H00OkJ0DRKTh2AuHQ+OfEJpQ2lHvXa7UyKDyG/okFfE2U7BgOkXAZHNncrDWsnI7+yU/GSQRiYHT+bvyz4C59++1MemvUQz170LAlBCVpLPf/w9nz+wca+H+GSuBp0u6laXNWIn9nQY2evdiqOab89vJnqyIyRYew6Ua7LWLW0Wfn04CkSQv2JCvbVcvnjpsC5t8O3X4b7s+FHe2H5MzD7bph5c7/Ne7BYmBzNqeomXQ7QsDbuMDC57t0xEOGZgkrnOu6dKMtBRIxnfExQR8u93jAY4IYP2O0/m/t5Hd75ficJ3c5jH4a2JoidwhtZbzAqZBRzEubon5tO2jdVi1wNzVzRozQsQE1jC7mldT32TI30j2Rl6kqSw5O1vPDcz7WqRsPQeItMSrDvR7hp3B3i7sXVjcSG+DmvaWhPg+w/HZ1zRoVRUd/C0dLe87db2qzc+/Yevjlezg8X9jAfISB8tJbqu+T3EBzTDzMeXBYka8kSekIzQ+OV2wc0CYKBi7nbcQzP/O7r33l8fCmlzXPXqbDYVKMVbESOJzkmmBy9jS/8LDxkfIDVEXdqecHPLoDi/V3PsxmHDD9/9pXt47up33XaH9Ud7NruLilEQq/SsNCRRjjFWVUjaB9kNUVDJiQDEOJnZlREgOsZM4EREJLQKe5eUt2kM1Omf9IgHZkxUktT3NVLvntrm5Uf/3svG/cV86vLU1l5rvfE0V0lKtiX9ESLrmrVYW+B2RzYAAAgAElEQVTcYy1+nKpqcq2JbFtLpxiku8QExnBH+h18VfQVe0v29nk8RyrrW6hvbtPvuZ+2C4aNZ3xMMOV1zbris1JK8isbOTTmBrhxvRZnff5C2HtGuKk4E0z+vF60lWBzMFeOvdLFZ6SPyCBfYkP8XPdQTT4w4eIu0rB2XJL5Pfq59nvM0NhMtZOWYHGvn6a9UtVGsd7q1NNHISAS/DyTDdUdY6MCCQsws6OHuHtrm5WfvJPBhswifnFZCrfOG7xisqHCwpRo9uZVOq3vGfbGPS7Ej+Y2K+XOUv/sWK3w1Dnw6a89cv1vT/g2Yb5h/CvzXx4Zz06BTh33duxaMZETSI6xNe7QEZoprWmiqdWqbaaOPB/u2Kq1sFt7J3xwr6YtAlCUSXFMCp+e3MTV4692WbPdFSa5s6kK2gZaQ3l742xHMvOrSAr3JzxQhzZM7ueatzrEMi3SEiwUVDbo12OxEztF+zbS0oCUUgvL6M2U6ceQDGjfgGeMDO9WhqDNKnngPxmsyyjkwUtSuP2CgZFZHuosSolGSvjicO8NPIa9cY+1613rjbsbDJoRO/C+5qX2kQBzANdPup4vC77kwOmuDYndpUCnjns7ZYe1gpXwMUyICQLoaJjdC3kVZ6hBBsfA99fC3Ptg18vw4hKoOA7F+/i3JRiJ5LrU61x9Oi4xKT6Eo6W1NDTrLG6xM+4iMPp2W9CUWVDJFD1t9dpatKyLMQtcu/YAYP/W4ZK4Gmieu7TCqYNUNbTQ3GolOliH9EA/pkE6MnNUGMfK6jp902yzSn66OoO1ewv56ZJkfrBAGXY7afEWIoN8nUoRDHvjHudOIVP6tdBc01Ho0EeuTb6WYJ9gnst8ziPjQUeTDt3ZMqdzIHQkmHyJCvYlNMDMIWe57tB9AZPRBBf+H1z7FpQfg6fn0NhczermYhYmLdSySfqRifEWrBKyi1303n2DtLz0rPWdxLIq6prJK2/QpwSZvxOaa4dcSAY69iNcjru3a7tn6M9xb67T9h08rCnTHXYRMXtKpNUqeXBNJu/uLuAnF03groXjenv4WYfBIFiYHMVWb/fc3SpkGjkXQhIhwzNpjEE+QaxMXcnmk5u7NBl2l4KKBvzMBn1hBNAKmGwa7kIIJkQH60qHtOu4d1vAlHIZ3LEFwkezITCAyrbGfkl/PJO0BDcaZttJuVzrd+qwgZhpi1NP1mPccz/XvgGNnuf6tfuZ0AAfksL