Airborne_activity_Mazyr.ipynb

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    "colab": {
      "name": "Airborne_activity_Mazyr.ipynb",
      "provenance": [],
      "include_colab_link": true
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/ADv0rnik/Data-analysis-for-JER/blob/main/Airborne_activity_Mazyr.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hVHGQ_h1klep",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "7664adb4-282a-41d1-e376-446e2abc5343"
      },
      "source": [
        "import pandas as pd\n",
        "import matplotlib\n",
        "import matplotlib.pyplot as plt\n",
        "import numpy as np\n",
        "%matplotlib inline\n",
        "from statsmodels.tsa.seasonal import seasonal_decompose\n",
        "from statsmodels.tsa.holtwinters import SimpleExpSmoothing\n",
        "from statsmodels.tsa.holtwinters import ExponentialSmoothing\n",
        "import seaborn as sns"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/statsmodels/tools/_testing.py:19: FutureWarning: pandas.util.testing is deprecated. Use the functions in the public API at pandas.testing instead.\n",
            "  import pandas.util.testing as tm\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "eRbQi5fqk0VK",
        "outputId": "69358939-aa65-46a7-d309-09b0abd1ebff"
      },
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        },
        "id": "qQ8n3t_ckles",
        "outputId": "2d613934-64ff-4492-e8f5-2fcddbc913f5"
      },
      "source": [
        "df = pd.read_csv('/content/drive/MyDrive/Colab Notebooks/Data for JER/Airborne activity_Mazyr_2007_2018.csv', parse_dates = ['Date'])\n",
        "df.columns = ['Date', 'Conc']\n",
        "df"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Date</th>\n",
              "      <th>Conc</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2007-01-01</td>\n",
              "      <td>9.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2007-01-02</td>\n",
              "      <td>5.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2007-01-03</td>\n",
              "      <td>10.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2007-01-04</td>\n",
              "      <td>10.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2007-01-05</td>\n",
              "      <td>15.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4104</th>\n",
              "      <td>2018-12-27</td>\n",
              "      <td>16.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4105</th>\n",
              "      <td>2018-12-28</td>\n",
              "      <td>11.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4106</th>\n",
              "      <td>2018-12-29</td>\n",
              "      <td>6.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4107</th>\n",
              "      <td>2018-12-30</td>\n",
              "      <td>24.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4108</th>\n",
              "      <td>2018-12-31</td>\n",
              "      <td>8.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>4109 rows × 2 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "           Date  Conc\n",
              "0    2007-01-01   9.0\n",
              "1    2007-01-02   5.0\n",
              "2    2007-01-03  10.0\n",
              "3    2007-01-04  10.0\n",
              "4    2007-01-05  15.0\n",
              "...         ...   ...\n",
              "4104 2018-12-27  16.0\n",
              "4105 2018-12-28  11.0\n",
              "4106 2018-12-29   6.0\n",
              "4107 2018-12-30  24.0\n",
              "4108 2018-12-31   8.0\n",
              "\n",
              "[4109 rows x 2 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "J1ae6PdckwoM",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 297
        },
        "outputId": "368d55b1-fe14-4f3d-8924-d3d4f327dd50"
      },
      "source": [
        "df.describe()"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Conc</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>4035.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>19.402478</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>12.789265</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>11.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>16.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>24.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>115.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "              Conc\n",
              "count  4035.000000\n",
              "mean     19.402478\n",
              "std      12.789265\n",
              "min       1.000000\n",
              "25%      11.000000\n",
              "50%      16.000000\n",
              "75%      24.000000\n",
              "max     115.000000"
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "scrolled": true,
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 450
        },
        "id": "jsI5gltrklet",
        "outputId": "ec3a1c75-8cf7-4182-ba75-108878765b34"
      },
      "source": [
        "df = df.resample('W', on = 'Date').mean()\n",
        "df"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Conc</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Date</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2007-01-07</th>\n",
              "      <td>8.285714</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2007-01-14</th>\n",
              "      <td>6.428571</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2007-01-21</th>\n",
              "      <td>8.857143</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2007-01-28</th>\n",
              "      <td>9.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2007-02-04</th>\n",
              "      <td>10.333333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-12-09</th>\n",
              "      <td>16.857143</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-12-16</th>\n",
              "      <td>22.142857</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-12-23</th>\n",
              "      <td>15.571429</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-12-30</th>\n",
              "      <td>13.285714</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-01-06</th>\n",
              "      <td>8.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>627 rows × 1 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                 Conc\n",
              "Date                 \n",
              "2007-01-07   8.285714\n",
              "2007-01-14   6.428571\n",
              "2007-01-21   8.857143\n",
              "2007-01-28   9.000000\n",
              "2007-02-04  10.333333\n",
              "...               ...\n",
              "2018-12-09  16.857143\n",
              "2018-12-16  22.142857\n",
              "2018-12-23  15.571429\n",
              "2018-12-30  13.285714\n",
              "2019-01-06   8.000000\n",
              "\n",
              "[627 rows x 1 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "scrolled": true,
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        },
        "id": "L3FX8ngNklet",
        "outputId": "91270070-26be-41a1-bdf7-192b3ba8eab8"
      },
      "source": [
        "#OK result = df03.iloc[:, 1].div(df03.Conc.mean(), axis = 0)\n",
        "df.reset_index(inplace = True)\n",
        "df['Week'] = df.Date.dt.isocalendar().week\n",
        "df['Year'] = df.Date.dt.year\n",
        "df"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Date</th>\n",
              "      <th>Conc</th>\n",
              "      <th>Week</th>\n",
              "      <th>Year</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2007-01-07</td>\n",
              "      <td>8.285714</td>\n",
              "      <td>1</td>\n",
              "      <td>2007</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2007-01-14</td>\n",
              "      <td>6.428571</td>\n",
              "      <td>2</td>\n",
              "      <td>2007</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2007-01-21</td>\n",
              "      <td>8.857143</td>\n",
              "      <td>3</td>\n",
              "      <td>2007</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2007-01-28</td>\n",
              "      <td>9.000000</td>\n",
              "      <td>4</td>\n",
              "      <td>2007</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2007-02-04</td>\n",
              "      <td>10.333333</td>\n",
              "      <td>5</td>\n",
              "      <td>2007</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>622</th>\n",
              "      <td>2018-12-09</td>\n",
              "      <td>16.857143</td>\n",
              "      <td>49</td>\n",
              "      <td>2018</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>623</th>\n",
              "      <td>2018-12-16</td>\n",
              "      <td>22.142857</td>\n",
              "      <td>50</td>\n",
              "      <td>2018</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>624</th>\n",
              "      <td>2018-12-23</td>\n",
              "      <td>15.571429</td>\n",
              "      <td>51</td>\n",
              "      <td>2018</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>625</th>\n",
              "      <td>2018-12-30</td>\n",
              "      <td>13.285714</td>\n",
              "      <td>52</td>\n",
              "      <td>2018</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>626</th>\n",
              "      <td>2019-01-06</td>\n",
              "      <td>8.000000</td>\n",
              "      <td>1</td>\n",
              "      <td>2019</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>627 rows × 4 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "          Date       Conc  Week  Year\n",
              "0   2007-01-07   8.285714     1  2007\n",
              "1   2007-01-14   6.428571     2  2007\n",
              "2   2007-01-21   8.857143     3  2007\n",
              "3   2007-01-28   9.000000     4  2007\n",
              "4   2007-02-04  10.333333     5  2007\n",
              "..         ...        ...   ...   ...\n",
              "622 2018-12-09  16.857143    49  2018\n",
              "623 2018-12-16  22.142857    50  2018\n",
              "624 2018-12-23  15.571429    51  2018\n",
              "625 2018-12-30  13.285714    52  2018\n",
              "626 2019-01-06   8.000000     1  2019\n",
              "\n",
              "[627 rows x 4 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "f4-9qKR4kleu",
        "outputId": "f582759d-5d3c-45e6-8499-0a1c6eed98e2"
      },
      "source": [
        "df07 = df[df['Year'] == 2007]\n",
        "df07"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2007-01-07</td>\n",
              "      <td>8.285714</td>\n",
              "      <td>1</td>\n",
              "      <td>2007</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2007-01-14</td>\n",
              "      <td>6.428571</td>\n",
              "      <td>2</td>\n",
              "      <td>2007</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2007-01-21</td>\n",
              "      <td>8.857143</td>\n",
              "      <td>3</td>\n",
              "      <td>2007</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2007-01-28</td>\n",
              "      <td>9.000000</td>\n",
              "      <td>4</td>\n",
              "      <td>2007</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2007-02-04</td>\n",
              "      <td>10.333333</td>\n",
              "      <td>5</td>\n",
              "      <td>2007</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>2007-02-11</td>\n",
              "      <td>9.285714</td>\n",
              "      <td>6</td>\n",
              "      <td>2007</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>2007-02-18</td>\n",
              "      <td>15.142857</td>\n",
              "      <td>7</td>\n",
              "      <td>2007</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>2007-02-25</td>\n",
              "      <td>16.142857</td>\n",
              "      <td>8</td>\n",
              "      <td>2007</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>2007-03-04</td>\n",
              "      <td>16.714286</td>\n",
              "      <td>9</td>\n",
              "      <td>2007</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>2007-03-11</td>\n",
              "      <td>11.000000</td>\n",
              "      <td>10</td>\n",
              "      <td>2007</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>2007-03-18</td>\n",
              "      <td>14.000000</td>\n",
              "      <td>11</td>\n",
              "      <td>2007</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>2007-03-25</td>\n",
              "      <td>32.200000</td>\n",
              "      <td>12</td>\n",
              "      <td>2007</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>2007-04-01</td>\n",
              "      <td>21.000000</td>\n",
              "      <td>13</td>\n",
              "      <td>2007</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>2007-04-08</td>\n",
              "      <td>25.000000</td>\n",
              "      <td>14</td>\n",
              "      <td>2007</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>2007-04-15</td>\n",
              "      <td>12.428571</td>\n",
              "      <td>15</td>\n",
              "      <td>2007</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>2007-04-22</td>\n",
              "      <td>14.000000</td>\n",
              "      <td>16</td>\n",
              "      <td>2007</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>2007-04-29</td>\n",
              "      <td>13.428571</td>\n",
              "      <td>17</td>\n",
              "      <td>2007</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>2007-05-06</td>\n",
              "      <td>17.857143</td>\n",
              "      <td>18</td>\n",
              "      <td>2007</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>2007-05-13</td>\n",
              "      <td>11.857143</td>\n",
              "      <td>19</td>\n",
              "      <td>2007</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>2007-05-20</td>\n",
              "      <td>18.857143</td>\n",
              "      <td>20</td>\n",
              "      <td>2007</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>2007-05-27</td>\n",
              "      <td>30.571429</td>\n",
              "      <td>21</td>\n",
              "      <td>2007</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>2007-06-03</td>\n",
              "      <td>21.000000</td>\n",
              "      <td>22</td>\n",
              "      <td>2007</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>2007-06-10</td>\n",
              "      <td>20.714286</td>\n",
              "      <td>23</td>\n",
              "      <td>2007</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>2007-06-17</td>\n",
              "      <td>20.714286</td>\n",
              "      <td>24</td>\n",
              "      <td>2007</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>2007-06-24</td>\n",
              "      <td>15.285714</td>\n",
              "      <td>25</td>\n",
              "      <td>2007</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>2007-07-01</td>\n",
              "      <td>13.428571</td>\n",
              "      <td>26</td>\n",
              "      <td>2007</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>2007-07-08</td>\n",
              "      <td>9.571429</td>\n",
              "      <td>27</td>\n",
              "      <td>2007</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>2007-07-15</td>\n",
              "      <td>14.142857</td>\n",
              "      <td>28</td>\n",
              "      <td>2007</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>2007-07-22</td>\n",
              "      <td>15.714286</td>\n",
              "      <td>29</td>\n",
              "      <td>2007</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>2007-07-29</td>\n",
              "      <td>14.000000</td>\n",
              "      <td>30</td>\n",
              "      <td>2007</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>30</th>\n",
              "      <td>2007-08-05</td>\n",
              "      <td>8.714286</td>\n",
              "      <td>31</td>\n",
              "      <td>2007</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>31</th>\n",
              "      <td>2007-08-12</td>\n",
              "      <td>25.285714</td>\n",
              "      <td>32</td>\n",
              "      <td>2007</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>32</th>\n",
              "      <td>2007-08-19</td>\n",
              "      <td>21.428571</td>\n",
              "      <td>33</td>\n",
              "      <td>2007</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>33</th>\n",
              "      <td>2007-08-26</td>\n",
              "      <td>23.166667</td>\n",
              "      <td>34</td>\n",
              "      <td>2007</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>34</th>\n",
              "      <td>2007-09-02</td>\n",
              "      <td>16.000000</td>\n",
              "      <td>35</td>\n",
              "      <td>2007</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>35</th>\n",
              "      <td>2007-09-09</td>\n",
              "      <td>20.285714</td>\n",
              "      <td>36</td>\n",
              "      <td>2007</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>36</th>\n",
              "      <td>2007-09-16</td>\n",
              "      <td>12.142857</td>\n",
              "      <td>37</td>\n",
              "      <td>2007</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>37</th>\n",
              "      <td>2007-09-23</td>\n",
              "      <td>34.000000</td>\n",
              "      <td>38</td>\n",
              "      <td>2007</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>38</th>\n",
              "      <td>2007-09-30</td>\n",
              "      <td>28.333333</td>\n",
              "      <td>39</td>\n",
              "      <td>2007</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39</th>\n",
              "      <td>2007-10-07</td>\n",
              "      <td>32.428571</td>\n",
              "      <td>40</td>\n",
              "      <td>2007</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>40</th>\n",
              "      <td>2007-10-14</td>\n",
              "      <td>24.571429</td>\n",
              "      <td>41</td>\n",
              "      <td>2007</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>41</th>\n",
              "      <td>2007-10-21</td>\n",
              "      <td>20.142857</td>\n",
              "      <td>42</td>\n",
              "      <td>2007</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>42</th>\n",
              "      <td>2007-10-28</td>\n",
              "      <td>25.142857</td>\n",
              "      <td>43</td>\n",
              "      <td>2007</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>43</th>\n",
              "      <td>2007-11-04</td>\n",
              "      <td>18.285714</td>\n",
              "      <td>44</td>\n",
              "      <td>2007</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>44</th>\n",
              "      <td>2007-11-11</td>\n",
              "      <td>18.285714</td>\n",
              "      <td>45</td>\n",
              "      <td>2007</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>45</th>\n",
              "      <td>2007-11-18</td>\n",
              "      <td>23.285714</td>\n",
              "      <td>46</td>\n",
              "      <td>2007</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>46</th>\n",
              "      <td>2007-11-25</td>\n",
              "      <td>15.571429</td>\n",
              "      <td>47</td>\n",
              "      <td>2007</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>47</th>\n",
              "      <td>2007-12-02</td>\n",
              "      <td>24.000000</td>\n",
              "      <td>48</td>\n",
              "      <td>2007</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48</th>\n",
              "      <td>2007-12-09</td>\n",
              "      <td>17.000000</td>\n",
              "      <td>49</td>\n",
              "      <td>2007</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>49</th>\n",
              "      <td>2007-12-16</td>\n",
              "      <td>25.714286</td>\n",
              "      <td>50</td>\n",
              "      <td>2007</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50</th>\n",
              "      <td>2007-12-23</td>\n",
              "      <td>10.571429</td>\n",
              "      <td>51</td>\n",
              "      <td>2007</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>51</th>\n",
              "      <td>2007-12-30</td>\n",
              "      <td>19.285714</td>\n",
              "      <td>52</td>\n",
              "      <td>2007</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "         Date       Conc  Week  Year\n",
              "0  2007-01-07   8.285714     1  2007\n",
              "1  2007-01-14   6.428571     2  2007\n",
              "2  2007-01-21   8.857143     3  2007\n",
              "3  2007-01-28   9.000000     4  2007\n",
              "4  2007-02-04  10.333333     5  2007\n",
              "5  2007-02-11   9.285714     6  2007\n",
              "6  2007-02-18  15.142857     7  2007\n",
              "7  2007-02-25  16.142857     8  2007\n",
              "8  2007-03-04  16.714286     9  2007\n",
              "9  2007-03-11  11.000000    10  2007\n",
              "10 2007-03-18  14.000000    11  2007\n",
              "11 2007-03-25  32.200000    12  2007\n",
              "12 2007-04-01  21.000000    13  2007\n",
              "13 2007-04-08  25.000000    14  2007\n",
              "14 2007-04-15  12.428571    15  2007\n",
              "15 2007-04-22  14.000000    16  2007\n",
              "16 2007-04-29  13.428571    17  2007\n",
              "17 2007-05-06  17.857143    18  2007\n",
              "18 2007-05-13  11.857143    19  2007\n",
              "19 2007-05-20  18.857143    20  2007\n",
              "20 2007-05-27  30.571429    21  2007\n",
              "21 2007-06-03  21.000000    22  2007\n",
              "22 2007-06-10  20.714286    23  2007\n",
              "23 2007-06-17  20.714286    24  2007\n",
              "24 2007-06-24  15.285714    25  2007\n",
              "25 2007-07-01  13.428571    26  2007\n",
              "26 2007-07-08   9.571429    27  2007\n",
              "27 2007-07-15  14.142857    28  2007\n",
              "28 2007-07-22  15.714286    29  2007\n",
              "29 2007-07-29  14.000000    30  2007\n",
              "30 2007-08-05   8.714286    31  2007\n",
              "31 2007-08-12  25.285714    32  2007\n",
              "32 2007-08-19  21.428571    33  2007\n",
              "33 2007-08-26  23.166667    34  2007\n",
              "34 2007-09-02  16.000000    35  2007\n",
              "35 2007-09-09  20.285714    36  2007\n",
              "36 2007-09-16  12.142857    37  2007\n",
              "37 2007-09-23  34.000000    38  2007\n",
              "38 2007-09-30  28.333333    39  2007\n",
              "39 2007-10-07  32.428571    40  2007\n",
              "40 2007-10-14  24.571429    41  2007\n",
              "41 2007-10-21  20.142857    42  2007\n",
              "42 2007-10-28  25.142857    43  2007\n",
              "43 2007-11-04  18.285714    44  2007\n",
              "44 2007-11-11  18.285714    45  2007\n",
              "45 2007-11-18  23.285714    46  2007\n",
              "46 2007-11-25  15.571429    47  2007\n",
              "47 2007-12-02  24.000000    48  2007\n",
              "48 2007-12-09  17.000000    49  2007\n",
              "49 2007-12-16  25.714286    50  2007\n",
              "50 2007-12-23  10.571429    51  2007\n",
              "51 2007-12-30  19.285714    52  2007"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4axi_vISkleu"
      },
      "source": [
        "#df_uni = df03.append(df04, sort = False)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "9e3Fu4jIklev",
        "outputId": "c9b33a9f-6386-4e84-95d2-1109fcf36add"
      },
      "source": [
        "#write function for calculating w_i\n",
        "def wi_calc(my_df, year):\n",
        "    df_x = my_df[my_df['Year'] == year].dropna()\n",
        "    result = df_x.iloc[:, 1].div(df_x.Conc.mean(), axis = 0)\n",
        "    return result\n",
        "\n",
        "df07['w_i'] = wi_calc(df, 2007)\n",
        "df07"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:7: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  import sys\n"
          ]
        },
        {
          "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>Date</th>\n",
              "      <th>Conc</th>\n",
              "      <th>Week</th>\n",
              "      <th>Year</th>\n",
              "      <th>w_i</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2007-01-07</td>\n",
              "      <td>8.285714</td>\n",
              "      <td>1</td>\n",
              "      <td>2007</td>\n",
              "      <td>0.462986</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2007-01-14</td>\n",
              "      <td>6.428571</td>\n",
              "      <td>2</td>\n",
              "      <td>2007</td>\n",
              "      <td>0.359213</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2007-01-21</td>\n",
              "      <td>8.857143</td>\n",
              "      <td>3</td>\n",
              "      <td>2007</td>\n",
              "      <td>0.494916</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2007-01-28</td>\n",
              "      <td>9.000000</td>\n",
              "      <td>4</td>\n",
              "      <td>2007</td>\n",
              "      <td>0.502899</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2007-02-04</td>\n",
              "      <td>10.333333</td>\n",
              "      <td>5</td>\n",
              "      <td>2007</td>\n",
              "      <td>0.577402</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>2007-02-11</td>\n",
              "      <td>9.285714</td>\n",
              "      <td>6</td>\n",
              "      <td>2007</td>\n",
              "      <td>0.518864</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>2007-02-18</td>\n",
              "      <td>15.142857</td>\n",
              "      <td>7</td>\n",
              "      <td>2007</td>\n",
              "      <td>0.846147</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>2007-02-25</td>\n",
              "      <td>16.142857</td>\n",
              "      <td>8</td>\n",
              "      <td>2007</td>\n",
              "      <td>0.902025</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>2007-03-04</td>\n",
              "      <td>16.714286</td>\n",
              "      <td>9</td>\n",
              "      <td>2007</td>\n",
              "      <td>0.933955</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>2007-03-11</td>\n",
              "      <td>11.000000</td>\n",
              "      <td>10</td>\n",
              "      <td>2007</td>\n",
              "      <td>0.614654</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>2007-03-18</td>\n",
              "      <td>14.000000</td>\n",
              "      <td>11</td>\n",
              "      <td>2007</td>\n",
              "      <td>0.782287</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>2007-03-25</td>\n",
              "      <td>32.200000</td>\n",
              "      <td>12</td>\n",
              "      <td>2007</td>\n",
              "      <td>1.799260</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>2007-04-01</td>\n",
              "      <td>21.000000</td>\n",
              "      <td>13</td>\n",
              "      <td>2007</td>\n",
              "      <td>1.173430</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>2007-04-08</td>\n",
              "      <td>25.000000</td>\n",
              "      <td>14</td>\n",
              "      <td>2007</td>\n",
              "      <td>1.396941</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>2007-04-15</td>\n",
              "      <td>12.428571</td>\n",
              "      <td>15</td>\n",
              "      <td>2007</td>\n",
              "      <td>0.694479</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>2007-04-22</td>\n",
              "      <td>14.000000</td>\n",
              "      <td>16</td>\n",
              "      <td>2007</td>\n",
              "      <td>0.782287</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>2007-04-29</td>\n",
              "      <td>13.428571</td>\n",
              "      <td>17</td>\n",
              "      <td>2007</td>\n",
              "      <td>0.750357</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>2007-05-06</td>\n",
              "      <td>17.857143</td>\n",
              "      <td>18</td>\n",
              "      <td>2007</td>\n",
              "      <td>0.997815</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>2007-05-13</td>\n",
              "      <td>11.857143</td>\n",
              "      <td>19</td>\n",
              "      <td>2007</td>\n",
              "      <td>0.662549</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>2007-05-20</td>\n",
              "      <td>18.857143</td>\n",
              "      <td>20</td>\n",
              "      <td>2007</td>\n",
              "      <td>1.053693</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>2007-05-27</td>\n",
              "      <td>30.571429</td>\n",
              "      <td>21</td>\n",
              "      <td>2007</td>\n",
              "      <td>1.708259</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>2007-06-03</td>\n",
              "      <td>21.000000</td>\n",
              "      <td>22</td>\n",
              "      <td>2007</td>\n",
              "      <td>1.173430</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>2007-06-10</td>\n",
              "      <td>20.714286</td>\n",
              "      <td>23</td>\n",
              "      <td>2007</td>\n",
