data_features_preprocessing.ipynb

{
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  {
   "cell_type": "markdown",
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   "source": [
    "# Data Preprocessing\n",
    "\n",
    "This notebook explains how to prepare the data cleaned in section 1.1 for use in the naive model set.\n",
    "\n",
    "\n",
    "1. Problem Framing\n",
    "2. Data Manipulation\n",
    "\n",
    "\n",
    "\n",
    "## Supervised learning problem framing\n",
    "\n",
    "Data read from the file load_forecast_2016_2018 is in the format:\n",
    "\n",
    "|time |day_forecast|actual_load|\n",
    "|-----|------------|---------------|\n",
    "| 2016-01-01 00:00:00 | 23273.0 | 22431.0 |\n",
    "| 2016-01-01 01:00:00\t| 22495.0\t| 21632.0 |\n",
    "| 2016-01-01 02:00:00\t| 21272.0\t| 20357.0 |\n",
    "\n",
    "In this form it is easy to predict the next hour in advance. One wya to predict the next day would be to predict the same hour the next day i.e. jumping 24 values. According to the problem definition the goal is to predict the next 24 hours in advance. An easier way to do this is to create a window of calendar days consisting of 24 hour segments. That way each indivdual hour from day-1, is used to predict each hour of the current day.\n",
    "\n",
    "Isolating for only the actual_load, the data is reformatted into the following format\n",
    "\n",
    "\n",
    "| date | h00 | h01 | ... | h23 |\n",
    "|------|----|----|-----|-----|\n",
    "| 2016-01-01 | 22431.0 | 21632.0 | ... | 24000.0 |\n",
    "| 2016-01-01 | 22113.0 | 20515.0 | ... | 26029.0 |\n",
    "\n",
    "\n",
    "Therefore the naive problem becomes predicting the next day's loads at any given hour using the previous day's hourly loads. We have reduced a multiple input, multiple output problem into 24 univariate naive predictions.\n",
    "\n",
    "\n",
    "### Walk Forward Validation\n",
    "\n",
    "Using the above structure we can establish a walk forward method of predicting the next value. The table below shows how for each hour of the day, there is a separate model to predict the next day's predicted maximum load for the given hour. In this case ARIMA is a distinct statistical model for hours h0, h1, ... h23.\n",
    "\n",
    "| date | h00 | h01 | ... | h23 |\n",
    "|------|----|----|-----|-----|\n",
    "| 2016-01-01 | 22431.0 | 21632.0 | ... | 24000.0 |\n",
    "| |⌄⌄⌄⌄⌄|⌄⌄⌄⌄⌄|⌄⌄⌄⌄⌄|⌄⌄⌄⌄⌄|\n",
    "||ARIMA-h0|ARIMA-h1|...|ARIMA-h23|\n",
    "| |⌄⌄⌄⌄⌄|⌄⌄⌄⌄⌄|⌄⌄⌄⌄⌄|⌄⌄⌄⌄⌄|\n",
    "| 2016-01-01 | 22113.0 | 20515.0 | ... | 26029.0 |\n",
    "\n",
    "### Feature engineering (Windowing)\n",
    "\n",
    "To prepare the data for the walk forward validation model structure the data is windowed per day. This means hourly data at time t is shifted to become time t-1. The model is then fed data from time t-1, and compared to time t in a supervised learning problem.\n",
    "\n",
    "Generalizing this, more features are defined in a similar way. Data is shifted by x steps, and the last x steps of the data set are removed. The result of a similar transform is shown below.\n",
    "\n",
    "| date | h00 | h01 | ... | h23 |\n",
    "|------|----|----|-----|-----|\n",
    "| t | 22431.0 | 21632.0 | ... | 24000.0 |\n",
    "\n",
    "\n",
    "#### Days shifted by x steps\n",
    "\n",
    "| Date | t | t-1 | t-2 | t-3 |\n",
    "|---|---|---|---|---|\n",
    "| Day 1:| 0 | Nan | Nan | Nan |\n",
    "| Day 2:| 1 | 0 | Nan | Nan |   \n",
    "| Day 3:| 2 | 1 | 0 | Nan |\n",
    "| Day 4:| 3 | 2 | 1 | 0 |\n",
    "| Day 5:| 4 | 3 | 2 | 1 |\n",
    "| Day 6:| 5 | 4 | 3 | 2 |\n",
    "| Day 7:| 6 | 5 | 4 | 3 |\n",
    "\n",
    "\n",
    "\n",
    "#### Days shifted and truncated\n",
    "| Date | t | t-1 | t-2 | t-3 |\n",
    "|---|---|---|---|---|\n",
    "| Day 4:| 3 | 2 | 1 | 0 |\n",
    "| Day 5:| 4 | 3 | 2 | 1 |\n",
    "| Day 6:| 5 | 4 | 3 | 2 |\n",
    "| Day 7:| 6 | 5 | 4 | 3 |\n",
    "\n",
    "Where each set of t represents a vector of length (number of days, 24 hours).\n",
    "\n",
    "\n",
    "\n",
    "## Summary of functions\n",
    "- transform_to_windows\n",
    "    - converts the data from row data into windowed rows where each row is a day with 24 columns representing each hour of the day.\n",
    "- plot_hour\n",
    "    - helper function to view series data\n",
    "- shift_by_days\n",
    "    - helper function to make_shifted_features. calls pd.shift on the input dataframe to shift the data x number of rows.\n",
    "- make_shifted_features\n",
    "    - calls shift_by_days for a list of shift values.\n",
    "    - shortenes the resulting dataframe\n",
    "- trim_length\n",
    "    - helper function to make_shifted features. Shortens the length of the final dataframe of fatures so there are no NaNs.\n",
    "- rename_cols\n",
    "    - Helper function used in make_shifted_features. Labels the columns of the shifted dataframes with an appropriate label indicating the shift value.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "#read in the dataframe\n",
    "data = pd.read_csv('./data/cleaned_data/load_forecast_2016_2018.csv', parse_dates=True, index_col='time')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Window transforms\n",
    "\n",
    "Desribe function here"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "#a function to transform\n",
    "def transform_to_windows(data, load_type='actual_load'):\n",
    "    \"\"\"\n",
    "    Input\n",
    "    \n",
    "    Output\n",
    "    \n",
    "    \"\"\"\n",
    "    \n",
    "    #from the original datetime index create new columns with each of the year, month, day, and hour.\n",
    "    data.loc[:,'year'] = data.index.year\n",
    "    data.loc[:,'month'] = data.index.month\n",
    "    data.loc[:,'day'] = data.index.day\n",
    "    data.loc[:,'hours'] = data.index.hour\n",
    "    \n",
    "    #construct datetimes from the split year, month, day columns\n",
    "    data.loc[:,'date'] = pd.to_datetime(data.loc[:,['year', 'month', 'day']], format='%Y-%m-%d', errors='ignore')\n",
    "    \n",
    "    #set the index to dates only\n",
    "    data = data.set_index(pd.DatetimeIndex(data['date']))\n",
    "    \n",
    "    #drop non target columns \n",
    "    data = data.loc[:,[load_type, 'hours']]\n",
    "    \n",
    "    #pivot the table into the format Date h0, h1, ...h23\n",
    "    data = data.pivot(columns='hours', values=load_type)\n",
    "    \n",
    "    return data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>hours</th>\n",
       "      <th>0</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2016-01-01</th>\n",
       "      <td>22431.0</td>\n",
       "      <td>21632.0</td>\n",
       "      <td>20357.0</td>\n",
       "      <td>19152.0</td>\n",
       "      <td>18310.0</td>\n",
       "      <td>18054.0</td>\n",
       "      <td>18234.0</td>\n",
       "      <td>18596.0</td>\n",
       "      <td>18541.0</td>\n",
       "      <td>18942.0</td>\n",
       "      <td>...</td>\n",
       "      <td>23265.0</td>\n",
       "      <td>22061.0</td>\n",
       "      <td>21481.0</td>\n",
       "      <td>21830.0</td>\n",
       "      <td>24291.0</td>\n",
       "      <td>25234.0</td>\n",
       "      <td>25881.0</td>\n",
       "      <td>26149.0</td>\n",
       "      <td>25610.0</td>\n",
       "      <td>24000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-02</th>\n",
       "      <td>24937.0</td>\n",
       "      <td>23121.0</td>\n",
       "      <td>22101.0</td>\n",
       "      <td>21718.0</td>\n",
       "      <td>21760.0</td>\n",
       "      <td>22695.0</td>\n",
       "      <td>25689.0</td>\n",
       "      <td>30493.0</td>\n",
       "      <td>33164.0</td>\n",
       "      <td>34001.0</td>\n",
       "      <td>...</td>\n",
       "      <td>32099.0</td>\n",
       "      <td>31449.0</td>\n",
       "      <td>31179.0</td>\n",
       "      <td>31175.0</td>\n",
       "      <td>32515.0</td>\n",
       "      <td>34967.0</td>\n",
       "      <td>35381.0</td>\n",
       "      <td>34700.0</td>\n",
       "      <td>32055.0</td>\n",
       "      <td>28939.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-03</th>\n",
       "      <td>27227.0</td>\n",
       "      <td>25292.0</td>\n",
       "      <td>24265.0</td>\n",
       "      <td>23774.0</td>\n",
       "      <td>23650.0</td>\n",
       "      <td>24275.0</td>\n",
       "      <td>27243.0</td>\n",
       "      <td>31518.0</td>\n",
       "      <td>34093.0</td>\n",
       "      <td>35371.0</td>\n",
       "      <td>...</td>\n",
       "      <td>33029.0</td>\n",
       "      <td>32344.0</td>\n",
       "      <td>31927.0</td>\n",
       "      <td>31824.0</td>\n",
       "      <td>32226.0</td>\n",
       "      <td>35161.0</td>\n",
       "      <td>36599.0</td>\n",
       "      <td>35729.0</td>\n",
       "      <td>33154.0</td>\n",
       "      <td>29838.0</td>\n",
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       "    <tr>\n",
       "      <th>2016-01-04</th>\n",
       "      <td>26751.0</td>\n",
       "      <td>24882.0</td>\n",
       "      <td>23736.0</td>\n",
       "      <td>23199.0</td>\n",
       "      <td>23000.0</td>\n",
       "      <td>23348.0</td>\n",
       "      <td>25748.0</td>\n",
       "      <td>29620.0</td>\n",
       "      <td>31776.0</td>\n",
       "      <td>33087.0</td>\n",
       "      <td>...</td>\n",
       "      <td>31594.0</td>\n",
       "      <td>30376.0</td>\n",
       "      <td>29915.0</td>\n",
       "      <td>29633.0</td>\n",
       "      <td>29158.0</td>\n",
       "      <td>29159.0</td>\n",
       "      <td>30469.0</td>\n",
       "      <td>32482.0</td>\n",
       "      <td>30508.0</td>\n",
       "      <td>28598.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-05</th>\n",
       "      <td>23642.0</td>\n",
       "      <td>21990.0</td>\n",
       "      <td>20629.0</td>\n",
       "      <td>19865.0</td>\n",
       "      <td>19446.0</td>\n",
       "      <td>19248.0</td>\n",
       "      <td>19296.0</td>\n",
       "      <td>18956.0</td>\n",
       "      <td>20072.0</td>\n",
       "      <td>21911.0</td>\n",
       "      <td>...</td>\n",
       "      <td>23378.0</td>\n",
       "      <td>22190.0</td>\n",
       "      <td>21549.0</td>\n",
       "      <td>21233.0</td>\n",
       "      <td>21298.0</td>\n",
       "      <td>21756.0</td>\n",
       "      <td>22929.0</td>\n",
       "      <td>25815.0</td>\n",
       "      <td>25843.0</td>\n",
       "      <td>24167.0</td>\n",
       "    </tr>\n",
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      "text/plain": [
       "hours            0        1        2        3        4        5        6   \\\n",
       "date                                                                        \n",
       "2016-01-01  22431.0  21632.0  20357.0  19152.0  18310.0  18054.0  18234.0   \n",
       "2016-01-02  24937.0  23121.0  22101.0  21718.0  21760.0  22695.0  25689.0   \n",
       "2016-01-03  27227.0  25292.0  24265.0  23774.0  23650.0  24275.0  27243.0   \n",
       "2016-01-04  26751.0  24882.0  23736.0  23199.0  23000.0  23348.0  25748.0   \n",
       "2016-01-05  23642.0  21990.0  20629.0  19865.0  19446.0  19248.0  19296.0   \n",
       "\n",
       "hours            7        8        9   ...       14       15       16  \\\n",
       "date                                   ...                              \n",
       "2016-01-01  18596.0  18541.0  18942.0  ...  23265.0  22061.0  21481.0   \n",
       "2016-01-02  30493.0  33164.0  34001.0  ...  32099.0  31449.0  31179.0   \n",
       "2016-01-03  31518.0  34093.0  35371.0  ...  33029.0  32344.0  31927.0   \n",
       "2016-01-04  29620.0  31776.0  33087.0  ...  31594.0  30376.0  29915.0   \n",
       "2016-01-05  18956.0  20072.0  21911.0  ...  23378.0  22190.0  21549.0   \n",
       "\n",
       "hours            17       18       19       20       21       22       23  \n",
       "date                                                                       \n",
       "2016-01-01  21830.0  24291.0  25234.0  25881.0  26149.0  25610.0  24000.0  \n",
       "2016-01-02  31175.0  32515.0  34967.0  35381.0  34700.0  32055.0  28939.0  \n",
       "2016-01-03  31824.0  32226.0  35161.0  36599.0  35729.0  33154.0  29838.0  \n",
       "2016-01-04  29633.0  29158.0  29159.0  30469.0  32482.0  30508.0  28598.0  \n",
       "2016-01-05  21233.0  21298.0  21756.0  22929.0  25815.0  25843.0  24167.0  \n",
       "\n",
       "[5 rows x 24 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "loads = transform_to_windows(data)\n",
    "loads.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "#define a helper function to plot the indivdual hours\n",
    "def plot_hour(data, hour):\n",
    "    \n",
    "    #set figure size\n",
    "    fig = plt.figure(figsize = (20,7))\n",
    "    \n",
    "    #select the hour to display\n",
    "    series = data.iloc[:,hour]\n",
    "    \n",
    "    plt.plot(series.index, series.values)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/ns/anaconda3/envs/fuck/lib/python3.6/site-packages/pandas/plotting/_matplotlib/converter.py:102: FutureWarning: Using an implicitly registered datetime converter for a matplotlib plotting method. The converter was registered by pandas on import. Future versions of pandas will require you to explicitly register matplotlib converters.\n",
      "\n",
      "To register the converters:\n",
      "\t>>> from pandas.plotting import register_matplotlib_converters\n",
      "\t>>> register_matplotlib_converters()\n",
      "  warnings.warn(msg, FutureWarning)\n"
     ]
    },
    {
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\n",
      "text/plain": [
       "<Figure size 1440x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#preview of the actual load readings over two years at midnight.\n",
    "plot_hour(loads, 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#preview of the actual load readings over two years at midday.\n",
    "plot_hour(loads, 12)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "def shift_by_days(data, num_days):\n",
    "    \"\"\"\n",
    "    Input a timeseries of the form 24 hourly measurements per day\n",
    "    \n",
    "    Output returns \n",
    "    \n",
    "    \"\"\"\n",
    "    data_shifted = data.shift(num_days)\n",
    "    \n",
    "    return data_shifted\n",
    "    \n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "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>t-0 h_0</th>\n",
       "      <th>t-0 h_1</th>\n",
       "      <th>t-0 h_2</th>\n",
       "      <th>t-0 h_3</th>\n",
       "      <th>t-0 h_4</th>\n",
       "      <th>t-0 h_5</th>\n",
       "      <th>t-0 h_6</th>\n",
       "      <th>t-0 h_7</th>\n",
       "      <th>t-0 h_8</th>\n",
       "      <th>t-0 h_9</th>\n",
       "      <th>...</th>\n",
       "      <th>t-0 h_14</th>\n",
       "      <th>t-0 h_15</th>\n",
       "      <th>t-0 h_16</th>\n",
       "      <th>t-0 h_17</th>\n",
       "      <th>t-0 h_18</th>\n",
       "      <th>t-0 h_19</th>\n",
       "      <th>t-0 h_20</th>\n",
       "      <th>t-0 h_21</th>\n",
       "      <th>t-0 h_22</th>\n",
       "      <th>t-0 h_23</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2016-01-01</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-02</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-03</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-04</th>\n",
       "      <td>22431.0</td>\n",
       "      <td>21632.0</td>\n",
       "      <td>20357.0</td>\n",
       "      <td>19152.0</td>\n",
       "      <td>18310.0</td>\n",
       "      <td>18054.0</td>\n",
       "      <td>18234.0</td>\n",
       "      <td>18596.0</td>\n",
       "      <td>18541.0</td>\n",
       "      <td>18942.0</td>\n",
       "      <td>...</td>\n",
       "      <td>23265.0</td>\n",
       "      <td>22061.0</td>\n",
       "      <td>21481.0</td>\n",
       "      <td>21830.0</td>\n",
       "      <td>24291.0</td>\n",
       "      <td>25234.0</td>\n",
       "      <td>25881.0</td>\n",
       "      <td>26149.0</td>\n",
       "      <td>25610.0</td>\n",
       "      <td>24000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-05</th>\n",
       "      <td>24937.0</td>\n",
       "      <td>23121.0</td>\n",
       "      <td>22101.0</td>\n",
       "      <td>21718.0</td>\n",
       "      <td>21760.0</td>\n",
       "      <td>22695.0</td>\n",
       "      <td>25689.0</td>\n",
       "      <td>30493.0</td>\n",
       "      <td>33164.0</td>\n",
       "      <td>34001.0</td>\n",
       "      <td>...</td>\n",
       "      <td>32099.0</td>\n",
       "      <td>31449.0</td>\n",
       "      <td>31179.0</td>\n",
       "      <td>31175.0</td>\n",
       "      <td>32515.0</td>\n",
       "      <td>34967.0</td>\n",
       "      <td>35381.0</td>\n",
       "      <td>34700.0</td>\n",
       "      <td>32055.0</td>\n",
       "      <td>28939.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            t-0 h_0  t-0 h_1  t-0 h_2  t-0 h_3  t-0 h_4  t-0 h_5  t-0 h_6  \\\n",
       "date                                                                        \n",
       "2016-01-01      NaN      NaN      NaN      NaN      NaN      NaN      NaN   \n",
       "2016-01-02      NaN      NaN      NaN      NaN      NaN      NaN      NaN   \n",
       "2016-01-03      NaN      NaN      NaN      NaN      NaN      NaN      NaN   \n",
       "2016-01-04  22431.0  21632.0  20357.0  19152.0  18310.0  18054.0  18234.0   \n",
       "2016-01-05  24937.0  23121.0  22101.0  21718.0  21760.0  22695.0  25689.0   \n",
       "\n",
       "            t-0 h_7  t-0 h_8  t-0 h_9  ...  t-0 h_14  t-0 h_15  t-0 h_16  \\\n",
       "date                                   ...                                 \n",
       "2016-01-01      NaN      NaN      NaN  ...       NaN       NaN       NaN   \n",
       "2016-01-02      NaN      NaN      NaN  ...       NaN       NaN       NaN   \n",
       "2016-01-03      NaN      NaN      NaN  ...       NaN       NaN       NaN   \n",
       "2016-01-04  18596.0  18541.0  18942.0  ...   23265.0   22061.0   21481.0   \n",
       "2016-01-05  30493.0  33164.0  34001.0  ...   32099.0   31449.0   31179.0   \n",
       "\n",
       "            t-0 h_17  t-0 h_18  t-0 h_19  t-0 h_20  t-0 h_21  t-0 h_22  \\\n",
       "date                                                                     \n",
       "2016-01-01       NaN       NaN       NaN       NaN       NaN       NaN   \n",
       "2016-01-02       NaN       NaN       NaN       NaN       NaN       NaN   \n",
       "2016-01-03       NaN       NaN       NaN       NaN       NaN       NaN   \n",
       "2016-01-04   21830.0   24291.0   25234.0   25881.0   26149.0   25610.0   \n",
       "2016-01-05   31175.0   32515.0   34967.0   35381.0   34700.0   32055.0   \n",
       "\n",
       "            t-0 h_23  \n",
       "date                  \n",
       "2016-01-01       NaN  \n",
       "2016-01-02       NaN  \n",
       "2016-01-03       NaN  \n",
       "2016-01-04   24000.0  \n",
       "2016-01-05   28939.0  \n",
       "\n",
       "[5 rows x 24 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# example of how data is shifted\n",
    "loads_shifted_3_days = shift_by_days(loads, 3)\n",
    "loads_shifted_3_days.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Construct features\n",
    "\n",
    "Descrption of the features."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def make_shifted_features(data, shifts_list):\n",
    "    \n",
    "    #set the columns names on the original data set\n",
    "    data = rename_cols(data, 0)\n",
    "    \n",
    "    #initate list of dataframes\n",
    "    periods = [data]\n",
    "    \n",
    "    #cycle through list of shifts i.e. features\n",
    "    for shift in shifts_list:\n",
    "        \n",
    "        #shift the data by shift value\n",
    "        data_shifted = shift_by_days(data, shift)\n",
    "\n",
    "        #update column identifers\n",
    "        data_shifted = rename_cols(data_shifted, shift)\n",
    "    \n",
    "        periods.append(data_shifted)\n",
    "        \n",
    "    #concatenate all shifted datasets into one dataframe.    \n",
    "    data = pd.concat(periods, axis = 1)\n",
    "    \n",
    "    data = trim_length(data, shifts_list)\n",
    "    \n",
    "    return data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def rename_cols(data, shift):\n",
    "    \n",
    "    cols = data.columns\n",
    "    \n",
    "    cols_list = []\n",
    "    \n",
    "    for idx, col in enumerate(cols):\n",
    "        \n",
    "        new_col = 't-' + str(shift) + ' h_' + str(idx)\n",
    "        \n",
    "        cols_list.append(new_col)\n",
    "        \n",
    "    data.columns = cols_list\n",
    "    \n",
    "    return data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "def trim_length(data, shifts_list):\n",
    "    \n",
    "    start_point = sorted(shifts_list, reverse=True)[0]\n",
    "    \n",
    "    return data.iloc[start_point:,:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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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>t-0 h_0</th>\n",
       "      <th>t-0 h_1</th>\n",
       "      <th>t-0 h_2</th>\n",
       "      <th>t-0 h_3</th>\n",
       "      <th>t-0 h_4</th>\n",
       "      <th>t-0 h_5</th>\n",
       "      <th>t-0 h_6</th>\n",
       "      <th>t-0 h_7</th>\n",
       "      <th>t-0 h_8</th>\n",
       "      <th>t-0 h_9</th>\n",
       "      <th>...</th>\n",
       "      <th>t-4 h_14</th>\n",
       "      <th>t-4 h_15</th>\n",
       "      <th>t-4 h_16</th>\n",
       "      <th>t-4 h_17</th>\n",
       "      <th>t-4 h_18</th>\n",
       "      <th>t-4 h_19</th>\n",
       "      <th>t-4 h_20</th>\n",
       "      <th>t-4 h_21</th>\n",
       "      <th>t-4 h_22</th>\n",
       "      <th>t-4 h_23</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2016-01-05</th>\n",
       "      <td>23642.0</td>\n",
       "      <td>21990.0</td>\n",
       "      <td>20629.0</td>\n",
       "      <td>19865.0</td>\n",
       "      <td>19446.0</td>\n",
       "      <td>19248.0</td>\n",
       "      <td>19296.0</td>\n",
       "      <td>18956.0</td>\n",
       "      <td>20072.0</td>\n",
       "      <td>21911.0</td>\n",
       "      <td>...</td>\n",
       "      <td>23265.0</td>\n",
       "      <td>22061.0</td>\n",
       "      <td>21481.0</td>\n",
       "      <td>21830.0</td>\n",
       "      <td>24291.0</td>\n",
       "      <td>25234.0</td>\n",
       "      <td>25881.0</td>\n",
       "      <td>26149.0</td>\n",
       "      <td>25610.0</td>\n",
       "      <td>24000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-06</th>\n",
       "      <td>25135.0</td>\n",
       "      <td>23717.0</td>\n",
       "      <td>22747.0</td>\n",
       "      <td>22440.0</td>\n",
       "      <td>22396.0</td>\n",
       "      <td>22737.0</td>\n",
       "      <td>24350.0</td>\n",
       "      <td>26788.0</td>\n",
       "      <td>28705.0</td>\n",
       "      <td>30029.0</td>\n",
       "      <td>...</td>\n",
       "      <td>32099.0</td>\n",
       "      <td>31449.0</td>\n",
       "      <td>31179.0</td>\n",
       "      <td>31175.0</td>\n",
       "      <td>32515.0</td>\n",
       "      <td>34967.0</td>\n",
       "      <td>35381.0</td>\n",
       "      <td>34700.0</td>\n",
       "      <td>32055.0</td>\n",
       "      <td>28939.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-07</th>\n",
       "      <td>28425.0</td>\n",
       "      <td>26609.0</td>\n",
       "      <td>25442.0</td>\n",
       "      <td>24864.0</td>\n",
       "      <td>24609.0</td>\n",
       "      <td>24776.0</td>\n",
       "      <td>26062.0</td>\n",
       "      <td>28023.0</td>\n",
       "      <td>30354.0</td>\n",
       "      <td>32641.0</td>\n",
       "      <td>...</td>\n",
       "      <td>33029.0</td>\n",