9Xd+PCB2pbTYX7+OUTXrAqa5Mua0vwAB47pMTLfiYDOw6UY7VKvn5u/tYvSufexeP50eLxzsf4CxkUUo01Y29yxA4VXsSQrwIXAGUSCnTbMf+D7gNsH90/EJKudF238+BW4A24EdSyu6bdnqIiCBfTAbhmuduMED6NfDlX6GmGIKdCG3p4Hup3+PVA6/yfObzPDb/sT6PV1jVQHyoDgle0PYRTh/pFEoYG+3HuqztPLalgrhQX+JCffEzC6zSilVaaZNtWKWVb0pzCYuqZ3dpGAGmAPxMfvib/Dt+QkdgvPkTXl93Nck+QcyMmdnn5+aMhFB/LP5m9yoyky8Dca/W2MHmse46UYEQWszaKblbNBnhftBS8QRp8RbXwzJCaKGZokxOxegsYBqANEg7viYjUxIsfHO8gl+u3c+/d+Zxz6Jx/PhCZdh7Yu74SMzG3m2DHim/l4GngFfPOP5XKeUqxwNCiInAtcAkIB7YJISYIKV0MXiqH6NBEBPiRq77lGth219g33/g/Hv6PA+Lr4VrU67lpf0v8YOpP2C0ZXSfxiuocKGAqSpP60gU2fFmaAn+FEPia7x2AnDWYyQS7vj0xR7vNhlMtFpb+W36bwekC5EQgknxIe5lhgRGarIKWeth4S+QUrIhs5BzRoUT4mfu/bGNVVpYZu597k18AEhLsPDh/mKqGlqw+Dt5Po7EToZdL3OqSssnj3Ym9zsAaZCOzBgVxr++yCUjr5IfLhjLTy6aMKAdr4YbwX5mZo0O50gv5zg17lLKrUKIUTqveSXwtpSyCTgmhDgCzAK+6v1hfSPW4kYbsqgJWtl6xtseMe4A10+8njez3uT5fc/z+7m/79NYBZWNpDrrD2nHJhhGhGbcW62t7Kn4mBkxM1kx+iYKK5soqGgiv6KB/PIm8ioaaWqRgABpYEFKGHcvHklDawONrY3Ut9bT0NrQ/ndDawM+Rh+uGDNwTQ/OHxvBqk8Ok19R71zz5kxSr4CPfwHluRxsjOBoaR03z9XxYXv8S5BtQ3Iz1Y7928eBwirOH+tCv9q4KdDaQFHuPkZGROJrciJpcToXgmLAN7gPs9XPvHFR/OuLXO6YP4afLklWhl0Hq76dzpu39Xx/X0S47xZCXA/sBO6XUlYACYBjHlq+7VgXhBC3A7cDjBjRS3MJHcRa/FwvegFIvw42PqDFZ2Mn92kOABH+EXxrwrd4K/stfpD+AxKDE90ap7GljbLaJhcyZWzG3RZz/7LgS0oaSvjFub9g8cgLupxutUoKKhvIKakht7SOBclRjIsemDexXq6cmsCqTw6zdk8Bdy9y8et5yuWacc/ewLrKCzEZBJelxTl/XO4Wrd9m0iy35jwQpMV3VKq6ZNxtlaoNeRksnvVd5+eXHx0wrx20MMOXDy4kQW8oUkGcpXf74O6G6tPAWGAqUAT8xdUBpJTPSilnSilnRkVFuTkNjbgQP4qqGlzr4AMw6WowmDXv3UPcOOlGDMLAi/t7DnM4w/4tRL8a5GGt0CRQe7OvyVlDhF8EFyR1Neyg7bYnhQewKCWGW+eNGXKGHTQRs/PGhLNmd4Hr6xo2CmImI7M2sC6jkPkToghztjHdXAeHP4aRc8CkI01wkIgI8iXe4ud6xkxUMlaDmWR5jAtTnej9N1RC6aEB2Ux1JDEsQBl2D+KWcZdSnpJStkkprcBzaKEXgAIgyeHURNuxfiXW4kdji5WqBhfEpkArzZ6wBDLf6baq0R1iAmO4atxVrD2yluK6YrfGKKhwNcfdlikjBCX1JWzL38byccsxG1yIyQ5Brp6eyLGyOvbY2qq5ROoVkPc1LVWnWDY1vvdzWxrhreu0vYtZt7s32QEkLcHiesaM0Uyhz2immE5yzuheOhPlfQPPzIOmapi4rG8TVQwqbhl3IYTjd9yrALsYyTrgWiGErxBiNDAe+KZvU3SO/euJW0070q+DuhItBc5D3Dz5ZqSUvHzgZbceX+hydWpHGuTaI2tpk20e6440mFyaFouf2cC7u/Ndf3DK5Qgkl/rs4cLUXgSkWpvhnevh2FZY/rQmYTDESUuwkFtWR02jfmfGapXsakpksvEE5u46GFmtsO1xePESEMBNH2mOj2LY4tS4CyHeQtsQTRZC5AshbgEeE0LsE0JkAguB+wCklAeAd4CDwEfAXf2ZKWMntj3X3Q3jPv5iLe3NQznvAAlBCVwx9gpWH15NWYO+rimO5Fc2IITOTjmN1VBbDBHjsEor7+a8y6zYWYwI6ds+xlAg2M/MJZNi+SCjiKZW115GzRETySeaa4MzCfTtYWuprRXW3AI5H8MVj2vFbcMAe6WqK/tMe/Mr2dWcRHBblVac5EjNKXj9Ktj8G61P6R3bNH10xbDGqXGXUl4npYyTUpqllIlSyheklN+XUk6WUk6RUi6TUhY5nP97KeVYKWWylPLD/p2+hltVqnZMPpD2La1kvSe5Wze4Je0WWqwtvHrgzAxS5xRWNhAT7IePSccXq9Mdm6lfF31NQW0BK8avcPmaQ5WrpydS1dDCZ1n6GwMDfHm0jI9aZ5DasEtTzDwTaxus/QFkrYMlfxxW2t/t8r8uGPdNB0+RzSjtD8e2e0c2wTNz4OR2WPqEpovur0OmQTHkGfYVqqDJYBpEH9rtpV+n5YkffN9jcxplGcWSUUt4+9DbVDa6FjMuqHBBx72sQw3y3Zx3sfhaWDxysYuzHbrMGRdJTIgva3a7tnXz/t5C/muejcHa0rX9npSw/sew7x1Y9GuY/UMPzrj/iQ72IybE16W4++asEgKSbI1Hivdp4ahPfg2vr9CUH2//HGbcqBU8KbwCrzDuZqOBqGBf9xtlJ0zXcsQ9mDUDcPvk22lobeD1rNddelxhVQMJenO7yw6DMFLuH8rmk5tZOmYpvsahm+3hKkaDYPm0BLYcKnEqcWqnvrmVTw6cIn7yfM1wZTtovEsJHz0Eu1+FeQ/ABQ/008z7l7R4/ZuqeeX1HDpVw9xJo7X0xqOb4aVL4H9Pat9Ybv8colP7ecaKgcYrjDto6pDF7vZSFUKLt574r6aA6CHGhY3jwhEX8mbWm9Q06+iMhLbxVVTZ6JpgWNgoPjjxEa3WVq8Kydi5eloirVbJuoxCXed/evAUDS1tLJ2aBMmXwuFPoLVJM+ybfwPbn4Hz7oJFv+rnmfcfaQkWjpbWUt/sPMtrU9YpAG1jOXaK1l+07Ah851W44q9gdqGVo2LY4DXGXct170O7vSnXaL8z3/HMhGzcNuU2alpqdPdaLattornNSoLusEwOMmI8qw+vJj0qnXFh3qeglxwbTFpCCO/qDM2s21tIbIgfs0aFaxuEzTVwbBtsXaXpCc24SWvDNoxDEGkJmnJmVpHzuPvmrBLGRgUyKjIQpn0fJl0Fd26Dif3TcEUxNPAa497nXqqhSVqrtoy3OsnF9pWJERO5IPECXjv4GvUtzvXj8+1Sv3rSIK1tcPoouy3hHK8+7pVeu52rpyWyr6DKqUZ9RV0zXxwuZdnUeAwGAaPng08QbLwfPv+dpil0+ePD2rBDR8aMvcNUT1Q3tvB17mkunGhLBx1/obZpOsQakSg8j9cY9ziLH7VNrS7l/nYh/TpN6jR/h+cmBtw+5XYqmyp5bMdjTqstC11p0lF5EtqaeLetgiBzEEtGeW9e8rKp8ZgMgjVOct4/3F9Mq1WyLN1WuGT2g3EXauG2icvhyn8MmabXfSEmxJfIIB/2OalU3Xq4lFar7D3XX+GVDP9XuY0+5brbmbgMTP4ezXkHSI9K57bJt7EmZ43T8Iy9OlVXzL0sh2qD4JPqHC4bfVm/tr4bbCKDfFmQHMXaPQW09dIv9/29BYyNCmxvbAHAgp/Dgl/A1c9pjUi8ACEEaQkWp7LIm7NKCAswM33E0JQwVvQfXmPc+1Slasc3WIvR7l+jbcB5kLun3c2CpAU8tuMxvi7q2uPTTmFlA8F+JoKdydMCnM5hQ2AgjdZmVkzw3pCMnaunJ3Kquon/Hum+MKywsoFvjpdz5dSEzhol0Smw4EGtpsGLSIu3kFNSS2NL9wVerW1WPssuYWFKNMbuqlIVXo0XGXcPeO6gZc00VsHhjzwwqw4MwsAf5/6R0ZbRPPDFA+RV53V7XkGlfh13WXqINRYLqeGpTIyY6MnpDkkWp0YT4mfqUY5gfWYhUtIRkvFy0hIstFllj5uqu05UUNXQokIyZyleY9ztpfp98txB0/IOivV4zjto7fieXPgkAPd8dg+1zV17nOa70KTjwOmDHDIbvXoj1RFfk5Gl6fF8dKCY2qauKYDv7y0kPdGiZYWcBdjbEfaU7745uwQfo4ELJvRNdVUxPPEa4+5jMhAZ5EtxtZtVqnYMRpjyHcj5BOpc14VxRlJIEqvmr+J49XF+vu3nWKW10/2FlQ36MmWA1U0F+GPgsjGXeXyeQ5WrpyfS2GJl477O+ihHSmo5UFjNsqn927x7KJEQ6k9YgLlH+d9NB09x7phwgnrS1lF4NV5j3EELzfTZcwcta8baqsXe+4Hz4s7jZ+f8jC35W3hqz1Ptx2saW6hubNWVKVNfXciHvgYuDh5LsM/Q02PvL6aPCGV0ZGCX0My6jEKEgKVTdDTl8BLsm6rdtSM8WlpLblkdF01UIZmzFa8y7n3OdbcTM1Gr5PNw1owj16Vcx4rxK3hu33N8dEyL7xdW6m/S8VH229QbDHwr6cJ+m+NQRAjB1dMS+Dq3nPwKrW5ASsm6vQWcPzaCaD1Kml5EWoKFw6dquqhmbrZVpS5KcdKYQ+G1eJVx95jnDpr3XrgH3rtTU8zzYGETaEbql+f+kunR0/n1f3/NwdMHKajUjJUez33NiY8Z29xM+qizy7gDLJ+mhV7es1WsZuZXcfx0PVemnz0hGTtp8RZarZJDxZ2LuzZllZAaF+J6/1mF1+BVxj3W4kdVQwsFlX2Mu4OmkHfObZC1Hl68GJ6eA9uf9agssNlo5vEFjxPqF8qPPvsRh8u0OLKzJh2HKw6TWV/I1bUNiHAdjZ+9jKTwAM4dHc67e7QWfO/vLcTHaGBJWuxgT23AsVeqOsbdK+qa2XWiwnk7PYVX41XG/eKJMQT5mvj+C9sp06kg2CM+AXD5Krg/G5Y+qeVIf/hTWJUMa++C/J0e8eYj/CN4cuGTVDVV8e+Tv8NsaiMqqHdVxzWH12BGsNQcBcbh3UrPXVbM0Frw7TpRwQeZhSxIjsLif/b9L5LC/QnxM3WKu285XEKbVbJYpUCe1XjVNvq46GBevPEcrn9xO997fjtv334eoQF9LFzxDYIZN2g/hXth10uQ+R/Y+zrETIaZN2qiY77ub2qmRqTyu7m/44EvHsAy+gUe2LqFprYm7ae1qeO27aeisYKLWwyERST37bkNYy5Ni+Xh9/fzq7X7Ka1p4sqzKEvGke4qVTdllRAV7MsUm1evODvxKs8dYNbocJ67fia5pXXc8OI3fdOaOZP4qVq3mgcOaVKpQsCG++GN7/R56Ikh82g8dTm+fnUcrTxKaX0pTa1N+Jp8iQqIYmzoWKZFT2N+4nyuS76Gu0uKIHK8B57U8CTYz8ySSbFkF9cQ6GNk8VkcgkhLsJBdVENzq5XmVitfHCplcUq0JpymOGvxKs/dzrzxUfxj5XR+8Poubnl5J6/cPAt/H6NLY5RUN7LlcCkrpid2Ld32DdaaHMy4SWt48OnDmlcfP9XtOW/cV0RL+TzeuuVhRkQ42QQ7fRQ+fPSsNu4AK6Yn8v7eQpakxeJndm19vYm0BAvNbVZySmqoqGuhtqlVVaUqvM9zt3PRxBj+es1Udp4o5/bXdupusNzcauXZrUdZuGoLP1udyacHi3s+WQiYfoMmNrbrpT7Nd8O+ItITLc4NO0BZR9/Us5k54yK5Y/4Yfrhg7GBPZVBJi++oVN2UdQpfk4E54yIHeVaKwcZrjTvA0vR4Hl0xhW05Zdz95h5a2qy9nr8tp5RLn9jKHzZmc96YCIL9THyW7aQxs38oTF6hxeEb9TcsduTE6Toy86u4XG8Bjr0pdoT3NeZwBaNB8PNLUxkXffYUcXXHqIhAgny1TdVNWaeYOy7S5W+qCu/Dq407wHdmJvHbKyfx6cFT/OSdjG7lYvMr6rnztV18/4VvaLVKXrhhJi/ceA4LkqP5LLsUay8SswDMuBla6mDff9ya4wZbKf1lk3Ua97LDWm/QgHC3rqfwLgwGwcT4ED7aX0x+RUNHYw7FWY1XxtzP5PrZo6hvbuPRD7PxNxt49OopGAyCxpY2/vVFLv/ccgQh4KdLkrll7uj2+O3ilGg+yCgks6CKqUmhPV8gYbpW0brzJS0W72KXn/UZRUwbEaq/4KTsyFkfb1d0ZnKChW+OlQPa61ahOCuMO8Cd88dS39TKk58dwd9sZM64SP7fhoPklTdw+eQ4fnF5apey//kTojAI+CzrVO/GXQiYeROsvw8KdkHiTN3zyi2t5WBRNb+63IXu82WHIeXsEQtTOMeuEJmeaDnrJBgU3eP1YRlH7rtoArfOHc0rX53g9td24Wcy8uat5/KPldO71XMJC/RhxsgwNjuLuwNM/rbWq3Pniy7Nya5uqDvefnI71JdBXLpL11F4N1MSNedDFS4p7Jw1njvY9FwuTyUs0IcAHyPfO28kZmPvn2+LUmL400fZFFc1trfy6xbfYM3AZ7wFS34P/vramq3PLGLmyLD2TlJO+eJRCIjQtG8UChtjo4L41/dnMFdlyShsnFWeO2gG/q6F47hpzminhh1oL45xmjUDWmimtREy/q1rLkdKasguruEKvV573jdw9DOYcy/4nB0NKRT6WTIplkCl3a6wcdYZd1cZHx1EYpg/n2Wfcn5yXDokzNBCMzp0Z9ZnFiEEXKo3S2aLzWs/51Z95ysUirMWZdydIITgwtQYvjxS1mMj4k7MvBnKDsHJr5yeuiGziFmjwttbBPZK3jdwdDOc/yPltSsUCqco466DRSnRNLZY+d9RHW33Jl0NvhanG6uHimvIKanVH5JRXrtCoXABp8ZdCPGiEKJECLHf4Vi4EOJTIUSO7XeY7bgQQjwphDgihMgUQkzvz8kPFOeOCSfAx8jmLB1xd58ASL8WDr4Pdad7PG1DZiEGAZek6TDueTs6vHbfIBdmrlAozlb0eO4vA5eccewhYLOUcjyw2fY3wKXAeNvP7cDTnpnm4OJrMjJvfCSfZZcg9Wi4z7wJ2pph7xvd3i2lZH1mEeeNiSAquHftdqAjQ0Z57QqFQidOjbuUcitQfsbhK4FXbLdfAZY7HH9VanwNhAohvKJj8eKUGIqqGskqqnF+cnQqjJgNu14Ga1c9m6yiGnLL6rhiSrzzsfJ2wJFNymtXKBQu4W7MPUZKWWS7XQzYKycSgDyH8/Jtx4Y9C1KiAPRlzYAmB1x+FI5v7XLX+sxCjAbBkkk6Ck6U165QKNygzxuqUotTuNxvTghxuxBipxBiZ2lpaV+n0e9EB/uRnmhhk564O8DEK7VCpp2dpYCllGzYV8T5YyOIcNJOj/ydNq/9HuW1KxQKl3DXuJ+yh1tsv+0WrwBIcjgv0XasC1LKZ6WUM6WUM6OiotycxsCyODWGjPxKSmt09Gc1+8HUlZC9Hmo6vP39BdWcOF2vL0tmy6PgH6416lYoFAoXcNe4rwNusN2+AXjf4fj1tqyZ84Aqh/DNsGdRSjRSwpZDOr33GTeCtRX2vNZ+aP2+QkwGwZJJsb0/Nn8nHPkU5qhYu0KhcB09qZBvAV8ByUKIfCHELcCjwEVCiBzgQtvfABuBXOAI8Bzww36Z9SAxKT6EmBBffVIEoMnyjpoHu18Ba5sWksksYu74SOeNu5XXrlAo+oBTIQopZU8KVYu7OVcCd/V1UkMVIQSLUmJYt7eA5lYrPiYdX3xm3gyrb4Kjn5Hhdw75FQ3cu9iJFnv+Ls1rX/yI8toVCoVbqApVF1mcEk1dc1t7YwSnpFwBgVGw8yU2ZBZiNgoudhaS+cLmtc9SXrtCoXAPZdxdZM64SHxNBjZl6UyJNPnA1JXIwx9Su+c9Lh3jg8Xf3PP5+bsg5xNbhszZ3RtUoVC4jzLuLuLvY+T8sRFszj6lr1oVYObNtPmE8MfWx3gybwU8dQ68fxfsfg1KD3dWkPziT1oKpfLaFQpFH1Diz26wODWGzw+VcrS0lnHROrzrsJH8aeK7HNyxhRcXW/Et2gnZG2DP69r9/mGQdC5EToCcj2Hxw8prVygUfUIZdzdYZGtAvDmrRJdxb7NK1h2oIH3CfHwX2vqrWq1w+gjkfQ1527X2eYc/goBImHV7f05foVCcBSjj7gbxof6kxoWwObuEO+aP7fXckupG7ntnL6eqm7hqmoMSg8EAURO0n+nXa8fqToO0Kq9doVD0GRVzd5PFKdHsOlFBZX1zj+dsOVTCpU9sY9eJCv60YjKXpDnJkgmMgKDhUa2rUCiGNsq4u8mi1GjarJIvDnfVxWlutfLHjVnc+NIOooJ9+eDuuVxzzgiEEIMwU4VCcTaiwjJukp4YSkSgD5uzSrhyake45eTpeu55ew8ZeZV877wR/OryifiZjYM4U4VCcTaijLubGA2CBcnRfHqwmNY2KyajgQ8yCvnFu/tAwNMrp+tvfK1QKBQeRhn3PnBhajRrdufz5ZEyPj5QzFvf5DF9RChPXDuNpPCAwZ6eQqE4i1HGvQ/MHR+J2Si47dWdtFolP1wwlvsumoDZqLYyFArF4KKMex8I9jOzMDma3Scr+es16cwbrzJdFArF0EAZ9z7y5HXTEEJroq1QKBRDBWXc+4jKhFEoFEMRFRxWKBQKL0QZd4VCofBClHFXKBQKL0QZd4VCofBClHFXKBQKL0QZd4VCofBClHFXKBQKL0To7gPan5MQogY4pONUC1DlgXMGY6zBuOZgjBUJlA3wNYfzWINxTU+u5VB9joNxzcEYa7yU0tLtPVLKQf8Bduo871lPnDMYYw33+bswltev5Vn0unC6lkP1OQ7x/+uAjDXcwjIfeOicwRhrMK45GGPpZajOX70uXGOoPsfBuOaQGmuohGV2SilnDvY8FH1HraX3oNZyeDNUPPdnB3sCCo+h1tJ7UGs5jBkSnrtCoVAoPMtQ8dy9DiFErZP7twgh1FfeYYBaS+/hbFpLZdwVCoXCCxlQ4+7sU9PbEEIsEEKsd/j7KSHEjYM4JY+h1lKt5XDFm9fSEeW5KxQKhRcy4MZdCBEkhNgshNgthNgnhLjSdnyUECJLCPGcEOKAEOITIYT/QM9PoR+1lt6DWkvvYzA890bgKinldGAh8BchhLDdNx74h5RyElAJrBiE+XmSVjr/j/0GayL9hFpL70GtpZcxGMZdAH8QQmQCm4AEIMZ23zEp5V7b7V3AqIGfnkc5AUwUQvgKIUKBxYM9IQ+j1tJ7UGvpZQxGg+yVQBQwQ0rZIoQ4TscnZ5PDeW3AsPz6J4QwAU1SyjwhxDvAfuAYsGdwZ+Zx1Fp6D2otvYzBMO4WoMT2AloIjByEOfQ3k4CjAFLKnwE/O/MEKeWCAZ5Tf6DWErWWw4izZS2BATTu9k9N4A3gAyHEPmAnkD1QcxgIhBB3Aj8CfjzYc+kv1Fp6D2otvZcBkx8QQqQDz0kpZw3IBRX9hlpL70GtpfcyIBuqtk/Nt4BfDcT1FP2HWkvvQa2ld6OEwxQKhcIL6RfPXQiRJIT4XAhx0Fb4cK/teLgQ4lMhRI7td5jteIoQ4ishRJMQ4oEzxie+Tz8AAATMSURBVAoVQqwWQmTbiilm98ecFd3jqbUUQiQLIfY6/FQLIc6a+OdQwMPvy/tsY+wXQrwlhPDKXPHhTL947kKIOCBOSrlbCBGMlhu7HLgRKJdSPiqEeAgIk1I+KISIRtudXw5USClXOYz1CrBNSvm8EMIHCJBSVnp80opu8eRaOoxpBAqAc6WUJwbquZzteGothRAJwJfARCllgy2tcKOU8uWBf1aKnugXz11KWSSl3G27XQNkoRVFXAm8YjvtFbQXDVLKEinlDqDFcRwhhAW4AHjBdl6zMuwDi6fW8gwWA0eVYR9YPLyWJsDflm0TABT28/QVLtLvG6pCiFHANGA7ECOlLLLdVUxHBVxPjAZKgZeEEHuEEM8LIQL7a66K3unjWjpyLdpGnmKQ6MtaSikLgFXASaAIqJJSftJvk1W4Rb8adyFEELAG+LGUstrxPqnFg5zFhEzAdOBpKeU0oA54qD/mqugdD6ylfRwfYBnwH49PUqGLvq6lLSZ/JZrzFQ8ECiG+10/TVbhJvxl3IYQZ7QX0hpTyXdvhU7a4nz3+V+JkmHwgX0q53fb3ajRjrxhAPLSWdi4FdkspT3l+pgpneGgtL0TTmymVUrYA7wLn99ecFe7RX9kyAi1OniWlfNzhrnXADbbbNwDv9zaOlLIYyBNCJNsOLQYOeni6il7w1Fo6cB0qJDMoeHAtTwLnCSECbGMuRovfK4YQ/ZUtMxfYBuwDrLbDv0CL770DjEBTZvuOlLJcCBGLVvIcYju/Fm0nvloIMRV4HvABcoGbpJQVHp+0ols8vJaBaIZhjJSyamCficLDa/kb4Bo0+dw9wK1SSkeBMcUgo4qYFAqFwgtRbfYUCoXCC1HGXaFQKLwQZdwVCoXCC1HGXaFQKLwQZdwVCoXCC1HGXaFQKLwQZdwVXoMQos0mJ5whhNgthDjfdjxeCLHadnuBEGK97faNQoinehnv/4QQBbYxc4QQ7wohJuqYx41CiHhPPS+Fwh2UcVd4Ew1SyqlSynTg58AfAaSUhVLKb7k55l9tY44H/g18JoSIcvKYG9E0VxSKQUMZd4W3EgJUgKaAKITY39cBpZT/Bj4Bvmsb92EhxA5bw4pnhca3gJnAGzaP318IMUMI8YUQYpcQ4mO7jotC0Z8o467wJvxtBjUbTbLi//XDNXYDKbbbT0kpz5FSpgH+wBVSytVoJfsrpZRT0crz/w58S0o5A3gR+H0/zEuh6IRpsCegUHiQBptBRWjtGF8VQqR5+BrC4fZCIcTP0JpVhAMHgA/OOD8ZSAM+1TS2MKJpoCsU/Yoy7gqvREr5lRAiEnAWH3eVacBOW8/QfwIzpZR5Qoj/A7rrIyqAA1JK1ftXMaCosIzCKxFCpKB5yac9OOYK4GI0yWK7IS+zNb9w3LCtAYJttw8BUbZvEgghzEKISZ6ak0LRE8pzV3gT/kKIvbbbArhBStlmC4e4y322LkOBwH5gkZSyFEAI8ZztWDGww+ExLwPPCCEagNlohv9JW09gE/A3tBCOQtFvKMlfhUKh8EJUWEahUCi8EBWWUZz1CCF+CXz7jMP/kVKqlEXFsEWFZRQKhcILUWEZhUKh8EKUcVcoFAovRBl3hUKh8EKUcVcoFAovRBl3hUKh8EL+P5dZWt/aHbTAAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "uhcPr9xknBNt"
      },
      "source": [
        "![alt text](data:image/png;base64,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)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HYvGM7b-_dxS",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "e3d2a2a2-5fae-4483-e763-dabb7c5e857e"
      },
      "source": [
        "((bill_2018['Billed_amount']-bill_2018['ma_rolling_3'])**2).mean()**0.5"
      ],