              "      <td>1.157465</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>2007-06-17</td>\n",
              "      <td>20.714286</td>\n",
              "      <td>24</td>\n",
              "      <td>2007</td>\n",
              "      <td>1.157465</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>2007-06-24</td>\n",
              "      <td>15.285714</td>\n",
              "      <td>25</td>\n",
              "      <td>2007</td>\n",
              "      <td>0.854130</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>2007-07-01</td>\n",
              "      <td>13.428571</td>\n",
              "      <td>26</td>\n",
              "      <td>2007</td>\n",
              "      <td>0.750357</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>2007-07-08</td>\n",
              "      <td>9.571429</td>\n",
              "      <td>27</td>\n",
              "      <td>2007</td>\n",
              "      <td>0.534829</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>2007-07-15</td>\n",
              "      <td>14.142857</td>\n",
              "      <td>28</td>\n",
              "      <td>2007</td>\n",
              "      <td>0.790270</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>2007-07-22</td>\n",
              "      <td>15.714286</td>\n",
              "      <td>29</td>\n",
              "      <td>2007</td>\n",
              "      <td>0.878077</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>2007-07-29</td>\n",
              "      <td>14.000000</td>\n",
              "      <td>30</td>\n",
              "      <td>2007</td>\n",
              "      <td>0.782287</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>30</th>\n",
              "      <td>2007-08-05</td>\n",
              "      <td>8.714286</td>\n",
              "      <td>31</td>\n",
              "      <td>2007</td>\n",
              "      <td>0.486934</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>31</th>\n",
              "      <td>2007-08-12</td>\n",
              "      <td>25.285714</td>\n",
              "      <td>32</td>\n",
              "      <td>2007</td>\n",
              "      <td>1.412906</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>32</th>\n",
              "      <td>2007-08-19</td>\n",
              "      <td>21.428571</td>\n",
              "      <td>33</td>\n",
              "      <td>2007</td>\n",
              "      <td>1.197378</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>33</th>\n",
              "      <td>2007-08-26</td>\n",
              "      <td>23.166667</td>\n",
              "      <td>34</td>\n",
              "      <td>2007</td>\n",
              "      <td>1.294499</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>34</th>\n",
              "      <td>2007-09-02</td>\n",
              "      <td>16.000000</td>\n",
              "      <td>35</td>\n",
              "      <td>2007</td>\n",
              "      <td>0.894042</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>35</th>\n",
              "      <td>2007-09-09</td>\n",
              "      <td>20.285714</td>\n",
              "      <td>36</td>\n",
              "      <td>2007</td>\n",
              "      <td>1.133518</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>36</th>\n",
              "      <td>2007-09-16</td>\n",
              "      <td>12.142857</td>\n",
              "      <td>37</td>\n",
              "      <td>2007</td>\n",
              "      <td>0.678514</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>37</th>\n",
              "      <td>2007-09-23</td>\n",
              "      <td>34.000000</td>\n",
              "      <td>38</td>\n",
              "      <td>2007</td>\n",
              "      <td>1.899840</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>38</th>\n",
              "      <td>2007-09-30</td>\n",
              "      <td>28.333333</td>\n",
              "      <td>39</td>\n",
              "      <td>2007</td>\n",
              "      <td>1.583200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39</th>\n",
              "      <td>2007-10-07</td>\n",
              "      <td>32.428571</td>\n",
              "      <td>40</td>\n",
              "      <td>2007</td>\n",
              "      <td>1.812032</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>40</th>\n",
              "      <td>2007-10-14</td>\n",
              "      <td>24.571429</td>\n",
              "      <td>41</td>\n",
              "      <td>2007</td>\n",
              "      <td>1.372993</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>41</th>\n",
              "      <td>2007-10-21</td>\n",
              "      <td>20.142857</td>\n",
              "      <td>42</td>\n",
              "      <td>2007</td>\n",
              "      <td>1.125535</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>42</th>\n",
              "      <td>2007-10-28</td>\n",
              "      <td>25.142857</td>\n",
              "      <td>43</td>\n",
              "      <td>2007</td>\n",
              "      <td>1.404924</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>43</th>\n",
              "      <td>2007-11-04</td>\n",
              "      <td>18.285714</td>\n",
              "      <td>44</td>\n",
              "      <td>2007</td>\n",
              "      <td>1.021763</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>44</th>\n",
              "      <td>2007-11-11</td>\n",
              "      <td>18.285714</td>\n",
              "      <td>45</td>\n",
              "      <td>2007</td>\n",
              "      <td>1.021763</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>45</th>\n",
              "      <td>2007-11-18</td>\n",
              "      <td>23.285714</td>\n",
              "      <td>46</td>\n",
              "      <td>2007</td>\n",
              "      <td>1.301151</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>46</th>\n",
              "      <td>2007-11-25</td>\n",
              "      <td>15.571429</td>\n",
              "      <td>47</td>\n",
              "      <td>2007</td>\n",
              "      <td>0.870095</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>47</th>\n",
              "      <td>2007-12-02</td>\n",
              "      <td>24.000000</td>\n",
              "      <td>48</td>\n",
              "      <td>2007</td>\n",
              "      <td>1.341063</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48</th>\n",
              "      <td>2007-12-09</td>\n",
              "      <td>17.000000</td>\n",
              "      <td>49</td>\n",
              "      <td>2007</td>\n",
              "      <td>0.949920</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>49</th>\n",
              "      <td>2007-12-16</td>\n",
              "      <td>25.714286</td>\n",
              "      <td>50</td>\n",
              "      <td>2007</td>\n",
              "      <td>1.436854</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50</th>\n",
              "      <td>2007-12-23</td>\n",
              "      <td>10.571429</td>\n",
              "      <td>51</td>\n",
              "      <td>2007</td>\n",
              "      <td>0.590707</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>51</th>\n",
              "      <td>2007-12-30</td>\n",
              "      <td>19.285714</td>\n",
              "      <td>52</td>\n",
              "      <td>2007</td>\n",
              "      <td>1.077640</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "         Date       Conc  Week  Year       w_i\n",
              "0  2007-01-07   8.285714     1  2007  0.462986\n",
              "1  2007-01-14   6.428571     2  2007  0.359213\n",
              "2  2007-01-21   8.857143     3  2007  0.494916\n",
              "3  2007-01-28   9.000000     4  2007  0.502899\n",
              "4  2007-02-04  10.333333     5  2007  0.577402\n",
              "5  2007-02-11   9.285714     6  2007  0.518864\n",
              "6  2007-02-18  15.142857     7  2007  0.846147\n",
              "7  2007-02-25  16.142857     8  2007  0.902025\n",
              "8  2007-03-04  16.714286     9  2007  0.933955\n",
              "9  2007-03-11  11.000000    10  2007  0.614654\n",
              "10 2007-03-18  14.000000    11  2007  0.782287\n",
              "11 2007-03-25  32.200000    12  2007  1.799260\n",
              "12 2007-04-01  21.000000    13  2007  1.173430\n",
              "13 2007-04-08  25.000000    14  2007  1.396941\n",
              "14 2007-04-15  12.428571    15  2007  0.694479\n",
              "15 2007-04-22  14.000000    16  2007  0.782287\n",
              "16 2007-04-29  13.428571    17  2007  0.750357\n",
              "17 2007-05-06  17.857143    18  2007  0.997815\n",
              "18 2007-05-13  11.857143    19  2007  0.662549\n",
              "19 2007-05-20  18.857143    20  2007  1.053693\n",
              "20 2007-05-27  30.571429    21  2007  1.708259\n",
              "21 2007-06-03  21.000000    22  2007  1.173430\n",
              "22 2007-06-10  20.714286    23  2007  1.157465\n",
              "23 2007-06-17  20.714286    24  2007  1.157465\n",
              "24 2007-06-24  15.285714    25  2007  0.854130\n",
              "25 2007-07-01  13.428571    26  2007  0.750357\n",
              "26 2007-07-08   9.571429    27  2007  0.534829\n",
              "27 2007-07-15  14.142857    28  2007  0.790270\n",
              "28 2007-07-22  15.714286    29  2007  0.878077\n",
              "29 2007-07-29  14.000000    30  2007  0.782287\n",
              "30 2007-08-05   8.714286    31  2007  0.486934\n",
              "31 2007-08-12  25.285714    32  2007  1.412906\n",
              "32 2007-08-19  21.428571    33  2007  1.197378\n",
              "33 2007-08-26  23.166667    34  2007  1.294499\n",
              "34 2007-09-02  16.000000    35  2007  0.894042\n",
              "35 2007-09-09  20.285714    36  2007  1.133518\n",
              "36 2007-09-16  12.142857    37  2007  0.678514\n",
              "37 2007-09-23  34.000000    38  2007  1.899840\n",
              "38 2007-09-30  28.333333    39  2007  1.583200\n",
              "39 2007-10-07  32.428571    40  2007  1.812032\n",
              "40 2007-10-14  24.571429    41  2007  1.372993\n",
              "41 2007-10-21  20.142857    42  2007  1.125535\n",
              "42 2007-10-28  25.142857    43  2007  1.404924\n",
              "43 2007-11-04  18.285714    44  2007  1.021763\n",
              "44 2007-11-11  18.285714    45  2007  1.021763\n",
              "45 2007-11-18  23.285714    46  2007  1.301151\n",
              "46 2007-11-25  15.571429    47  2007  0.870095\n",
              "47 2007-12-02  24.000000    48  2007  1.341063\n",
              "48 2007-12-09  17.000000    49  2007  0.949920\n",
              "49 2007-12-16  25.714286    50  2007  1.436854\n",
              "50 2007-12-23  10.571429    51  2007  0.590707\n",
              "51 2007-12-30  19.285714    52  2007  1.077640"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FcfQTPe1klev"
      },
      "source": [
        "df08 = df[df['Year'] == 2008]"
      ],
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qrTiv5pWklev",
        "outputId": "55da5746-487e-48db-d65d-d4c2182fc2a2"
      },
      "source": [
        "df08['w_i'] = wi_calc(df, 2008)"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:1: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \"\"\"Entry point for launching an IPython kernel.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "lBqEVOWkklew",
        "outputId": "d9e75f64-7677-4600-acbd-7e4018b15bd7"
      },
      "source": [
        "df08.dropna()"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Date</th>\n",
              "      <th>Conc</th>\n",
              "      <th>Week</th>\n",
              "      <th>Year</th>\n",
              "      <th>w_i</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>52</th>\n",
              "      <td>2008-01-06</td>\n",
              "      <td>30.142857</td>\n",
              "      <td>1</td>\n",
              "      <td>2008</td>\n",
              "      <td>1.791249</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>53</th>\n",
              "      <td>2008-01-13</td>\n",
              "      <td>28.000000</td>\n",
              "      <td>2</td>\n",
              "      <td>2008</td>\n",
              "      <td>1.663909</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>54</th>\n",
              "      <td>2008-01-20</td>\n",
              "      <td>23.142857</td>\n",
              "      <td>3</td>\n",
              "      <td>2008</td>\n",
              "      <td>1.375272</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>55</th>\n",
              "      <td>2008-01-27</td>\n",
              "      <td>15.285714</td>\n",
              "      <td>4</td>\n",
              "      <td>2008</td>\n",
              "      <td>0.908359</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>56</th>\n",
              "      <td>2008-02-03</td>\n",
              "      <td>18.428571</td>\n",
              "      <td>5</td>\n",
              "      <td>2008</td>\n",
              "      <td>1.095124</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>57</th>\n",
              "      <td>2008-02-10</td>\n",
              "      <td>16.428571</td>\n",
              "      <td>6</td>\n",
              "      <td>2008</td>\n",
              "      <td>0.976273</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>58</th>\n",
              "      <td>2008-02-17</td>\n",
              "      <td>19.714286</td>\n",
              "      <td>7</td>\n",
              "      <td>2008</td>\n",
              "      <td>1.171528</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>59</th>\n",
              "      <td>2008-02-24</td>\n",
              "      <td>14.571429</td>\n",
              "      <td>8</td>\n",
              "      <td>2008</td>\n",
              "      <td>0.865912</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>60</th>\n",
              "      <td>2008-03-02</td>\n",
              "      <td>21.714286</td>\n",
              "      <td>9</td>\n",
              "      <td>2008</td>\n",
              "      <td>1.290379</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>61</th>\n",
              "      <td>2008-03-09</td>\n",
              "      <td>19.285714</td>\n",
              "      <td>10</td>\n",
              "      <td>2008</td>\n",
              "      <td>1.146060</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>62</th>\n",
              "      <td>2008-03-16</td>\n",
              "      <td>13.428571</td>\n",
              "      <td>11</td>\n",
              "      <td>2008</td>\n",
              "      <td>0.797997</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>63</th>\n",
              "      <td>2008-03-23</td>\n",
              "      <td>17.142857</td>\n",
              "      <td>12</td>\n",
              "      <td>2008</td>\n",
              "      <td>1.018720</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>64</th>\n",
              "      <td>2008-03-30</td>\n",
              "      <td>17.142857</td>\n",
              "      <td>13</td>\n",
              "      <td>2008</td>\n",
              "      <td>1.018720</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>65</th>\n",
              "      <td>2008-04-06</td>\n",
              "      <td>24.857143</td>\n",
              "      <td>14</td>\n",
              "      <td>2008</td>\n",
              "      <td>1.477144</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>66</th>\n",
              "      <td>2008-04-13</td>\n",
              "      <td>20.428571</td>\n",
              "      <td>15</td>\n",
              "      <td>2008</td>\n",
              "      <td>1.213975</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>67</th>\n",
              "      <td>2008-04-20</td>\n",
              "      <td>9.571429</td>\n",
              "      <td>16</td>\n",
              "      <td>2008</td>\n",
              "      <td>0.568785</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>68</th>\n",
              "      <td>2008-04-27</td>\n",
              "      <td>21.857143</td>\n",
              "      <td>17</td>\n",
              "      <td>2008</td>\n",
              "      <td>1.298868</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>69</th>\n",
              "      <td>2008-05-04</td>\n",
              "      <td>14.142857</td>\n",
              "      <td>18</td>\n",
              "      <td>2008</td>\n",
              "      <td>0.840444</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>70</th>\n",
              "      <td>2008-05-11</td>\n",
              "      <td>17.571429</td>\n",
              "      <td>19</td>\n",
              "      <td>2008</td>\n",
              "      <td>1.044188</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>71</th>\n",
              "      <td>2008-05-18</td>\n",
              "      <td>21.428571</td>\n",
              "      <td>20</td>\n",
              "      <td>2008</td>\n",
              "      <td>1.273400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>72</th>\n",
              "      <td>2008-05-25</td>\n",
              "      <td>15.714286</td>\n",
              "      <td>21</td>\n",
              "      <td>2008</td>\n",
              "      <td>0.933827</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>73</th>\n",
              "      <td>2008-06-01</td>\n",
              "      <td>16.142857</td>\n",
              "      <td>22</td>\n",
              "      <td>2008</td>\n",
              "      <td>0.959295</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>74</th>\n",
              "      <td>2008-06-08</td>\n",
              "      <td>12.857143</td>\n",
              "      <td>23</td>\n",
              "      <td>2008</td>\n",
              "      <td>0.764040</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75</th>\n",
              "      <td>2008-06-15</td>\n",
              "      <td>20.714286</td>\n",
              "      <td>24</td>\n",
              "      <td>2008</td>\n",
              "      <td>1.230953</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>76</th>\n",
              "      <td>2008-06-22</td>\n",
              "      <td>13.285714</td>\n",
              "      <td>25</td>\n",
              "      <td>2008</td>\n",
              "      <td>0.789508</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>77</th>\n",
              "      <td>2008-06-29</td>\n",
              "      <td>17.857143</td>\n",
              "      <td>26</td>\n",
              "      <td>2008</td>\n",
              "      <td>1.061167</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>78</th>\n",
              "      <td>2008-07-06</td>\n",
              "      <td>15.333333</td>\n",
              "      <td>27</td>\n",
              "      <td>2008</td>\n",
              "      <td>0.911189</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>79</th>\n",
              "      <td>2008-07-13</td>\n",
              "      <td>11.285714</td>\n",
              "      <td>28</td>\n",
              "      <td>2008</td>\n",
              "      <td>0.670657</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>80</th>\n",
              "      <td>2008-07-20</td>\n",
              "      <td>13.285714</td>\n",
              "      <td>29</td>\n",
              "      <td>2008</td>\n",
              "      <td>0.789508</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>81</th>\n",
              "      <td>2008-07-27</td>\n",
              "      <td>20.857143</td>\n",
              "      <td>30</td>\n",
              "      <td>2008</td>\n",
              "      <td>1.239443</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>82</th>\n",
              "      <td>2008-08-03</td>\n",
              "      <td>13.428571</td>\n",
              "      <td>31</td>\n",
              "      <td>2008</td>\n",
              "      <td>0.797997</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>83</th>\n",
              "      <td>2008-08-10</td>\n",
              "      <td>15.142857</td>\n",
              "      <td>32</td>\n",
              "      <td>2008</td>\n",
              "      <td>0.899869</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>84</th>\n",
              "      <td>2008-08-17</td>\n",
              "      <td>29.571429</td>\n",
              "      <td>33</td>\n",
              "      <td>2008</td>\n",
              "      <td>1.757292</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>85</th>\n",
              "      <td>2008-08-24</td>\n",
              "      <td>13.428571</td>\n",
              "      <td>34</td>\n",
              "      <td>2008</td>\n",
              "      <td>0.797997</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>86</th>\n",
              "      <td>2008-08-31</td>\n",
              "      <td>14.714286</td>\n",
              "      <td>35</td>\n",
              "      <td>2008</td>\n",
              "      <td>0.874401</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>87</th>\n",
              "      <td>2008-09-07</td>\n",
              "      <td>32.428571</td>\n",
              "      <td>36</td>\n",
              "      <td>2008</td>\n",
              "      <td>1.927079</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>88</th>\n",
              "      <td>2008-09-14</td>\n",
              "      <td>9.428571</td>\n",
              "      <td>37</td>\n",
              "      <td>2008</td>\n",
              "      <td>0.560296</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>89</th>\n",
              "      <td>2008-09-21</td>\n",
              "      <td>12.285714</td>\n",
              "      <td>38</td>\n",
              "      <td>2008</td>\n",
              "      <td>0.730083</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>90</th>\n",
              "      <td>2008-09-28</td>\n",
              "      <td>14.000000</td>\n",
              "      <td>39</td>\n",
              "      <td>2008</td>\n",
              "      <td>0.831955</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>91</th>\n",
              "      <td>2008-10-05</td>\n",
              "      <td>19.857143</td>\n",
              "      <td>40</td>\n",
              "      <td>2008</td>\n",
              "      <td>1.180017</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>92</th>\n",
              "      <td>2008-10-12</td>\n",
              "      <td>12.714286</td>\n",
              "      <td>41</td>\n",
              "      <td>2008</td>\n",
              "      <td>0.755551</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>93</th>\n",
              "      <td>2008-10-19</td>\n",
              "      <td>17.571429</td>\n",
              "      <td>42</td>\n",
              "      <td>2008</td>\n",
              "      <td>1.044188</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>94</th>\n",
              "      <td>2008-10-26</td>\n",
              "      <td>13.000000</td>\n",
              "      <td>43</td>\n",
              "      <td>2008</td>\n",
              "      <td>0.772529</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>95</th>\n",
              "      <td>2008-11-02</td>\n",
              "      <td>13.857143</td>\n",
              "      <td>44</td>\n",
              "      <td>2008</td>\n",
              "      <td>0.823465</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>96</th>\n",
              "      <td>2008-11-09</td>\n",
              "      <td>17.714286</td>\n",
              "      <td>45</td>\n",
              "      <td>2008</td>\n",
              "      <td>1.052677</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>97</th>\n",
              "      <td>2008-11-16</td>\n",
              "      <td>15.571429</td>\n",
              "      <td>46</td>\n",
              "      <td>2008</td>\n",
              "      <td>0.925337</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>98</th>\n",
              "      <td>2008-11-23</td>\n",
              "      <td>8.857143</td>\n",
              "      <td>47</td>\n",
              "      <td>2008</td>\n",
              "      <td>0.526339</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>99</th>\n",
              "      <td>2008-11-30</td>\n",
              "      <td>8.285714</td>\n",
              "      <td>48</td>\n",
              "      <td>2008</td>\n",
              "      <td>0.492381</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>100</th>\n",
              "      <td>2008-12-07</td>\n",
              "      <td>13.285714</td>\n",
              "      <td>49</td>\n",
              "      <td>2008</td>\n",
              "      <td>0.789508</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>101</th>\n",
              "      <td>2008-12-14</td>\n",
              "      <td>10.857143</td>\n",
              "      <td>50</td>\n",
              "      <td>2008</td>\n",
              "      <td>0.645189</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>102</th>\n",
              "      <td>2008-12-21</td>\n",
              "      <td>13.571429</td>\n",
              "      <td>51</td>\n",
              "      <td>2008</td>\n",
              "      <td>0.806487</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>103</th>\n",
              "      <td>2008-12-28</td>\n",
              "      <td>13.857143</td>\n",
              "      <td>52</td>\n",
              "      <td>2008</td>\n",
              "      <td>0.823465</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "          Date       Conc  Week  Year       w_i\n",
              "52  2008-01-06  30.142857     1  2008  1.791249\n",
              "53  2008-01-13  28.000000     2  2008  1.663909\n",
              "54  2008-01-20  23.142857     3  2008  1.375272\n",
              "55  2008-01-27  15.285714     4  2008  0.908359\n",
              "56  2008-02-03  18.428571     5  2008  1.095124\n",
              "57  2008-02-10  16.428571     6  2008  0.976273\n",
              "58  2008-02-17  19.714286     7  2008  1.171528\n",
              "59  2008-02-24  14.571429     8  2008  0.865912\n",
              "60  2008-03-02  21.714286     9  2008  1.290379\n",
              "61  2008-03-09  19.285714    10  2008  1.146060\n",
              "62  2008-03-16  13.428571    11  2008  0.797997\n",
              "63  2008-03-23  17.142857    12  2008  1.018720\n",
              "64  2008-03-30  17.142857    13  2008  1.018720\n",
              "65  2008-04-06  24.857143    14  2008  1.477144\n",
              "66  2008-04-13  20.428571    15  2008  1.213975\n",
              "67  2008-04-20   9.571429    16  2008  0.568785\n",
              "68  2008-04-27  21.857143    17  2008  1.298868\n",
              "69  2008-05-04  14.142857    18  2008  0.840444\n",
              "70  2008-05-11  17.571429    19  2008  1.044188\n",
              "71  2008-05-18  21.428571    20  2008  1.273400\n",
              "72  2008-05-25  15.714286    21  2008  0.933827\n",
              "73  2008-06-01  16.142857    22  2008  0.959295\n",
              "74  2008-06-08  12.857143    23  2008  0.764040\n",
              "75  2008-06-15  20.714286    24  2008  1.230953\n",
              "76  2008-06-22  13.285714    25  2008  0.789508\n",
              "77  2008-06-29  17.857143    26  2008  1.061167\n",
              "78  2008-07-06  15.333333    27  2008  0.911189\n",
              "79  2008-07-13  11.285714    28  2008  0.670657\n",
              "80  2008-07-20  13.285714    29  2008  0.789508\n",
              "81  2008-07-27  20.857143    30  2008  1.239443\n",
              "82  2008-08-03  13.428571    31  2008  0.797997\n",
              "83  2008-08-10  15.142857    32  2008  0.899869\n",
              "84  2008-08-17  29.571429    33  2008  1.757292\n",
              "85  2008-08-24  13.428571    34  2008  0.797997\n",
              "86  2008-08-31  14.714286    35  2008  0.874401\n",
              "87  2008-09-07  32.428571    36  2008  1.927079\n",
              "88  2008-09-14   9.428571    37  2008  0.560296\n",
              "89  2008-09-21  12.285714    38  2008  0.730083\n",
              "90  2008-09-28  14.000000    39  2008  0.831955\n",
              "91  2008-10-05  19.857143    40  2008  1.180017\n",
              "92  2008-10-12  12.714286    41  2008  0.755551\n",
              "93  2008-10-19  17.571429    42  2008  1.044188\n",
              "94  2008-10-26  13.000000    43  2008  0.772529\n",
              "95  2008-11-02  13.857143    44  2008  0.823465\n",
              "96  2008-11-09  17.714286    45  2008  1.052677\n",
              "97  2008-11-16  15.571429    46  2008  0.925337\n",
              "98  2008-11-23   8.857143    47  2008  0.526339\n",
              "99  2008-11-30   8.285714    48  2008  0.492381\n",
              "100 2008-12-07  13.285714    49  2008  0.789508\n",
              "101 2008-12-14  10.857143    50  2008  0.645189\n",
              "102 2008-12-21  13.571429    51  2008  0.806487\n",
              "103 2008-12-28  13.857143    52  2008  0.823465"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "s1cQ9TMNklew"
      },
      "source": [
        "df09 = df[df['Year'] == 2009].dropna()"
      ],
      "execution_count": 13,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "XgGX9PS6klew",
        "outputId": "667a6364-06eb-4356-895d-b5a9783fd439"
      },
      "source": [
        "df09['w_i'] = wi_calc(df, 2009)\n",
        "df09"
      ],
      "execution_count": 14,
      "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",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Date</th>\n",
              "      <th>Conc</th>\n",
              "      <th>Week</th>\n",
              "      <th>Year</th>\n",
              "      <th>w_i</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>104</th>\n",
              "      <td>2009-01-04</td>\n",
              "      <td>20.857143</td>\n",
              "      <td>1</td>\n",
              "      <td>2009</td>\n",
              "      <td>1.366451</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>105</th>\n",