       "      <td>32344.0</td>\n",
       "      <td>31927.0</td>\n",
       "      <td>31824.0</td>\n",
       "      <td>32226.0</td>\n",
       "      <td>35161.0</td>\n",
       "      <td>36599.0</td>\n",
       "      <td>35729.0</td>\n",
       "      <td>33154.0</td>\n",
       "      <td>29838.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-08</th>\n",
       "      <td>26986.0</td>\n",
       "      <td>25125.0</td>\n",
       "      <td>23969.0</td>\n",
       "      <td>23281.0</td>\n",
       "      <td>23088.0</td>\n",
       "      <td>23573.0</td>\n",
       "      <td>25487.0</td>\n",
       "      <td>27299.0</td>\n",
       "      <td>29776.0</td>\n",
       "      <td>31487.0</td>\n",
       "      <td>...</td>\n",
       "      <td>31594.0</td>\n",
       "      <td>30376.0</td>\n",
       "      <td>29915.0</td>\n",
       "      <td>29633.0</td>\n",
       "      <td>29158.0</td>\n",
       "      <td>29159.0</td>\n",
       "      <td>30469.0</td>\n",
       "      <td>32482.0</td>\n",
       "      <td>30508.0</td>\n",
       "      <td>28598.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-09</th>\n",
       "      <td>28284.0</td>\n",
       "      <td>26487.0</td>\n",
       "      <td>25264.0</td>\n",
       "      <td>24744.0</td>\n",
       "      <td>24505.0</td>\n",
       "      <td>24766.0</td>\n",
       "      <td>26459.0</td>\n",
       "      <td>28734.0</td>\n",
       "      <td>30505.0</td>\n",
       "      <td>32582.0</td>\n",
       "      <td>...</td>\n",
       "      <td>23378.0</td>\n",
       "      <td>22190.0</td>\n",
       "      <td>21549.0</td>\n",
       "      <td>21233.0</td>\n",
       "      <td>21298.0</td>\n",
       "      <td>21756.0</td>\n",
       "      <td>22929.0</td>\n",
       "      <td>25815.0</td>\n",
       "      <td>25843.0</td>\n",
       "      <td>24167.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-10</th>\n",
       "      <td>25362.0</td>\n",
       "      <td>24135.0</td>\n",
       "      <td>23117.0</td>\n",
       "      <td>22487.0</td>\n",
       "      <td>22063.0</td>\n",
       "      <td>21869.0</td>\n",
       "      <td>22198.0</td>\n",
       "      <td>23304.0</td>\n",
       "      <td>23972.0</td>\n",
       "      <td>25986.0</td>\n",
       "      <td>...</td>\n",
       "      <td>30470.0</td>\n",
       "      <td>29970.0</td>\n",
       "      <td>29979.0</td>\n",
       "      <td>29924.0</td>\n",
       "      <td>29640.0</td>\n",
       "      <td>29409.0</td>\n",
       "      <td>29484.0</td>\n",
       "      <td>30027.0</td>\n",
       "      <td>29332.0</td>\n",
       "      <td>26854.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-11</th>\n",
       "      <td>22557.0</td>\n",
       "      <td>21261.0</td>\n",
       "      <td>20403.0</td>\n",
       "      <td>19960.0</td>\n",
       "      <td>19710.0</td>\n",
       "      <td>19764.0</td>\n",
       "      <td>20230.0</td>\n",
       "      <td>20643.0</td>\n",
       "      <td>21168.0</td>\n",
       "      <td>22967.0</td>\n",
       "      <td>...</td>\n",
       "      <td>34702.0</td>\n",
       "      <td>33939.0</td>\n",
       "      <td>33753.0</td>\n",
       "      <td>33510.0</td>\n",
       "      <td>33079.0</td>\n",
       "      <td>32697.0</td>\n",
       "      <td>32172.0</td>\n",
       "      <td>31560.0</td>\n",
       "      <td>30943.0</td>\n",
       "      <td>29025.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-12</th>\n",
       "      <td>27046.0</td>\n",
       "      <td>25058.0</td>\n",
       "      <td>23874.0</td>\n",
       "      <td>23410.0</td>\n",
       "      <td>23365.0</td>\n",
       "      <td>24116.0</td>\n",
       "      <td>26763.0</td>\n",
       "      <td>30980.0</td>\n",
       "      <td>33422.0</td>\n",
       "      <td>34280.0</td>\n",
       "      <td>...</td>\n",
       "      <td>35288.0</td>\n",
       "      <td>34479.0</td>\n",
       "      <td>34240.0</td>\n",
       "      <td>34101.0</td>\n",
       "      <td>33693.0</td>\n",
       "      <td>32919.0</td>\n",
       "      <td>32267.0</td>\n",
       "      <td>32709.0</td>\n",
       "      <td>32355.0</td>\n",
       "      <td>29998.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-13</th>\n",
       "      <td>27421.0</td>\n",
       "      <td>25382.0</td>\n",
       "      <td>24219.0</td>\n",
       "      <td>23562.0</td>\n",
       "      <td>23555.0</td>\n",
       "      <td>24198.0</td>\n",
       "      <td>26792.0</td>\n",
       "      <td>31474.0</td>\n",
       "      <td>34420.0</td>\n",
       "      <td>35186.0</td>\n",
       "      <td>...</td>\n",
       "      <td>36004.0</td>\n",
       "      <td>35417.0</td>\n",
       "      <td>35492.0</td>\n",
       "      <td>35529.0</td>\n",
       "      <td>34992.0</td>\n",
       "      <td>34052.0</td>\n",
       "      <td>33899.0</td>\n",
       "      <td>34957.0</td>\n",
       "      <td>32547.0</td>\n",
       "      <td>30096.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-14</th>\n",
       "      <td>27936.0</td>\n",
       "      <td>25936.0</td>\n",
       "      <td>24731.0</td>\n",
       "      <td>24167.0</td>\n",
       "      <td>24087.0</td>\n",
       "      <td>24584.0</td>\n",
       "      <td>27035.0</td>\n",
       "      <td>31511.0</td>\n",
       "      <td>34484.0</td>\n",
       "      <td>35004.0</td>\n",
       "      <td>...</td>\n",
       "      <td>27507.0</td>\n",
       "      <td>26346.0</td>\n",
       "      <td>25651.0</td>\n",
       "      <td>25559.0</td>\n",
       "      <td>25497.0</td>\n",
       "      <td>26352.0</td>\n",
       "      <td>28617.0</td>\n",
       "      <td>28678.0</td>\n",
       "      <td>26798.0</td>\n",
       "      <td>24930.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-15</th>\n",
       "      <td>27672.0</td>\n",
       "      <td>25688.0</td>\n",
       "      <td>24408.0</td>\n",
       "      <td>23893.0</td>\n",
       "      <td>23765.0</td>\n",
       "      <td>24392.0</td>\n",
       "      <td>26975.0</td>\n",
       "      <td>31392.0</td>\n",
       "      <td>34356.0</td>\n",
       "      <td>35177.0</td>\n",
       "      <td>...</td>\n",
       "      <td>24807.0</td>\n",
       "      <td>23577.0</td>\n",
       "      <td>22945.0</td>\n",
       "      <td>23000.0</td>\n",
       "      <td>25449.0</td>\n",
       "      <td>27006.0</td>\n",
       "      <td>27672.0</td>\n",
       "      <td>27136.0</td>\n",
       "      <td>25633.0</td>\n",
       "      <td>23727.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-16</th>\n",
       "      <td>28539.0</td>\n",
       "      <td>26495.0</td>\n",
       "      <td>24938.0</td>\n",
       "      <td>24058.0</td>\n",
       "      <td>23633.0</td>\n",
       "      <td>23500.0</td>\n",
       "      <td>24176.0</td>\n",
       "      <td>25631.0</td>\n",
       "      <td>27257.0</td>\n",
       "      <td>29776.0</td>\n",
       "      <td>...</td>\n",
       "      <td>33651.0</td>\n",
       "      <td>33084.0</td>\n",
       "      <td>33033.0</td>\n",
       "      <td>33961.0</td>\n",
       "      <td>35578.0</td>\n",
       "      <td>35923.0</td>\n",
       "      <td>36345.0</td>\n",
       "      <td>35454.0</td>\n",
       "      <td>32681.0</td>\n",
       "      <td>29650.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-17</th>\n",
       "      <td>27057.0</td>\n",
       "      <td>24791.0</td>\n",
       "      <td>23259.0</td>\n",
       "      <td>22417.0</td>\n",
       "      <td>21960.0</td>\n",
       "      <td>21919.0</td>\n",
       "      <td>22384.0</td>\n",
       "      <td>23181.0</td>\n",
       "      <td>23900.0</td>\n",
       "      <td>25833.0</td>\n",
       "      <td>...</td>\n",
       "      <td>33798.0</td>\n",
       "      <td>33252.0</td>\n",
       "      <td>33146.0</td>\n",
       "      <td>33652.0</td>\n",
       "      <td>35573.0</td>\n",
       "      <td>36708.0</td>\n",
       "      <td>36875.0</td>\n",
       "      <td>36084.0</td>\n",
       "      <td>33413.0</td>\n",
       "      <td>30202.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-18</th>\n",
       "      <td>26586.0</td>\n",
       "      <td>24656.0</td>\n",
       "      <td>23420.0</td>\n",
       "      <td>22859.0</td>\n",
       "      <td>22742.0</td>\n",
       "      <td>23866.0</td>\n",
       "      <td>27094.0</td>\n",
       "      <td>32027.0</td>\n",
       "      <td>35569.0</td>\n",
       "      <td>36437.0</td>\n",
       "      <td>...</td>\n",
       "      <td>34366.0</td>\n",
       "      <td>33763.0</td>\n",
       "      <td>33641.0</td>\n",
       "      <td>34137.0</td>\n",
       "      <td>35735.0</td>\n",
       "      <td>36701.0</td>\n",
       "      <td>36677.0</td>\n",
       "      <td>35828.0</td>\n",
       "      <td>33228.0</td>\n",
       "      <td>30088.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-19</th>\n",
       "      <td>27958.0</td>\n",
       "      <td>25831.0</td>\n",
       "      <td>24589.0</td>\n",
       "      <td>24185.0</td>\n",
       "      <td>24103.0</td>\n",
       "      <td>24736.0</td>\n",
       "      <td>27449.0</td>\n",
       "      <td>32326.0</td>\n",
       "      <td>35535.0</td>\n",
       "      <td>36174.0</td>\n",
       "      <td>...</td>\n",
       "      <td>34082.0</td>\n",
       "      <td>33308.0</td>\n",
       "      <td>33078.0</td>\n",
       "      <td>33189.0</td>\n",
       "      <td>34985.0</td>\n",
       "      <td>36107.0</td>\n",
       "      <td>35951.0</td>\n",
       "      <td>35364.0</td>\n",
       "      <td>33193.0</td>\n",
       "      <td>30665.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-20</th>\n",
       "      <td>28222.0</td>\n",
       "      <td>25955.0</td>\n",
       "      <td>24813.0</td>\n",
       "      <td>24307.0</td>\n",
       "      <td>24212.0</td>\n",
       "      <td>24793.0</td>\n",
       "      <td>27378.0</td>\n",
       "      <td>32354.0</td>\n",
       "      <td>35577.0</td>\n",
       "      <td>36514.0</td>\n",
       "      <td>...</td>\n",
       "      <td>30663.0</td>\n",
       "      <td>29402.0</td>\n",
       "      <td>28726.0</td>\n",
       "      <td>28691.0</td>\n",
       "      <td>30848.0</td>\n",
       "      <td>32436.0</td>\n",
       "      <td>32998.0</td>\n",
       "      <td>32956.0</td>\n",
       "      <td>31734.0</td>\n",
       "      <td>29453.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-21</th>\n",
       "      <td>27991.0</td>\n",
       "      <td>25797.0</td>\n",
       "      <td>24501.0</td>\n",
       "      <td>23998.0</td>\n",
       "      <td>23886.0</td>\n",
       "      <td>24549.0</td>\n",
       "      <td>27280.0</td>\n",
       "      <td>32095.0</td>\n",
       "      <td>35003.0</td>\n",
       "      <td>35707.0</td>\n",
       "      <td>...</td>\n",
       "      <td>29630.0</td>\n",
       "      <td>28555.0</td>\n",
       "      <td>27787.0</td>\n",
       "      <td>27845.0</td>\n",
       "      <td>30332.0</td>\n",
       "      <td>32083.0</td>\n",
       "      <td>33266.0</td>\n",
       "      <td>33461.0</td>\n",
       "      <td>32212.0</td>\n",
       "      <td>29475.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-22</th>\n",
       "      <td>28033.0</td>\n",
       "      <td>26102.0</td>\n",
       "      <td>24711.0</td>\n",
       "      <td>24148.0</td>\n",
       "      <td>24103.0</td>\n",
       "      <td>24749.0</td>\n",
       "      <td>27295.0</td>\n",
       "      <td>31913.0</td>\n",
       "      <td>34785.0</td>\n",
       "      <td>35569.0</td>\n",
       "      <td>...</td>\n",
       "      <td>35096.0</td>\n",
       "      <td>34498.0</td>\n",
       "      <td>34437.0</td>\n",
       "      <td>34665.0</td>\n",
       "      <td>36335.0</td>\n",
       "      <td>37564.0</td>\n",
       "      <td>37724.0</td>\n",
       "      <td>36751.0</td>\n",
       "      <td>33951.0</td>\n",
