preprocessing_cnr.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import os\n",
    "import sys\n",
    "import numpy as np\n",
    "import re\n",
    "from datetime import datetime"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "raw_df = pd.read_csv(\"data/raw_data/X_train_v2.csv\")\n",
    "raw_df_test = pd.read_csv(\"data/raw_data/X_test_v2.csv\")\n",
    "raw_df_y = pd.read_csv(\"data/raw_data/Y_train_sl9m6Jh.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "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>ID</th>\n",
       "      <th>WF</th>\n",
       "      <th>Time</th>\n",
       "      <th>NWP1_00h_D-2_U</th>\n",
       "      <th>NWP1_00h_D-2_V</th>\n",
       "      <th>NWP1_00h_D-2_T</th>\n",
       "      <th>NWP1_06h_D-2_U</th>\n",
       "      <th>NWP1_06h_D-2_V</th>\n",
       "      <th>NWP1_06h_D-2_T</th>\n",
       "      <th>NWP1_12h_D-2_U</th>\n",
       "      <th>...</th>\n",
       "      <th>NWP4_00h_D-1_CLCT</th>\n",
       "      <th>NWP4_12h_D-1_U</th>\n",
       "      <th>NWP4_12h_D-1_V</th>\n",
       "      <th>NWP4_12h_D-1_CLCT</th>\n",
       "      <th>NWP4_00h_D_U</th>\n",
       "      <th>NWP4_00h_D_V</th>\n",
       "      <th>NWP4_00h_D_CLCT</th>\n",
       "      <th>NWP4_12h_D_U</th>\n",
       "      <th>NWP4_12h_D_V</th>\n",
       "      <th>NWP4_12h_D_CLCT</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>WF1</td>\n",
       "      <td>01/05/2018 01:00</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>1.254603</td>\n",
       "      <td>-0.289687</td>\n",
       "      <td>82.543144</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>WF1</td>\n",
       "      <td>01/05/2018 02:00</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>2.490908</td>\n",
       "      <td>-0.413370</td>\n",
       "      <td>99.990844</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>WF1</td>\n",
       "      <td>01/05/2018 03:00</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>0.997093</td>\n",
       "      <td>-1.415138</td>\n",
       "      <td>98.367235</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>WF1</td>\n",
       "      <td>01/05/2018 04:00</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>0.689598</td>\n",
       "      <td>-0.961441</td>\n",
       "      <td>94.860604</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>WF1</td>\n",
       "      <td>01/05/2018 05:00</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>0.290994</td>\n",
       "      <td>-0.294963</td>\n",
       "      <td>95.905879</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>WF1</td>\n",
       "      <td>01/05/2018 06:00</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>0.265054</td>\n",
       "      <td>-0.170694</td>\n",
       "      <td>65.376218</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>WF1</td>\n",
       "      <td>01/05/2018 07:00</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>1.230561</td>\n",
       "      <td>-0.128490</td>\n",
       "      <td>75.218589</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>WF1</td>\n",
       "      <td>01/05/2018 08:00</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>2.703497</td>\n",
       "      <td>-0.072804</td>\n",
       "      <td>90.929759</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>WF1</td>\n",
       "      <td>01/05/2018 09:00</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>3.204599</td>\n",
       "      <td>-0.791451</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>WF1</td>\n",
       "      <td>01/05/2018 10:00</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>3.257113</td>\n",
       "      <td>-2.163680</td>\n",
       "      <td>96.865701</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>11</td>\n",
       "      <td>WF1</td>\n",
       "      <td>01/05/2018 11:00</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>2.243520</td>\n",
       "      <td>-2.020068</td>\n",
       "      <td>96.589504</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>12</td>\n",
       "      <td>WF1</td>\n",
       "      <td>01/05/2018 12:00</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>1.908820</td>\n",
       "      <td>-2.987252</td>\n",
       "      <td>99.896235</td>\n",
       "      <td>0.882653</td>\n",
       "      <td>-3.794436</td>\n",
       "      <td>97.579845</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>13</td>\n",
       "      <td>WF1</td>\n",
       "      <td>01/05/2018 13:00</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>2.051178</td>\n",
       "      <td>-2.661340</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>1.235389</td>\n",
       "      <td>-3.403565</td>\n",
       "      <td>100.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>14</td>\n",
       "      <td>WF1</td>\n",
       "      <td>01/05/2018 14:00</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>1.326099</td>\n",