              "      <td>2009-01-11</td>\n",
              "      <td>10.428571</td>\n",
              "      <td>2</td>\n",
              "      <td>2009</td>\n",
              "      <td>0.683225</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>106</th>\n",
              "      <td>2009-01-18</td>\n",
              "      <td>19.428571</td>\n",
              "      <td>3</td>\n",
              "      <td>2009</td>\n",
              "      <td>1.272858</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>107</th>\n",
              "      <td>2009-01-25</td>\n",
              "      <td>11.000000</td>\n",
              "      <td>4</td>\n",
              "      <td>2009</td>\n",
              "      <td>0.720662</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>108</th>\n",
              "      <td>2009-02-01</td>\n",
              "      <td>16.428571</td>\n",
              "      <td>5</td>\n",
              "      <td>2009</td>\n",
              "      <td>1.076314</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>109</th>\n",
              "      <td>2009-02-08</td>\n",
              "      <td>5.857143</td>\n",
              "      <td>6</td>\n",
              "      <td>2009</td>\n",
              "      <td>0.383729</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>110</th>\n",
              "      <td>2009-02-15</td>\n",
              "      <td>7.714286</td>\n",
              "      <td>7</td>\n",
              "      <td>2009</td>\n",
              "      <td>0.505400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>111</th>\n",
              "      <td>2009-02-22</td>\n",
              "      <td>13.714286</td>\n",
              "      <td>8</td>\n",
              "      <td>2009</td>\n",
              "      <td>0.898488</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>112</th>\n",
              "      <td>2009-03-01</td>\n",
              "      <td>21.714286</td>\n",
              "      <td>9</td>\n",
              "      <td>2009</td>\n",
              "      <td>1.422606</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>113</th>\n",
              "      <td>2009-03-08</td>\n",
              "      <td>12.857143</td>\n",
              "      <td>10</td>\n",
              "      <td>2009</td>\n",
              "      <td>0.842333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>114</th>\n",
              "      <td>2009-03-15</td>\n",
              "      <td>9.857143</td>\n",
              "      <td>11</td>\n",
              "      <td>2009</td>\n",
              "      <td>0.645788</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>115</th>\n",
              "      <td>2009-03-22</td>\n",
              "      <td>18.285714</td>\n",
              "      <td>12</td>\n",
              "      <td>2009</td>\n",
              "      <td>1.197984</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>116</th>\n",
              "      <td>2009-03-29</td>\n",
              "      <td>24.142857</td>\n",
              "      <td>13</td>\n",
              "      <td>2009</td>\n",
              "      <td>1.581713</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>117</th>\n",
              "      <td>2009-04-05</td>\n",
              "      <td>17.142857</td>\n",
              "      <td>14</td>\n",
              "      <td>2009</td>\n",
              "      <td>1.123110</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>118</th>\n",
              "      <td>2009-04-12</td>\n",
              "      <td>26.285714</td>\n",
              "      <td>15</td>\n",
              "      <td>2009</td>\n",
              "      <td>1.722102</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>119</th>\n",
              "      <td>2009-04-19</td>\n",
              "      <td>23.000000</td>\n",
              "      <td>16</td>\n",
              "      <td>2009</td>\n",
              "      <td>1.506839</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>120</th>\n",
              "      <td>2009-04-26</td>\n",
              "      <td>18.000000</td>\n",
              "      <td>17</td>\n",
              "      <td>2009</td>\n",
              "      <td>1.179266</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>121</th>\n",
              "      <td>2009-05-03</td>\n",
              "      <td>25.428571</td>\n",
              "      <td>18</td>\n",
              "      <td>2009</td>\n",
              "      <td>1.665947</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>122</th>\n",
              "      <td>2009-05-10</td>\n",
              "      <td>15.142857</td>\n",
              "      <td>19</td>\n",
              "      <td>2009</td>\n",
              "      <td>0.992081</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>123</th>\n",
              "      <td>2009-05-17</td>\n",
              "      <td>9.857143</td>\n",
              "      <td>20</td>\n",
              "      <td>2009</td>\n",
              "      <td>0.645788</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>124</th>\n",
              "      <td>2009-05-24</td>\n",
              "      <td>16.428571</td>\n",
              "      <td>21</td>\n",
              "      <td>2009</td>\n",
              "      <td>1.076314</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>125</th>\n",
              "      <td>2009-05-31</td>\n",
              "      <td>18.285714</td>\n",
              "      <td>22</td>\n",
              "      <td>2009</td>\n",
              "      <td>1.197984</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>126</th>\n",
              "      <td>2009-06-07</td>\n",
              "      <td>14.857143</td>\n",
              "      <td>23</td>\n",
              "      <td>2009</td>\n",
              "      <td>0.973362</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>127</th>\n",
              "      <td>2009-06-14</td>\n",
              "      <td>15.285714</td>\n",
              "      <td>24</td>\n",
              "      <td>2009</td>\n",
              "      <td>1.001440</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>128</th>\n",
              "      <td>2009-06-21</td>\n",
              "      <td>13.714286</td>\n",
              "      <td>25</td>\n",
              "      <td>2009</td>\n",
              "      <td>0.898488</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>129</th>\n",
              "      <td>2009-06-28</td>\n",
              "      <td>19.428571</td>\n",
              "      <td>26</td>\n",
              "      <td>2009</td>\n",
              "      <td>1.272858</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>130</th>\n",
              "      <td>2009-07-05</td>\n",
              "      <td>16.428571</td>\n",
              "      <td>27</td>\n",
              "      <td>2009</td>\n",
              "      <td>1.076314</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>131</th>\n",
              "      <td>2009-07-12</td>\n",
              "      <td>10.428571</td>\n",
              "      <td>28</td>\n",
              "      <td>2009</td>\n",
              "      <td>0.683225</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>132</th>\n",
              "      <td>2009-07-19</td>\n",
              "      <td>14.571429</td>\n",
              "      <td>29</td>\n",
              "      <td>2009</td>\n",
              "      <td>0.954644</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>133</th>\n",
              "      <td>2009-07-26</td>\n",
              "      <td>16.000000</td>\n",
              "      <td>30</td>\n",
              "      <td>2009</td>\n",
              "      <td>1.048236</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>134</th>\n",
              "      <td>2009-08-02</td>\n",
              "      <td>13.857143</td>\n",
              "      <td>31</td>\n",
              "      <td>2009</td>\n",
              "      <td>0.907847</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>135</th>\n",
              "      <td>2009-08-09</td>\n",
              "      <td>12.000000</td>\n",
              "      <td>32</td>\n",
              "      <td>2009</td>\n",
              "      <td>0.786177</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>136</th>\n",
              "      <td>2009-08-16</td>\n",
              "      <td>18.571429</td>\n",
              "      <td>33</td>\n",
              "      <td>2009</td>\n",
              "      <td>1.216703</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>137</th>\n",
              "      <td>2009-08-23</td>\n",
              "      <td>15.000000</td>\n",
              "      <td>34</td>\n",
              "      <td>2009</td>\n",
              "      <td>0.982721</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>138</th>\n",
              "      <td>2009-08-30</td>\n",
              "      <td>13.714286</td>\n",
              "      <td>35</td>\n",
              "      <td>2009</td>\n",
              "      <td>0.898488</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>139</th>\n",
              "      <td>2009-09-06</td>\n",
              "      <td>19.714286</td>\n",
              "      <td>36</td>\n",
              "      <td>2009</td>\n",
              "      <td>1.291577</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>140</th>\n",
              "      <td>2009-09-13</td>\n",
              "      <td>26.000000</td>\n",
              "      <td>37</td>\n",
              "      <td>2009</td>\n",
              "      <td>1.703384</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>141</th>\n",
              "      <td>2009-09-20</td>\n",
              "      <td>14.000000</td>\n",
              "      <td>38</td>\n",
              "      <td>2009</td>\n",
              "      <td>0.917207</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>142</th>\n",
              "      <td>2009-09-27</td>\n",
              "      <td>16.428571</td>\n",
              "      <td>39</td>\n",
              "      <td>2009</td>\n",
              "      <td>1.076314</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>143</th>\n",
              "      <td>2009-10-04</td>\n",
              "      <td>13.428571</td>\n",
              "      <td>40</td>\n",
              "      <td>2009</td>\n",
              "      <td>0.879770</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>144</th>\n",
              "      <td>2009-10-11</td>\n",
              "      <td>18.714286</td>\n",
              "      <td>41</td>\n",
              "      <td>2009</td>\n",
              "      <td>1.226062</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>145</th>\n",
              "      <td>2009-10-18</td>\n",
              "      <td>6.000000</td>\n",
              "      <td>42</td>\n",
              "      <td>2009</td>\n",
              "      <td>0.393089</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>146</th>\n",
              "      <td>2009-10-25</td>\n",
              "      <td>23.428571</td>\n",
              "      <td>43</td>\n",
              "      <td>2009</td>\n",
              "      <td>1.534917</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>147</th>\n",
              "      <td>2009-11-01</td>\n",
              "      <td>7.714286</td>\n",
              "      <td>44</td>\n",
              "      <td>2009</td>\n",
              "      <td>0.505400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>148</th>\n",
              "      <td>2009-11-08</td>\n",
              "      <td>16.857143</td>\n",
              "      <td>45</td>\n",
              "      <td>2009</td>\n",
              "      <td>1.104392</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>149</th>\n",
              "      <td>2009-11-15</td>\n",
              "      <td>4.285714</td>\n",
              "      <td>46</td>\n",
              "      <td>2009</td>\n",
              "      <td>0.280778</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>150</th>\n",
              "      <td>2009-11-22</td>\n",
              "      <td>8.857143</td>\n",
              "      <td>47</td>\n",
              "      <td>2009</td>\n",
              "      <td>0.580274</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>151</th>\n",
              "      <td>2009-11-29</td>\n",
              "      <td>10.714286</td>\n",
              "      <td>48</td>\n",
              "      <td>2009</td>\n",
              "      <td>0.701944</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>152</th>\n",
              "      <td>2009-12-06</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>49</td>\n",
              "      <td>2009</td>\n",
              "      <td>0.655148</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>153</th>\n",
              "      <td>2009-12-13</td>\n",
              "      <td>9.714286</td>\n",
              "      <td>50</td>\n",
              "      <td>2009</td>\n",
              "      <td>0.636429</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>154</th>\n",
              "      <td>2009-12-20</td>\n",
              "      <td>20.428571</td>\n",
              "      <td>51</td>\n",
              "      <td>2009</td>\n",
              "      <td>1.338373</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>155</th>\n",
              "      <td>2009-12-27</td>\n",
              "      <td>11.714286</td>\n",
              "      <td>52</td>\n",
              "      <td>2009</td>\n",
              "      <td>0.767459</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "          Date       Conc  Week  Year       w_i\n",
              "104 2009-01-04  20.857143     1  2009  1.366451\n",
              "105 2009-01-11  10.428571     2  2009  0.683225\n",
              "106 2009-01-18  19.428571     3  2009  1.272858\n",
              "107 2009-01-25  11.000000     4  2009  0.720662\n",
              "108 2009-02-01  16.428571     5  2009  1.076314\n",
              "109 2009-02-08   5.857143     6  2009  0.383729\n",
              "110 2009-02-15   7.714286     7  2009  0.505400\n",
              "111 2009-02-22  13.714286     8  2009  0.898488\n",
              "112 2009-03-01  21.714286     9  2009  1.422606\n",
              "113 2009-03-08  12.857143    10  2009  0.842333\n",
              "114 2009-03-15   9.857143    11  2009  0.645788\n",
              "115 2009-03-22  18.285714    12  2009  1.197984\n",
              "116 2009-03-29  24.142857    13  2009  1.581713\n",
              "117 2009-04-05  17.142857    14  2009  1.123110\n",
              "118 2009-04-12  26.285714    15  2009  1.722102\n",
              "119 2009-04-19  23.000000    16  2009  1.506839\n",
              "120 2009-04-26  18.000000    17  2009  1.179266\n",
              "121 2009-05-03  25.428571    18  2009  1.665947\n",
              "122 2009-05-10  15.142857    19  2009  0.992081\n",
              "123 2009-05-17   9.857143    20  2009  0.645788\n",
              "124 2009-05-24  16.428571    21  2009  1.076314\n",
              "125 2009-05-31  18.285714    22  2009  1.197984\n",
              "126 2009-06-07  14.857143    23  2009  0.973362\n",
              "127 2009-06-14  15.285714    24  2009  1.001440\n",
              "128 2009-06-21  13.714286    25  2009  0.898488\n",
              "129 2009-06-28  19.428571    26  2009  1.272858\n",
              "130 2009-07-05  16.428571    27  2009  1.076314\n",
              "131 2009-07-12  10.428571    28  2009  0.683225\n",
              "132 2009-07-19  14.571429    29  2009  0.954644\n",
              "133 2009-07-26  16.000000    30  2009  1.048236\n",
              "134 2009-08-02  13.857143    31  2009  0.907847\n",
              "135 2009-08-09  12.000000    32  2009  0.786177\n",
              "136 2009-08-16  18.571429    33  2009  1.216703\n",
              "137 2009-08-23  15.000000    34  2009  0.982721\n",
              "138 2009-08-30  13.714286    35  2009  0.898488\n",
              "139 2009-09-06  19.714286    36  2009  1.291577\n",
              "140 2009-09-13  26.000000    37  2009  1.703384\n",
              "141 2009-09-20  14.000000    38  2009  0.917207\n",
              "142 2009-09-27  16.428571    39  2009  1.076314\n",
              "143 2009-10-04  13.428571    40  2009  0.879770\n",
              "144 2009-10-11  18.714286    41  2009  1.226062\n",
              "145 2009-10-18   6.000000    42  2009  0.393089\n",
              "146 2009-10-25  23.428571    43  2009  1.534917\n",
              "147 2009-11-01   7.714286    44  2009  0.505400\n",
              "148 2009-11-08  16.857143    45  2009  1.104392\n",
              "149 2009-11-15   4.285714    46  2009  0.280778\n",
              "150 2009-11-22   8.857143    47  2009  0.580274\n",
              "151 2009-11-29  10.714286    48  2009  0.701944\n",
              "152 2009-12-06  10.000000    49  2009  0.655148\n",
              "153 2009-12-13   9.714286    50  2009  0.636429\n",
              "154 2009-12-20  20.428571    51  2009  1.338373\n",
              "155 2009-12-27  11.714286    52  2009  0.767459"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "iPhKHNOGklex"
      },
      "source": [
        "df10 = df[df['Year'] == 2010].dropna()"
      ],
      "execution_count": 16,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "p9fTc1rpklex",
        "outputId": "b494ef10-825d-441c-a2c4-78acecc983fc"
      },
      "source": [
        "df10['w_i'] = wi_calc(df, 2010)\n",
        "df10"
      ],
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Date</th>\n",
              "      <th>Conc</th>\n",
              "      <th>Week</th>\n",
              "      <th>Year</th>\n",
              "      <th>w_i</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>156</th>\n",
              "      <td>2010-01-03</td>\n",
              "      <td>9.142857</td>\n",
              "      <td>53</td>\n",
              "      <td>2010</td>\n",
              "      <td>0.491145</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>157</th>\n",
              "      <td>2010-01-10</td>\n",
              "      <td>15.285714</td>\n",
              "      <td>1</td>\n",
              "      <td>2010</td>\n",
              "      <td>0.821133</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>158</th>\n",
              "      <td>2010-01-17</td>\n",
              "      <td>11.285714</td>\n",
              "      <td>2</td>\n",
              "      <td>2010</td>\n",
              "      <td>0.606257</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>159</th>\n",
              "      <td>2010-01-24</td>\n",
              "      <td>14.142857</td>\n",
              "      <td>3</td>\n",
              "      <td>2010</td>\n",
              "      <td>0.759740</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>160</th>\n",
              "      <td>2010-01-31</td>\n",
              "      <td>15.428571</td>\n",
              "      <td>4</td>\n",
              "      <td>2010</td>\n",
              "      <td>0.828808</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>161</th>\n",
              "      <td>2010-02-07</td>\n",
              "      <td>15.285714</td>\n",
              "      <td>5</td>\n",
              "      <td>2010</td>\n",
              "      <td>0.821133</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>162</th>\n",
              "      <td>2010-02-14</td>\n",
              "      <td>17.857143</td>\n",
              "      <td>6</td>\n",
              "      <td>2010</td>\n",
              "      <td>0.959268</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>163</th>\n",
              "      <td>2010-02-21</td>\n",
              "      <td>11.857143</td>\n",
              "      <td>7</td>\n",
              "      <td>2010</td>\n",
              "      <td>0.636954</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>164</th>\n",
              "      <td>2010-02-28</td>\n",
              "      <td>12.285714</td>\n",
              "      <td>8</td>\n",
              "      <td>2010</td>\n",
              "      <td>0.659976</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>165</th>\n",
              "      <td>2010-03-07</td>\n",
              "      <td>12.714286</td>\n",
              "      <td>9</td>\n",
              "      <td>2010</td>\n",
              "      <td>0.682999</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>166</th>\n",
              "      <td>2010-03-14</td>\n",
              "      <td>14.714286</td>\n",
              "      <td>10</td>\n",
              "      <td>2010</td>\n",
              "      <td>0.790437</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>167</th>\n",
              "      <td>2010-03-21</td>\n",
              "      <td>24.142857</td>\n",
              "      <td>11</td>\n",
              "      <td>2010</td>\n",
              "      <td>1.296930</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>168</th>\n",
              "      <td>2010-03-28</td>\n",
              "      <td>19.833333</td>\n",
              "      <td>12</td>\n",
              "      <td>2010</td>\n",
              "      <td>1.065427</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>169</th>\n",
              "      <td>2010-04-04</td>\n",
              "      <td>31.285714</td>\n",
              "      <td>13</td>\n",
              "      <td>2010</td>\n",
              "      <td>1.680638</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>170</th>\n",
              "      <td>2010-04-11</td>\n",
              "      <td>34.714286</td>\n",
              "      <td>14</td>\n",
              "      <td>2010</td>\n",
              "      <td>1.864817</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>171</th>\n",
              "      <td>2010-04-18</td>\n",
              "      <td>20.428571</td>\n",
              "      <td>15</td>\n",
              "      <td>2010</td>\n",
              "      <td>1.097403</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>172</th>\n",
              "      <td>2010-04-25</td>\n",
              "      <td>22.142857</td>\n",
              "      <td>16</td>\n",
              "      <td>2010</td>\n",
              "      <td>1.189492</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>173</th>\n",
              "      <td>2010-05-02</td>\n",
              "      <td>21.714286</td>\n",
              "      <td>17</td>\n",
              "      <td>2010</td>\n",
              "      <td>1.166470</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>174</th>\n",
              "      <td>2010-05-09</td>\n",
              "      <td>25.500000</td>\n",
              "      <td>18</td>\n",
              "      <td>2010</td>\n",
              "      <td>1.369835</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>175</th>\n",
              "      <td>2010-05-16</td>\n",
              "      <td>24.500000</td>\n",
              "      <td>19</td>\n",
              "      <td>2010</td>\n",
              "      <td>1.316116</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>176</th>\n",
              "      <td>2010-05-23</td>\n",
              "      <td>19.142857</td>\n",
              "      <td>20</td>\n",
              "      <td>2010</td>\n",
              "      <td>1.028335</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>177</th>\n",
              "      <td>2010-05-30</td>\n",
              "      <td>22.142857</td>\n",
              "      <td>21</td>\n",
              "      <td>2010</td>\n",
              "      <td>1.189492</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>178</th>\n",
              "      <td>2010-06-06</td>\n",
              "      <td>13.285714</td>\n",
              "      <td>22</td>\n",
              "      <td>2010</td>\n",
              "      <td>0.713695</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>179</th>\n",
              "      <td>2010-06-13</td>\n",
              "      <td>29.571429</td>\n",
              "      <td>23</td>\n",
              "      <td>2010</td>\n",
              "      <td>1.588548</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>180</th>\n",
              "      <td>2010-06-20</td>\n",
              "      <td>13.571429</td>\n",
              "      <td>24</td>\n",
              "      <td>2010</td>\n",
              "      <td>0.729044</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>181</th>\n",
              "      <td>2010-06-27</td>\n",
              "      <td>13.857143</td>\n",
              "      <td>25</td>\n",
              "      <td>2010</td>\n",
              "      <td>0.744392</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>182</th>\n",
              "      <td>2010-07-04</td>\n",
              "      <td>13.142857</td>\n",
              "      <td>26</td>\n",
              "      <td>2010</td>\n",
              "      <td>0.706021</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>183</th>\n",
              "      <td>2010-07-11</td>\n",
              "      <td>13.000000</td>\n",
              "      <td>27</td>\n",
              "      <td>2010</td>\n",
              "      <td>0.698347</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>184</th>\n",
              "      <td>2010-07-18</td>\n",
              "      <td>27.857143</td>\n",
              "      <td>28</td>\n",
              "      <td>2010</td>\n",
              "      <td>1.496458</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>185</th>\n",
              "      <td>2010-07-25</td>\n",
              "      <td>29.285714</td>\n",
              "      <td>29</td>\n",
              "      <td>2010</td>\n",
              "      <td>1.573200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>186</th>\n",
              "      <td>2010-08-01</td>\n",
              "      <td>17.333333</td>\n",
              "      <td>30</td>\n",
              "      <td>2010</td>\n",
              "      <td>0.931129</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>187</th>\n",
              "      <td>2010-08-08</td>\n",
              "      <td>38.857143</td>\n",
              "      <td>31</td>\n",
              "      <td>2010</td>\n",
              "      <td>2.087367</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>188</th>\n",
              "      <td>2010-08-15</td>\n",
              "      <td>24.333333</td>\n",
              "      <td>32</td>\n",
              "      <td>2010</td>\n",
              "      <td>1.307163</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>189</th>\n",
              "      <td>2010-08-22</td>\n",
              "      <td>8.500000</td>\n",
              "      <td>33</td>\n",
              "      <td>2010</td>\n",
              "      <td>0.456612</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>190</th>\n",
              "      <td>2010-08-29</td>\n",
              "      <td>19.000000</td>\n",
              "      <td>34</td>\n",
              "      <td>2010</td>\n",
              "      <td>1.020661</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>191</th>\n",
              "      <td>2010-09-05</td>\n",
              "      <td>10.428571</td>\n",
              "      <td>35</td>\n",
              "      <td>2010</td>\n",
              "      <td>0.560213</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>192</th>\n",
              "      <td>2010-09-12</td>\n",
              "      <td>21.571429</td>\n",
              "      <td>36</td>\n",
              "      <td>2010</td>\n",
              "      <td>1.158796</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>193</th>\n",
              "      <td>2010-09-19</td>\n",
              "      <td>24.142857</td>\n",
              "      <td>37</td>\n",
              "      <td>2010</td>\n",
              "      <td>1.296930</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>194</th>\n",
              "      <td>2010-09-26</td>\n",
              "      <td>22.571429</td>\n",
              "      <td>38</td>\n",
              "      <td>2010</td>\n",
              "      <td>1.212515</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>195</th>\n",
              "      <td>2010-10-03</td>\n",
              "      <td>23.571429</td>\n",
              "      <td>39</td>\n",
              "      <td>2010</td>\n",
              "      <td>1.266234</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>196</th>\n",
              "      <td>2010-10-10</td>\n",
              "      <td>24.142857</td>\n",
              "      <td>40</td>\n",
              "      <td>2010</td>\n",
              "      <td>1.296930</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>197</th>\n",
              "      <td>2010-10-17</td>\n",
              "      <td>10.571429</td>\n",
              "      <td>41</td>\n",
              "      <td>2010</td>\n",
              "      <td>0.567887</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>198</th>\n",
              "      <td>2010-10-24</td>\n",
              "      <td>13.666667</td>\n",
              "      <td>42</td>\n",
              "      <td>2010</td>\n",
              "      <td>0.734160</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>199</th>\n",
              "      <td>2010-10-31</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>43</td>\n",
              "      <td>2010</td>\n",
              "      <td>0.537190</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>200</th>\n",
              "      <td>2010-11-07</td>\n",
              "      <td>24.571429</td>\n",
              "      <td>44</td>\n",
              "      <td>2010</td>\n",
              "      <td>1.319953</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>201</th>\n",
              "      <td>2010-11-14</td>\n",
              "      <td>21.000000</td>\n",
              "      <td>45</td>\n",
              "      <td>2010</td>\n",
              "      <td>1.128099</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>202</th>\n",
              "      <td>2010-11-21</td>\n",
              "      <td>28.571429</td>\n",
              "      <td>46</td>\n",
              "      <td>2010</td>\n",
              "      <td>1.534829</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>203</th>\n",
              "      <td>2010-11-28</td>\n",