       "      <td>30623.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-23</th>\n",
       "      <td>27902.0</td>\n",
       "      <td>25682.0</td>\n",
       "      <td>24283.0</td>\n",
       "      <td>23496.0</td>\n",
       "      <td>23013.0</td>\n",
       "      <td>22880.0</td>\n",
       "      <td>23410.0</td>\n",
       "      <td>25031.0</td>\n",
       "      <td>26616.0</td>\n",
       "      <td>29158.0</td>\n",
       "      <td>...</td>\n",
       "      <td>34662.0</td>\n",
       "      <td>34144.0</td>\n",
       "      <td>34045.0</td>\n",
       "      <td>34591.0</td>\n",
       "      <td>36577.0</td>\n",
       "      <td>37962.0</td>\n",
       "      <td>38071.0</td>\n",
       "      <td>37231.0</td>\n",
       "      <td>34426.0</td>\n",
       "      <td>30932.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-24</th>\n",
       "      <td>25595.0</td>\n",
       "      <td>23640.0</td>\n",
       "      <td>22264.0</td>\n",
       "      <td>21493.0</td>\n",
       "      <td>21165.0</td>\n",
       "      <td>21121.0</td>\n",
       "      <td>21416.0</td>\n",
       "      <td>22033.0</td>\n",
       "      <td>22686.0</td>\n",
       "      <td>24652.0</td>\n",
       "      <td>...</td>\n",
       "      <td>34434.0</td>\n",
       "      <td>33737.0</td>\n",
       "      <td>33688.0</td>\n",
       "      <td>34107.0</td>\n",
       "      <td>35952.0</td>\n",
       "      <td>37314.0</td>\n",
       "      <td>37527.0</td>\n",
       "      <td>36520.0</td>\n",
       "      <td>33839.0</td>\n",
       "      <td>30538.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-25</th>\n",
       "      <td>25027.0</td>\n",
       "      <td>23121.0</td>\n",
       "      <td>22169.0</td>\n",
       "      <td>21953.0</td>\n",
       "      <td>22281.0</td>\n",
       "      <td>22807.0</td>\n",
       "      <td>25716.0</td>\n",
       "      <td>30429.0</td>\n",
       "      <td>33289.0</td>\n",
       "      <td>34131.0</td>\n",
       "      <td>...</td>\n",
       "      <td>34331.0</td>\n",
       "      <td>33846.0</td>\n",
       "      <td>34028.0</td>\n",
       "      <td>34504.0</td>\n",
       "      <td>36109.0</td>\n",
       "      <td>37423.0</td>\n",
       "      <td>37468.0</td>\n",
       "      <td>36555.0</td>\n",
       "      <td>33817.0</td>\n",
       "      <td>30587.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-26</th>\n",
       "      <td>27018.0</td>\n",
       "      <td>25028.0</td>\n",
       "      <td>23973.0</td>\n",
       "      <td>23498.0</td>\n",
       "      <td>23313.0</td>\n",
       "      <td>23985.0</td>\n",
       "      <td>26596.0</td>\n",
       "      <td>31080.0</td>\n",
       "      <td>33918.0</td>\n",
       "      <td>34567.0</td>\n",
       "      <td>...</td>\n",
       "      <td>33741.0</td>\n",
       "      <td>33041.0</td>\n",
       "      <td>32828.0</td>\n",
       "      <td>32907.0</td>\n",
       "      <td>34408.0</td>\n",
       "      <td>35512.0</td>\n",
       "      <td>35335.0</td>\n",
       "      <td>34802.0</td>\n",
       "      <td>32627.0</td>\n",
       "      <td>30025.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-27</th>\n",
       "      <td>27219.0</td>\n",
       "      <td>25294.0</td>\n",
       "      <td>24026.0</td>\n",
       "      <td>23580.0</td>\n",
       "      <td>23533.0</td>\n",
       "      <td>24083.0</td>\n",
       "      <td>26674.0</td>\n",
       "      <td>31367.0</td>\n",
       "      <td>33898.0</td>\n",
       "      <td>34723.0</td>\n",
       "      <td>...</td>\n",
       "      <td>29387.0</td>\n",
       "      <td>28137.0</td>\n",
       "      <td>27400.0</td>\n",
       "      <td>27264.0</td>\n",
       "      <td>29144.0</td>\n",
       "      <td>30855.0</td>\n",
       "      <td>31189.0</td>\n",
       "      <td>31254.0</td>\n",
       "      <td>29814.0</td>\n",
       "      <td>27761.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-28</th>\n",
       "      <td>27170.0</td>\n",
       "      <td>25087.0</td>\n",
       "      <td>23820.0</td>\n",
       "      <td>23349.0</td>\n",
       "      <td>23270.0</td>\n",
       "      <td>23837.0</td>\n",
       "      <td>26329.0</td>\n",
       "      <td>30815.0</td>\n",
       "      <td>33507.0</td>\n",
       "      <td>34188.0</td>\n",
       "      <td>...</td>\n",
       "      <td>27160.0</td>\n",
       "      <td>25942.0</td>\n",
       "      <td>25285.0</td>\n",
       "      <td>25271.0</td>\n",
       "      <td>27393.0</td>\n",
       "      <td>29919.0</td>\n",
       "      <td>30986.0</td>\n",
       "      <td>31188.0</td>\n",
       "      <td>30141.0</td>\n",
       "      <td>27640.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-29</th>\n",
       "      <td>27306.0</td>\n",
       "      <td>25299.0</td>\n",
       "      <td>24024.0</td>\n",
       "      <td>23490.0</td>\n",
       "      <td>23345.0</td>\n",
       "      <td>23961.0</td>\n",
       "      <td>26402.0</td>\n",
       "      <td>30730.0</td>\n",
       "      <td>33390.0</td>\n",
       "      <td>34230.0</td>\n",
       "      <td>...</td>\n",
       "      <td>32707.0</td>\n",
       "      <td>31908.0</td>\n",
       "      <td>31660.0</td>\n",
       "      <td>31960.0</td>\n",
       "      <td>33634.0</td>\n",
       "      <td>35427.0</td>\n",
       "      <td>35742.0</td>\n",
       "      <td>34888.0</td>\n",
       "      <td>32218.0</td>\n",
       "      <td>29032.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-30</th>\n",
       "      <td>27662.0</td>\n",
       "      <td>25660.0</td>\n",
       "      <td>24106.0</td>\n",
       "      <td>23276.0</td>\n",
       "      <td>22893.0</td>\n",
       "      <td>22841.0</td>\n",
       "      <td>23253.0</td>\n",
       "      <td>24655.0</td>\n",
       "      <td>26373.0</td>\n",
       "      <td>28990.0</td>\n",
       "      <td>...</td>\n",
       "      <td>32994.0</td>\n",
       "      <td>32401.0</td>\n",
       "      <td>32197.0</td>\n",
       "      <td>32359.0</td>\n",
       "      <td>33962.0</td>\n",
       "      <td>35859.0</td>\n",
       "      <td>36244.0</td>\n",
       "      <td>35565.0</td>\n",
       "      <td>32719.0</td>\n",
       "      <td>29521.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-31</th>\n",
       "      <td>25833.0</td>\n",
       "      <td>23820.0</td>\n",
       "      <td>22863.0</td>\n",
       "      <td>22056.0</td>\n",
       "      <td>21622.0</td>\n",
       "      <td>21588.0</td>\n",
       "      <td>21940.0</td>\n",
       "      <td>22543.0</td>\n",
       "      <td>23143.0</td>\n",
       "      <td>24923.0</td>\n",
       "      <td>...</td>\n",
       "      <td>33087.0</td>\n",
       "      <td>32455.0</td>\n",
       "      <td>32179.0</td>\n",
       "      <td>32402.0</td>\n",
       "      <td>34025.0</td>\n",
       "      <td>35807.0</td>\n",
       "      <td>36066.0</td>\n",
       "      <td>35282.0</td>\n",
       "      <td>32572.0</td>\n",
       "      <td>29506.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-02-01</th>\n",
       "      <td>22113.0</td>\n",
       "      <td>20515.0</td>\n",
       "      <td>19284.0</td>\n",
       "      <td>18637.0</td>\n",
       "      <td>18352.0</td>\n",
       "      <td>18574.0</td>\n",
       "      <td>19751.0</td>\n",
       "      <td>20857.0</td>\n",
       "      <td>22156.0</td>\n",
       "      <td>24125.0</td>\n",
       "      <td>...</td>\n",
       "      <td>33404.0</td>\n",
       "      <td>32958.0</td>\n",
       "      <td>32824.0</td>\n",
       "      <td>33062.0</td>\n",
       "      <td>34403.0</td>\n",
       "      <td>36016.0</td>\n",
       "      <td>36105.0</td>\n",
       "      <td>35306.0</td>\n",
       "      <td>32601.0</td>\n",
       "      <td>29557.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-02-02</th>\n",
       "      <td>26810.0</td>\n",
       "      <td>24903.0</td>\n",
       "      <td>23819.0</td>\n",
       "      <td>23418.0</td>\n",
       "      <td>23240.0</td>\n",
       "      <td>23890.0</td>\n",
       "      <td>26441.0</td>\n",
       "      <td>30975.0</td>\n",
       "      <td>33582.0</td>\n",
       "      <td>34277.0</td>\n",
       "      <td>...</td>\n",
       "      <td>32993.0</td>\n",
       "      <td>32371.0</td>\n",
       "      <td>32086.0</td>\n",
       "      <td>32049.0</td>\n",
       "      <td>33235.0</td>\n",
       "      <td>34921.0</td>\n",
       "      <td>34867.0</td>\n",
       "      <td>34302.0</td>\n",
       "      <td>32177.0</td>\n",
       "      <td>29489.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-02-03</th>\n",
       "      <td>27578.0</td>\n",
       "      <td>25540.0</td>\n",
       "      <td>24448.0</td>\n",
       "      <td>23929.0</td>\n",
       "      <td>23895.0</td>\n",
       "      <td>24570.0</td>\n",
       "      <td>27320.0</td>\n",
       "      <td>31510.0</td>\n",
       "      <td>34134.0</td>\n",
       "      <td>35154.0</td>\n",
       "      <td>...</td>\n",
       "      <td>29306.0</td>\n",
       "      <td>28055.0</td>\n",
       "      <td>27312.0</td>\n",
       "      <td>27155.0</td>\n",
       "      <td>29016.0</td>\n",
       "      <td>30999.0</td>\n",
       "      <td>31700.0</td>\n",
       "      <td>31771.0</td>\n",
       "      <td>30296.0</td>\n",
       "      <td>28200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-12-02</th>\n",
       "      <td>26971.0</td>\n",
       "      <td>25062.0</td>\n",
       "      <td>23779.0</td>\n",
       "      <td>23460.0</td>\n",
       "      <td>23515.0</td>\n",
       "      <td>24193.0</td>\n",
       "      <td>27254.0</td>\n",
       "      <td>32070.0</td>\n",
       "      <td>35028.0</td>\n",
       "      <td>36940.0</td>\n",
       "      <td>...</td>\n",
       "      <td>33442.0</td>\n",
       "      <td>33161.0</td>\n",
       "      <td>32972.0</td>\n",
       "      <td>33814.0</td>\n",
       "      <td>36115.0</td>\n",
       "      <td>36642.0</td>\n",
       "      <td>36803.0</td>\n",
       "      <td>35710.0</td>\n",
       "      <td>33018.0</td>\n",
       "      <td>29814.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-12-03</th>\n",
       "      <td>25503.0</td>\n",
       "      <td>23830.0</td>\n",
       "      <td>22753.0</td>\n",
       "      <td>22533.0</td>\n",
       "      <td>22536.0</td>\n",
       "      <td>23495.0</td>\n",
       "      <td>26793.0</td>\n",
       "      <td>30850.0</td>\n",
       "      <td>33785.0</td>\n",
       "      <td>34977.0</td>\n",
       "      <td>...</td>\n",
       "      <td>33839.0</td>\n",
       "      <td>33492.0</td>\n",
       "      <td>33408.0</td>\n",
       "      <td>34319.0</td>\n",
       "      <td>36124.0</td>\n",
       "      <td>36702.0</td>\n",
       "      <td>36813.0</td>\n",
       "      <td>35670.0</td>\n",
       "      <td>33192.0</td>\n",
       "      <td>30066.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-12-04</th>\n",
       "      <td>27710.0</td>\n",
       "      <td>25730.0</td>\n",
       "      <td>24636.0</td>\n",
       "      <td>24126.0</td>\n",
       "      <td>23915.0</td>\n",
       "      <td>24437.0</td>\n",
       "      <td>26962.0</td>\n",
       "      <td>30781.0</td>\n",
       "      <td>33269.0</td>\n",
       "      <td>34663.0</td>\n",
       "      <td>...</td>\n",
       "      <td>33498.0</td>\n",
       "      <td>32736.0</td>\n",
       "      <td>32280.0</td>\n",
       "      <td>32783.0</td>\n",
       "      <td>34791.0</td>\n",
       "      <td>35117.0</td>\n",
       "      <td>35104.0</td>\n",
       "      <td>33993.0</td>\n",
       "      <td>32092.0</td>\n",
       "      <td>29645.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-12-05</th>\n",
       "      <td>25670.0</td>\n",
       "      <td>24166.0</td>\n",
       "      <td>23019.0</td>\n",
       "      <td>22349.0</td>\n",
       "      <td>22050.0</td>\n",
       "      <td>21894.0</td>\n",