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "70.98561687433802"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 32
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1arUawX-_dt3",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "c3a3e869-bec7-4d4b-d412-b8584e7d7a27"
      },
      "source": [
        "((bill_2018['Billed_amount']-bill_2018['wma_rolling_3'])**2).mean()**0.5"
      ],
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "65.82572602256133"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 33
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MUWkFpAl_dqN",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "80051e2d-8702-43ec-d769-a95e9d4647bb"
      },
      "source": [
        "((bill_2018['Billed_amount']-bill_2018['ewm_window_3'])**2).mean()**0.5"
      ],
      "execution_count": 34,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "64.32131239414655"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 34
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "sKzKitcI_dnB",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "ff17fb18-1c8c-46ff-e06b-5b3ac9505732"
      },
      "source": [
        "((bill_2018['Billed_amount']-bill_2018['esm_window_3_7'])**2).mean()**0.5"
      ],
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "61.26408398853503"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 35
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "V44L0DG3_dhD",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "5d4b3b0d-d305-4b70-9c82-9f7a34ccfb7c"
      },
      "source": [
        "((bill_2018['Billed_amount']-bill_2018['esm_window_3_3'])**2).mean()**0.5"
      ],
      "execution_count": 36,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "65.22424423118377"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 36
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "lYSR2JBr1d6o"
      },
      "source": [
        "-----------------------------------------"
      ]
    }
  ]
}