              "      <td>10.333333</td>\n",
              "      <td>47</td>\n",
              "      <td>2010</td>\n",
              "      <td>0.555096</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>204</th>\n",
              "      <td>2010-12-05</td>\n",
              "      <td>17.142857</td>\n",
              "      <td>48</td>\n",
              "      <td>2010</td>\n",
              "      <td>0.920897</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>205</th>\n",
              "      <td>2010-12-12</td>\n",
              "      <td>6.285714</td>\n",
              "      <td>49</td>\n",
              "      <td>2010</td>\n",
              "      <td>0.337662</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>206</th>\n",
              "      <td>2010-12-19</td>\n",
              "      <td>12.714286</td>\n",
              "      <td>50</td>\n",
              "      <td>2010</td>\n",
              "      <td>0.682999</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>207</th>\n",
              "      <td>2010-12-26</td>\n",
              "      <td>9.571429</td>\n",
              "      <td>51</td>\n",
              "      <td>2010</td>\n",
              "      <td>0.514168</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "          Date       Conc  Week  Year       w_i\n",
              "156 2010-01-03   9.142857    53  2010  0.491145\n",
              "157 2010-01-10  15.285714     1  2010  0.821133\n",
              "158 2010-01-17  11.285714     2  2010  0.606257\n",
              "159 2010-01-24  14.142857     3  2010  0.759740\n",
              "160 2010-01-31  15.428571     4  2010  0.828808\n",
              "161 2010-02-07  15.285714     5  2010  0.821133\n",
              "162 2010-02-14  17.857143     6  2010  0.959268\n",
              "163 2010-02-21  11.857143     7  2010  0.636954\n",
              "164 2010-02-28  12.285714     8  2010  0.659976\n",
              "165 2010-03-07  12.714286     9  2010  0.682999\n",
              "166 2010-03-14  14.714286    10  2010  0.790437\n",
              "167 2010-03-21  24.142857    11  2010  1.296930\n",
              "168 2010-03-28  19.833333    12  2010  1.065427\n",
              "169 2010-04-04  31.285714    13  2010  1.680638\n",
              "170 2010-04-11  34.714286    14  2010  1.864817\n",
              "171 2010-04-18  20.428571    15  2010  1.097403\n",
              "172 2010-04-25  22.142857    16  2010  1.189492\n",
              "173 2010-05-02  21.714286    17  2010  1.166470\n",
              "174 2010-05-09  25.500000    18  2010  1.369835\n",
              "175 2010-05-16  24.500000    19  2010  1.316116\n",
              "176 2010-05-23  19.142857    20  2010  1.028335\n",
              "177 2010-05-30  22.142857    21  2010  1.189492\n",
              "178 2010-06-06  13.285714    22  2010  0.713695\n",
              "179 2010-06-13  29.571429    23  2010  1.588548\n",
              "180 2010-06-20  13.571429    24  2010  0.729044\n",
              "181 2010-06-27  13.857143    25  2010  0.744392\n",
              "182 2010-07-04  13.142857    26  2010  0.706021\n",
              "183 2010-07-11  13.000000    27  2010  0.698347\n",
              "184 2010-07-18  27.857143    28  2010  1.496458\n",
              "185 2010-07-25  29.285714    29  2010  1.573200\n",
              "186 2010-08-01  17.333333    30  2010  0.931129\n",
              "187 2010-08-08  38.857143    31  2010  2.087367\n",
              "188 2010-08-15  24.333333    32  2010  1.307163\n",
              "189 2010-08-22   8.500000    33  2010  0.456612\n",
              "190 2010-08-29  19.000000    34  2010  1.020661\n",
              "191 2010-09-05  10.428571    35  2010  0.560213\n",
              "192 2010-09-12  21.571429    36  2010  1.158796\n",
              "193 2010-09-19  24.142857    37  2010  1.296930\n",
              "194 2010-09-26  22.571429    38  2010  1.212515\n",
              "195 2010-10-03  23.571429    39  2010  1.266234\n",
              "196 2010-10-10  24.142857    40  2010  1.296930\n",
              "197 2010-10-17  10.571429    41  2010  0.567887\n",
              "198 2010-10-24  13.666667    42  2010  0.734160\n",
              "199 2010-10-31  10.000000    43  2010  0.537190\n",
              "200 2010-11-07  24.571429    44  2010  1.319953\n",
              "201 2010-11-14  21.000000    45  2010  1.128099\n",
              "202 2010-11-21  28.571429    46  2010  1.534829\n",
              "203 2010-11-28  10.333333    47  2010  0.555096\n",
              "204 2010-12-05  17.142857    48  2010  0.920897\n",
              "205 2010-12-12   6.285714    49  2010  0.337662\n",
              "206 2010-12-19  12.714286    50  2010  0.682999\n",
              "207 2010-12-26   9.571429    51  2010  0.514168"
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "aYlKQnewklex",
        "outputId": "5e8756b4-2a6a-4f71-d58b-2f1fbe9fd434"
      },
      "source": [
        "df11 = df[df['Year'] == 2011].dropna()\n",
        "df11['w_i'] = wi_calc(df, 2011)\n",
        "df11"
      ],
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Date</th>\n",
              "      <th>Conc</th>\n",
              "      <th>Week</th>\n",
              "      <th>Year</th>\n",
              "      <th>w_i</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>208</th>\n",
              "      <td>2011-01-02</td>\n",
              "      <td>13.142857</td>\n",
              "      <td>52</td>\n",
              "      <td>2011</td>\n",
              "      <td>0.807701</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>209</th>\n",
              "      <td>2011-01-09</td>\n",
              "      <td>11.000000</td>\n",
              "      <td>1</td>\n",
              "      <td>2011</td>\n",
              "      <td>0.676010</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>210</th>\n",
              "      <td>2011-01-16</td>\n",
              "      <td>11.571429</td>\n",
              "      <td>2</td>\n",
              "      <td>2011</td>\n",
              "      <td>0.711128</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>211</th>\n",
              "      <td>2011-01-23</td>\n",
              "      <td>23.571429</td>\n",
              "      <td>3</td>\n",
              "      <td>2011</td>\n",
              "      <td>1.448593</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>212</th>\n",
              "      <td>2011-01-30</td>\n",
              "      <td>14.428571</td>\n",
              "      <td>4</td>\n",
              "      <td>2011</td>\n",
              "      <td>0.886715</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>213</th>\n",
              "      <td>2011-02-06</td>\n",
              "      <td>10.857143</td>\n",
              "      <td>5</td>\n",
              "      <td>2011</td>\n",
              "      <td>0.667231</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>214</th>\n",
              "      <td>2011-02-13</td>\n",
              "      <td>10.571429</td>\n",
              "      <td>6</td>\n",
              "      <td>2011</td>\n",
              "      <td>0.649672</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>215</th>\n",
              "      <td>2011-02-20</td>\n",
              "      <td>17.833333</td>\n",
              "      <td>7</td>\n",
              "      <td>2011</td>\n",
              "      <td>1.095956</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>216</th>\n",
              "      <td>2011-02-27</td>\n",
              "      <td>12.714286</td>\n",
              "      <td>8</td>\n",
              "      <td>2011</td>\n",
              "      <td>0.781362</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>217</th>\n",
              "      <td>2011-03-06</td>\n",
              "      <td>22.142857</td>\n",
              "      <td>9</td>\n",
              "      <td>2011</td>\n",
              "      <td>1.360800</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>218</th>\n",
              "      <td>2011-03-13</td>\n",
              "      <td>22.285714</td>\n",
              "      <td>10</td>\n",
              "      <td>2011</td>\n",
              "      <td>1.369579</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>219</th>\n",
              "      <td>2011-03-20</td>\n",
              "      <td>25.285714</td>\n",
              "      <td>11</td>\n",
              "      <td>2011</td>\n",
              "      <td>1.553946</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>220</th>\n",
              "      <td>2011-03-27</td>\n",
              "      <td>19.000000</td>\n",
              "      <td>12</td>\n",
              "      <td>2011</td>\n",
              "      <td>1.167654</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>221</th>\n",
              "      <td>2011-04-03</td>\n",
              "      <td>47.333333</td>\n",
              "      <td>13</td>\n",
              "      <td>2011</td>\n",
              "      <td>2.908892</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>222</th>\n",
              "      <td>2011-04-10</td>\n",
              "      <td>24.857143</td>\n",
              "      <td>14</td>\n",
              "      <td>2011</td>\n",
              "      <td>1.527608</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>223</th>\n",
              "      <td>2011-04-17</td>\n",
              "      <td>12.714286</td>\n",
              "      <td>15</td>\n",
              "      <td>2011</td>\n",
              "      <td>0.781362</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>224</th>\n",
              "      <td>2011-04-24</td>\n",
              "      <td>16.428571</td>\n",
              "      <td>16</td>\n",
              "      <td>2011</td>\n",
              "      <td>1.009626</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>225</th>\n",
              "      <td>2011-05-01</td>\n",
              "      <td>23.428571</td>\n",
              "      <td>17</td>\n",
              "      <td>2011</td>\n",
              "      <td>1.439814</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>226</th>\n",
              "      <td>2011-05-08</td>\n",
              "      <td>19.142857</td>\n",
              "      <td>18</td>\n",
              "      <td>2011</td>\n",
              "      <td>1.176433</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>227</th>\n",
              "      <td>2011-05-15</td>\n",
              "      <td>27.428571</td>\n",
              "      <td>19</td>\n",
              "      <td>2011</td>\n",
              "      <td>1.685636</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>228</th>\n",
              "      <td>2011-05-22</td>\n",
              "      <td>18.142857</td>\n",
              "      <td>20</td>\n",
              "      <td>2011</td>\n",
              "      <td>1.114978</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>229</th>\n",
              "      <td>2011-05-29</td>\n",
              "      <td>18.285714</td>\n",
              "      <td>21</td>\n",
              "      <td>2011</td>\n",
              "      <td>1.123757</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>230</th>\n",
              "      <td>2011-06-05</td>\n",
              "      <td>20.000000</td>\n",
              "      <td>22</td>\n",
              "      <td>2011</td>\n",
              "      <td>1.229109</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>234</th>\n",
              "      <td>2011-07-03</td>\n",
              "      <td>7.666667</td>\n",
              "      <td>26</td>\n",
              "      <td>2011</td>\n",
              "      <td>0.471159</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>235</th>\n",
              "      <td>2011-07-10</td>\n",
              "      <td>9.285714</td>\n",
              "      <td>27</td>\n",
              "      <td>2011</td>\n",
              "      <td>0.570658</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>236</th>\n",
              "      <td>2011-07-17</td>\n",
              "      <td>16.714286</td>\n",
              "      <td>28</td>\n",
              "      <td>2011</td>\n",
              "      <td>1.027184</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>237</th>\n",
              "      <td>2011-07-24</td>\n",
              "      <td>28.714286</td>\n",
              "      <td>29</td>\n",
              "      <td>2011</td>\n",
              "      <td>1.764650</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>238</th>\n",
              "      <td>2011-07-31</td>\n",
              "      <td>12.571429</td>\n",
              "      <td>30</td>\n",
              "      <td>2011</td>\n",
              "      <td>0.772583</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>239</th>\n",
              "      <td>2011-08-07</td>\n",
              "      <td>11.285714</td>\n",
              "      <td>31</td>\n",
              "      <td>2011</td>\n",
              "      <td>0.693569</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>240</th>\n",
              "      <td>2011-08-14</td>\n",
              "      <td>15.142857</td>\n",
              "      <td>32</td>\n",
              "      <td>2011</td>\n",
              "      <td>0.930611</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>241</th>\n",
              "      <td>2011-08-21</td>\n",
              "      <td>12.000000</td>\n",
              "      <td>33</td>\n",
              "      <td>2011</td>\n",
              "      <td>0.737466</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>242</th>\n",
              "      <td>2011-08-28</td>\n",
              "      <td>8.285714</td>\n",
              "      <td>34</td>\n",
              "      <td>2011</td>\n",
              "      <td>0.509203</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>243</th>\n",
              "      <td>2011-09-04</td>\n",
              "      <td>3.714286</td>\n",
              "      <td>35</td>\n",
              "      <td>2011</td>\n",
              "      <td>0.228263</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>244</th>\n",
              "      <td>2011-09-11</td>\n",
              "      <td>7.571429</td>\n",
              "      <td>36</td>\n",
              "      <td>2011</td>\n",
              "      <td>0.465306</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>245</th>\n",
              "      <td>2011-09-18</td>\n",
              "      <td>8.000000</td>\n",
              "      <td>37</td>\n",
              "      <td>2011</td>\n",
              "      <td>0.491644</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>246</th>\n",
              "      <td>2011-09-25</td>\n",
              "      <td>9.142857</td>\n",
              "      <td>38</td>\n",
              "      <td>2011</td>\n",
              "      <td>0.561879</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>247</th>\n",
              "      <td>2011-10-02</td>\n",
              "      <td>9.800000</td>\n",
              "      <td>39</td>\n",
              "      <td>2011</td>\n",
              "      <td>0.602264</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "          Date       Conc  Week  Year       w_i\n",
              "208 2011-01-02  13.142857    52  2011  0.807701\n",
              "209 2011-01-09  11.000000     1  2011  0.676010\n",
              "210 2011-01-16  11.571429     2  2011  0.711128\n",
              "211 2011-01-23  23.571429     3  2011  1.448593\n",
              "212 2011-01-30  14.428571     4  2011  0.886715\n",
              "213 2011-02-06  10.857143     5  2011  0.667231\n",
              "214 2011-02-13  10.571429     6  2011  0.649672\n",
              "215 2011-02-20  17.833333     7  2011  1.095956\n",
              "216 2011-02-27  12.714286     8  2011  0.781362\n",
              "217 2011-03-06  22.142857     9  2011  1.360800\n",
              "218 2011-03-13  22.285714    10  2011  1.369579\n",
              "219 2011-03-20  25.285714    11  2011  1.553946\n",
              "220 2011-03-27  19.000000    12  2011  1.167654\n",
              "221 2011-04-03  47.333333    13  2011  2.908892\n",
              "222 2011-04-10  24.857143    14  2011  1.527608\n",
              "223 2011-04-17  12.714286    15  2011  0.781362\n",
              "224 2011-04-24  16.428571    16  2011  1.009626\n",
              "225 2011-05-01  23.428571    17  2011  1.439814\n",
              "226 2011-05-08  19.142857    18  2011  1.176433\n",
              "227 2011-05-15  27.428571    19  2011  1.685636\n",
              "228 2011-05-22  18.142857    20  2011  1.114978\n",
              "229 2011-05-29  18.285714    21  2011  1.123757\n",
              "230 2011-06-05  20.000000    22  2011  1.229109\n",
              "234 2011-07-03   7.666667    26  2011  0.471159\n",
              "235 2011-07-10   9.285714    27  2011  0.570658\n",
              "236 2011-07-17  16.714286    28  2011  1.027184\n",
              "237 2011-07-24  28.714286    29  2011  1.764650\n",
              "238 2011-07-31  12.571429    30  2011  0.772583\n",
              "239 2011-08-07  11.285714    31  2011  0.693569\n",
              "240 2011-08-14  15.142857    32  2011  0.930611\n",
              "241 2011-08-21  12.000000    33  2011  0.737466\n",
              "242 2011-08-28   8.285714    34  2011  0.509203\n",
              "243 2011-09-04   3.714286    35  2011  0.228263\n",
              "244 2011-09-11   7.571429    36  2011  0.465306\n",
              "245 2011-09-18   8.000000    37  2011  0.491644\n",
              "246 2011-09-25   9.142857    38  2011  0.561879\n",
              "247 2011-10-02   9.800000    39  2011  0.602264"
            ]
          },
          "metadata": {},
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 979
        },
        "id": "tCe1f5Njklex",
        "outputId": "7cdaf737-61bf-45a3-83b4-7c27d8235bc9"
      },
      "source": [
        "df12 = df[df['Year'] == 2012].dropna()\n",
        "df12['w_i'] = wi_calc(df, 2012)\n",
        "df12"
      ],
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
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              "    }\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Date</th>\n",
              "      <th>Conc</th>\n",
              "      <th>Week</th>\n",
              "      <th>Year</th>\n",
              "      <th>w_i</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>282</th>\n",
              "      <td>2012-06-03</td>\n",
              "      <td>12.666667</td>\n",
              "      <td>22</td>\n",
              "      <td>2012</td>\n",
              "      <td>0.691580</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>283</th>\n",
              "      <td>2012-06-10</td>\n",
              "      <td>11.142857</td>\n",
              "      <td>23</td>\n",
              "      <td>2012</td>\n",
              "      <td>0.608382</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>284</th>\n",
              "      <td>2012-06-17</td>\n",
              "      <td>11.571429</td>\n",
              "      <td>24</td>\n",
              "      <td>2012</td>\n",
              "      <td>0.631781</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>285</th>\n",
              "      <td>2012-06-24</td>\n",
              "      <td>14.714286</td>\n",
              "      <td>25</td>\n",
              "      <td>2012</td>\n",
              "      <td>0.803376</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>286</th>\n",
              "      <td>2012-07-01</td>\n",
              "      <td>14.142857</td>\n",
              "      <td>26</td>\n",
              "      <td>2012</td>\n",
              "      <td>0.772177</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>287</th>\n",
              "      <td>2012-07-08</td>\n",
              "      <td>21.714286</td>\n",
              "      <td>27</td>\n",
              "      <td>2012</td>\n",
              "      <td>1.185565</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>288</th>\n",
              "      <td>2012-07-15</td>\n",
              "      <td>16.142857</td>\n",
              "      <td>28</td>\n",
              "      <td>2012</td>\n",
              "      <td>0.881374</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>289</th>\n",
              "      <td>2012-07-22</td>\n",
              "      <td>12.857143</td>\n",
              "      <td>29</td>\n",
              "      <td>2012</td>\n",
              "      <td>0.701979</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>290</th>\n",
              "      <td>2012-07-29</td>\n",
              "      <td>20.714286</td>\n",
              "      <td>30</td>\n",
              "      <td>2012</td>\n",
              "      <td>1.130967</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>291</th>\n",
              "      <td>2012-08-05</td>\n",
              "      <td>15.142857</td>\n",
              "      <td>31</td>\n",
              "      <td>2012</td>\n",
              "      <td>0.826776</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>292</th>\n",
              "      <td>2012-08-12</td>\n",
              "      <td>16.714286</td>\n",
              "      <td>32</td>\n",
              "      <td>2012</td>\n",
              "      <td>0.912573</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>293</th>\n",
              "      <td>2012-08-19</td>\n",
              "      <td>8.571429</td>\n",
              "      <td>33</td>\n",
              "      <td>2012</td>\n",
              "      <td>0.467986</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>294</th>\n",
              "      <td>2012-08-26</td>\n",
              "      <td>17.285714</td>\n",
              "      <td>34</td>\n",
              "      <td>2012</td>\n",
              "      <td>0.943772</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>295</th>\n",
              "      <td>2012-09-02</td>\n",
              "      <td>13.714286</td>\n",
              "      <td>35</td>\n",
              "      <td>2012</td>\n",
              "      <td>0.748778</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>296</th>\n",
              "      <td>2012-09-09</td>\n",
              "      <td>15.857143</td>\n",
              "      <td>36</td>\n",
              "      <td>2012</td>\n",
              "      <td>0.865775</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>297</th>\n",
              "      <td>2012-09-16</td>\n",
              "      <td>16.428571</td>\n",
              "      <td>37</td>\n",
              "      <td>2012</td>\n",
              "      <td>0.896974</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>298</th>\n",
              "      <td>2012-09-23</td>\n",
              "      <td>18.714286</td>\n",
              "      <td>38</td>\n",
              "      <td>2012</td>\n",
              "      <td>1.021770</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>299</th>\n",
              "      <td>2012-09-30</td>\n",
              "      <td>20.285714</td>\n",
              "      <td>39</td>\n",
              "      <td>2012</td>\n",
              "      <td>1.107568</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>300</th>\n",
              "      <td>2012-10-07</td>\n",
              "      <td>20.285714</td>\n",
              "      <td>40</td>\n",
              "      <td>2012</td>\n",
              "      <td>1.107568</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>301</th>\n",
              "      <td>2012-10-14</td>\n",
              "      <td>19.428571</td>\n",
              "      <td>41</td>\n",
              "      <td>2012</td>\n",
              "      <td>1.060769</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>302</th>\n",
              "      <td>2012-10-21</td>\n",
              "      <td>19.428571</td>\n",
              "      <td>42</td>\n",
              "      <td>2012</td>\n",
              "      <td>1.060769</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>303</th>\n",
              "      <td>2012-10-28</td>\n",
              "      <td>15.857143</td>\n",
              "      <td>43</td>\n",
              "      <td>2012</td>\n",
              "      <td>0.865775</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>305</th>\n",
              "      <td>2012-11-11</td>\n",
              "      <td>26.200000</td>\n",
              "      <td>45</td>\n",
              "      <td>2012</td>\n",
              "      <td>1.430478</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>306</th>\n",
              "      <td>2012-11-18</td>\n",
              "      <td>21.857143</td>\n",
              "      <td>46</td>\n",
              "      <td>2012</td>\n",
              "      <td>1.193365</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>307</th>\n",
              "      <td>2012-11-25</td>\n",
              "      <td>35.428571</td>\n",
              "      <td>47</td>\n",
              "      <td>2012</td>\n",
              "      <td>1.934343</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>308</th>\n",
              "      <td>2012-12-02</td>\n",
              "      <td>26.571429</td>\n",
              "      <td>48</td>\n",
              "      <td>2012</td>\n",
              "      <td>1.450757</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>309</th>\n",
              "      <td>2012-12-09</td>\n",
              "      <td>16.000000</td>\n",
              "      <td>49</td>\n",
              "      <td>2012</td>\n",
              "      <td>0.873574</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>310</th>\n",
              "      <td>2012-12-16</td>\n",
              "      <td>18.571429</td>\n",
              "      <td>50</td>\n",
              "      <td>2012</td>\n",
              "      <td>1.013970</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>311</th>\n",
              "      <td>2012-12-23</td>\n",
              "      <td>28.857143</td>\n",
              "      <td>51</td>\n",
              "      <td>2012</td>\n",
              "      <td>1.575554</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>312</th>\n",
              "      <td>2012-12-30</td>\n",
              "      <td>22.600000</td>\n",
              "      <td>52</td>\n",
              "      <td>2012</td>\n",
              "      <td>1.233924</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "          Date       Conc  Week  Year       w_i\n",
              "282 2012-06-03  12.666667    22  2012  0.691580\n",
              "283 2012-06-10  11.142857    23  2012  0.608382\n",
              "284 2012-06-17  11.571429    24  2012  0.631781\n",
              "285 2012-06-24  14.714286    25  2012  0.803376\n",
              "286 2012-07-01  14.142857    26  2012  0.772177\n",
              "287 2012-07-08  21.714286    27  2012  1.185565\n",
              "288 2012-07-15  16.142857    28  2012  0.881374\n",
              "289 2012-07-22  12.857143    29  2012  0.701979\n",
              "290 2012-07-29  20.714286    30  2012  1.130967\n",
              "291 2012-08-05  15.142857    31  2012  0.826776\n",
              "292 2012-08-12  16.714286    32  2012  0.912573\n",
              "293 2012-08-19   8.571429    33  2012  0.467986\n",
              "294 2012-08-26  17.285714    34  2012  0.943772\n",
              "295 2012-09-02  13.714286    35  2012  0.748778\n",
              "296 2012-09-09  15.857143    36  2012  0.865775\n",
              "297 2012-09-16  16.428571    37  2012  0.896974\n",
              "298 2012-09-23  18.714286    38  2012  1.021770\n",
              "299 2012-09-30  20.285714    39  2012  1.107568\n",
              "300 2012-10-07  20.285714    40  2012  1.107568\n",
              "301 2012-10-14  19.428571    41  2012  1.060769\n",
              "302 2012-10-21  19.428571    42  2012  1.060769\n",
              "303 2012-10-28  15.857143    43  2012  0.865775\n",
              "305 2012-11-11  26.200000    45  2012  1.430478\n",
              "306 2012-11-18  21.857143    46  2012  1.193365\n",
              "307 2012-11-25  35.428571    47  2012  1.934343\n",
              "308 2012-12-02  26.571429    48  2012  1.450757\n",
              "309 2012-12-09  16.000000    49  2012  0.873574\n",
              "310 2012-12-16  18.571429    50  2012  1.013970\n",
              "311 2012-12-23  28.857143    51  2012  1.575554\n",
              "312 2012-12-30  22.600000    52  2012  1.233924"
            ]
          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "D_4I7lAlVNU9",
        "outputId": "9a254d64-82c6-4c09-e081-b6f88e260b87"
      },
      "source": [
        "df13 = df[df['Year'] == 2013].dropna()\n",
        "df13['w_i'] = wi_calc(df, 2013)\n",
        "df13"
      ],
      "execution_count": 20,
      "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>Date</th>\n",
              "      <th>Conc</th>\n",
              "      <th>Week</th>\n",
              "      <th>Year</th>\n",
              "      <th>w_i</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>313</th>\n",
              "      <td>2013-01-06</td>\n",
              "      <td>10.666667</td>\n",
              "      <td>1</td>\n",
              "      <td>2013</td>\n",
              "      <td>0.567468</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>314</th>\n",
              "      <td>2013-01-13</td>\n",
              "      <td>17.714286</td>\n",
              "      <td>2</td>\n",
              "      <td>2013</td>\n",
              "      <td>0.942403</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>315</th>\n",
              "      <td>2013-01-20</td>\n",
              "      <td>14.857143</td>\n",
              "      <td>3</td>\n",
              "      <td>2013</td>\n",
              "      <td>0.790403</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>316</th>\n",
              "      <td>2013-01-27</td>\n",
              "      <td>28.000000</td>\n",
              "      <td>4</td>\n",
              "      <td>2013</td>\n",
              "      <td>1.489605</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>317</th>\n",
              "      <td>2013-02-03</td>\n",
              "      <td>14.714286</td>\n",
              "      <td>5</td>\n",