       "      <td>22201.0</td>\n",
       "      <td>22448.0</td>\n",
       "      <td>24394.0</td>\n",
       "      <td>26495.0</td>\n",
       "      <td>...</td>\n",
       "      <td>35588.0</td>\n",
       "      <td>34803.0</td>\n",
       "      <td>34445.0</td>\n",
       "      <td>34702.0</td>\n",
       "      <td>36671.0</td>\n",
       "      <td>37541.0</td>\n",
       "      <td>37474.0</td>\n",
       "      <td>36841.0</td>\n",
       "      <td>34624.0</td>\n",
       "      <td>31942.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-12-06</th>\n",
       "      <td>25732.0</td>\n",
       "      <td>24356.0</td>\n",
       "      <td>23490.0</td>\n",
       "      <td>23125.0</td>\n",
       "      <td>22978.0</td>\n",
       "      <td>23300.0</td>\n",
       "      <td>24976.0</td>\n",
       "      <td>27606.0</td>\n",
       "      <td>29701.0</td>\n",
       "      <td>30960.0</td>\n",
       "      <td>...</td>\n",
       "      <td>36775.0</td>\n",
       "      <td>36021.0</td>\n",
       "      <td>35638.0</td>\n",
       "      <td>35526.0</td>\n",
       "      <td>35755.0</td>\n",
       "      <td>38202.0</td>\n",
       "      <td>38783.0</td>\n",
       "      <td>37934.0</td>\n",
       "      <td>35230.0</td>\n",
       "      <td>31690.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-12-07</th>\n",
       "      <td>28518.0</td>\n",
       "      <td>26746.0</td>\n",
       "      <td>25737.0</td>\n",
       "      <td>25253.0</td>\n",
       "      <td>25078.0</td>\n",
       "      <td>25414.0</td>\n",
       "      <td>26956.0</td>\n",
       "      <td>29071.0</td>\n",
       "      <td>31395.0</td>\n",
       "      <td>33377.0</td>\n",
       "      <td>...</td>\n",
       "      <td>33547.0</td>\n",
       "      <td>32668.0</td>\n",
       "      <td>32404.0</td>\n",
       "      <td>32121.0</td>\n",
       "      <td>32044.0</td>\n",
       "      <td>34188.0</td>\n",
       "      <td>35768.0</td>\n",
       "      <td>34789.0</td>\n",
       "      <td>32301.0</td>\n",
       "      <td>29336.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-12-08</th>\n",
       "      <td>26589.0</td>\n",
       "      <td>25191.0</td>\n",
       "      <td>23966.0</td>\n",
       "      <td>23125.0</td>\n",
       "      <td>22650.0</td>\n",
       "      <td>22406.0</td>\n",
       "      <td>22428.0</td>\n",
       "      <td>22115.0</td>\n",
       "      <td>22616.0</td>\n",
       "      <td>24240.0</td>\n",
       "      <td>...</td>\n",
       "      <td>33613.0</td>\n",
       "      <td>33216.0</td>\n",
       "      <td>33060.0</td>\n",
       "      <td>32704.0</td>\n",
       "      <td>31895.0</td>\n",
       "      <td>31776.0</td>\n",
       "      <td>33445.0</td>\n",
       "      <td>35217.0</td>\n",
       "      <td>32555.0</td>\n",
       "      <td>29863.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-12-09</th>\n",
       "      <td>26155.0</td>\n",
       "      <td>24884.0</td>\n",
       "      <td>24140.0</td>\n",
       "      <td>23805.0</td>\n",
       "      <td>23665.0</td>\n",
       "      <td>24053.0</td>\n",
       "      <td>26228.0</td>\n",
       "      <td>29285.0</td>\n",
       "      <td>31054.0</td>\n",
       "      <td>32434.0</td>\n",
       "      <td>...</td>\n",
       "      <td>27530.0</td>\n",
       "      <td>26271.0</td>\n",
       "      <td>25460.0</td>\n",
       "      <td>25137.0</td>\n",
       "      <td>24971.0</td>\n",
       "      <td>25277.0</td>\n",
       "      <td>26017.0</td>\n",
       "      <td>27483.0</td>\n",
       "      <td>26875.0</td>\n",
       "      <td>25171.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-12-10</th>\n",
       "      <td>24752.0</td>\n",
       "      <td>23491.0</td>\n",
       "      <td>22544.0</td>\n",
       "      <td>22088.0</td>\n",
       "      <td>21687.0</td>\n",
       "      <td>21360.0</td>\n",
       "      <td>21380.0</td>\n",
       "      <td>22265.0</td>\n",
       "      <td>22657.0</td>\n",
       "      <td>24274.0</td>\n",
       "      <td>...</td>\n",
       "      <td>31601.0</td>\n",
       "      <td>31098.0</td>\n",
       "      <td>31048.0</td>\n",
       "      <td>30875.0</td>\n",
       "      <td>30389.0</td>\n",
       "      <td>30143.0</td>\n",
       "      <td>30364.0</td>\n",
       "      <td>30756.0</td>\n",
       "      <td>29915.0</td>\n",
       "      <td>27434.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-12-11</th>\n",
       "      <td>24437.0</td>\n",
       "      <td>22865.0</td>\n",
       "      <td>21969.0</td>\n",
       "      <td>21664.0</td>\n",
       "      <td>21576.0</td>\n",
       "      <td>22475.0</td>\n",
       "      <td>25431.0</td>\n",
       "      <td>29533.0</td>\n",
       "      <td>31533.0</td>\n",
       "      <td>32618.0</td>\n",
       "      <td>...</td>\n",
       "      <td>35869.0</td>\n",
       "      <td>35308.0</td>\n",
       "      <td>35509.0</td>\n",
       "      <td>35397.0</td>\n",
       "      <td>34752.0</td>\n",
       "      <td>34093.0</td>\n",
       "      <td>33506.0</td>\n",
       "      <td>33098.0</td>\n",
       "      <td>32485.0</td>\n",
       "      <td>30418.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-12-12</th>\n",
       "      <td>27325.0</td>\n",
       "      <td>25461.0</td>\n",
       "      <td>24351.0</td>\n",
       "      <td>23940.0</td>\n",
       "      <td>23963.0</td>\n",
       "      <td>24568.0</td>\n",
       "      <td>27192.0</td>\n",
       "      <td>31879.0</td>\n",
       "      <td>34447.0</td>\n",
       "      <td>35252.0</td>\n",
       "      <td>...</td>\n",
       "      <td>28990.0</td>\n",
       "      <td>28634.0</td>\n",
       "      <td>28102.0</td>\n",
       "      <td>27699.0</td>\n",
       "      <td>27567.0</td>\n",
       "      <td>27444.0</td>\n",
       "      <td>27596.0</td>\n",
       "      <td>29247.0</td>\n",
       "      <td>29348.0</td>\n",
       "      <td>27795.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-12-13</th>\n",
       "      <td>27560.0</td>\n",
       "      <td>25679.0</td>\n",
       "      <td>24466.0</td>\n",
       "      <td>23909.0</td>\n",
       "      <td>23895.0</td>\n",
       "      <td>24770.0</td>\n",
       "      <td>27396.0</td>\n",
       "      <td>31955.0</td>\n",
       "      <td>34486.0</td>\n",
       "      <td>35441.0</td>\n",
       "      <td>...</td>\n",
       "      <td>34748.0</td>\n",
       "      <td>34381.0</td>\n",
       "      <td>34258.0</td>\n",
       "      <td>34185.0</td>\n",
       "      <td>33548.0</td>\n",
       "      <td>33052.0</td>\n",
       "      <td>33733.0</td>\n",
       "      <td>33900.0</td>\n",
       "      <td>30864.0</td>\n",
       "      <td>28453.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-12-14</th>\n",
       "      <td>28303.0</td>\n",
       "      <td>26284.0</td>\n",
       "      <td>24931.0</td>\n",
       "      <td>24422.0</td>\n",
       "      <td>24255.0</td>\n",
       "      <td>24996.0</td>\n",
       "      <td>27539.0</td>\n",
       "      <td>32067.0</td>\n",
       "      <td>34698.0</td>\n",
       "      <td>35663.0</td>\n",
       "      <td>...</td>\n",
       "      <td>26386.0</td>\n",
       "      <td>25106.0</td>\n",
       "      <td>24465.0</td>\n",
       "      <td>24068.0</td>\n",
       "      <td>24018.0</td>\n",
       "      <td>25036.0</td>\n",
       "      <td>27411.0</td>\n",
       "      <td>27375.0</td>\n",
       "      <td>26204.0</td>\n",
       "      <td>24516.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-12-15</th>\n",
       "      <td>27979.0</td>\n",
       "      <td>26094.0</td>\n",
       "      <td>24605.0</td>\n",
       "      <td>23691.0</td>\n",
       "      <td>23430.0</td>\n",
       "      <td>23281.0</td>\n",
       "      <td>23831.0</td>\n",
       "      <td>25342.0</td>\n",
       "      <td>27081.0</td>\n",
       "      <td>29602.0</td>\n",
       "      <td>...</td>\n",
       "      <td>32458.0</td>\n",
       "      <td>31978.0</td>\n",
       "      <td>31625.0</td>\n",
       "      <td>31945.0</td>\n",
       "      <td>33727.0</td>\n",
       "      <td>34366.0</td>\n",
       "      <td>34706.0</td>\n",
       "      <td>33582.0</td>\n",
       "      <td>30953.0</td>\n",
       "      <td>28232.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-12-16</th>\n",
       "      <td>26136.0</td>\n",
       "      <td>24182.0</td>\n",
       "      <td>22707.0</td>\n",
       "      <td>21841.0</td>\n",
       "      <td>21543.0</td>\n",
       "      <td>21398.0</td>\n",
       "      <td>21882.0</td>\n",
       "      <td>22793.0</td>\n",
       "      <td>23515.0</td>\n",
       "      <td>25653.0</td>\n",
       "      <td>...</td>\n",
       "      <td>34191.0</td>\n",
       "      <td>33899.0</td>\n",
       "      <td>33954.0</td>\n",
       "      <td>34651.0</td>\n",
       "      <td>36213.0</td>\n",
       "      <td>36490.0</td>\n",
       "      <td>36663.0</td>\n",
       "      <td>35684.0</td>\n",
       "      <td>32893.0</td>\n",
       "      <td>29689.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-12-17</th>\n",
       "      <td>25677.0</td>\n",
       "      <td>23998.0</td>\n",
       "      <td>22900.0</td>\n",
       "      <td>22515.0</td>\n",
       "      <td>22631.0</td>\n",
       "      <td>23603.0</td>\n",
       "      <td>26865.0</td>\n",
       "      <td>31683.0</td>\n",
       "      <td>34826.0</td>\n",
       "      <td>35999.0</td>\n",
       "      <td>...</td>\n",
       "      <td>35012.0</td>\n",
       "      <td>34626.0</td>\n",
       "      <td>34613.0</td>\n",
       "      <td>35033.0</td>\n",
       "      <td>36549.0</td>\n",
       "      <td>37065.0</td>\n",
       "      <td>37179.0</td>\n",
       "      <td>36201.0</td>\n",
       "      <td>33400.0</td>\n",
       "      <td>30339.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-12-18</th>\n",
       "      <td>27932.0</td>\n",
       "      <td>25927.0</td>\n",
       "      <td>24876.0</td>\n",
       "      <td>24389.0</td>\n",
       "      <td>24433.0</td>\n",
       "      <td>25124.0</td>\n",
       "      <td>27995.0</td>\n",
       "      <td>32711.0</td>\n",
       "      <td>35654.0</td>\n",
       "      <td>36692.0</td>\n",
       "      <td>...</td>\n",
       "      <td>33965.0</td>\n",
       "      <td>33305.0</td>\n",
       "      <td>33011.0</td>\n",
       "      <td>33485.0</td>\n",
       "      <td>35369.0</td>\n",
       "      <td>35708.0</td>\n",
       "      <td>35655.0</td>\n",
       "      <td>34758.0</td>\n",
       "      <td>32518.0</td>\n",
       "      <td>29979.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-12-19</th>\n",
       "      <td>28144.0</td>\n",
       "      <td>26046.0</td>\n",
       "      <td>24800.0</td>\n",
       "      <td>24218.0</td>\n",
       "      <td>24142.0</td>\n",
       "      <td>24754.0</td>\n",
       "      <td>27642.0</td>\n",
       "      <td>32381.0</td>\n",
       "      <td>35277.0</td>\n",
       "      <td>36093.0</td>\n",
       "      <td>...</td>\n",
       "      <td>30493.0</td>\n",
       "      <td>29424.0</td>\n",
       "      <td>28838.0</td>\n",
       "      <td>29362.0</td>\n",
       "      <td>31262.0</td>\n",
       "      <td>31838.0</td>\n",
       "      <td>32068.0</td>\n",
       "      <td>31728.0</td>\n",
       "      <td>30189.0</td>\n",
       "      <td>28303.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-12-20</th>\n",
       "      <td>27987.0</td>\n",
       "      <td>25935.0</td>\n",
       "      <td>24684.0</td>\n",
       "      <td>24040.0</td>\n",
       "      <td>23989.0</td>\n",
       "      <td>24642.0</td>\n",
       "      <td>27262.0</td>\n",
       "      <td>31876.0</td>\n",
       "      <td>34912.0</td>\n",
       "      <td>35642.0</td>\n",
       "      <td>...</td>\n",
       "      <td>29529.0</td>\n",
       "      <td>28227.0</td>\n",
       "      <td>27340.0</td>\n",