       "      <td>-3.894060</td>\n",
       "      <td>86.255778</td>\n",
       "      <td>1.632916</td>\n",
       "      <td>-4.047811</td>\n",
       "      <td>98.750248</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>15</td>\n",
       "      <td>WF1</td>\n",
       "      <td>01/05/2018 15:00</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>0.977479</td>\n",
       "      <td>-4.057602</td>\n",
       "      <td>93.855003</td>\n",
       "      <td>1.240988</td>\n",
       "      <td>-4.487316</td>\n",
       "      <td>89.463322</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>16</td>\n",
       "      <td>WF1</td>\n",
       "      <td>01/05/2018 16:00</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>0.924332</td>\n",
       "      <td>-3.855959</td>\n",
       "      <td>85.776630</td>\n",
       "      <td>0.268632</td>\n",
       "      <td>-4.810940</td>\n",
       "      <td>78.000393</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>17</td>\n",
       "      <td>WF1</td>\n",
       "      <td>01/05/2018 17:00</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>1.396329</td>\n",
       "      <td>-3.966746</td>\n",
       "      <td>71.360990</td>\n",
       "      <td>0.483881</td>\n",
       "      <td>-4.692058</td>\n",
       "      <td>58.352274</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>18</td>\n",
       "      <td>WF1</td>\n",
       "      <td>01/05/2018 18:00</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>1.505154</td>\n",
       "      <td>-3.777412</td>\n",
       "      <td>59.133560</td>\n",
       "      <td>0.811733</td>\n",
       "      <td>-4.503527</td>\n",
       "      <td>72.673306</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>19</td>\n",
       "      <td>WF1</td>\n",
       "      <td>01/05/2018 19:00</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>2.013216</td>\n",
       "      <td>-3.626180</td>\n",
       "      <td>78.133151</td>\n",
       "      <td>2.167308</td>\n",
       "      <td>-3.744001</td>\n",
       "      <td>97.230403</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>20</td>\n",
       "      <td>WF1</td>\n",
       "      <td>01/05/2018 20:00</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>2.128368</td>\n",
       "      <td>-3.977883</td>\n",
       "      <td>10.271148</td>\n",
       "      <td>1.976320</td>\n",
       "      <td>-3.728390</td>\n",
       "      <td>71.301477</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>21</td>\n",
       "      <td>WF1</td>\n",
       "      <td>01/05/2018 21:00</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>2.097366</td>\n",
       "      <td>-3.503083</td>\n",
       "      <td>68.653956</td>\n",
       "      <td>1.580659</td>\n",
       "      <td>-3.299092</td>\n",
       "      <td>85.144887</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>22</td>\n",
       "      <td>WF1</td>\n",
       "      <td>01/05/2018 22:00</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>2.230866</td>\n",
       "      <td>-3.783860</td>\n",
       "      <td>20.345463</td>\n",
       "      <td>1.855009</td>\n",
       "      <td>-2.956855</td>\n",
       "      <td>84.595545</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>23</td>\n",
       "      <td>WF1</td>\n",
       "      <td>01/05/2018 23:00</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>2.002460</td>\n",
       "      <td>-3.733449</td>\n",
       "      <td>2.839777</td>\n",
       "      <td>1.978187</td>\n",
       "      <td>-3.643731</td>\n",
       "      <td>82.483632</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>24</td>\n",
       "      <td>WF1</td>\n",
       "      <td>02/05/2018 00:00</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>2.201930</td>\n",
       "      <td>2.039775</td>\n",
       "      <td>-3.862883</td>\n",
       "      <td>99.879450</td>\n",
       "      <td>1.484437</td>\n",
       "      <td>-4.114376</td>\n",
       "      <td>92.121526</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>25</td>\n",
       "      <td>WF1</td>\n",
       "      <td>02/05/2018 01:00</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>59.734784</td>\n",
       "      <td>2.271200</td>\n",
       "      <td>-4.077832</td>\n",
       "      <td>32.372993</td>\n",
       "      <td>2.142778</td>\n",
       "      <td>-4.139025</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>26</td>\n",
       "      <td>WF1</td>\n",
       "      <td>02/05/2018 02:00</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>8.687213</td>\n",
       "      <td>2.702943</td>\n",
       "      <td>-3.887500</td>\n",
       "      <td>63.816698</td>\n",
       "      <td>2.501176</td>\n",
       "      <td>-4.206309</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>27</td>\n",