              "      <td>2013</td>\n",
              "      <td>0.782803</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>318</th>\n",
              "      <td>2013-02-10</td>\n",
              "      <td>11.571429</td>\n",
              "      <td>6</td>\n",
              "      <td>2013</td>\n",
              "      <td>0.615602</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>319</th>\n",
              "      <td>2013-02-17</td>\n",
              "      <td>23.000000</td>\n",
              "      <td>7</td>\n",
              "      <td>2013</td>\n",
              "      <td>1.223604</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>320</th>\n",
              "      <td>2013-02-24</td>\n",
              "      <td>27.285714</td>\n",
              "      <td>8</td>\n",
              "      <td>2013</td>\n",
              "      <td>1.451605</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>321</th>\n",
              "      <td>2013-03-03</td>\n",
              "      <td>12.285714</td>\n",
              "      <td>9</td>\n",
              "      <td>2013</td>\n",
              "      <td>0.653602</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>322</th>\n",
              "      <td>2013-03-10</td>\n",
              "      <td>20.428571</td>\n",
              "      <td>10</td>\n",
              "      <td>2013</td>\n",
              "      <td>1.086803</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>323</th>\n",
              "      <td>2013-03-17</td>\n",
              "      <td>22.428571</td>\n",
              "      <td>11</td>\n",
              "      <td>2013</td>\n",
              "      <td>1.193204</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>324</th>\n",
              "      <td>2013-03-24</td>\n",
              "      <td>21.428571</td>\n",
              "      <td>12</td>\n",
              "      <td>2013</td>\n",
              "      <td>1.140004</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>325</th>\n",
              "      <td>2013-03-31</td>\n",
              "      <td>14.714286</td>\n",
              "      <td>13</td>\n",
              "      <td>2013</td>\n",
              "      <td>0.782803</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>326</th>\n",
              "      <td>2013-04-07</td>\n",
              "      <td>9.142857</td>\n",
              "      <td>14</td>\n",
              "      <td>2013</td>\n",
              "      <td>0.486402</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>327</th>\n",
              "      <td>2013-04-14</td>\n",
              "      <td>16.750000</td>\n",
              "      <td>15</td>\n",
              "      <td>2013</td>\n",
              "      <td>0.891103</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>328</th>\n",
              "      <td>2013-04-21</td>\n",
              "      <td>29.142857</td>\n",
              "      <td>16</td>\n",
              "      <td>2013</td>\n",
              "      <td>1.550405</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>329</th>\n",
              "      <td>2013-04-28</td>\n",
              "      <td>19.428571</td>\n",
              "      <td>17</td>\n",
              "      <td>2013</td>\n",
              "      <td>1.033603</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>330</th>\n",
              "      <td>2013-05-05</td>\n",
              "      <td>12.285714</td>\n",
              "      <td>18</td>\n",
              "      <td>2013</td>\n",
              "      <td>0.653602</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>331</th>\n",
              "      <td>2013-05-12</td>\n",
              "      <td>21.571429</td>\n",
              "      <td>19</td>\n",
              "      <td>2013</td>\n",
              "      <td>1.147604</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>332</th>\n",
              "      <td>2013-05-19</td>\n",
              "      <td>24.857143</td>\n",
              "      <td>20</td>\n",
              "      <td>2013</td>\n",
              "      <td>1.322404</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>333</th>\n",
              "      <td>2013-05-26</td>\n",
              "      <td>16.428571</td>\n",
              "      <td>21</td>\n",
              "      <td>2013</td>\n",
              "      <td>0.874003</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>334</th>\n",
              "      <td>2013-06-02</td>\n",
              "      <td>18.571429</td>\n",
              "      <td>22</td>\n",
              "      <td>2013</td>\n",
              "      <td>0.988003</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>335</th>\n",
              "      <td>2013-06-09</td>\n",
              "      <td>18.857143</td>\n",
              "      <td>23</td>\n",
              "      <td>2013</td>\n",
              "      <td>1.003203</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>336</th>\n",
              "      <td>2013-06-16</td>\n",
              "      <td>19.571429</td>\n",
              "      <td>24</td>\n",
              "      <td>2013</td>\n",
              "      <td>1.041203</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>337</th>\n",
              "      <td>2013-06-23</td>\n",
              "      <td>11.285714</td>\n",
              "      <td>25</td>\n",
              "      <td>2013</td>\n",
              "      <td>0.600402</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>338</th>\n",
              "      <td>2013-06-30</td>\n",
              "      <td>15.571429</td>\n",
              "      <td>26</td>\n",
              "      <td>2013</td>\n",
              "      <td>0.828403</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>339</th>\n",
              "      <td>2013-07-07</td>\n",
              "      <td>16.714286</td>\n",
              "      <td>27</td>\n",
              "      <td>2013</td>\n",
              "      <td>0.889203</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>340</th>\n",
              "      <td>2013-07-14</td>\n",
              "      <td>17.142857</td>\n",
              "      <td>28</td>\n",
              "      <td>2013</td>\n",
              "      <td>0.912003</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>341</th>\n",
              "      <td>2013-07-21</td>\n",
              "      <td>10.714286</td>\n",
              "      <td>29</td>\n",
              "      <td>2013</td>\n",
              "      <td>0.570002</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>342</th>\n",
              "      <td>2013-07-28</td>\n",
              "      <td>19.285714</td>\n",
              "      <td>30</td>\n",
              "      <td>2013</td>\n",
              "      <td>1.026003</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>343</th>\n",
              "      <td>2013-08-04</td>\n",
              "      <td>22.428571</td>\n",
              "      <td>31</td>\n",
              "      <td>2013</td>\n",
              "      <td>1.193204</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>344</th>\n",
              "      <td>2013-08-11</td>\n",
              "      <td>25.428571</td>\n",
              "      <td>32</td>\n",
              "      <td>2013</td>\n",
              "      <td>1.352804</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>345</th>\n",
              "      <td>2013-08-18</td>\n",
              "      <td>12.000000</td>\n",
              "      <td>33</td>\n",
              "      <td>2013</td>\n",
              "      <td>0.638402</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>346</th>\n",
              "      <td>2013-08-25</td>\n",
              "      <td>20.000000</td>\n",
              "      <td>34</td>\n",
              "      <td>2013</td>\n",
              "      <td>1.064003</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>347</th>\n",
              "      <td>2013-09-01</td>\n",
              "      <td>14.857143</td>\n",
              "      <td>35</td>\n",
              "      <td>2013</td>\n",
              "      <td>0.790403</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>348</th>\n",
              "      <td>2013-09-08</td>\n",
              "      <td>17.857143</td>\n",
              "      <td>36</td>\n",
              "      <td>2013</td>\n",
              "      <td>0.950003</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>349</th>\n",
              "      <td>2013-09-15</td>\n",
              "      <td>19.857143</td>\n",
              "      <td>37</td>\n",
              "      <td>2013</td>\n",
              "      <td>1.056403</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>350</th>\n",
              "      <td>2013-09-22</td>\n",
              "      <td>18.142857</td>\n",
              "      <td>38</td>\n",
              "      <td>2013</td>\n",
              "      <td>0.965203</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>351</th>\n",
              "      <td>2013-09-29</td>\n",
              "      <td>16.000000</td>\n",
              "      <td>39</td>\n",
              "      <td>2013</td>\n",
              "      <td>0.851203</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>352</th>\n",
              "      <td>2013-10-06</td>\n",
              "      <td>19.571429</td>\n",
              "      <td>40</td>\n",
              "      <td>2013</td>\n",
              "      <td>1.041203</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>353</th>\n",
              "      <td>2013-10-13</td>\n",
              "      <td>27.428571</td>\n",
              "      <td>41</td>\n",
              "      <td>2013</td>\n",
              "      <td>1.459205</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>354</th>\n",
              "      <td>2013-10-20</td>\n",
              "      <td>17.000000</td>\n",
              "      <td>42</td>\n",
              "      <td>2013</td>\n",
              "      <td>0.904403</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>355</th>\n",
              "      <td>2013-10-27</td>\n",
              "      <td>10.500000</td>\n",
              "      <td>43</td>\n",
              "      <td>2013</td>\n",
              "      <td>0.558602</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>356</th>\n",
              "      <td>2013-11-03</td>\n",
              "      <td>27.666667</td>\n",
              "      <td>44</td>\n",
              "      <td>2013</td>\n",
              "      <td>1.471871</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>357</th>\n",
              "      <td>2013-11-10</td>\n",
              "      <td>21.000000</td>\n",
              "      <td>45</td>\n",
              "      <td>2013</td>\n",
              "      <td>1.117204</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>358</th>\n",
              "      <td>2013-11-17</td>\n",
              "      <td>26.571429</td>\n",
              "      <td>46</td>\n",
              "      <td>2013</td>\n",
              "      <td>1.413605</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>359</th>\n",
              "      <td>2013-11-24</td>\n",
              "      <td>19.000000</td>\n",
              "      <td>47</td>\n",
              "      <td>2013</td>\n",
              "      <td>1.010803</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>360</th>\n",
              "      <td>2013-12-01</td>\n",
              "      <td>13.000000</td>\n",
              "      <td>48</td>\n",
              "      <td>2013</td>\n",
              "      <td>0.691602</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>361</th>\n",
              "      <td>2013-12-08</td>\n",
              "      <td>15.714286</td>\n",
              "      <td>49</td>\n",
              "      <td>2013</td>\n",
              "      <td>0.836003</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>362</th>\n",
              "      <td>2013-12-15</td>\n",
              "      <td>28.142857</td>\n",
              "      <td>50</td>\n",
              "      <td>2013</td>\n",
              "      <td>1.497205</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>363</th>\n",
              "      <td>2013-12-22</td>\n",
              "      <td>22.714286</td>\n",
              "      <td>51</td>\n",
              "      <td>2013</td>\n",
              "      <td>1.208404</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>364</th>\n",
              "      <td>2013-12-29</td>\n",
              "      <td>26.142857</td>\n",
              "      <td>52</td>\n",
              "      <td>2013</td>\n",
              "      <td>1.390804</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "          Date       Conc  Week  Year       w_i\n",
              "313 2013-01-06  10.666667     1  2013  0.567468\n",
              "314 2013-01-13  17.714286     2  2013  0.942403\n",
              "315 2013-01-20  14.857143     3  2013  0.790403\n",
              "316 2013-01-27  28.000000     4  2013  1.489605\n",
              "317 2013-02-03  14.714286     5  2013  0.782803\n",
              "318 2013-02-10  11.571429     6  2013  0.615602\n",
              "319 2013-02-17  23.000000     7  2013  1.223604\n",
              "320 2013-02-24  27.285714     8  2013  1.451605\n",
              "321 2013-03-03  12.285714     9  2013  0.653602\n",
              "322 2013-03-10  20.428571    10  2013  1.086803\n",
              "323 2013-03-17  22.428571    11  2013  1.193204\n",
              "324 2013-03-24  21.428571    12  2013  1.140004\n",
              "325 2013-03-31  14.714286    13  2013  0.782803\n",
              "326 2013-04-07   9.142857    14  2013  0.486402\n",
              "327 2013-04-14  16.750000    15  2013  0.891103\n",
              "328 2013-04-21  29.142857    16  2013  1.550405\n",
              "329 2013-04-28  19.428571    17  2013  1.033603\n",
              "330 2013-05-05  12.285714    18  2013  0.653602\n",
              "331 2013-05-12  21.571429    19  2013  1.147604\n",
              "332 2013-05-19  24.857143    20  2013  1.322404\n",
              "333 2013-05-26  16.428571    21  2013  0.874003\n",
              "334 2013-06-02  18.571429    22  2013  0.988003\n",
              "335 2013-06-09  18.857143    23  2013  1.003203\n",
              "336 2013-06-16  19.571429    24  2013  1.041203\n",
              "337 2013-06-23  11.285714    25  2013  0.600402\n",
              "338 2013-06-30  15.571429    26  2013  0.828403\n",
              "339 2013-07-07  16.714286    27  2013  0.889203\n",
              "340 2013-07-14  17.142857    28  2013  0.912003\n",
              "341 2013-07-21  10.714286    29  2013  0.570002\n",
              "342 2013-07-28  19.285714    30  2013  1.026003\n",
              "343 2013-08-04  22.428571    31  2013  1.193204\n",
              "344 2013-08-11  25.428571    32  2013  1.352804\n",
              "345 2013-08-18  12.000000    33  2013  0.638402\n",
              "346 2013-08-25  20.000000    34  2013  1.064003\n",
              "347 2013-09-01  14.857143    35  2013  0.790403\n",
              "348 2013-09-08  17.857143    36  2013  0.950003\n",
              "349 2013-09-15  19.857143    37  2013  1.056403\n",
              "350 2013-09-22  18.142857    38  2013  0.965203\n",
              "351 2013-09-29  16.000000    39  2013  0.851203\n",
              "352 2013-10-06  19.571429    40  2013  1.041203\n",
              "353 2013-10-13  27.428571    41  2013  1.459205\n",
              "354 2013-10-20  17.000000    42  2013  0.904403\n",
              "355 2013-10-27  10.500000    43  2013  0.558602\n",
              "356 2013-11-03  27.666667    44  2013  1.471871\n",
              "357 2013-11-10  21.000000    45  2013  1.117204\n",
              "358 2013-11-17  26.571429    46  2013  1.413605\n",
              "359 2013-11-24  19.000000    47  2013  1.010803\n",
              "360 2013-12-01  13.000000    48  2013  0.691602\n",
              "361 2013-12-08  15.714286    49  2013  0.836003\n",
              "362 2013-12-15  28.142857    50  2013  1.497205\n",
              "363 2013-12-22  22.714286    51  2013  1.208404\n",
              "364 2013-12-29  26.142857    52  2013  1.390804"
            ]
          },
          "metadata": {},
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "20k8llJ6VVr6",
        "outputId": "6217b9de-22f6-4a09-a79e-3093a86ca41d"
      },
      "source": [
        "df14 = df[df['Year'] == 2014].dropna()\n",
        "df14['w_i'] = wi_calc(df, 2014)\n",
        "df14"
      ],
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "    .dataframe tbody tr th:only-of-type {\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Date</th>\n",
              "      <th>Conc</th>\n",
              "      <th>Week</th>\n",
              "      <th>Year</th>\n",
              "      <th>w_i</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>365</th>\n",
              "      <td>2014-01-05</td>\n",
              "      <td>14.857143</td>\n",
              "      <td>1</td>\n",
              "      <td>2014</td>\n",
              "      <td>0.668480</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>366</th>\n",
              "      <td>2014-01-12</td>\n",
              "      <td>13.428571</td>\n",
              "      <td>2</td>\n",
              "      <td>2014</td>\n",
              "      <td>0.604203</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>367</th>\n",
              "      <td>2014-01-19</td>\n",
              "      <td>12.714286</td>\n",
              "      <td>3</td>\n",
              "      <td>2014</td>\n",
              "      <td>0.572064</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>368</th>\n",
              "      <td>2014-01-26</td>\n",
              "      <td>12.857143</td>\n",
              "      <td>4</td>\n",
              "      <td>2014</td>\n",
              "      <td>0.578492</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>369</th>\n",
              "      <td>2014-02-02</td>\n",
              "      <td>14.000000</td>\n",
              "      <td>5</td>\n",
              "      <td>2014</td>\n",
              "      <td>0.629913</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>370</th>\n",
              "      <td>2014-02-09</td>\n",
              "      <td>14.714286</td>\n",
              "      <td>6</td>\n",
              "      <td>2014</td>\n",
              "      <td>0.662052</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>371</th>\n",
              "      <td>2014-02-16</td>\n",
              "      <td>16.142857</td>\n",
              "      <td>7</td>\n",
              "      <td>2014</td>\n",
              "      <td>0.726329</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>372</th>\n",
              "      <td>2014-02-23</td>\n",
              "      <td>16.428571</td>\n",
              "      <td>8</td>\n",
              "      <td>2014</td>\n",
              "      <td>0.739184</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>373</th>\n",
              "      <td>2014-03-02</td>\n",
              "      <td>28.857143</td>\n",
              "      <td>9</td>\n",
              "      <td>2014</td>\n",
              "      <td>1.298393</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>374</th>\n",
              "      <td>2014-03-09</td>\n",
              "      <td>22.000000</td>\n",
              "      <td>10</td>\n",
              "      <td>2014</td>\n",
              "      <td>0.989864</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>375</th>\n",
              "      <td>2014-03-16</td>\n",
              "      <td>18.714286</td>\n",
              "      <td>11</td>\n",
              "      <td>2014</td>\n",
              "      <td>0.842027</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>376</th>\n",
              "      <td>2014-03-23</td>\n",
              "      <td>21.571429</td>\n",
              "      <td>12</td>\n",
              "      <td>2014</td>\n",
              "      <td>0.970581</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>377</th>\n",
              "      <td>2014-03-30</td>\n",
              "      <td>23.285714</td>\n",
              "      <td>13</td>\n",
              "      <td>2014</td>\n",
              "      <td>1.047713</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>378</th>\n",
              "      <td>2014-04-06</td>\n",
              "      <td>24.000000</td>\n",
              "      <td>14</td>\n",
              "      <td>2014</td>\n",
              "      <td>1.079852</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>379</th>\n",
              "      <td>2014-04-13</td>\n",
              "      <td>24.571429</td>\n",
              "      <td>15</td>\n",
              "      <td>2014</td>\n",
              "      <td>1.105562</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>380</th>\n",
              "      <td>2014-04-20</td>\n",
              "      <td>25.000000</td>\n",
              "      <td>16</td>\n",
              "      <td>2014</td>\n",
              "      <td>1.124845</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>381</th>\n",
              "      <td>2014-04-27</td>\n",
              "      <td>25.857143</td>\n",
              "      <td>17</td>\n",
              "      <td>2014</td>\n",
              "      <td>1.163412</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>382</th>\n",
              "      <td>2014-05-04</td>\n",
              "      <td>18.571429</td>\n",
              "      <td>18</td>\n",
              "      <td>2014</td>\n",
              "      <td>0.835600</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>383</th>\n",
              "      <td>2014-05-11</td>\n",
              "      <td>27.428571</td>\n",
              "      <td>19</td>\n",
              "      <td>2014</td>\n",
              "      <td>1.234116</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>384</th>\n",
              "      <td>2014-05-18</td>\n",
              "      <td>20.428571</td>\n",
              "      <td>20</td>\n",
              "      <td>2014</td>\n",
              "      <td>0.919159</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>385</th>\n",
              "      <td>2014-05-25</td>\n",
              "      <td>22.571429</td>\n",
              "      <td>21</td>\n",
              "      <td>2014</td>\n",
              "      <td>1.015575</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>386</th>\n",
              "      <td>2014-06-01</td>\n",
              "      <td>18.142857</td>\n",
              "      <td>22</td>\n",
              "      <td>2014</td>\n",
              "      <td>0.816316</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>387</th>\n",
              "      <td>2014-06-08</td>\n",
              "      <td>25.428571</td>\n",
              "      <td>23</td>\n",
              "      <td>2014</td>\n",
              "      <td>1.144129</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>388</th>\n",
              "      <td>2014-06-15</td>\n",
              "      <td>13.571429</td>\n",
              "      <td>24</td>\n",
              "      <td>2014</td>\n",
              "      <td>0.610630</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>389</th>\n",
              "      <td>2014-06-22</td>\n",
              "      <td>22.142857</td>\n",
              "      <td>25</td>\n",
              "      <td>2014</td>\n",
              "      <td>0.996292</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>390</th>\n",
              "      <td>2014-06-29</td>\n",
              "      <td>17.428571</td>\n",
              "      <td>26</td>\n",
              "      <td>2014</td>\n",
              "      <td>0.784178</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>391</th>\n",
              "      <td>2014-07-06</td>\n",
              "      <td>15.142857</td>\n",
              "      <td>27</td>\n",
              "      <td>2014</td>\n",
              "      <td>0.681335</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>392</th>\n",
              "      <td>2014-07-13</td>\n",
              "      <td>24.714286</td>\n",
              "      <td>28</td>\n",
              "      <td>2014</td>\n",
              "      <td>1.111990</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>393</th>\n",
              "      <td>2014-07-20</td>\n",
              "      <td>24.142857</td>\n",
              "      <td>29</td>\n",
              "      <td>2014</td>\n",
              "      <td>1.086279</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>394</th>\n",
              "      <td>2014-07-27</td>\n",
              "      <td>16.142857</td>\n",
              "      <td>30</td>\n",
              "      <td>2014</td>\n",
              "      <td>0.726329</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>395</th>\n",
              "      <td>2014-08-03</td>\n",
              "      <td>24.857143</td>\n",
              "      <td>31</td>\n",
              "      <td>2014</td>\n",
              "      <td>1.118418</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>396</th>\n",
              "      <td>2014-08-10</td>\n",
              "      <td>28.428571</td>\n",
              "      <td>32</td>\n",
              "      <td>2014</td>\n",
              "      <td>1.279110</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>397</th>\n",
              "      <td>2014-08-17</td>\n",
              "      <td>13.428571</td>\n",
              "      <td>33</td>\n",
              "      <td>2014</td>\n",
              "      <td>0.604203</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>398</th>\n",
              "      <td>2014-08-24</td>\n",
              "      <td>13.142857</td>\n",
              "      <td>34</td>\n",
              "      <td>2014</td>\n",
              "      <td>0.591347</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>399</th>\n",
              "      <td>2014-08-31</td>\n",
              "      <td>12.285714</td>\n",
              "      <td>35</td>\n",
              "      <td>2014</td>\n",
              "      <td>0.552781</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>400</th>\n",
              "      <td>2014-09-07</td>\n",
              "      <td>34.142857</td>\n",
              "      <td>36</td>\n",
              "      <td>2014</td>\n",
              "      <td>1.536218</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>401</th>\n",
              "      <td>2014-09-14</td>\n",
              "      <td>28.857143</td>\n",
              "      <td>37</td>\n",
              "      <td>2014</td>\n",
              "      <td>1.298393</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>402</th>\n",
              "      <td>2014-09-21</td>\n",
              "      <td>23.285714</td>\n",
              "      <td>38</td>\n",
              "      <td>2014</td>\n",
              "      <td>1.047713</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>403</th>\n",
              "      <td>2014-09-28</td>\n",
              "      <td>13.142857</td>\n",
              "      <td>39</td>\n",
              "      <td>2014</td>\n",
              "      <td>0.591347</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>404</th>\n",
              "      <td>2014-10-05</td>\n",
              "      <td>19.428571</td>\n",
              "      <td>40</td>\n",
              "      <td>2014</td>\n",
              "      <td>0.874166</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>405</th>\n",
              "      <td>2014-10-12</td>\n",
              "      <td>27.142857</td>\n",
              "      <td>41</td>\n",
              "      <td>2014</td>\n",
              "      <td>1.221261</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>406</th>\n",
              "      <td>2014-10-19</td>\n",
              "      <td>20.714286</td>\n",
              "      <td>42</td>\n",
              "      <td>2014</td>\n",
              "      <td>0.932015</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>407</th>\n",
              "      <td>2014-10-26</td>\n",
              "      <td>24.571429</td>\n",
              "      <td>43</td>\n",
              "      <td>2014</td>\n",
              "      <td>1.105562</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>408</th>\n",
              "      <td>2014-11-02</td>\n",
              "      <td>34.285714</td>\n",
              "      <td>44</td>\n",
              "      <td>2014</td>\n",
              "      <td>1.542645</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>409</th>\n",
              "      <td>2014-11-09</td>\n",
              "      <td>29.142857</td>\n",
              "      <td>45</td>\n",
              "      <td>2014</td>\n",
              "      <td>1.311248</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>410</th>\n",
              "      <td>2014-11-16</td>\n",
              "      <td>30.000000</td>\n",
              "      <td>46</td>\n",
              "      <td>2014</td>\n",
              "      <td>1.349815</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>411</th>\n",
              "      <td>2014-11-23</td>\n",
              "      <td>39.857143</td>\n",
              "      <td>47</td>\n",
              "      <td>2014</td>\n",
              "      <td>1.793325</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>412</th>\n",
              "      <td>2014-11-30</td>\n",
              "      <td>46.000000</td>\n",
              "      <td>48</td>\n",
              "      <td>2014</td>\n",
              "      <td>2.069716</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>413</th>\n",
              "      <td>2014-12-07</td>\n",
              "      <td>23.714286</td>\n",
              "      <td>49</td>\n",
              "      <td>2014</td>\n",
              "      <td>1.066996</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>414</th>\n",
              "      <td>2014-12-14</td>\n",
              "      <td>32.428571</td>\n",
              "      <td>50</td>\n",
              "      <td>2014</td>\n",
              "      <td>1.459085</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>415</th>\n",
              "      <td>2014-12-21</td>\n",
              "      <td>11.000000</td>\n",