       "      <td>27558.0</td>\n",
       "      <td>29698.0</td>\n",
       "      <td>30958.0</td>\n",
       "      <td>31890.0</td>\n",
       "      <td>31965.0</td>\n",
       "      <td>30672.0</td>\n",
       "      <td>28319.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-12-21</th>\n",
       "      <td>27831.0</td>\n",
       "      <td>25772.0</td>\n",
       "      <td>24320.0</td>\n",
       "      <td>23784.0</td>\n",
       "      <td>23656.0</td>\n",
       "      <td>24203.0</td>\n",
       "      <td>26675.0</td>\n",
       "      <td>31103.0</td>\n",
       "      <td>33847.0</td>\n",
       "      <td>34653.0</td>\n",
       "      <td>...</td>\n",
       "      <td>34491.0</td>\n",
       "      <td>33938.0</td>\n",
       "      <td>33833.0</td>\n",
       "      <td>34562.0</td>\n",
       "      <td>36606.0</td>\n",
       "      <td>36987.0</td>\n",
       "      <td>37448.0</td>\n",
       "      <td>36205.0</td>\n",
       "      <td>33444.0</td>\n",
       "      <td>30171.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-12-22</th>\n",
       "      <td>26591.0</td>\n",
       "      <td>24533.0</td>\n",
       "      <td>23053.0</td>\n",
       "      <td>22329.0</td>\n",
       "      <td>21891.0</td>\n",
       "      <td>21853.0</td>\n",
       "      <td>22551.0</td>\n",
       "      <td>24115.0</td>\n",
       "      <td>25761.0</td>\n",
       "      <td>28444.0</td>\n",
       "      <td>...</td>\n",
       "      <td>35318.0</td>\n",
       "      <td>34890.0</td>\n",
       "      <td>34799.0</td>\n",
       "      <td>35776.0</td>\n",
       "      <td>37183.0</td>\n",
       "      <td>37454.0</td>\n",
       "      <td>37579.0</td>\n",
       "      <td>36681.0</td>\n",
       "      <td>33880.0</td>\n",
       "      <td>30489.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-12-23</th>\n",
       "      <td>24956.0</td>\n",
       "      <td>22910.0</td>\n",
       "      <td>21599.0</td>\n",
       "      <td>20744.0</td>\n",
       "      <td>20397.0</td>\n",
       "      <td>20439.0</td>\n",
       "      <td>20989.0</td>\n",
       "      <td>22014.0</td>\n",
       "      <td>22978.0</td>\n",
       "      <td>25196.0</td>\n",
       "      <td>...</td>\n",
       "      <td>34226.0</td>\n",
       "      <td>33710.0</td>\n",
       "      <td>33574.0</td>\n",
       "      <td>34426.0</td>\n",
       "      <td>36288.0</td>\n",
       "      <td>36610.0</td>\n",
       "      <td>36694.0</td>\n",
       "      <td>35971.0</td>\n",
       "      <td>33405.0</td>\n",
       "      <td>30292.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-12-24</th>\n",
       "      <td>24074.0</td>\n",
       "      <td>22040.0</td>\n",
       "      <td>20759.0</td>\n",
       "      <td>20087.0</td>\n",
       "      <td>19894.0</td>\n",
       "      <td>20299.0</td>\n",
       "      <td>21617.0</td>\n",
       "      <td>23853.0</td>\n",
       "      <td>25773.0</td>\n",
       "      <td>28255.0</td>\n",
       "      <td>...</td>\n",
       "      <td>33505.0</td>\n",
       "      <td>33053.0</td>\n",
       "      <td>32899.0</td>\n",
       "      <td>33647.0</td>\n",
       "      <td>35657.0</td>\n",
       "      <td>35967.0</td>\n",
       "      <td>36154.0</td>\n",
       "      <td>35422.0</td>\n",
       "      <td>33081.0</td>\n",
       "      <td>30075.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-12-25</th>\n",
       "      <td>22499.0</td>\n",
       "      <td>21353.0</td>\n",
       "      <td>20021.0</td>\n",
       "      <td>18899.0</td>\n",
       "      <td>18279.0</td>\n",
       "      <td>18179.0</td>\n",
       "      <td>18472.0</td>\n",
       "      <td>19012.0</td>\n",
       "      <td>19244.0</td>\n",
       "      <td>20540.0</td>\n",
       "      <td>...</td>\n",
       "      <td>32252.0</td>\n",
       "      <td>31475.0</td>\n",
       "      <td>31178.0</td>\n",
       "      <td>31761.0</td>\n",
       "      <td>33563.0</td>\n",
       "      <td>34041.0</td>\n",
       "      <td>33953.0</td>\n",
       "      <td>33098.0</td>\n",
       "      <td>31194.0</td>\n",
       "      <td>28684.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-12-26</th>\n",
       "      <td>22138.0</td>\n",
       "      <td>20267.0</td>\n",
       "      <td>19102.0</td>\n",
       "      <td>18598.0</td>\n",
       "      <td>18522.0</td>\n",
       "      <td>19135.0</td>\n",
       "      <td>20917.0</td>\n",
       "      <td>23860.0</td>\n",
       "      <td>26435.0</td>\n",
       "      <td>28792.0</td>\n",
       "      <td>...</td>\n",
       "      <td>29157.0</td>\n",
       "      <td>28044.0</td>\n",
       "      <td>27345.0</td>\n",
       "      <td>27815.0</td>\n",
       "      <td>29901.0</td>\n",
       "      <td>30400.0</td>\n",
       "      <td>30931.0</td>\n",
       "      <td>30580.0</td>\n",
       "      <td>29293.0</td>\n",
       "      <td>27320.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-12-27</th>\n",
       "      <td>24679.0</td>\n",
       "      <td>22620.0</td>\n",
       "      <td>21316.0</td>\n",
       "      <td>20739.0</td>\n",
       "      <td>20676.0</td>\n",
       "      <td>21231.0</td>\n",
       "      <td>23195.0</td>\n",
       "      <td>26398.0</td>\n",
       "      <td>29222.0</td>\n",
       "      <td>31599.0</td>\n",
       "      <td>...</td>\n",
       "      <td>27598.0</td>\n",
       "      <td>26415.0</td>\n",
       "      <td>25724.0</td>\n",
       "      <td>26020.0</td>\n",
       "      <td>28361.0</td>\n",
       "      <td>29187.0</td>\n",
       "      <td>29880.0</td>\n",
       "      <td>29973.0</td>\n",
       "      <td>28806.0</td>\n",
       "      <td>26608.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-12-28</th>\n",
       "      <td>25147.0</td>\n",
       "      <td>23068.0</td>\n",
       "      <td>21779.0</td>\n",
       "      <td>21244.0</td>\n",
       "      <td>21132.0</td>\n",
       "      <td>21642.0</td>\n",
       "      <td>23591.0</td>\n",
       "      <td>26804.0</td>\n",
       "      <td>29506.0</td>\n",
       "      <td>31863.0</td>\n",
       "      <td>...</td>\n",
       "      <td>27707.0</td>\n",
       "      <td>26728.0</td>\n",
       "      <td>26319.0</td>\n",
       "      <td>26882.0</td>\n",
       "      <td>29305.0</td>\n",
       "      <td>29570.0</td>\n",
       "      <td>28474.0</td>\n",
       "      <td>26583.0</td>\n",
       "      <td>24287.0</td>\n",
       "      <td>23231.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-12-29</th>\n",
       "      <td>25709.0</td>\n",
       "      <td>23622.0</td>\n",
       "      <td>22122.0</td>\n",
       "      <td>21368.0</td>\n",
       "      <td>21084.0</td>\n",
       "      <td>21168.0</td>\n",
       "      <td>21927.0</td>\n",
       "      <td>23347.0</td>\n",
       "      <td>24931.0</td>\n",
       "      <td>27300.0</td>\n",
       "      <td>...</td>\n",
       "      <td>23736.0</td>\n",
       "      <td>22063.0</td>\n",
       "      <td>21618.0</td>\n",
       "      <td>22204.0</td>\n",
       "      <td>24487.0</td>\n",
       "      <td>25638.0</td>\n",
       "      <td>26518.0</td>\n",
       "      <td>26921.0</td>\n",
       "      <td>26318.0</td>\n",
       "      <td>24341.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-12-30</th>\n",
       "      <td>24922.0</td>\n",
       "      <td>22772.0</td>\n",
       "      <td>21301.0</td>\n",
       "      <td>20386.0</td>\n",
       "      <td>20103.0</td>\n",
       "      <td>20112.0</td>\n",
       "      <td>20651.0</td>\n",
       "      <td>21639.0</td>\n",
       "      <td>22662.0</td>\n",
       "      <td>24759.0</td>\n",
       "      <td>...</td>\n",
       "      <td>29732.0</td>\n",
       "      <td>28525.0</td>\n",
       "      <td>28144.0</td>\n",
       "      <td>28627.0</td>\n",
       "      <td>30534.0</td>\n",
       "      <td>31167.0</td>\n",
       "      <td>31577.0</td>\n",
       "      <td>31459.0</td>\n",
       "      <td>29812.0</td>\n",
       "      <td>27108.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-12-31</th>\n",
       "      <td>24312.0</td>\n",
       "      <td>22140.0</td>\n",
       "      <td>20851.0</td>\n",
       "      <td>20200.0</td>\n",
       "      <td>20006.0</td>\n",
       "      <td>20366.0</td>\n",
       "      <td>21723.0</td>\n",
       "      <td>23850.0</td>\n",
       "      <td>25969.0</td>\n",
       "      <td>28382.0</td>\n",
       "      <td>...</td>\n",
       "      <td>31399.0</td>\n",
       "      <td>30469.0</td>\n",
       "      <td>30184.0</td>\n",
       "      <td>30819.0</td>\n",
       "      <td>32522.0</td>\n",
       "      <td>32940.0</td>\n",
       "      <td>33142.0</td>\n",
       "      <td>32669.0</td>\n",
       "      <td>30753.0</td>\n",
       "      <td>27882.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1092 rows × 120 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            t-0 h_0  t-0 h_1  t-0 h_2  t-0 h_3  t-0 h_4  t-0 h_5  t-0 h_6  \\\n",
       "date                                                                        \n",
       "2016-01-05  23642.0  21990.0  20629.0  19865.0  19446.0  19248.0  19296.0   \n",
       "2016-01-06  25135.0  23717.0  22747.0  22440.0  22396.0  22737.0  24350.0   \n",
       "2016-01-07  28425.0  26609.0  25442.0  24864.0  24609.0  24776.0  26062.0   \n",
       "2016-01-08  26986.0  25125.0  23969.0  23281.0  23088.0  23573.0  25487.0   \n",
       "2016-01-09  28284.0  26487.0  25264.0  24744.0  24505.0  24766.0  26459.0   \n",
       "2016-01-10  25362.0  24135.0  23117.0  22487.0  22063.0  21869.0  22198.0   \n",
       "2016-01-11  22557.0  21261.0  20403.0  19960.0  19710.0  19764.0  20230.0   \n",
       "2016-01-12  27046.0  25058.0  23874.0  23410.0  23365.0  24116.0  26763.0   \n",
       "2016-01-13  27421.0  25382.0  24219.0  23562.0  23555.0  24198.0  26792.0   \n",
       "2016-01-14  27936.0  25936.0  24731.0  24167.0  24087.0  24584.0  27035.0   \n",
       "2016-01-15  27672.0  25688.0  24408.0  23893.0  23765.0  24392.0  26975.0   \n",
       "2016-01-16  28539.0  26495.0  24938.0  24058.0  23633.0  23500.0  24176.0   \n",
       "2016-01-17  27057.0  24791.0  23259.0  22417.0  21960.0  21919.0  22384.0   \n",
       "2016-01-18  26586.0  24656.0  23420.0  22859.0  22742.0  23866.0  27094.0   \n",
       "2016-01-19  27958.0  25831.0  24589.0  24185.0  24103.0  24736.0  27449.0   \n",
       "2016-01-20  28222.0  25955.0  24813.0  24307.0  24212.0  24793.0  27378.0   \n",
       "2016-01-21  27991.0  25797.0  24501.0  23998.0  23886.0  24549.0  27280.0   \n",
       "2016-01-22  28033.0  26102.0  24711.0  24148.0  24103.0  24749.0  27295.0   \n",
       "2016-01-23  27902.0  25682.0  24283.0  23496.0  23013.0  22880.0  23410.0   \n",
       "2016-01-24  25595.0  23640.0  22264.0  21493.0  21165.0  21121.0  21416.0   \n",
       "2016-01-25  25027.0  23121.0  22169.0  21953.0  22281.0  22807.0  25716.0   \n",
       "2016-01-26  27018.0  25028.0  23973.0  23498.0  23313.0  23985.0  26596.0   \n",
       "2016-01-27  27219.0  25294.0  24026.0  23580.0  23533.0  24083.0  26674.0   \n",
       "2016-01-28  27170.0  25087.0  23820.0  23349.0  23270.0  23837.0  26329.0   \n",
       "2016-01-29  27306.0  25299.0  24024.0  23490.0  23345.0  23961.0  26402.0   \n",
       "2016-01-30  27662.0  25660.0  24106.0  23276.0  22893.0  22841.0  23253.0   \n",
       "2016-01-31  25833.0  23820.0  22863.0  22056.0  21622.0  21588.0  21940.0   \n",
       "2016-02-01  22113.0  20515.0  19284.0  18637.0  18352.0  18574.0  19751.0   \n",
       "2016-02-02  26810.0  24903.0  23819.0  23418.0  23240.0  23890.0  26441.0   \n",
       "2016-02-03  27578.0  25540.0  24448.0  23929.0  23895.0  24570.0  27320.0   \n",
       "...             ...      ...      ...      ...      ...      ...      ...   \n",
       "2018-12-02  26971.0  25062.0  23779.0  23460.0  23515.0  24193.0  27254.0   \n",