       "      <td>WF1</td>\n",
       "      <td>02/05/2018 03:00</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>100.000000</td>\n",
       "      <td>2.526264</td>\n",
       "      <td>-3.587892</td>\n",
       "      <td>82.242532</td>\n",
       "      <td>2.523022</td>\n",
       "      <td>-3.656705</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>28</td>\n",
       "      <td>WF1</td>\n",
       "      <td>02/05/2018 04:00</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>70.034940</td>\n",
       "      <td>2.952409</td>\n",
       "      <td>-3.812448</td>\n",
       "      <td>75.546667</td>\n",
       "      <td>2.401982</td>\n",
       "      <td>-3.419543</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>29</td>\n",
       "      <td>WF1</td>\n",
       "      <td>02/05/2018 05:00</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>88.111332</td>\n",
       "      <td>2.854116</td>\n",
       "      <td>-4.123464</td>\n",
       "      <td>43.298787</td>\n",
       "      <td>2.482282</td>\n",
       "      <td>-3.476169</td>\n",
       "      <td>40.587178</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>30</td>\n",
       "      <td>WF1</td>\n",
       "      <td>02/05/2018 06:00</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>100.000000</td>\n",
       "      <td>2.752712</td>\n",
       "      <td>-4.614003</td>\n",
       "      <td>0.315856</td>\n",
       "      <td>2.777502</td>\n",
       "      <td>-3.531462</td>\n",
       "      <td>91.384492</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>31</td>\n",
       "      <td>WF1</td>\n",
       "      <td>02/05/2018 07:00</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>12.969026</td>\n",
       "      <td>2.773242</td>\n",
       "      <td>-6.454279</td>\n",
       "      <td>5.618529</td>\n",
       "      <td>2.425599</td>\n",
       "      <td>-5.259551</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>32</td>\n",
       "      <td>WF1</td>\n",
       "      <td>02/05/2018 08:00</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>100.000000</td>\n",
       "      <td>1.897312</td>\n",
       "      <td>-7.835836</td>\n",
       "      <td>99.594098</td>\n",
       "      <td>1.409451</td>\n",
       "      <td>-7.608527</td>\n",
       "      <td>53.861408</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>33</td>\n",
       "      <td>WF1</td>\n",
       "      <td>02/05/2018 09:00</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>8.176020</td>\n",
       "      <td>1.642870</td>\n",
       "      <td>-7.874863</td>\n",
       "      <td>10.370334</td>\n",
       "      <td>2.089048</td>\n",
       "      <td>-8.139478</td>\n",
       "      <td>99.586468</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>34</td>\n",
       "      <td>WF1</td>\n",
       "      <td>02/05/2018 10:00</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>3.363177</td>\n",
       "      <td>1.787821</td>\n",
       "      <td>-7.937907</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>2.166396</td>\n",
       "      <td>-8.527865</td>\n",
       "      <td>99.751270</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>35</td>\n",
       "      <td>WF1</td>\n",
       "      <td>02/05/2018 11:00</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>94.544732</td>\n",
       "      <td>2.619581</td>\n",
       "      <td>-7.957120</td>\n",
       "      <td>50.835450</td>\n",
       "      <td>2.525384</td>\n",
       "      <td>-8.445258</td>\n",
       "      <td>97.560008</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>36</td>\n",
       "      <td>WF1</td>\n",
       "      <td>02/05/2018 12:00</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>56.742398</td>\n",
       "      <td>2.837941</td>\n",
       "      <td>-7.988342</td>\n",
       "      <td>94.334151</td>\n",
       "      <td>3.499611</td>\n",
       "      <td>-8.483230</td>\n",
       "      <td>51.734235</td>\n",
       "      <td>2.356626</td>\n",
       "      <td>-7.909963</td>\n",
       "      <td>10.477150</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>37</td>\n",
       "      <td>WF1</td>\n",
       "      <td>02/05/2018 13:00</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>99.195825</td>\n",
       "      <td>3.102959</td>\n",
       "      <td>-8.042980</td>\n",
       "      <td>82.836126</td>\n",
       "      <td>3.731654</td>\n",
       "      <td>-8.613803</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>2.353141</td>\n",
       "      <td>-8.055063</td>\n",
       "      <td>73.851338</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>38</td>\n",
       "      <td>WF1</td>\n",
       "      <td>02/05/2018 14:00</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>99.542215</td>\n",
       "      <td>2.964851</td>\n",
       "      <td>-8.483085</td>\n",
       "      <td>1.017793</td>\n",
       "      <td>4.167399</td>\n",
       "      <td>-9.000191</td>\n",
       "      <td>71.287745</td>\n",
       "      <td>2.595898</td>\n",
       "      <td>-8.174631</td>\n",
       "      <td>97.775166</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>39</td>\n",
       "      <td>WF1</td>\n",
       "      <td>02/05/2018 15:00</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>75.247582</td>\n",
       "      <td>3.226759</td>\n",
       "      <td>-8.752671</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>3.712760</td>\n",
       "      <td>-8.788344</td>\n",
       "      <td>99.580364</td>\n",
       "      <td>2.112127</td>\n",
       "      <td>-7.955424</td>\n",
       "      <td>93.520821</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>40</td>\n",
       "      <td>WF1</td>\n",
       "      <td>02/05/2018 16:00</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>100.000000</td>\n",
       "      <td>3.296435</td>\n",
       "      <td>-8.546128</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>3.091616</td>\n",
       "      <td>-8.906259</td>\n",
       "      <td>67.582741</td>\n",
       "      <td>2.152199</td>\n",
       "      <td>-7.808456</td>\n",
       "      <td>99.876398</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>41</td>\n",
       "      <td>WF1</td>\n",
       "      <td>02/05/2018 17:00</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>100.000000</td>\n",
       "      <td>2.884599</td>\n",
       "      <td>-8.501697</td>\n",
       "      <td>61.158494</td>\n",
       "      <td>2.720229</td>\n",
       "      <td>-8.597814</td>\n",
       "      <td>90.236979</td>\n",
       "      <td>1.497104</td>\n",
       "      <td>-7.827761</td>\n",
       "      <td>100.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>42</td>\n",
       "      <td>WF1</td>\n",
       "      <td>02/05/2018 18:00</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>100.000000</td>\n",
       "      <td>2.762044</td>\n",
       "      <td>-7.773993</td>\n",
       "      <td>74.521230</td>\n",
       "      <td>2.528926</td>\n",
       "      <td>-8.401289</td>\n",
       "      <td>75.358976</td>\n",
       "      <td>1.288031</td>\n",
       "      <td>-7.055555</td>\n",
       "      <td>100.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>43</td>\n",
       "      <td>WF1</td>\n",
       "      <td>02/05/2018 19:00</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>100.000000</td>\n",
       "      <td>3.478091</td>\n",
       "      <td>-7.007262</td>\n",
       "      <td>70.001369</td>\n",
       "      <td>3.006003</td>\n",
       "      <td>-8.693079</td>\n",
       "      <td>99.450658</td>\n",
       "      <td>2.400183</td>\n",
       "      <td>-6.676926</td>\n",
       "      <td>70.297403</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>44</td>\n",
       "      <td>WF1</td>\n",
       "      <td>02/05/2018 20:00</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>100.000000</td>\n",
       "      <td>3.758040</td>\n",
       "      <td>-7.524220</td>\n",
       "      <td>52.939733</td>\n",
       "      <td>3.687371</td>\n",
       "      <td>-8.522535</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>3.007075</td>\n",
       "      <td>-6.238512</td>\n",
       "      <td>83.835622</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>45</td>\n",
       "      <td>WF1</td>\n",
       "      <td>02/05/2018 21:00</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>99.992370</td>\n",
       "      <td>5.116103</td>\n",
       "      <td>-7.429955</td>\n",
       "      <td>45.595341</td>\n",
       "      <td>4.584251</td>\n",
       "      <td>-8.120158</td>\n",
       "      <td>99.708544</td>\n",
       "      <td>4.097158</td>\n",
       "      <td>-5.714159</td>\n",
       "      <td>100.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>46</td>\n",
       "      <td>WF1</td>\n",
       "      <td>02/05/2018 22:00</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>98.805182</td>\n",
       "      <td>5.531672</td>\n",
       "      <td>-8.150454</td>\n",
       "      <td>20.746787</td>\n",
       "      <td>4.792086</td>\n",
       "      <td>-8.270050</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>4.944484</td>\n",
       "      <td>-5.801967</td>\n",
       "      <td>100.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>47</td>\n",
       "      <td>WF1</td>\n",
       "      <td>02/05/2018 23:00</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>97.823997</td>\n",
       "      <td>5.762474</td>\n",
       "      <td>-8.417639</td>\n",
       "      <td>65.351802</td>\n",
       "      <td>4.663370</td>\n",
       "      <td>-8.625794</td>\n",
       "      <td>84.641324</td>\n",
       "      <td>5.194790</td>\n",
       "      <td>-6.508161</td>\n",