              "      <td>51</td>\n",
              "      <td>2014</td>\n",
              "      <td>0.494932</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>416</th>\n",
              "      <td>2014-12-28</td>\n",
              "      <td>31.000000</td>\n",
              "      <td>52</td>\n",
              "      <td>2014</td>\n",
              "      <td>1.394808</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "          Date       Conc  Week  Year       w_i\n",
              "365 2014-01-05  14.857143     1  2014  0.668480\n",
              "366 2014-01-12  13.428571     2  2014  0.604203\n",
              "367 2014-01-19  12.714286     3  2014  0.572064\n",
              "368 2014-01-26  12.857143     4  2014  0.578492\n",
              "369 2014-02-02  14.000000     5  2014  0.629913\n",
              "370 2014-02-09  14.714286     6  2014  0.662052\n",
              "371 2014-02-16  16.142857     7  2014  0.726329\n",
              "372 2014-02-23  16.428571     8  2014  0.739184\n",
              "373 2014-03-02  28.857143     9  2014  1.298393\n",
              "374 2014-03-09  22.000000    10  2014  0.989864\n",
              "375 2014-03-16  18.714286    11  2014  0.842027\n",
              "376 2014-03-23  21.571429    12  2014  0.970581\n",
              "377 2014-03-30  23.285714    13  2014  1.047713\n",
              "378 2014-04-06  24.000000    14  2014  1.079852\n",
              "379 2014-04-13  24.571429    15  2014  1.105562\n",
              "380 2014-04-20  25.000000    16  2014  1.124845\n",
              "381 2014-04-27  25.857143    17  2014  1.163412\n",
              "382 2014-05-04  18.571429    18  2014  0.835600\n",
              "383 2014-05-11  27.428571    19  2014  1.234116\n",
              "384 2014-05-18  20.428571    20  2014  0.919159\n",
              "385 2014-05-25  22.571429    21  2014  1.015575\n",
              "386 2014-06-01  18.142857    22  2014  0.816316\n",
              "387 2014-06-08  25.428571    23  2014  1.144129\n",
              "388 2014-06-15  13.571429    24  2014  0.610630\n",
              "389 2014-06-22  22.142857    25  2014  0.996292\n",
              "390 2014-06-29  17.428571    26  2014  0.784178\n",
              "391 2014-07-06  15.142857    27  2014  0.681335\n",
              "392 2014-07-13  24.714286    28  2014  1.111990\n",
              "393 2014-07-20  24.142857    29  2014  1.086279\n",
              "394 2014-07-27  16.142857    30  2014  0.726329\n",
              "395 2014-08-03  24.857143    31  2014  1.118418\n",
              "396 2014-08-10  28.428571    32  2014  1.279110\n",
              "397 2014-08-17  13.428571    33  2014  0.604203\n",
              "398 2014-08-24  13.142857    34  2014  0.591347\n",
              "399 2014-08-31  12.285714    35  2014  0.552781\n",
              "400 2014-09-07  34.142857    36  2014  1.536218\n",
              "401 2014-09-14  28.857143    37  2014  1.298393\n",
              "402 2014-09-21  23.285714    38  2014  1.047713\n",
              "403 2014-09-28  13.142857    39  2014  0.591347\n",
              "404 2014-10-05  19.428571    40  2014  0.874166\n",
              "405 2014-10-12  27.142857    41  2014  1.221261\n",
              "406 2014-10-19  20.714286    42  2014  0.932015\n",
              "407 2014-10-26  24.571429    43  2014  1.105562\n",
              "408 2014-11-02  34.285714    44  2014  1.542645\n",
              "409 2014-11-09  29.142857    45  2014  1.311248\n",
              "410 2014-11-16  30.000000    46  2014  1.349815\n",
              "411 2014-11-23  39.857143    47  2014  1.793325\n",
              "412 2014-11-30  46.000000    48  2014  2.069716\n",
              "413 2014-12-07  23.714286    49  2014  1.066996\n",
              "414 2014-12-14  32.428571    50  2014  1.459085\n",
              "415 2014-12-21  11.000000    51  2014  0.494932\n",
              "416 2014-12-28  31.000000    52  2014  1.394808"
            ]
          },
          "metadata": {},
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "bWXy94xgVa8F",
        "outputId": "3e809ba2-19b6-4fc4-bd6b-eea1c1284663"
      },
      "source": [
        "df15 = df[df['Year'] == 2015].dropna()\n",
        "df15['w_i'] = wi_calc(df, 2015)\n",
        "df15"
      ],
      "execution_count": 22,
      "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",
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              "        vertical-align: top;\n",
              "    }\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Date</th>\n",
              "      <th>Conc</th>\n",
              "      <th>Week</th>\n",
              "      <th>Year</th>\n",
              "      <th>w_i</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>417</th>\n",
              "      <td>2015-01-04</td>\n",
              "      <td>22.000000</td>\n",
              "      <td>1</td>\n",
              "      <td>2015</td>\n",
              "      <td>0.854202</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>418</th>\n",
              "      <td>2015-01-11</td>\n",
              "      <td>30.571429</td>\n",
              "      <td>2</td>\n",
              "      <td>2015</td>\n",
              "      <td>1.187008</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>419</th>\n",
              "      <td>2015-01-18</td>\n",
              "      <td>36.571429</td>\n",
              "      <td>3</td>\n",
              "      <td>2015</td>\n",
              "      <td>1.419972</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>420</th>\n",
              "      <td>2015-01-25</td>\n",
              "      <td>28.857143</td>\n",
              "      <td>4</td>\n",
              "      <td>2015</td>\n",
              "      <td>1.120447</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>421</th>\n",
              "      <td>2015-02-01</td>\n",
              "      <td>18.142857</td>\n",
              "      <td>5</td>\n",
              "      <td>2015</td>\n",
              "      <td>0.704439</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>422</th>\n",
              "      <td>2015-02-08</td>\n",
              "      <td>20.857143</td>\n",
              "      <td>6</td>\n",
              "      <td>2015</td>\n",
              "      <td>0.809828</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>423</th>\n",
              "      <td>2015-02-15</td>\n",
              "      <td>22.857143</td>\n",
              "      <td>7</td>\n",
              "      <td>2015</td>\n",
              "      <td>0.887482</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>424</th>\n",
              "      <td>2015-02-22</td>\n",
              "      <td>21.571429</td>\n",
              "      <td>8</td>\n",
              "      <td>2015</td>\n",
              "      <td>0.837562</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>425</th>\n",
              "      <td>2015-03-01</td>\n",
              "      <td>27.714286</td>\n",
              "      <td>9</td>\n",
              "      <td>2015</td>\n",
              "      <td>1.076072</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>426</th>\n",
              "      <td>2015-03-08</td>\n",
              "      <td>22.000000</td>\n",
              "      <td>10</td>\n",
              "      <td>2015</td>\n",
              "      <td>0.854202</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>427</th>\n",
              "      <td>2015-03-15</td>\n",
              "      <td>23.571429</td>\n",
              "      <td>11</td>\n",
              "      <td>2015</td>\n",
              "      <td>0.915216</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>428</th>\n",
              "      <td>2015-03-22</td>\n",
              "      <td>31.142857</td>\n",
              "      <td>12</td>\n",
              "      <td>2015</td>\n",
              "      <td>1.209195</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>429</th>\n",
              "      <td>2015-03-29</td>\n",
              "      <td>39.142857</td>\n",
              "      <td>13</td>\n",
              "      <td>2015</td>\n",
              "      <td>1.519814</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>430</th>\n",
              "      <td>2015-04-05</td>\n",
              "      <td>19.857143</td>\n",
              "      <td>14</td>\n",
              "      <td>2015</td>\n",
              "      <td>0.771000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>431</th>\n",
              "      <td>2015-04-12</td>\n",
              "      <td>13.285714</td>\n",
              "      <td>15</td>\n",
              "      <td>2015</td>\n",
              "      <td>0.515849</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>432</th>\n",
              "      <td>2015-04-19</td>\n",
              "      <td>8.571429</td>\n",
              "      <td>16</td>\n",
              "      <td>2015</td>\n",
              "      <td>0.332806</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>433</th>\n",
              "      <td>2015-04-26</td>\n",
              "      <td>17.428571</td>\n",
              "      <td>17</td>\n",
              "      <td>2015</td>\n",
              "      <td>0.676705</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>434</th>\n",
              "      <td>2015-05-03</td>\n",
              "      <td>11.714286</td>\n",
              "      <td>18</td>\n",
              "      <td>2015</td>\n",
              "      <td>0.454835</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>435</th>\n",
              "      <td>2015-05-10</td>\n",
              "      <td>27.571429</td>\n",
              "      <td>19</td>\n",
              "      <td>2015</td>\n",
              "      <td>1.070526</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>436</th>\n",
              "      <td>2015-05-17</td>\n",
              "      <td>15.571429</td>\n",
              "      <td>20</td>\n",
              "      <td>2015</td>\n",
              "      <td>0.604597</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>437</th>\n",
              "      <td>2015-05-24</td>\n",
              "      <td>30.714286</td>\n",
              "      <td>21</td>\n",
              "      <td>2015</td>\n",
              "      <td>1.192555</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>438</th>\n",
              "      <td>2015-05-31</td>\n",
              "      <td>23.571429</td>\n",
              "      <td>22</td>\n",
              "      <td>2015</td>\n",
              "      <td>0.915216</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>439</th>\n",
              "      <td>2015-06-07</td>\n",
              "      <td>21.571429</td>\n",
              "      <td>23</td>\n",
              "      <td>2015</td>\n",
              "      <td>0.837562</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>440</th>\n",
              "      <td>2015-06-14</td>\n",
              "      <td>28.857143</td>\n",
              "      <td>24</td>\n",
              "      <td>2015</td>\n",
              "      <td>1.120447</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>441</th>\n",
              "      <td>2015-06-21</td>\n",
              "      <td>27.571429</td>\n",
              "      <td>25</td>\n",
              "      <td>2015</td>\n",
              "      <td>1.070526</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>442</th>\n",
              "      <td>2015-06-28</td>\n",
              "      <td>25.571429</td>\n",
              "      <td>26</td>\n",
              "      <td>2015</td>\n",
              "      <td>0.992871</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>443</th>\n",
              "      <td>2015-07-05</td>\n",
              "      <td>17.428571</td>\n",
              "      <td>27</td>\n",
              "      <td>2015</td>\n",
              "      <td>0.676705</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>444</th>\n",
              "      <td>2015-07-12</td>\n",
              "      <td>26.142857</td>\n",
              "      <td>28</td>\n",
              "      <td>2015</td>\n",
              "      <td>1.015058</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>445</th>\n",
              "      <td>2015-07-19</td>\n",
              "      <td>20.714286</td>\n",
              "      <td>29</td>\n",
              "      <td>2015</td>\n",
              "      <td>0.804281</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>446</th>\n",
              "      <td>2015-07-26</td>\n",
              "      <td>18.571429</td>\n",
              "      <td>30</td>\n",
              "      <td>2015</td>\n",
              "      <td>0.721079</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>447</th>\n",
              "      <td>2015-08-02</td>\n",
              "      <td>27.714286</td>\n",
              "      <td>31</td>\n",
              "      <td>2015</td>\n",
              "      <td>1.076072</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>448</th>\n",
              "      <td>2015-08-09</td>\n",
              "      <td>25.714286</td>\n",
              "      <td>32</td>\n",
              "      <td>2015</td>\n",
              "      <td>0.998418</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>449</th>\n",
              "      <td>2015-08-16</td>\n",
              "      <td>51.833333</td>\n",
              "      <td>33</td>\n",
              "      <td>2015</td>\n",
              "      <td>2.012551</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>450</th>\n",
              "      <td>2015-08-23</td>\n",
              "      <td>29.428571</td>\n",
              "      <td>34</td>\n",
              "      <td>2015</td>\n",
              "      <td>1.142634</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>451</th>\n",
              "      <td>2015-08-30</td>\n",
              "      <td>30.142857</td>\n",
              "      <td>35</td>\n",
              "      <td>2015</td>\n",
              "      <td>1.170367</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>452</th>\n",
              "      <td>2015-09-06</td>\n",
              "      <td>30.714286</td>\n",
              "      <td>36</td>\n",
              "      <td>2015</td>\n",
              "      <td>1.192555</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>453</th>\n",
              "      <td>2015-09-13</td>\n",
              "      <td>11.000000</td>\n",
              "      <td>37</td>\n",
              "      <td>2015</td>\n",
              "      <td>0.427101</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>454</th>\n",
              "      <td>2015-09-20</td>\n",
              "      <td>26.571429</td>\n",
              "      <td>38</td>\n",
              "      <td>2015</td>\n",
              "      <td>1.031698</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>455</th>\n",
              "      <td>2015-09-27</td>\n",
              "      <td>37.571429</td>\n",
              "      <td>39</td>\n",
              "      <td>2015</td>\n",
              "      <td>1.458799</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>456</th>\n",
              "      <td>2015-10-04</td>\n",
              "      <td>38.571429</td>\n",
              "      <td>40</td>\n",
              "      <td>2015</td>\n",
              "      <td>1.497627</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>457</th>\n",
              "      <td>2015-10-11</td>\n",
              "      <td>21.285714</td>\n",
              "      <td>41</td>\n",
              "      <td>2015</td>\n",
              "      <td>0.826468</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>458</th>\n",
              "      <td>2015-10-18</td>\n",
              "      <td>52.000000</td>\n",
              "      <td>42</td>\n",
              "      <td>2015</td>\n",
              "      <td>2.019023</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>459</th>\n",
              "      <td>2015-10-25</td>\n",
              "      <td>14.857143</td>\n",
              "      <td>43</td>\n",
              "      <td>2015</td>\n",
              "      <td>0.576864</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>460</th>\n",
              "      <td>2015-11-01</td>\n",
              "      <td>22.857143</td>\n",
              "      <td>44</td>\n",
              "      <td>2015</td>\n",
              "      <td>0.887482</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>461</th>\n",
              "      <td>2015-11-08</td>\n",
              "      <td>29.000000</td>\n",
              "      <td>45</td>\n",
              "      <td>2015</td>\n",
              "      <td>1.125993</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>462</th>\n",
              "      <td>2015-11-15</td>\n",
              "      <td>37.428571</td>\n",
              "      <td>46</td>\n",
              "      <td>2015</td>\n",
              "      <td>1.453253</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>463</th>\n",
              "      <td>2015-11-22</td>\n",
              "      <td>15.285714</td>\n",
              "      <td>47</td>\n",
              "      <td>2015</td>\n",
              "      <td>0.593504</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>464</th>\n",
              "      <td>2015-11-29</td>\n",
              "      <td>24.142857</td>\n",
              "      <td>48</td>\n",
              "      <td>2015</td>\n",
              "      <td>0.937403</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>465</th>\n",
              "      <td>2015-12-06</td>\n",
              "      <td>19.285714</td>\n",
              "      <td>49</td>\n",
              "      <td>2015</td>\n",
              "      <td>0.748813</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>466</th>\n",
              "      <td>2015-12-13</td>\n",
              "      <td>50.714286</td>\n",
              "      <td>50</td>\n",
              "      <td>2015</td>\n",
              "      <td>1.969102</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>467</th>\n",
              "      <td>2015-12-20</td>\n",
              "      <td>20.857143</td>\n",
              "      <td>51</td>\n",
              "      <td>2015</td>\n",
              "      <td>0.809828</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>468</th>\n",
              "      <td>2015-12-27</td>\n",
              "      <td>22.571429</td>\n",
              "      <td>52</td>\n",
              "      <td>2015</td>\n",
              "      <td>0.876389</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "          Date       Conc  Week  Year       w_i\n",
              "417 2015-01-04  22.000000     1  2015  0.854202\n",
              "418 2015-01-11  30.571429     2  2015  1.187008\n",
              "419 2015-01-18  36.571429     3  2015  1.419972\n",
              "420 2015-01-25  28.857143     4  2015  1.120447\n",
              "421 2015-02-01  18.142857     5  2015  0.704439\n",
              "422 2015-02-08  20.857143     6  2015  0.809828\n",
              "423 2015-02-15  22.857143     7  2015  0.887482\n",
              "424 2015-02-22  21.571429     8  2015  0.837562\n",
              "425 2015-03-01  27.714286     9  2015  1.076072\n",
              "426 2015-03-08  22.000000    10  2015  0.854202\n",
              "427 2015-03-15  23.571429    11  2015  0.915216\n",
              "428 2015-03-22  31.142857    12  2015  1.209195\n",
              "429 2015-03-29  39.142857    13  2015  1.519814\n",
              "430 2015-04-05  19.857143    14  2015  0.771000\n",
              "431 2015-04-12  13.285714    15  2015  0.515849\n",
              "432 2015-04-19   8.571429    16  2015  0.332806\n",
              "433 2015-04-26  17.428571    17  2015  0.676705\n",
              "434 2015-05-03  11.714286    18  2015  0.454835\n",
              "435 2015-05-10  27.571429    19  2015  1.070526\n",
              "436 2015-05-17  15.571429    20  2015  0.604597\n",
              "437 2015-05-24  30.714286    21  2015  1.192555\n",
              "438 2015-05-31  23.571429    22  2015  0.915216\n",
              "439 2015-06-07  21.571429    23  2015  0.837562\n",
              "440 2015-06-14  28.857143    24  2015  1.120447\n",
              "441 2015-06-21  27.571429    25  2015  1.070526\n",
              "442 2015-06-28  25.571429    26  2015  0.992871\n",
              "443 2015-07-05  17.428571    27  2015  0.676705\n",
              "444 2015-07-12  26.142857    28  2015  1.015058\n",
              "445 2015-07-19  20.714286    29  2015  0.804281\n",
              "446 2015-07-26  18.571429    30  2015  0.721079\n",
              "447 2015-08-02  27.714286    31  2015  1.076072\n",
              "448 2015-08-09  25.714286    32  2015  0.998418\n",
              "449 2015-08-16  51.833333    33  2015  2.012551\n",
              "450 2015-08-23  29.428571    34  2015  1.142634\n",
              "451 2015-08-30  30.142857    35  2015  1.170367\n",
              "452 2015-09-06  30.714286    36  2015  1.192555\n",
              "453 2015-09-13  11.000000    37  2015  0.427101\n",
              "454 2015-09-20  26.571429    38  2015  1.031698\n",
              "455 2015-09-27  37.571429    39  2015  1.458799\n",
              "456 2015-10-04  38.571429    40  2015  1.497627\n",
              "457 2015-10-11  21.285714    41  2015  0.826468\n",
              "458 2015-10-18  52.000000    42  2015  2.019023\n",
              "459 2015-10-25  14.857143    43  2015  0.576864\n",
              "460 2015-11-01  22.857143    44  2015  0.887482\n",
              "461 2015-11-08  29.000000    45  2015  1.125993\n",
              "462 2015-11-15  37.428571    46  2015  1.453253\n",
              "463 2015-11-22  15.285714    47  2015  0.593504\n",
              "464 2015-11-29  24.142857    48  2015  0.937403\n",
              "465 2015-12-06  19.285714    49  2015  0.748813\n",
              "466 2015-12-13  50.714286    50  2015  1.969102\n",
              "467 2015-12-20  20.857143    51  2015  0.809828\n",
              "468 2015-12-27  22.571429    52  2015  0.876389"
            ]
          },
          "metadata": {},
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "oTopZSm3Vgsb",
        "outputId": "a3ac1cc0-93e7-4495-c867-19d538962e1b"
      },
      "source": [
        "df16 = df[df['Year'] == 2016].dropna()\n",
        "df16['w_i'] = wi_calc(df, 2016)\n",
        "df16"
      ],
      "execution_count": 23,
      "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",
              "    .dataframe tbody tr th {\n",
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              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Date</th>\n",
              "      <th>Conc</th>\n",
              "      <th>Week</th>\n",
              "      <th>Year</th>\n",
              "      <th>w_i</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>469</th>\n",
              "      <td>2016-01-03</td>\n",
              "      <td>27.714286</td>\n",
              "      <td>53</td>\n",
              "      <td>2016</td>\n",
              "      <td>1.105383</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>470</th>\n",
              "      <td>2016-01-10</td>\n",
              "      <td>34.000000</td>\n",
              "      <td>1</td>\n",
              "      <td>2016</td>\n",
              "      <td>1.356088</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>471</th>\n",
              "      <td>2016-01-17</td>\n",
              "      <td>21.857143</td>\n",
              "      <td>2</td>\n",
              "      <td>2016</td>\n",
              "      <td>0.871771</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>472</th>\n",
              "      <td>2016-01-24</td>\n",
              "      <td>28.000000</td>\n",
              "      <td>3</td>\n",
              "      <td>2016</td>\n",
              "      <td>1.116779</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>473</th>\n",
              "      <td>2016-01-31</td>\n",
              "      <td>22.714286</td>\n",
              "      <td>4</td>\n",
              "      <td>2016</td>\n",
              "      <td>0.905958</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>474</th>\n",
              "      <td>2016-02-07</td>\n",
              "      <td>35.428571</td>\n",
              "      <td>5</td>\n",
              "      <td>2016</td>\n",
              "      <td>1.413067</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>475</th>\n",
              "      <td>2016-02-14</td>\n",
              "      <td>23.285714</td>\n",
              "      <td>6</td>\n",
              "      <td>2016</td>\n",
              "      <td>0.928749</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>476</th>\n",
              "      <td>2016-02-21</td>\n",
              "      <td>20.000000</td>\n",
              "      <td>7</td>\n",
              "      <td>2016</td>\n",
              "      <td>0.797699</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>477</th>\n",
              "      <td>2016-02-28</td>\n",
              "      <td>22.428571</td>\n",
              "      <td>8</td>\n",
              "      <td>2016</td>\n",
              "      <td>0.894562</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>478</th>\n",
              "      <td>2016-03-06</td>\n",
              "      <td>16.571429</td>\n",
              "      <td>9</td>\n",
              "      <td>2016</td>\n",
              "      <td>0.660951</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>479</th>\n",
              "      <td>2016-03-13</td>\n",
              "      <td>25.428571</td>\n",
              "      <td>10</td>\n",
              "      <td>2016</td>\n",
              "      <td>1.014217</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>480</th>\n",
              "      <td>2016-03-20</td>\n",
              "      <td>27.714286</td>\n",
              "      <td>11</td>\n",
              "      <td>2016</td>\n",
              "      <td>1.105383</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>481</th>\n",
              "      <td>2016-03-27</td>\n",
              "      <td>27.428571</td>\n",
              "      <td>12</td>\n",
              "      <td>2016</td>\n",
              "      <td>1.093987</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>482</th>\n",
              "      <td>2016-04-03</td>\n",
              "      <td>22.428571</td>\n",
              "      <td>13</td>\n",
              "      <td>2016</td>\n",
              "      <td>0.894562</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>483</th>\n",
              "      <td>2016-04-10</td>\n",
              "      <td>29.285714</td>\n",
              "      <td>14</td>\n",
              "      <td>2016</td>\n",
              "      <td>1.168059</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>484</th>\n",
              "      <td>2016-04-17</td>\n",
              "      <td>42.571429</td>\n",
              "      <td>15</td>\n",
              "      <td>2016</td>\n",
              "      <td>1.697959</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>485</th>\n",
              "      <td>2016-04-24</td>\n",
              "      <td>28.571429</td>\n",
              "      <td>16</td>\n",
              "      <td>2016</td>\n",
              "      <td>1.139570</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>486</th>\n",
              "      <td>2016-05-01</td>\n",
              "      <td>19.000000</td>\n",
              "      <td>17</td>\n",
              "      <td>2016</td>\n",
              "      <td>0.757814</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>487</th>\n",
              "      <td>2016-05-08</td>\n",
              "      <td>31.000000</td>\n",
              "      <td>18</td>\n",
              "      <td>2016</td>\n",
              "      <td>1.236433</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>488</th>\n",
              "      <td>2016-05-15</td>\n",
              "      <td>23.000000</td>\n",
              "      <td>19</td>\n",
              "      <td>2016</td>\n",
              "      <td>0.917354</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>489</th>\n",
              "      <td>2016-05-22</td>\n",
              "      <td>24.714286</td>\n",
              "      <td>20</td>\n",
              "      <td>2016</td>\n",
              "      <td>0.985728</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>490</th>\n",
              "      <td>2016-05-29</td>\n",
              "      <td>21.285714</td>\n",
              "      <td>21</td>\n",
              "      <td>2016</td>\n",
              "      <td>0.848980</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>491</th>\n",
              "      <td>2016-06-05</td>\n",
              "      <td>28.857143</td>\n",
              "      <td>22</td>\n",
              "      <td>2016</td>\n",
              "      <td>1.150966</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>492</th>\n",
              "      <td>2016-06-12</td>\n",
              "      <td>31.714286</td>\n",
              "      <td>23</td>\n",
              "      <td>2016</td>\n",
              "      <td>1.264923</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>493</th>\n",
              "      <td>2016-06-19</td>\n",
              "      <td>25.000000</td>\n",
              "      <td>24</td>\n",
              "      <td>2016</td>\n",
              "      <td>0.997124</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>494</th>\n",
              "      <td>2016-06-26</td>\n",
              "      <td>29.142857</td>\n",
              "      <td>25</td>\n",
              "      <td>2016</td>\n",
              "      <td>1.162361</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>495</th>\n",
              "      <td>2016-07-03</td>\n",
              "      <td>25.571429</td>\n",
              "      <td>26</td>\n",
              "      <td>2016</td>\n",
              "      <td>1.019915</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>496</th>\n",
              "      <td>2016-07-10</td>\n",
              "      <td>20.000000</td>\n",
              "      <td>27</td>\n",
              "      <td>2016</td>\n",