       "2018-12-03  25503.0  23830.0  22753.0  22533.0  22536.0  23495.0  26793.0   \n",
       "2018-12-04  27710.0  25730.0  24636.0  24126.0  23915.0  24437.0  26962.0   \n",
       "2018-12-05  25670.0  24166.0  23019.0  22349.0  22050.0  21894.0  22201.0   \n",
       "2018-12-06  25732.0  24356.0  23490.0  23125.0  22978.0  23300.0  24976.0   \n",
       "2018-12-07  28518.0  26746.0  25737.0  25253.0  25078.0  25414.0  26956.0   \n",
       "2018-12-08  26589.0  25191.0  23966.0  23125.0  22650.0  22406.0  22428.0   \n",
       "2018-12-09  26155.0  24884.0  24140.0  23805.0  23665.0  24053.0  26228.0   \n",
       "2018-12-10  24752.0  23491.0  22544.0  22088.0  21687.0  21360.0  21380.0   \n",
       "2018-12-11  24437.0  22865.0  21969.0  21664.0  21576.0  22475.0  25431.0   \n",
       "2018-12-12  27325.0  25461.0  24351.0  23940.0  23963.0  24568.0  27192.0   \n",
       "2018-12-13  27560.0  25679.0  24466.0  23909.0  23895.0  24770.0  27396.0   \n",
       "2018-12-14  28303.0  26284.0  24931.0  24422.0  24255.0  24996.0  27539.0   \n",
       "2018-12-15  27979.0  26094.0  24605.0  23691.0  23430.0  23281.0  23831.0   \n",
       "2018-12-16  26136.0  24182.0  22707.0  21841.0  21543.0  21398.0  21882.0   \n",
       "2018-12-17  25677.0  23998.0  22900.0  22515.0  22631.0  23603.0  26865.0   \n",
       "2018-12-18  27932.0  25927.0  24876.0  24389.0  24433.0  25124.0  27995.0   \n",
       "2018-12-19  28144.0  26046.0  24800.0  24218.0  24142.0  24754.0  27642.0   \n",
       "2018-12-20  27987.0  25935.0  24684.0  24040.0  23989.0  24642.0  27262.0   \n",
       "2018-12-21  27831.0  25772.0  24320.0  23784.0  23656.0  24203.0  26675.0   \n",
       "2018-12-22  26591.0  24533.0  23053.0  22329.0  21891.0  21853.0  22551.0   \n",
       "2018-12-23  24956.0  22910.0  21599.0  20744.0  20397.0  20439.0  20989.0   \n",
       "2018-12-24  24074.0  22040.0  20759.0  20087.0  19894.0  20299.0  21617.0   \n",
       "2018-12-25  22499.0  21353.0  20021.0  18899.0  18279.0  18179.0  18472.0   \n",
       "2018-12-26  22138.0  20267.0  19102.0  18598.0  18522.0  19135.0  20917.0   \n",
       "2018-12-27  24679.0  22620.0  21316.0  20739.0  20676.0  21231.0  23195.0   \n",
       "2018-12-28  25147.0  23068.0  21779.0  21244.0  21132.0  21642.0  23591.0   \n",
       "2018-12-29  25709.0  23622.0  22122.0  21368.0  21084.0  21168.0  21927.0   \n",
       "2018-12-30  24922.0  22772.0  21301.0  20386.0  20103.0  20112.0  20651.0   \n",
       "2018-12-31  24312.0  22140.0  20851.0  20200.0  20006.0  20366.0  21723.0   \n",
       "\n",
       "            t-0 h_7  t-0 h_8  t-0 h_9  ...  t-4 h_14  t-4 h_15  t-4 h_16  \\\n",
       "date                                   ...                                 \n",
       "2016-01-05  18956.0  20072.0  21911.0  ...   23265.0   22061.0   21481.0   \n",
       "2016-01-06  26788.0  28705.0  30029.0  ...   32099.0   31449.0   31179.0   \n",
       "2016-01-07  28023.0  30354.0  32641.0  ...   33029.0   32344.0   31927.0   \n",
       "2016-01-08  27299.0  29776.0  31487.0  ...   31594.0   30376.0   29915.0   \n",
       "2016-01-09  28734.0  30505.0  32582.0  ...   23378.0   22190.0   21549.0   \n",
       "2016-01-10  23304.0  23972.0  25986.0  ...   30470.0   29970.0   29979.0   \n",
       "2016-01-11  20643.0  21168.0  22967.0  ...   34702.0   33939.0   33753.0   \n",
       "2016-01-12  30980.0  33422.0  34280.0  ...   35288.0   34479.0   34240.0   \n",
       "2016-01-13  31474.0  34420.0  35186.0  ...   36004.0   35417.0   35492.0   \n",
       "2016-01-14  31511.0  34484.0  35004.0  ...   27507.0   26346.0   25651.0   \n",
       "2016-01-15  31392.0  34356.0  35177.0  ...   24807.0   23577.0   22945.0   \n",
       "2016-01-16  25631.0  27257.0  29776.0  ...   33651.0   33084.0   33033.0   \n",
       "2016-01-17  23181.0  23900.0  25833.0  ...   33798.0   33252.0   33146.0   \n",
       "2016-01-18  32027.0  35569.0  36437.0  ...   34366.0   33763.0   33641.0   \n",
       "2016-01-19  32326.0  35535.0  36174.0  ...   34082.0   33308.0   33078.0   \n",
       "2016-01-20  32354.0  35577.0  36514.0  ...   30663.0   29402.0   28726.0   \n",
       "2016-01-21  32095.0  35003.0  35707.0  ...   29630.0   28555.0   27787.0   \n",
       "2016-01-22  31913.0  34785.0  35569.0  ...   35096.0   34498.0   34437.0   \n",
       "2016-01-23  25031.0  26616.0  29158.0  ...   34662.0   34144.0   34045.0   \n",
       "2016-01-24  22033.0  22686.0  24652.0  ...   34434.0   33737.0   33688.0   \n",
       "2016-01-25  30429.0  33289.0  34131.0  ...   34331.0   33846.0   34028.0   \n",
       "2016-01-26  31080.0  33918.0  34567.0  ...   33741.0   33041.0   32828.0   \n",
       "2016-01-27  31367.0  33898.0  34723.0  ...   29387.0   28137.0   27400.0   \n",
       "2016-01-28  30815.0  33507.0  34188.0  ...   27160.0   25942.0   25285.0   \n",
       "2016-01-29  30730.0  33390.0  34230.0  ...   32707.0   31908.0   31660.0   \n",
       "2016-01-30  24655.0  26373.0  28990.0  ...   32994.0   32401.0   32197.0   \n",
       "2016-01-31  22543.0  23143.0  24923.0  ...   33087.0   32455.0   32179.0   \n",
       "2016-02-01  20857.0  22156.0  24125.0  ...   33404.0   32958.0   32824.0   \n",
       "2016-02-02  30975.0  33582.0  34277.0  ...   32993.0   32371.0   32086.0   \n",
       "2016-02-03  31510.0  34134.0  35154.0  ...   29306.0   28055.0   27312.0   \n",
       "...             ...      ...      ...  ...       ...       ...       ...   \n",
       "2018-12-02  32070.0  35028.0  36940.0  ...   33442.0   33161.0   32972.0   \n",
       "2018-12-03  30850.0  33785.0  34977.0  ...   33839.0   33492.0   33408.0   \n",
       "2018-12-04  30781.0  33269.0  34663.0  ...   33498.0   32736.0   32280.0   \n",
       "2018-12-05  22448.0  24394.0  26495.0  ...   35588.0   34803.0   34445.0   \n",
       "2018-12-06  27606.0  29701.0  30960.0  ...   36775.0   36021.0   35638.0   \n",
       "2018-12-07  29071.0  31395.0  33377.0  ...   33547.0   32668.0   32404.0   \n",
       "2018-12-08  22115.0  22616.0  24240.0  ...   33613.0   33216.0   33060.0   \n",
       "2018-12-09  29285.0  31054.0  32434.0  ...   27530.0   26271.0   25460.0   \n",
       "2018-12-10  22265.0  22657.0  24274.0  ...   31601.0   31098.0   31048.0   \n",
       "2018-12-11  29533.0  31533.0  32618.0  ...   35869.0   35308.0   35509.0   \n",
       "2018-12-12  31879.0  34447.0  35252.0  ...   28990.0   28634.0   28102.0   \n",
       "2018-12-13  31955.0  34486.0  35441.0  ...   34748.0   34381.0   34258.0   \n",
       "2018-12-14  32067.0  34698.0  35663.0  ...   26386.0   25106.0   24465.0   \n",
       "2018-12-15  25342.0  27081.0  29602.0  ...   32458.0   31978.0   31625.0   \n",
       "2018-12-16  22793.0  23515.0  25653.0  ...   34191.0   33899.0   33954.0   \n",
       "2018-12-17  31683.0  34826.0  35999.0  ...   35012.0   34626.0   34613.0   \n",
       "2018-12-18  32711.0  35654.0  36692.0  ...   33965.0   33305.0   33011.0   \n",
       "2018-12-19  32381.0  35277.0  36093.0  ...   30493.0   29424.0   28838.0   \n",
       "2018-12-20  31876.0  34912.0  35642.0  ...   29529.0   28227.0   27340.0   \n",
       "2018-12-21  31103.0  33847.0  34653.0  ...   34491.0   33938.0   33833.0   \n",
       "2018-12-22  24115.0  25761.0  28444.0  ...   35318.0   34890.0   34799.0   \n",
       "2018-12-23  22014.0  22978.0  25196.0  ...   34226.0   33710.0   33574.0   \n",
       "2018-12-24  23853.0  25773.0  28255.0  ...   33505.0   33053.0   32899.0   \n",
       "2018-12-25  19012.0  19244.0  20540.0  ...   32252.0   31475.0   31178.0   \n",
       "2018-12-26  23860.0  26435.0  28792.0  ...   29157.0   28044.0   27345.0   \n",
       "2018-12-27  26398.0  29222.0  31599.0  ...   27598.0   26415.0   25724.0   \n",
       "2018-12-28  26804.0  29506.0  31863.0  ...   27707.0   26728.0   26319.0   \n",
       "2018-12-29  23347.0  24931.0  27300.0  ...   23736.0   22063.0   21618.0   \n",
       "2018-12-30  21639.0  22662.0  24759.0  ...   29732.0   28525.0   28144.0   \n",
       "2018-12-31  23850.0  25969.0  28382.0  ...   31399.0   30469.0   30184.0   \n",
       "\n",
       "            t-4 h_17  t-4 h_18  t-4 h_19  t-4 h_20  t-4 h_21  t-4 h_22  \\\n",
       "date                                                                     \n",
       "2016-01-05   21830.0   24291.0   25234.0   25881.0   26149.0   25610.0   \n",
       "2016-01-06   31175.0   32515.0   34967.0   35381.0   34700.0   32055.0   \n",
       "2016-01-07   31824.0   32226.0   35161.0   36599.0   35729.0   33154.0   \n",
       "2016-01-08   29633.0   29158.0   29159.0   30469.0   32482.0   30508.0   \n",
       "2016-01-09   21233.0   21298.0   21756.0   22929.0   25815.0   25843.0   \n",
       "2016-01-10   29924.0   29640.0   29409.0   29484.0   30027.0   29332.0   \n",
       "2016-01-11   33510.0   33079.0   32697.0   32172.0   31560.0   30943.0   \n",
       "2016-01-12   34101.0   33693.0   32919.0   32267.0   32709.0   32355.0   \n",
       "2016-01-13   35529.0   34992.0   34052.0   33899.0   34957.0   32547.0   \n",
       "2016-01-14   25559.0   25497.0   26352.0   28617.0   28678.0   26798.0   \n",
       "2016-01-15   23000.0   25449.0   27006.0   27672.0   27136.0   25633.0   \n",
       "2016-01-16   33961.0   35578.0   35923.0   36345.0   35454.0   32681.0   \n",
       "2016-01-17   33652.0   35573.0   36708.0   36875.0   36084.0   33413.0   \n",
       "2016-01-18   34137.0   35735.0   36701.0   36677.0   35828.0   33228.0   \n",
       "2016-01-19   33189.0   34985.0   36107.0   35951.0   35364.0   33193.0   \n",
       "2016-01-20   28691.0   30848.0   32436.0   32998.0   32956.0   31734.0   \n",
       "2016-01-21   27845.0   30332.0   32083.0   33266.0   33461.0   32212.0   \n",
       "2016-01-22   34665.0   36335.0   37564.0   37724.0   36751.0   33951.0   \n",
       "2016-01-23   34591.0   36577.0   37962.0   38071.0   37231.0   34426.0   \n",
       "2016-01-24   34107.0   35952.0   37314.0   37527.0   36520.0   33839.0   \n",
       "2016-01-25   34504.0   36109.0   37423.0   37468.0   36555.0   33817.0   \n",
       "2016-01-26   32907.0   34408.0   35512.0   35335.0   34802.0   32627.0   \n",
       "2016-01-27   27264.0   29144.0   30855.0   31189.0   31254.0   29814.0   \n",
       "2016-01-28   25271.0   27393.0   29919.0   30986.0   31188.0   30141.0   \n",
       "2016-01-29   31960.0   33634.0   35427.0   35742.0   34888.0   32218.0   \n",
       "2016-01-30   32359.0   33962.0   35859.0   36244.0   35565.0   32719.0   \n",
       "2016-01-31   32402.0   34025.0   35807.0   36066.0   35282.0   32572.0   \n",
       "2016-02-01   33062.0   34403.0   36016.0   36105.0   35306.0   32601.0   \n",
       "2016-02-02   32049.0   33235.0   34921.0   34867.0   34302.0   32177.0   \n",
       "2016-02-03   27155.0   29016.0   30999.0   31700.0   31771.0   30296.0   \n",
       "...              ...       ...       ...       ...       ...       ...   \n",
       "2018-12-02   33814.0   36115.0   36642.0   36803.0   35710.0   33018.0   \n",
       "2018-12-03   34319.0   36124.0   36702.0   36813.0   35670.0   33192.0   \n",
       "2018-12-04   32783.0   34791.0   35117.0   35104.0   33993.0   32092.0   \n",
       "2018-12-05   34702.0   36671.0   37541.0   37474.0   36841.0   34624.0   \n",
       "2018-12-06   35526.0   35755.0   38202.0   38783.0   37934.0   35230.0   \n",
       "2018-12-07   32121.0   32044.0   34188.0   35768.0   34789.0   32301.0   \n",
       "2018-12-08   32704.0   31895.0   31776.0   33445.0   35217.0   32555.0   \n",
       "2018-12-09   25137.0   24971.0   25277.0   26017.0   27483.0   26875.0   \n",
       "2018-12-10   30875.0   30389.0   30143.0   30364.0   30756.0   29915.0   \n",
       "2018-12-11   35397.0   34752.0   34093.0   33506.0   33098.0   32485.0   \n",
       "2018-12-12   27699.0   27567.0   27444.0   27596.0   29247.0   29348.0   \n",
       "2018-12-13   34185.0   33548.0   33052.0   33733.0   33900.0   30864.0   \n",
       "2018-12-14   24068.0   24018.0   25036.0   27411.0   27375.0   26204.0   \n",
       "2018-12-15   31945.0   33727.0   34366.0   34706.0   33582.0   30953.0   \n",
       "2018-12-16   34651.0   36213.0   36490.0   36663.0   35684.0   32893.0   \n",
       "2018-12-17   35033.0   36549.0   37065.0   37179.0   36201.0   33400.0   \n",
       "2018-12-18   33485.0   35369.0   35708.0   35655.0   34758.0   32518.0   \n",
       "2018-12-19   29362.0   31262.0   31838.0   32068.0   31728.0   30189.0   \n",
       "2018-12-20   27558.0   29698.0   30958.0   31890.0   31965.0   30672.0   \n",
       "2018-12-21   34562.0   36606.0   36987.0   37448.0   36205.0   33444.0   \n",
       "2018-12-22   35776.0   37183.0   37454.0   37579.0   36681.0   33880.0   \n",
       "2018-12-23   34426.0   36288.0   36610.0   36694.0   35971.0   33405.0   \n",
       "2018-12-24   33647.0   35657.0   35967.0   36154.0   35422.0   33081.0   \n",
       "2018-12-25   31761.0   33563.0   34041.0   33953.0   33098.0   31194.0   \n",
       "2018-12-26   27815.0   29901.0   30400.0   30931.0   30580.0   29293.0   \n",
       "2018-12-27   26020.0   28361.0   29187.0   29880.0   29973.0   28806.0   \n",
       "2018-12-28   26882.0   29305.0   29570.0   28474.0   26583.0   24287.0   \n",
       "2018-12-29   22204.0   24487.0   25638.0   26518.0   26921.0   26318.0   \n",
       "2018-12-30   28627.0   30534.0   31167.0   31577.0   31459.0   29812.0   \n",
       "2018-12-31   30819.0   32522.0   32940.0   33142.0   32669.0   30753.0   \n",
       "\n",
       "            t-4 h_23  \n",
       "date                  \n",
       "2016-01-05   24000.0  \n",
       "2016-01-06   28939.0  \n",
       "2016-01-07   29838.0  \n",
       "2016-01-08   28598.0  \n",
       "2016-01-09   24167.0  \n",
       "2016-01-10   26854.0  \n",
       "2016-01-11   29025.0  \n",
       "2016-01-12   29998.0  \n",
       "2016-01-13   30096.0  \n",
       "2016-01-14   24930.0  \n",
       "2016-01-15   23727.0  \n",
       "2016-01-16   29650.0  \n",
       "2016-01-17   30202.0  \n",
       "2016-01-18   30088.0  \n",
       "2016-01-19   30665.0  \n",
       "2016-01-20   29453.0  \n",
       "2016-01-21   29475.0  \n",
       "2016-01-22   30623.0  \n",
       "2016-01-23   30932.0  \n",
       "2016-01-24   30538.0  \n",
       "2016-01-25   30587.0  \n",
       "2016-01-26   30025.0  \n",
       "2016-01-27   27761.0  \n",
       "2016-01-28   27640.0  \n",
       "2016-01-29   29032.0  \n",
       "2016-01-30   29521.0  \n",
       "2016-01-31   29506.0  \n",
       "2016-02-01   29557.0  \n",
       "2016-02-02   29489.0  \n",
       "2016-02-03   28200.0  \n",
       "...              ...  \n",
       "2018-12-02   29814.0  \n",
       "2018-12-03   30066.0  \n",
       "2018-12-04   29645.0  \n",
       "2018-12-05   31942.0  \n",
       "2018-12-06   31690.0  \n",
       "2018-12-07   29336.0  \n",
       "2018-12-08   29863.0  \n",
       "2018-12-09   25171.0  \n",
       "2018-12-10   27434.0  \n",
       "2018-12-11   30418.0  \n",
       "2018-12-12   27795.0  \n",
       "2018-12-13   28453.0  \n",
       "2018-12-14   24516.0  \n",
       "2018-12-15   28232.0  \n",
       "2018-12-16   29689.0  \n",
       "2018-12-17   30339.0  \n",
       "2018-12-18   29979.0  \n",
       "2018-12-19   28303.0  \n",
       "2018-12-20   28319.0  \n",
       "2018-12-21   30171.0  \n",
       "2018-12-22   30489.0  \n",
       "2018-12-23   30292.0  \n",
       "2018-12-24   30075.0  \n",
       "2018-12-25   28684.0  \n",
       "2018-12-26   27320.0  \n",
       "2018-12-27   26608.0  \n",
       "2018-12-28   23231.0  \n",
       "2018-12-29   24341.0  \n",
       "2018-12-30   27108.0  \n",
       "2018-12-31   27882.0  \n",
       "\n",
       "[1092 rows x 120 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#example of shifting data by 1, 2, 3, 7, 14, 30 days\n",
    "shifts_list = [1, 2, 3, 4]\n",
    "\n",
    "load_features = make_shifted_features(loads, shifts_list)\n",
    "\n",
    "load_features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1066, 168)"
      ]
     },
     "execution_count": 132,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#check dataframe size\n",
    "# 6 additional features plus the original = 24*7 = 168 expected columns\n",
    "# maximum shift is 30 so expected length is 1096-30= 1066\n",
    "load_features.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>t0 h_0</th>\n",
       "      <th>t0 h_1</th>\n",
       "      <th>t0 h_2</th>\n",
       "      <th>t0 h_3</th>\n",
       "      <th>t0 h_4</th>\n",
       "      <th>t0 h_5</th>\n",
       "      <th>t0 h_6</th>\n",
       "      <th>t0 h_7</th>\n",
       "      <th>t0 h_8</th>\n",
       "      <th>t0 h_9</th>\n",
       "      <th>...</th>\n",
       "      <th>t-30 h_14</th>\n",
       "      <th>t-30 h_15</th>\n",
       "      <th>t-30 h_16</th>\n",
       "      <th>t-30 h_17</th>\n",
       "      <th>t-30 h_18</th>\n",
       "      <th>t-30 h_19</th>\n",
       "      <th>t-30 h_20</th>\n",
       "      <th>t-30 h_21</th>\n",
       "      <th>t-30 h_22</th>\n",
       "      <th>t-30 h_23</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2018-11-27</th>\n",
       "      <td>27137.0</td>\n",
       "      <td>25346.0</td>\n",
       "      <td>24202.0</td>\n",
       "      <td>23659.0</td>\n",
       "      <td>23656.0</td>\n",
       "      <td>24337.0</td>\n",
       "      <td>27062.0</td>\n",
       "      <td>31591.0</td>\n",
       "      <td>34224.0</td>\n",
       "      <td>35361.0</td>\n",
       "      <td>...</td>\n",
       "      <td>31399.0</td>\n",
       "      <td>30469.0</td>\n",
       "      <td>30184.0</td>\n",
       "      <td>30819.0</td>\n",
       "      <td>32522.0</td>\n",
       "      <td>32940.0</td>\n",
       "      <td>33142.0</td>\n",
       "      <td>32669.0</td>\n",
       "      <td>30753.0</td>\n",
       "      <td>27882.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-11-28</th>\n",
       "      <td>27338.0</td>\n",
       "      <td>25444.0</td>\n",
       "      <td>24283.0</td>\n",
       "      <td>23897.0</td>\n",
       "      <td>23816.0</td>\n",
       "      <td>24510.0</td>\n",
       "      <td>27245.0</td>\n",
       "      <td>32072.0</td>\n",
       "      <td>34684.0</td>\n",
       "      <td>35360.0</td>\n",
       "      <td>...</td>\n",
       "      <td>31308.0</td>\n",
       "      <td>30281.0</td>\n",
       "      <td>29935.0</td>\n",
       "      <td>30428.0</td>\n",
       "      <td>32248.0</td>\n",
       "      <td>32728.0</td>\n",
       "      <td>32642.0</td>\n",
       "      <td>32155.0</td>\n",
       "      <td>30428.0</td>\n",
       "      <td>28015.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-11-29</th>\n",
       "      <td>27462.0</td>\n",
       "      <td>25490.0</td>\n",
       "      <td>24294.0</td>\n",
       "      <td>23889.0</td>\n",
       "      <td>23926.0</td>\n",
       "      <td>24544.0</td>\n",
       "      <td>27380.0</td>\n",
       "      <td>31927.0</td>\n",
       "      <td>34451.0</td>\n",
       "      <td>35313.0</td>\n",
       "      <td>...</td>\n",
       "      <td>28811.0</td>\n",
       "      <td>27815.0</td>\n",
       "      <td>27044.0</td>\n",
       "      <td>27317.0</td>\n",
       "      <td>29535.0</td>\n",
       "      <td>30271.0</td>\n",
       "      <td>30819.0</td>\n",
       "      <td>30718.0</td>\n",
       "      <td>29352.0</td>\n",
       "      <td>27332.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-11-30</th>\n",
       "      <td>27784.0</td>\n",
       "      <td>25822.0</td>\n",
       "      <td>24592.0</td>\n",
       "      <td>24171.0</td>\n",
       "      <td>23913.0</td>\n",
       "      <td>24607.0</td>\n",
       "      <td>27155.0</td>\n",
       "      <td>31675.0</td>\n",
       "      <td>34165.0</td>\n",
       "      <td>35012.0</td>\n",
       "      <td>...</td>\n",
       "      <td>27264.0</td>\n",
       "      <td>26002.0</td>\n",
       "      <td>25313.0</td>\n",
       "      <td>25552.0</td>\n",
       "      <td>28072.0</td>\n",
       "      <td>29221.0</td>\n",
       "      <td>30042.0</td>\n",
       "      <td>30229.0</td>\n",
       "      <td>29145.0</td>\n",
       "      <td>26934.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-12-01</th>\n",
       "      <td>29215.0</td>\n",
       "      <td>27059.0</td>\n",
       "      <td>25800.0</td>\n",
       "      <td>25302.0</td>\n",
       "      <td>25221.0</td>\n",
       "      <td>25872.0</td>\n",
       "      <td>28576.0</td>\n",
       "      <td>33557.0</td>\n",
       "      <td>36741.0</td>\n",
       "      <td>37809.0</td>\n",
       "      <td>...</td>\n",
       "      <td>27988.0</td>\n",
       "      <td>27009.0</td>\n",
       "      <td>26449.0</td>\n",
       "      <td>26738.0</td>\n",
       "      <td>29592.0</td>\n",
       "      <td>30653.0</td>\n",
       "      <td>29735.0</td>\n",
       "      <td>28071.0</td>\n",
       "      <td>25801.0</td>\n",
       "      <td>24455.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 168 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             t0 h_0   t0 h_1   t0 h_2   t0 h_3   t0 h_4   t0 h_5   t0 h_6  \\\n",
       "date                                                                        \n",
       "2018-11-27  27137.0  25346.0  24202.0  23659.0  23656.0  24337.0  27062.0   \n",
       "2018-11-28  27338.0  25444.0  24283.0  23897.0  23816.0  24510.0  27245.0   \n",
       "2018-11-29  27462.0  25490.0  24294.0  23889.0  23926.0  24544.0  27380.0   \n",
       "2018-11-30  27784.0  25822.0  24592.0  24171.0  23913.0  24607.0  27155.0   \n",
       "2018-12-01  29215.0  27059.0  25800.0  25302.0  25221.0  25872.0  28576.0   \n",
       "\n",
       "             t0 h_7   t0 h_8   t0 h_9  ...  t-30 h_14  t-30 h_15  t-30 h_16  \\\n",
       "date                                   ...                                    \n",
       "2018-11-27  31591.0  34224.0  35361.0  ...    31399.0    30469.0    30184.0   \n",
       "2018-11-28  32072.0  34684.0  35360.0  ...    31308.0    30281.0    29935.0   \n",
       "2018-11-29  31927.0  34451.0  35313.0  ...    28811.0    27815.0    27044.0   \n",
       "2018-11-30  31675.0  34165.0  35012.0  ...    27264.0    26002.0    25313.0   \n",
       "2018-12-01  33557.0  36741.0  37809.0  ...    27988.0    27009.0    26449.0   \n",
       "\n",
       "            t-30 h_17  t-30 h_18  t-30 h_19  t-30 h_20  t-30 h_21  t-30 h_22  \\\n",
       "date                                                                           \n",
       "2018-11-27    30819.0    32522.0    32940.0    33142.0    32669.0    30753.0   \n",
       "2018-11-28    30428.0    32248.0    32728.0    32642.0    32155.0    30428.0   \n",
       "2018-11-29    27317.0    29535.0    30271.0    30819.0    30718.0    29352.0   \n",
       "2018-11-30    25552.0    28072.0    29221.0    30042.0    30229.0    29145.0   \n",
       "2018-12-01    26738.0    29592.0    30653.0    29735.0    28071.0    25801.0   \n",
       "\n",
       "            t-30 h_23  \n",
       "date                   \n",
       "2018-11-27    27882.0  \n",
       "2018-11-28    28015.0  \n",
       "2018-11-29    27332.0  \n",
       "2018-11-30    26934.0  \n",
       "2018-12-01    24455.0  \n",
       "\n",
       "[5 rows x 168 columns]"
      ]
     },
     "execution_count": 135,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#look at last elements in dataframe to be sure it worked\n",
    "load_features.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "load_features.to_csv('./data/processed/energy_min_features.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
       "       18, 19])"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test = np.arange(1,20)\n",
    "test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([15, 16, 17, 18, 19])"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test[-5:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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