              "      <td>0.797699</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>497</th>\n",
              "      <td>2016-07-17</td>\n",
              "      <td>32.714286</td>\n",
              "      <td>28</td>\n",
              "      <td>2016</td>\n",
              "      <td>1.304808</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>498</th>\n",
              "      <td>2016-07-24</td>\n",
              "      <td>39.857143</td>\n",
              "      <td>29</td>\n",
              "      <td>2016</td>\n",
              "      <td>1.589700</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>499</th>\n",
              "      <td>2016-07-31</td>\n",
              "      <td>22.250000</td>\n",
              "      <td>30</td>\n",
              "      <td>2016</td>\n",
              "      <td>0.887440</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>500</th>\n",
              "      <td>2016-08-07</td>\n",
              "      <td>31.000000</td>\n",
              "      <td>31</td>\n",
              "      <td>2016</td>\n",
              "      <td>1.236433</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>501</th>\n",
              "      <td>2016-08-14</td>\n",
              "      <td>31.714286</td>\n",
              "      <td>32</td>\n",
              "      <td>2016</td>\n",
              "      <td>1.264923</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>502</th>\n",
              "      <td>2016-08-21</td>\n",
              "      <td>23.142857</td>\n",
              "      <td>33</td>\n",
              "      <td>2016</td>\n",
              "      <td>0.923052</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>503</th>\n",
              "      <td>2016-08-28</td>\n",
              "      <td>29.142857</td>\n",
              "      <td>34</td>\n",
              "      <td>2016</td>\n",
              "      <td>1.162361</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>504</th>\n",
              "      <td>2016-09-04</td>\n",
              "      <td>19.000000</td>\n",
              "      <td>35</td>\n",
              "      <td>2016</td>\n",
              "      <td>0.757814</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>505</th>\n",
              "      <td>2016-09-11</td>\n",
              "      <td>23.714286</td>\n",
              "      <td>36</td>\n",
              "      <td>2016</td>\n",
              "      <td>0.945843</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>506</th>\n",
              "      <td>2016-09-18</td>\n",
              "      <td>24.000000</td>\n",
              "      <td>37</td>\n",
              "      <td>2016</td>\n",
              "      <td>0.957239</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>507</th>\n",
              "      <td>2016-09-25</td>\n",
              "      <td>14.285714</td>\n",
              "      <td>38</td>\n",
              "      <td>2016</td>\n",
              "      <td>0.569785</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>508</th>\n",
              "      <td>2016-10-02</td>\n",
              "      <td>24.571429</td>\n",
              "      <td>39</td>\n",
              "      <td>2016</td>\n",
              "      <td>0.980030</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>509</th>\n",
              "      <td>2016-10-09</td>\n",
              "      <td>15.142857</td>\n",
              "      <td>40</td>\n",
              "      <td>2016</td>\n",
              "      <td>0.603972</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>510</th>\n",
              "      <td>2016-10-16</td>\n",
              "      <td>14.571429</td>\n",
              "      <td>41</td>\n",
              "      <td>2016</td>\n",
              "      <td>0.581181</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>511</th>\n",
              "      <td>2016-10-23</td>\n",
              "      <td>31.428571</td>\n",
              "      <td>42</td>\n",
              "      <td>2016</td>\n",
              "      <td>1.253527</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>512</th>\n",
              "      <td>2016-10-30</td>\n",
              "      <td>49.571429</td>\n",
              "      <td>43</td>\n",
              "      <td>2016</td>\n",
              "      <td>1.977154</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>513</th>\n",
              "      <td>2016-11-06</td>\n",
              "      <td>21.142857</td>\n",
              "      <td>44</td>\n",
              "      <td>2016</td>\n",
              "      <td>0.843282</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>514</th>\n",
              "      <td>2016-11-13</td>\n",
              "      <td>20.857143</td>\n",
              "      <td>45</td>\n",
              "      <td>2016</td>\n",
              "      <td>0.831886</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>515</th>\n",
              "      <td>2016-11-20</td>\n",
              "      <td>20.000000</td>\n",
              "      <td>46</td>\n",
              "      <td>2016</td>\n",
              "      <td>0.797699</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>516</th>\n",
              "      <td>2016-11-27</td>\n",
              "      <td>25.500000</td>\n",
              "      <td>47</td>\n",
              "      <td>2016</td>\n",
              "      <td>1.017066</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>517</th>\n",
              "      <td>2016-12-04</td>\n",
              "      <td>18.000000</td>\n",
              "      <td>48</td>\n",
              "      <td>2016</td>\n",
              "      <td>0.717929</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>518</th>\n",
              "      <td>2016-12-11</td>\n",
              "      <td>15.142857</td>\n",
              "      <td>49</td>\n",
              "      <td>2016</td>\n",
              "      <td>0.603972</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>519</th>\n",
              "      <td>2016-12-18</td>\n",
              "      <td>13.571429</td>\n",
              "      <td>50</td>\n",
              "      <td>2016</td>\n",
              "      <td>0.541296</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>520</th>\n",
              "      <td>2016-12-25</td>\n",
              "      <td>8.714286</td>\n",
              "      <td>51</td>\n",
              "      <td>2016</td>\n",
              "      <td>0.347569</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "          Date       Conc  Week  Year       w_i\n",
              "469 2016-01-03  27.714286    53  2016  1.105383\n",
              "470 2016-01-10  34.000000     1  2016  1.356088\n",
              "471 2016-01-17  21.857143     2  2016  0.871771\n",
              "472 2016-01-24  28.000000     3  2016  1.116779\n",
              "473 2016-01-31  22.714286     4  2016  0.905958\n",
              "474 2016-02-07  35.428571     5  2016  1.413067\n",
              "475 2016-02-14  23.285714     6  2016  0.928749\n",
              "476 2016-02-21  20.000000     7  2016  0.797699\n",
              "477 2016-02-28  22.428571     8  2016  0.894562\n",
              "478 2016-03-06  16.571429     9  2016  0.660951\n",
              "479 2016-03-13  25.428571    10  2016  1.014217\n",
              "480 2016-03-20  27.714286    11  2016  1.105383\n",
              "481 2016-03-27  27.428571    12  2016  1.093987\n",
              "482 2016-04-03  22.428571    13  2016  0.894562\n",
              "483 2016-04-10  29.285714    14  2016  1.168059\n",
              "484 2016-04-17  42.571429    15  2016  1.697959\n",
              "485 2016-04-24  28.571429    16  2016  1.139570\n",
              "486 2016-05-01  19.000000    17  2016  0.757814\n",
              "487 2016-05-08  31.000000    18  2016  1.236433\n",
              "488 2016-05-15  23.000000    19  2016  0.917354\n",
              "489 2016-05-22  24.714286    20  2016  0.985728\n",
              "490 2016-05-29  21.285714    21  2016  0.848980\n",
              "491 2016-06-05  28.857143    22  2016  1.150966\n",
              "492 2016-06-12  31.714286    23  2016  1.264923\n",
              "493 2016-06-19  25.000000    24  2016  0.997124\n",
              "494 2016-06-26  29.142857    25  2016  1.162361\n",
              "495 2016-07-03  25.571429    26  2016  1.019915\n",
              "496 2016-07-10  20.000000    27  2016  0.797699\n",
              "497 2016-07-17  32.714286    28  2016  1.304808\n",
              "498 2016-07-24  39.857143    29  2016  1.589700\n",
              "499 2016-07-31  22.250000    30  2016  0.887440\n",
              "500 2016-08-07  31.000000    31  2016  1.236433\n",
              "501 2016-08-14  31.714286    32  2016  1.264923\n",
              "502 2016-08-21  23.142857    33  2016  0.923052\n",
              "503 2016-08-28  29.142857    34  2016  1.162361\n",
              "504 2016-09-04  19.000000    35  2016  0.757814\n",
              "505 2016-09-11  23.714286    36  2016  0.945843\n",
              "506 2016-09-18  24.000000    37  2016  0.957239\n",
              "507 2016-09-25  14.285714    38  2016  0.569785\n",
              "508 2016-10-02  24.571429    39  2016  0.980030\n",
              "509 2016-10-09  15.142857    40  2016  0.603972\n",
              "510 2016-10-16  14.571429    41  2016  0.581181\n",
              "511 2016-10-23  31.428571    42  2016  1.253527\n",
              "512 2016-10-30  49.571429    43  2016  1.977154\n",
              "513 2016-11-06  21.142857    44  2016  0.843282\n",
              "514 2016-11-13  20.857143    45  2016  0.831886\n",
              "515 2016-11-20  20.000000    46  2016  0.797699\n",
              "516 2016-11-27  25.500000    47  2016  1.017066\n",
              "517 2016-12-04  18.000000    48  2016  0.717929\n",
              "518 2016-12-11  15.142857    49  2016  0.603972\n",
              "519 2016-12-18  13.571429    50  2016  0.541296\n",
              "520 2016-12-25   8.714286    51  2016  0.347569"
            ]
          },
          "metadata": {},
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "7DmbWEvxVnMB",
        "outputId": "fe62cec4-9f03-4f30-fe93-8cbab9226534"
      },
      "source": [
        "df17 = df[df['Year'] == 2017].dropna()\n",
        "df17['w_i'] = wi_calc(df, 2017)\n",
        "df17"
      ],
      "execution_count": 24,
      "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",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\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>Date</th>\n",
              "      <th>Conc</th>\n",
              "      <th>Week</th>\n",
              "      <th>Year</th>\n",
              "      <th>w_i</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>521</th>\n",
              "      <td>2017-01-01</td>\n",
              "      <td>23.857143</td>\n",
              "      <td>52</td>\n",
              "      <td>2017</td>\n",
              "      <td>1.470632</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>522</th>\n",
              "      <td>2017-01-08</td>\n",
              "      <td>12.000000</td>\n",
              "      <td>1</td>\n",
              "      <td>2017</td>\n",
              "      <td>0.739719</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>523</th>\n",
              "      <td>2017-01-15</td>\n",
              "      <td>9.857143</td>\n",
              "      <td>2</td>\n",
              "      <td>2017</td>\n",
              "      <td>0.607626</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>524</th>\n",
              "      <td>2017-01-22</td>\n",
              "      <td>15.428571</td>\n",
              "      <td>3</td>\n",
              "      <td>2017</td>\n",
              "      <td>0.951068</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>525</th>\n",
              "      <td>2017-01-29</td>\n",
              "      <td>13.857143</td>\n",
              "      <td>4</td>\n",
              "      <td>2017</td>\n",
              "      <td>0.854200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>526</th>\n",
              "      <td>2017-02-05</td>\n",
              "      <td>12.857143</td>\n",
              "      <td>5</td>\n",
              "      <td>2017</td>\n",
              "      <td>0.792556</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>527</th>\n",
              "      <td>2017-02-12</td>\n",
              "      <td>15.714286</td>\n",
              "      <td>6</td>\n",
              "      <td>2017</td>\n",
              "      <td>0.968680</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>528</th>\n",
              "      <td>2017-02-19</td>\n",
              "      <td>25.142857</td>\n",
              "      <td>7</td>\n",
              "      <td>2017</td>\n",
              "      <td>1.549888</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>529</th>\n",
              "      <td>2017-02-26</td>\n",
              "      <td>10.142857</td>\n",
              "      <td>8</td>\n",
              "      <td>2017</td>\n",
              "      <td>0.625239</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>530</th>\n",
              "      <td>2017-03-05</td>\n",
              "      <td>32.142857</td>\n",
              "      <td>9</td>\n",
              "      <td>2017</td>\n",
              "      <td>1.981391</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>531</th>\n",
              "      <td>2017-03-12</td>\n",
              "      <td>38.571429</td>\n",
              "      <td>10</td>\n",
              "      <td>2017</td>\n",
              "      <td>2.377669</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>532</th>\n",
              "      <td>2017-03-19</td>\n",
              "      <td>15.428571</td>\n",
              "      <td>11</td>\n",
              "      <td>2017</td>\n",
              "      <td>0.951068</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>533</th>\n",
              "      <td>2017-03-26</td>\n",
              "      <td>15.857143</td>\n",
              "      <td>12</td>\n",
              "      <td>2017</td>\n",
              "      <td>0.977486</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>534</th>\n",
              "      <td>2017-04-02</td>\n",
              "      <td>20.666667</td>\n",
              "      <td>13</td>\n",
              "      <td>2017</td>\n",
              "      <td>1.273961</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>535</th>\n",
              "      <td>2017-04-09</td>\n",
              "      <td>11.571429</td>\n",
              "      <td>14</td>\n",
              "      <td>2017</td>\n",
              "      <td>0.713301</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>536</th>\n",
              "      <td>2017-04-16</td>\n",
              "      <td>8.857143</td>\n",
              "      <td>15</td>\n",
              "      <td>2017</td>\n",
              "      <td>0.545983</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>537</th>\n",
              "      <td>2017-04-23</td>\n",
              "      <td>13.000000</td>\n",
              "      <td>16</td>\n",
              "      <td>2017</td>\n",
              "      <td>0.801362</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>538</th>\n",
              "      <td>2017-04-30</td>\n",
              "      <td>24.571429</td>\n",
              "      <td>17</td>\n",
              "      <td>2017</td>\n",
              "      <td>1.514663</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>539</th>\n",
              "      <td>2017-05-07</td>\n",
              "      <td>17.857143</td>\n",
              "      <td>18</td>\n",
              "      <td>2017</td>\n",
              "      <td>1.100773</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>540</th>\n",
              "      <td>2017-05-14</td>\n",
              "      <td>37.857143</td>\n",
              "      <td>19</td>\n",
              "      <td>2017</td>\n",
              "      <td>2.333638</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>541</th>\n",
              "      <td>2017-05-21</td>\n",
              "      <td>24.428571</td>\n",
              "      <td>20</td>\n",
              "      <td>2017</td>\n",
              "      <td>1.505857</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>542</th>\n",
              "      <td>2017-05-28</td>\n",
              "      <td>14.571429</td>\n",
              "      <td>21</td>\n",
              "      <td>2017</td>\n",
              "      <td>0.898230</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>543</th>\n",
              "      <td>2017-06-04</td>\n",
              "      <td>21.285714</td>\n",
              "      <td>22</td>\n",
              "      <td>2017</td>\n",
              "      <td>1.312121</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>544</th>\n",
              "      <td>2017-06-11</td>\n",
              "      <td>24.142857</td>\n",
              "      <td>23</td>\n",
              "      <td>2017</td>\n",
              "      <td>1.488245</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>545</th>\n",
              "      <td>2017-06-18</td>\n",
              "      <td>16.285714</td>\n",
              "      <td>24</td>\n",
              "      <td>2017</td>\n",
              "      <td>1.003905</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>546</th>\n",
              "      <td>2017-06-25</td>\n",
              "      <td>18.000000</td>\n",
              "      <td>25</td>\n",
              "      <td>2017</td>\n",
              "      <td>1.109579</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>547</th>\n",
              "      <td>2017-07-02</td>\n",
              "      <td>17.833333</td>\n",
              "      <td>26</td>\n",
              "      <td>2017</td>\n",
              "      <td>1.099305</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>548</th>\n",
              "      <td>2017-07-09</td>\n",
              "      <td>11.142857</td>\n",
              "      <td>27</td>\n",
              "      <td>2017</td>\n",
              "      <td>0.686882</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>549</th>\n",
              "      <td>2017-07-16</td>\n",
              "      <td>8.714286</td>\n",
              "      <td>28</td>\n",
              "      <td>2017</td>\n",
              "      <td>0.537177</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>550</th>\n",
              "      <td>2017-07-23</td>\n",
              "      <td>19.285714</td>\n",
              "      <td>29</td>\n",
              "      <td>2017</td>\n",
              "      <td>1.188834</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>551</th>\n",
              "      <td>2017-07-30</td>\n",
              "      <td>15.571429</td>\n",
              "      <td>30</td>\n",
              "      <td>2017</td>\n",
              "      <td>0.959874</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>552</th>\n",
              "      <td>2017-08-06</td>\n",
              "      <td>12.714286</td>\n",
              "      <td>31</td>\n",
              "      <td>2017</td>\n",
              "      <td>0.783750</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>553</th>\n",
              "      <td>2017-08-13</td>\n",
              "      <td>13.428571</td>\n",
              "      <td>32</td>\n",
              "      <td>2017</td>\n",
              "      <td>0.827781</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>554</th>\n",
              "      <td>2017-08-20</td>\n",
              "      <td>28.000000</td>\n",
              "      <td>33</td>\n",
              "      <td>2017</td>\n",
              "      <td>1.726011</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>555</th>\n",
              "      <td>2017-08-27</td>\n",
              "      <td>8.428571</td>\n",
              "      <td>34</td>\n",
              "      <td>2017</td>\n",
              "      <td>0.519565</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>556</th>\n",
              "      <td>2017-09-03</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>35</td>\n",
              "      <td>2017</td>\n",
              "      <td>0.616433</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>557</th>\n",
              "      <td>2017-09-10</td>\n",
              "      <td>14.142857</td>\n",
              "      <td>36</td>\n",
              "      <td>2017</td>\n",
              "      <td>0.871812</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>558</th>\n",
              "      <td>2017-09-17</td>\n",
              "      <td>15.857143</td>\n",
              "      <td>37</td>\n",
              "      <td>2017</td>\n",
              "      <td>0.977486</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>559</th>\n",
              "      <td>2017-09-24</td>\n",
              "      <td>13.428571</td>\n",
              "      <td>38</td>\n",
              "      <td>2017</td>\n",
              "      <td>0.827781</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>560</th>\n",
              "      <td>2017-10-01</td>\n",
              "      <td>14.714286</td>\n",
              "      <td>39</td>\n",
              "      <td>2017</td>\n",
              "      <td>0.907037</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>561</th>\n",
              "      <td>2017-10-08</td>\n",
              "      <td>13.571429</td>\n",
              "      <td>40</td>\n",
              "      <td>2017</td>\n",
              "      <td>0.836587</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>562</th>\n",
              "      <td>2017-10-15</td>\n",
              "      <td>10.571429</td>\n",
              "      <td>41</td>\n",
              "      <td>2017</td>\n",
              "      <td>0.651657</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>563</th>\n",
              "      <td>2017-10-22</td>\n",
              "      <td>9.000000</td>\n",
              "      <td>42</td>\n",
              "      <td>2017</td>\n",
              "      <td>0.554789</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>564</th>\n",
              "      <td>2017-10-29</td>\n",
              "      <td>15.000000</td>\n",
              "      <td>43</td>\n",
              "      <td>2017</td>\n",
              "      <td>0.924649</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>565</th>\n",
              "      <td>2017-11-05</td>\n",
              "      <td>15.571429</td>\n",
              "      <td>44</td>\n",
              "      <td>2017</td>\n",
              "      <td>0.959874</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>566</th>\n",
              "      <td>2017-11-12</td>\n",
              "      <td>16.000000</td>\n",
              "      <td>45</td>\n",
              "      <td>2017</td>\n",
              "      <td>0.986292</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>567</th>\n",
              "      <td>2017-11-19</td>\n",
              "      <td>15.714286</td>\n",
              "      <td>46</td>\n",
              "      <td>2017</td>\n",
              "      <td>0.968680</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>568</th>\n",
              "      <td>2017-11-26</td>\n",
              "      <td>14.857143</td>\n",
              "      <td>47</td>\n",
              "      <td>2017</td>\n",
              "      <td>0.915843</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>569</th>\n",
              "      <td>2017-12-03</td>\n",
              "      <td>9.285714</td>\n",
              "      <td>48</td>\n",
              "      <td>2017</td>\n",
              "      <td>0.572402</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>570</th>\n",
              "      <td>2017-12-10</td>\n",
              "      <td>9.857143</td>\n",
              "      <td>49</td>\n",
              "      <td>2017</td>\n",
              "      <td>0.607626</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>571</th>\n",
              "      <td>2017-12-17</td>\n",
              "      <td>13.857143</td>\n",
              "      <td>50</td>\n",
              "      <td>2017</td>\n",
              "      <td>0.854200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>572</th>\n",
              "      <td>2017-12-24</td>\n",
              "      <td>7.285714</td>\n",
              "      <td>51</td>\n",
              "      <td>2017</td>\n",
              "      <td>0.449115</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>573</th>\n",
              "      <td>2017-12-31</td>\n",
              "      <td>12.000000</td>\n",
              "      <td>52</td>\n",
              "      <td>2017</td>\n",
              "      <td>0.739719</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "          Date       Conc  Week  Year       w_i\n",
              "521 2017-01-01  23.857143    52  2017  1.470632\n",
              "522 2017-01-08  12.000000     1  2017  0.739719\n",
              "523 2017-01-15   9.857143     2  2017  0.607626\n",
              "524 2017-01-22  15.428571     3  2017  0.951068\n",
              "525 2017-01-29  13.857143     4  2017  0.854200\n",
              "526 2017-02-05  12.857143     5  2017  0.792556\n",
              "527 2017-02-12  15.714286     6  2017  0.968680\n",
              "528 2017-02-19  25.142857     7  2017  1.549888\n",
              "529 2017-02-26  10.142857     8  2017  0.625239\n",
              "530 2017-03-05  32.142857     9  2017  1.981391\n",
              "531 2017-03-12  38.571429    10  2017  2.377669\n",
              "532 2017-03-19  15.428571    11  2017  0.951068\n",
              "533 2017-03-26  15.857143    12  2017  0.977486\n",
              "534 2017-04-02  20.666667    13  2017  1.273961\n",
              "535 2017-04-09  11.571429    14  2017  0.713301\n",
              "536 2017-04-16   8.857143    15  2017  0.545983\n",
              "537 2017-04-23  13.000000    16  2017  0.801362\n",
              "538 2017-04-30  24.571429    17  2017  1.514663\n",
              "539 2017-05-07  17.857143    18  2017  1.100773\n",
              "540 2017-05-14  37.857143    19  2017  2.333638\n",
              "541 2017-05-21  24.428571    20  2017  1.505857\n",
              "542 2017-05-28  14.571429    21  2017  0.898230\n",
              "543 2017-06-04  21.285714    22  2017  1.312121\n",
              "544 2017-06-11  24.142857    23  2017  1.488245\n",
              "545 2017-06-18  16.285714    24  2017  1.003905\n",
              "546 2017-06-25  18.000000    25  2017  1.109579\n",
              "547 2017-07-02  17.833333    26  2017  1.099305\n",
              "548 2017-07-09  11.142857    27  2017  0.686882\n",
              "549 2017-07-16   8.714286    28  2017  0.537177\n",
              "550 2017-07-23  19.285714    29  2017  1.188834\n",
              "551 2017-07-30  15.571429    30  2017  0.959874\n",
              "552 2017-08-06  12.714286    31  2017  0.783750\n",
              "553 2017-08-13  13.428571    32  2017  0.827781\n",
              "554 2017-08-20  28.000000    33  2017  1.726011\n",
              "555 2017-08-27   8.428571    34  2017  0.519565\n",
              "556 2017-09-03  10.000000    35  2017  0.616433\n",
              "557 2017-09-10  14.142857    36  2017  0.871812\n",
              "558 2017-09-17  15.857143    37  2017  0.977486\n",
              "559 2017-09-24  13.428571    38  2017  0.827781\n",
              "560 2017-10-01  14.714286    39  2017  0.907037\n",
              "561 2017-10-08  13.571429    40  2017  0.836587\n",
              "562 2017-10-15  10.571429    41  2017  0.651657\n",
              "563 2017-10-22   9.000000    42  2017  0.554789\n",
              "564 2017-10-29  15.000000    43  2017  0.924649\n",
              "565 2017-11-05  15.571429    44  2017  0.959874\n",
              "566 2017-11-12  16.000000    45  2017  0.986292\n",
              "567 2017-11-19  15.714286    46  2017  0.968680\n",
              "568 2017-11-26  14.857143    47  2017  0.915843\n",
              "569 2017-12-03   9.285714    48  2017  0.572402\n",
              "570 2017-12-10   9.857143    49  2017  0.607626\n",
              "571 2017-12-17  13.857143    50  2017  0.854200\n",
              "572 2017-12-24   7.285714    51  2017  0.449115\n",
              "573 2017-12-31  12.000000    52  2017  0.739719"
            ]
          },
          "metadata": {},
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "TROGfSuiVseL",
        "outputId": "ede7cde4-93db-4d31-808c-24ee076569bb"
      },
      "source": [
        "df18 = df[df['Year'] == 2018].dropna()\n",
        "df18['w_i'] = wi_calc(df, 2018)\n",
        "df18"
      ],
      "execution_count": 25,
      "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",
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              "    }\n",
              "\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Date</th>\n",
              "      <th>Conc</th>\n",
              "      <th>Week</th>\n",
              "      <th>Year</th>\n",
              "      <th>w_i</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>574</th>\n",
              "      <td>2018-01-07</td>\n",
              "      <td>9.571429</td>\n",
              "      <td>1</td>\n",
              "      <td>2018</td>\n",
              "      <td>0.470366</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>575</th>\n",
              "      <td>2018-01-14</td>\n",
              "      <td>16.000000</td>\n",
              "      <td>2</td>\n",
              "      <td>2018</td>\n",
              "      <td>0.786283</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>576</th>\n",
              "      <td>2018-01-21</td>\n",
              "      <td>17.428571</td>\n",
              "      <td>3</td>\n",
              "      <td>2018</td>\n",
              "      <td>0.856487</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>577</th>\n",
              "      <td>2018-01-28</td>\n",
              "      <td>33.857143</td>\n",
              "      <td>4</td>\n",
              "      <td>2018</td>\n",
              "      <td>1.663832</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>578</th>\n",
              "      <td>2018-02-04</td>\n",
              "      <td>29.428571</td>\n",
              "      <td>5</td>\n",
              "      <td>2018</td>\n",
              "      <td>1.446200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>579</th>\n",
              "      <td>2018-02-11</td>\n",
              "      <td>28.428571</td>\n",
              "      <td>6</td>\n",
              "      <td>2018</td>\n",
              "      <td>1.397057</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>580</th>\n",
              "      <td>2018-02-18</td>\n",
              "      <td>40.857143</td>\n",
              "      <td>7</td>\n",
              "      <td>2018</td>\n",
              "      <td>2.007830</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>581</th>\n",
              "      <td>2018-02-25</td>\n",
              "      <td>18.571429</td>\n",
              "      <td>8</td>\n",
              "      <td>2018</td>\n",
              "      <td>0.912650</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>582</th>\n",
              "      <td>2018-03-04</td>\n",
              "      <td>16.428571</td>\n",
              "      <td>9</td>\n",
              "      <td>2018</td>\n",
              "      <td>0.807344</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>583</th>\n",
              "      <td>2018-03-11</td>\n",
              "      <td>31.285714</td>\n",
              "      <td>10</td>\n",
              "      <td>2018</td>\n",
              "      <td>1.537465</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>584</th>\n",
              "      <td>2018-03-18</td>\n",
              "      <td>27.857143</td>\n",
              "      <td>11</td>\n",
              "      <td>2018</td>\n",
              "      <td>1.368975</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>585</th>\n",
              "      <td>2018-03-25</td>\n",
              "      <td>18.428571</td>\n",
              "      <td>12</td>\n",
              "      <td>2018</td>\n",
              "      <td>0.905630</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>586</th>\n",
              "      <td>2018-04-01</td>\n",
              "      <td>22.571429</td>\n",
              "      <td>13</td>\n",
              "      <td>2018</td>\n",
              "      <td>1.109221</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>587</th>\n",
              "      <td>2018-04-08</td>\n",
              "      <td>16.000000</td>\n",
              "      <td>14</td>\n",
              "      <td>2018</td>\n",
              "      <td>0.786283</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>588</th>\n",
              "      <td>2018-04-15</td>\n",
              "      <td>27.571429</td>\n",
              "      <td>15</td>\n",
              "      <td>2018</td>\n",
              "      <td>1.354935</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>589</th>\n",
              "      <td>2018-04-22</td>\n",
              "      <td>23.857143</td>\n",
              "      <td>16</td>\n",
              "      <td>2018</td>\n",
              "      <td>1.172404</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>590</th>\n",
              "      <td>2018-04-29</td>\n",
              "      <td>15.142857</td>\n",
              "      <td>17</td>\n",
              "      <td>2018</td>\n",
              "      <td>0.744161</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>591</th>\n",
              "      <td>2018-05-06</td>\n",
              "      <td>24.142857</td>\n",
              "      <td>18</td>\n",
              "      <td>2018</td>\n",
              "      <td>1.186445</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>592</th>\n",
              "      <td>2018-05-13</td>\n",
              "      <td>19.571429</td>\n",
              "      <td>19</td>\n",
              "      <td>2018</td>\n",
              "      <td>0.961793</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>593</th>\n",
              "      <td>2018-05-20</td>\n",
              "      <td>15.571429</td>\n",
              "      <td>20</td>\n",
              "      <td>2018</td>\n",
              "      <td>0.765222</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>594</th>\n",
              "      <td>2018-05-27</td>\n",
              "      <td>13.000000</td>\n",
              "      <td>21</td>\n",
              "      <td>2018</td>\n",
              "      <td>0.638855</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>595</th>\n",
              "      <td>2018-06-03</td>\n",
              "      <td>15.857143</td>\n",
              "      <td>22</td>\n",
              "      <td>2018</td>\n",
              "      <td>0.779263</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>596</th>\n",
              "      <td>2018-06-10</td>\n",
              "      <td>10.714286</td>\n",
              "      <td>23</td>\n",
              "      <td>2018</td>\n",
              "      <td>0.526529</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>597</th>\n",
              "      <td>2018-06-17</td>\n",
              "      <td>14.142857</td>\n",
              "      <td>24</td>\n",
              "      <td>2018</td>\n",
              "      <td>0.695018</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>598</th>\n",
              "      <td>2018-06-24</td>\n",
              "      <td>30.000000</td>\n",
              "      <td>25</td>\n",
              "      <td>2018</td>\n",
              "      <td>1.474281</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>599</th>\n",
              "      <td>2018-07-01</td>\n",
              "      <td>15.142857</td>\n",
              "      <td>26</td>\n",
              "      <td>2018</td>\n",
              "      <td>0.744161</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>600</th>\n",
              "      <td>2018-07-08</td>\n",
              "      <td>14.142857</td>\n",
              "      <td>27</td>\n",
              "      <td>2018</td>\n",
              "      <td>0.695018</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>601</th>\n",
              "      <td>2018-07-15</td>\n",
              "      <td>10.857143</td>\n",
              "      <td>28</td>\n",
              "      <td>2018</td>\n",
              "      <td>0.533549</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>602</th>\n",
              "      <td>2018-07-22</td>\n",
              "      <td>15.428571</td>\n",
              "      <td>29</td>\n",
              "      <td>2018</td>\n",
              "      <td>0.758202</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>603</th>\n",
              "      <td>2018-07-29</td>\n",
              "      <td>21.142857</td>\n",
              "      <td>30</td>\n",
              "      <td>2018</td>\n",
              "      <td>1.039017</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>604</th>\n",
              "      <td>2018-08-05</td>\n",
              "      <td>19.571429</td>\n",
              "      <td>31</td>\n",
              "      <td>2018</td>\n",
              "      <td>0.961793</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>605</th>\n",
              "      <td>2018-08-12</td>\n",
              "      <td>15.428571</td>\n",
              "      <td>32</td>\n",
              "      <td>2018</td>\n",
              "      <td>0.758202</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>606</th>\n",
              "      <td>2018-08-19</td>\n",
              "      <td>15.857143</td>\n",
              "      <td>33</td>\n",
              "      <td>2018</td>\n",
              "      <td>0.779263</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>607</th>\n",
              "      <td>2018-08-26</td>\n",
              "      <td>8.571429</td>\n",
              "      <td>34</td>\n",
              "      <td>2018</td>\n",
              "      <td>0.421223</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>608</th>\n",
              "      <td>2018-09-02</td>\n",
              "      <td>15.428571</td>\n",
              "      <td>35</td>\n",
              "      <td>2018</td>\n",
              "      <td>0.758202</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>609</th>\n",
              "      <td>2018-09-09</td>\n",
              "      <td>27.142857</td>\n",
              "      <td>36</td>\n",
              "      <td>2018</td>\n",
              "      <td>1.333873</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>610</th>\n",
              "      <td>2018-09-16</td>\n",
              "      <td>16.714286</td>\n",
              "      <td>37</td>\n",
              "      <td>2018</td>\n",
              "      <td>0.821385</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>611</th>\n",
              "      <td>2018-09-23</td>\n",
              "      <td>20.714286</td>\n",
              "      <td>38</td>\n",
              "      <td>2018</td>\n",
              "      <td>1.017956</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>612</th>\n",
              "      <td>2018-09-30</td>\n",
              "      <td>15.571429</td>\n",
              "      <td>39</td>\n",
              "      <td>2018</td>\n",
              "      <td>0.765222</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>613</th>\n",
              "      <td>2018-10-07</td>\n",
              "      <td>21.571429</td>\n",
              "      <td>40</td>\n",
              "      <td>2018</td>\n",
              "      <td>1.060078</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>614</th>\n",
              "      <td>2018-10-14</td>\n",
              "      <td>21.714286</td>\n",
              "      <td>41</td>\n",
              "      <td>2018</td>\n",
              "      <td>1.067099</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>615</th>\n",
              "      <td>2018-10-21</td>\n",
              "      <td>29.857143</td>\n",
              "      <td>42</td>\n",
              "      <td>2018</td>\n",
              "      <td>1.467261</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>616</th>\n",
              "      <td>2018-10-28</td>\n",
              "      <td>17.285714</td>\n",
              "      <td>43</td>\n",
              "      <td>2018</td>\n",
              "      <td>0.849467</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>617</th>\n",
              "      <td>2018-11-04</td>\n",
              "      <td>34.142857</td>\n",
              "      <td>44</td>\n",
              "      <td>2018</td>\n",
              "      <td>1.677872</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>618</th>\n",
              "      <td>2018-11-11</td>\n",
              "      <td>14.571429</td>\n",
              "      <td>45</td>\n",
              "      <td>2018</td>\n",
              "      <td>0.716079</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>619</th>\n",
              "      <td>2018-11-18</td>\n",
              "      <td>38.857143</td>\n",
              "      <td>46</td>\n",
              "      <td>2018</td>\n",
              "      <td>1.909545</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>620</th>\n",
              "      <td>2018-11-25</td>\n",
              "      <td>28.000000</td>\n",
              "      <td>47</td>\n",
              "      <td>2018</td>\n",
              "      <td>1.375996</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>621</th>\n",
              "      <td>2018-12-02</td>\n",
              "      <td>16.285714</td>\n",
              "      <td>48</td>\n",
              "      <td>2018</td>\n",
              "      <td>0.800324</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>622</th>\n",
              "      <td>2018-12-09</td>\n",
              "      <td>16.857143</td>\n",
              "      <td>49</td>\n",
              "      <td>2018</td>\n",
              "      <td>0.828406</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>623</th>\n",
              "      <td>2018-12-16</td>\n",
              "      <td>22.142857</td>\n",
              "      <td>50</td>\n",
              "      <td>2018</td>\n",
              "      <td>1.088160</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>624</th>\n",
              "      <td>2018-12-23</td>\n",
              "      <td>15.571429</td>\n",
              "      <td>51</td>\n",
              "      <td>2018</td>\n",
              "      <td>0.765222</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>625</th>\n",
              "      <td>2018-12-30</td>\n",
              "      <td>13.285714</td>\n",
              "      <td>52</td>\n",
              "      <td>2018</td>\n",
              "      <td>0.652896</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "          Date       Conc  Week  Year       w_i\n",
              "574 2018-01-07   9.571429     1  2018  0.470366\n",
              "575 2018-01-14  16.000000     2  2018  0.786283\n",
              "576 2018-01-21  17.428571     3  2018  0.856487\n",
              "577 2018-01-28  33.857143     4  2018  1.663832\n",
              "578 2018-02-04  29.428571     5  2018  1.446200\n",
              "579 2018-02-11  28.428571     6  2018  1.397057\n",
              "580 2018-02-18  40.857143     7  2018  2.007830\n",
              "581 2018-02-25  18.571429     8  2018  0.912650\n",
              "582 2018-03-04  16.428571     9  2018  0.807344\n",
              "583 2018-03-11  31.285714    10  2018  1.537465\n",
              "584 2018-03-18  27.857143    11  2018  1.368975\n",
              "585 2018-03-25  18.428571    12  2018  0.905630\n",
              "586 2018-04-01  22.571429    13  2018  1.109221\n",
              "587 2018-04-08  16.000000    14  2018  0.786283\n",
              "588 2018-04-15  27.571429    15  2018  1.354935\n",
              "589 2018-04-22  23.857143    16  2018  1.172404\n",
              "590 2018-04-29  15.142857    17  2018  0.744161\n",
              "591 2018-05-06  24.142857    18  2018  1.186445\n",
              "592 2018-05-13  19.571429    19  2018  0.961793\n",
              "593 2018-05-20  15.571429    20  2018  0.765222\n",
              "594 2018-05-27  13.000000    21  2018  0.638855\n",
              "595 2018-06-03  15.857143    22  2018  0.779263\n",
              "596 2018-06-10  10.714286    23  2018  0.526529\n",
              "597 2018-06-17  14.142857    24  2018  0.695018\n",
              "598 2018-06-24  30.000000    25  2018  1.474281\n",
              "599 2018-07-01  15.142857    26  2018  0.744161\n",
              "600 2018-07-08  14.142857    27  2018  0.695018\n",
              "601 2018-07-15  10.857143    28  2018  0.533549\n",
              "602 2018-07-22  15.428571    29  2018  0.758202\n",
              "603 2018-07-29  21.142857    30  2018  1.039017\n",
              "604 2018-08-05  19.571429    31  2018  0.961793\n",
              "605 2018-08-12  15.428571    32  2018  0.758202\n",
              "606 2018-08-19  15.857143    33  2018  0.779263\n",
              "607 2018-08-26   8.571429    34  2018  0.421223\n",
              "608 2018-09-02  15.428571    35  2018  0.758202\n",
              "609 2018-09-09  27.142857    36  2018  1.333873\n",
              "610 2018-09-16  16.714286    37  2018  0.821385\n",
              "611 2018-09-23  20.714286    38  2018  1.017956\n",
              "612 2018-09-30  15.571429    39  2018  0.765222\n",
              "613 2018-10-07  21.571429    40  2018  1.060078\n",
              "614 2018-10-14  21.714286    41  2018  1.067099\n",
              "615 2018-10-21  29.857143    42  2018  1.467261\n",
              "616 2018-10-28  17.285714    43  2018  0.849467\n",
              "617 2018-11-04  34.142857    44  2018  1.677872\n",
              "618 2018-11-11  14.571429    45  2018  0.716079\n",
              "619 2018-11-18  38.857143    46  2018  1.909545\n",
              "620 2018-11-25  28.000000    47  2018  1.375996\n",
              "621 2018-12-02  16.285714    48  2018  0.800324\n",
              "622 2018-12-09  16.857143    49  2018  0.828406\n",
              "623 2018-12-16  22.142857    50  2018  1.088160\n",
              "624 2018-12-23  15.571429    51  2018  0.765222\n",
              "625 2018-12-30  13.285714    52  2018  0.652896"
            ]
          },
          "metadata": {},
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        },
        "id": "mpbiEnq4kley",
        "outputId": "8fa4ef7f-3fc7-40aa-f891-02a91355d5a7"
      },
      "source": [
        "df_uni = df07.append(df08, sort = False)\n",
        "df_uni"
      ],
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "    .dataframe tbody tr th:only-of-type {\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Date</th>\n",
              "      <th>Conc</th>\n",
              "      <th>Week</th>\n",
              "      <th>Year</th>\n",
              "      <th>w_i</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2007-01-07</td>\n",
              "      <td>8.285714</td>\n",
              "      <td>1</td>\n",
              "      <td>2007</td>\n",
              "      <td>0.462986</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2007-01-14</td>\n",
              "      <td>6.428571</td>\n",
              "      <td>2</td>\n",
              "      <td>2007</td>\n",
              "      <td>0.359213</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2007-01-21</td>\n",
              "      <td>8.857143</td>\n",
              "      <td>3</td>\n",
              "      <td>2007</td>\n",
              "      <td>0.494916</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2007-01-28</td>\n",
              "      <td>9.000000</td>\n",
              "      <td>4</td>\n",
              "      <td>2007</td>\n",
              "      <td>0.502899</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2007-02-04</td>\n",
              "      <td>10.333333</td>\n",
              "      <td>5</td>\n",
              "      <td>2007</td>\n",
              "      <td>0.577402</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>99</th>\n",
              "      <td>2008-11-30</td>\n",
              "      <td>8.285714</td>\n",
              "      <td>48</td>\n",
              "      <td>2008</td>\n",
              "      <td>0.492381</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>100</th>\n",
              "      <td>2008-12-07</td>\n",
              "      <td>13.285714</td>\n",
              "      <td>49</td>\n",
              "      <td>2008</td>\n",
              "      <td>0.789508</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>101</th>\n",
              "      <td>2008-12-14</td>\n",
              "      <td>10.857143</td>\n",
              "      <td>50</td>\n",
              "      <td>2008</td>\n",
              "      <td>0.645189</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>102</th>\n",
              "      <td>2008-12-21</td>\n",
              "      <td>13.571429</td>\n",
              "      <td>51</td>\n",
              "      <td>2008</td>\n",
              "      <td>0.806487</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>103</th>\n",
              "      <td>2008-12-28</td>\n",
              "      <td>13.857143</td>\n",
              "      <td>52</td>\n",
              "      <td>2008</td>\n",
              "      <td>0.823465</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>104 rows × 5 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "          Date       Conc  Week  Year       w_i\n",
              "0   2007-01-07   8.285714     1  2007  0.462986\n",
              "1   2007-01-14   6.428571     2  2007  0.359213\n",
              "2   2007-01-21   8.857143     3  2007  0.494916\n",
              "3   2007-01-28   9.000000     4  2007  0.502899\n",
              "4   2007-02-04  10.333333     5  2007  0.577402\n",
              "..         ...        ...   ...   ...       ...\n",
              "99  2008-11-30   8.285714    48  2008  0.492381\n",
              "100 2008-12-07  13.285714    49  2008  0.789508\n",
              "101 2008-12-14  10.857143    50  2008  0.645189\n",
              "102 2008-12-21  13.571429    51  2008  0.806487\n",
              "103 2008-12-28  13.857143    52  2008  0.823465\n",
              "\n",
              "[104 rows x 5 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        },
        "id": "hEtPyps0kley",
        "outputId": "9cc7312c-8d40-4303-dd74-50ad6f0e386f"
      },
      "source": [
        "df_uni1 = df_uni.append(df09, sort = False)\n",
        "df_uni2 = df_uni1.append(df10, sort = False)\n",
        "df_uni3 = df_uni2.append(df11, sort = False)\n",
        "df_uni4 = df_uni3.append(df12, sort = False)\n",
        "df_uni5 = df_uni4.append(df13, sort = False)\n",
        "df_uni6 = df_uni5.append(df14, sort = False)\n",
        "df_uni7 = df_uni6.append(df15, sort = False)\n",
        "df_uni8 = df_uni7.append(df16, sort = False)\n",
        "df_uni9 = df_uni8.append(df17, sort = False)\n",
        "df_uni10 = df_uni9.append(df18, sort = False)\n",
        "df_uni10"
      ],
      "execution_count": 27,
      "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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              "      <th>Conc</th>\n",
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              "      <th>Year</th>\n",
              "      <th>w_i</th>\n",
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              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2007-01-07</td>\n",
              "      <td>8.285714</td>\n",
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              "      <td>2007</td>\n",
              "      <td>0.462986</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2007-01-14</td>\n",
              "      <td>6.428571</td>\n",
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              "      <td>2007</td>\n",
              "      <td>0.359213</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2007-01-21</td>\n",
              "      <td>8.857143</td>\n",
              "      <td>3</td>\n",
              "      <td>2007</td>\n",
              "      <td>0.494916</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2007-01-28</td>\n",
              "      <td>9.000000</td>\n",
              "      <td>4</td>\n",
              "      <td>2007</td>\n",
              "      <td>0.502899</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2007-02-04</td>\n",
              "      <td>10.333333</td>\n",
              "      <td>5</td>\n",
              "      <td>2007</td>\n",
              "      <td>0.577402</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>621</th>\n",
              "      <td>2018-12-02</td>\n",
              "      <td>16.285714</td>\n",
              "      <td>48</td>\n",
              "      <td>2018</td>\n",
              "      <td>0.800324</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>622</th>\n",
              "      <td>2018-12-09</td>\n",
              "      <td>16.857143</td>\n",
              "      <td>49</td>\n",
              "      <td>2018</td>\n",
              "      <td>0.828406</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>623</th>\n",
              "      <td>2018-12-16</td>\n",
              "      <td>22.142857</td>\n",
              "      <td>50</td>\n",
              "      <td>2018</td>\n",
              "      <td>1.088160</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>624</th>\n",
              "      <td>2018-12-23</td>\n",
              "      <td>15.571429</td>\n",
              "      <td>51</td>\n",
              "      <td>2018</td>\n",
              "      <td>0.765222</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>625</th>\n",
              "      <td>2018-12-30</td>\n",
              "      <td>13.285714</td>\n",
              "      <td>52</td>\n",
              "      <td>2018</td>\n",
              "      <td>0.652896</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>588 rows × 5 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "          Date       Conc  Week  Year       w_i\n",
              "0   2007-01-07   8.285714     1  2007  0.462986\n",
              "1   2007-01-14   6.428571     2  2007  0.359213\n",
              "2   2007-01-21   8.857143     3  2007  0.494916\n",
              "3   2007-01-28   9.000000     4  2007  0.502899\n",
              "4   2007-02-04  10.333333     5  2007  0.577402\n",
              "..         ...        ...   ...   ...       ...\n",
              "621 2018-12-02  16.285714    48  2018  0.800324\n",
              "622 2018-12-09  16.857143    49  2018  0.828406\n",
              "623 2018-12-16  22.142857    50  2018  1.088160\n",
              "624 2018-12-23  15.571429    51  2018  0.765222\n",
              "625 2018-12-30  13.285714    52  2018  0.652896\n",
              "\n",
              "[588 rows x 5 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "scrolled": true,
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        },
        "id": "AeuFg6Mmkley",
        "outputId": "0a2ddd4f-64ae-421f-ad2a-eaca6a65e19f"
      },
      "source": [
        "df_final=df_uni10.drop(columns = ['Week', 'Year'])\n",
        "df_final"
      ],
      "execution_count": 28,
      "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",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Date</th>\n",
              "      <th>Conc</th>\n",
              "      <th>w_i</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2007-01-07</td>\n",
              "      <td>8.285714</td>\n",
              "      <td>0.462986</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2007-01-14</td>\n",
              "      <td>6.428571</td>\n",
              "      <td>0.359213</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2007-01-21</td>\n",
              "      <td>8.857143</td>\n",
              "      <td>0.494916</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2007-01-28</td>\n",
              "      <td>9.000000</td>\n",
              "      <td>0.502899</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2007-02-04</td>\n",
              "      <td>10.333333</td>\n",
              "      <td>0.577402</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>621</th>\n",
              "      <td>2018-12-02</td>\n",
              "      <td>16.285714</td>\n",
              "      <td>0.800324</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>622</th>\n",
              "      <td>2018-12-09</td>\n",
              "      <td>16.857143</td>\n",
              "      <td>0.828406</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>623</th>\n",
              "      <td>2018-12-16</td>\n",
              "      <td>22.142857</td>\n",
              "      <td>1.088160</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>624</th>\n",
              "      <td>2018-12-23</td>\n",
              "      <td>15.571429</td>\n",
              "      <td>0.765222</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>625</th>\n",
              "      <td>2018-12-30</td>\n",
              "      <td>13.285714</td>\n",
              "      <td>0.652896</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>588 rows × 3 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "          Date       Conc       w_i\n",
              "0   2007-01-07   8.285714  0.462986\n",
              "1   2007-01-14   6.428571  0.359213\n",
              "2   2007-01-21   8.857143  0.494916\n",
              "3   2007-01-28   9.000000  0.502899\n",
              "4   2007-02-04  10.333333  0.577402\n",
              "..         ...        ...       ...\n",
              "621 2018-12-02  16.285714  0.800324\n",
              "622 2018-12-09  16.857143  0.828406\n",
              "623 2018-12-16  22.142857  1.088160\n",
              "624 2018-12-23  15.571429  0.765222\n",
              "625 2018-12-30  13.285714  0.652896\n",
              "\n",
              "[588 rows x 3 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7CVaeoCUklez"
      },
      "source": [
        "df_final.to_csv('/content/drive/MyDrive/Colab Notebooks/Data for JER/Weekly_index07-18_Mazyr.csv', index = False)"
      ],
      "execution_count": 29,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 384
        },
        "id": "GJX9G894klez",
        "outputId": "ffe56309-bb41-4156-f12d-46ea08e7d9d1"
      },
      "source": [
        "df_final.plot('Date',\n",
        "              'w_i',\n",
        "              figsize=(12,6),\n",
        "              marker = 'o',\n",
        "              markersize = 4,\n",
        "              mfc = 'white',        \n",
        "              color = '#169acf')"
      ],
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f5fffa69690>"
            ]
          },
          "metadata": {},
          "execution_count": 30
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 864x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gfRuwHftklez",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 595
        },
        "outputId": "f2efaa9c-3569-4684-9f31-fb93372b40fb"
      },
      "source": [
        "x = df_final['Date']\n",
        "y = df_final['w_i']\n",
        "dates = df_final.Date.dt.year\n",
        "\n",
        "fig = plt.figure(figsize = (16, 6), dpi = 100)\n",
        "ax = fig.add_axes()\n",
        "plt.plot(x, y, marker = 'o',\n",
        "         markersize = 3,\n",
        "         #label = 'Weekly index',\n",
        "         color = '#169acf')\n",
        "plt.xlabel('Date', fontsize = 18, fontstyle='oblique', fontweight = 'medium')\n",
        "plt.ylabel('Weekly index', fontsize = 18, fontstyle='oblique', fontweight = 'medium')\n",
        "plt.xticks(rotation = 45, fontsize = 14)\n",
        "plt.yticks(fontsize = 14)\n",
        "plt.grid(alpha = 0.5)\n",
        "#plt.legend(loc = 'upper right')\n",
        "plt.show()\n",
        "plt.savefig('/content/drive/MyDrive/Colab Notebooks/Data for JER/fig6.png',dpi = 300)"
      ],
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1600x600 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 0 Axes>"
            ]
          },
          "metadata": {}
        }
      ]
    }
  ]
}