       "      <td>98.661743</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>48</td>\n",
       "      <td>WF1</td>\n",
       "      <td>03/05/2018 00:00</td>\n",
       "      <td>5.4041</td>\n",
       "      <td>-14.749</td>\n",
       "      <td>289.73</td>\n",
       "      <td>5.9457</td>\n",
       "      <td>-14.636</td>\n",
       "      <td>289.52</td>\n",
       "      <td>3.6308</td>\n",
       "      <td>...</td>\n",
       "      <td>68.173283</td>\n",
       "      <td>5.231959</td>\n",
       "      <td>-6.665716</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>5.251561</td>\n",
       "      <td>-6.225002</td>\n",
       "      <td>0.581374</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>49</td>\n",
       "      <td>WF1</td>\n",
       "      <td>03/05/2018 01:00</td>\n",
       "      <td>4.8424</td>\n",
       "      <td>-15.405</td>\n",
       "      <td>289.38</td>\n",
       "      <td>5.8611</td>\n",
       "      <td>-15.396</td>\n",
       "      <td>289.17</td>\n",
       "      <td>3.3366</td>\n",
       "      <td>...</td>\n",
       "      <td>68.757721</td>\n",
       "      <td>4.953195</td>\n",
       "      <td>-7.086070</td>\n",
       "      <td>68.599021</td>\n",
       "      <td>5.045156</td>\n",
       "      <td>-6.093691</td>\n",
       "      <td>-0.000013</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>50</td>\n",
       "      <td>WF1</td>\n",
       "      <td>03/05/2018 02:00</td>\n",
       "      <td>4.4050</td>\n",
       "      <td>-16.085</td>\n",
       "      <td>289.05</td>\n",
       "      <td>5.8946</td>\n",
       "      <td>-15.977</td>\n",
       "      <td>288.92</td>\n",
       "      <td>3.0016</td>\n",
       "      <td>...</td>\n",
       "      <td>97.662246</td>\n",
       "      <td>4.284162</td>\n",
       "      <td>-7.198787</td>\n",
       "      <td>0.224298</td>\n",
       "      <td>4.799436</td>\n",
       "      <td>-5.973324</td>\n",
       "      <td>-0.000013</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>51</td>\n",
       "      <td>WF1</td>\n",
       "      <td>03/05/2018 03:00</td>\n",
       "      <td>4.4229</td>\n",
       "      <td>-16.527</td>\n",
       "      <td>288.68</td>\n",
       "      <td>6.3428</td>\n",
       "      <td>-16.317</td>\n",
       "      <td>288.57</td>\n",
       "      <td>2.8521</td>\n",
       "      <td>...</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>4.295196</td>\n",
       "      <td>-7.850803</td>\n",
       "      <td>-0.000016</td>\n",
       "      <td>4.450514</td>\n",
       "      <td>-6.487014</td>\n",
       "      <td>-0.000013</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>52</td>\n",
       "      <td>WF1</td>\n",
       "      <td>03/05/2018 04:00</td>\n",
       "      <td>5.0740</td>\n",
       "      <td>-16.985</td>\n",
       "      <td>288.40</td>\n",
       "      <td>6.7567</td>\n",
       "      <td>-16.895</td>\n",
       "      <td>288.23</td>\n",
       "      <td>2.7426</td>\n",
       "      <td>...</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>4.295196</td>\n",
       "      <td>-8.693379</td>\n",
       "      <td>-0.000016</td>\n",
       "      <td>4.369153</td>\n",
       "      <td>-7.600720</td>\n",
       "      <td>-0.000013</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>53</td>\n",
       "      <td>WF1</td>\n",
       "      <td>03/05/2018 05:00</td>\n",
       "      <td>5.8899</td>\n",
       "      <td>-17.983</td>\n",
       "      <td>288.21</td>\n",
       "      <td>6.8435</td>\n",
       "      <td>-17.223</td>\n",
       "      <td>287.99</td>\n",
       "      <td>3.0243</td>\n",
       "      <td>...</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>4.292873</td>\n",
       "      <td>-8.995411</td>\n",
       "      <td>-0.000016</td>\n",
       "      <td>3.888633</td>\n",
       "      <td>-8.621414</td>\n",
       "      <td>-0.000013</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>54</td>\n",
       "      <td>WF1</td>\n",
       "      <td>03/05/2018 06:00</td>\n",
       "      <td>6.1131</td>\n",
       "      <td>-18.897</td>\n",
       "      <td>287.97</td>\n",
       "      <td>7.1638</td>\n",
       "      <td>-17.580</td>\n",
       "      <td>287.95</td>\n",
       "      <td>3.4257</td>\n",
       "      <td>...</td>\n",
       "      <td>98.792974</td>\n",
       "      <td>4.220859</td>\n",
       "      <td>-9.930776</td>\n",
       "      <td>-0.000016</td>\n",
       "      <td>3.100145</td>\n",
       "      <td>-9.882844</td>\n",
       "      <td>0.035084</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>55</td>\n",
       "      <td>WF1</td>\n",
       "      <td>03/05/2018 07:00</td>\n",
       "      <td>5.8758</td>\n",
       "      <td>-18.879</td>\n",
       "      <td>288.07</td>\n",
       "      <td>7.2675</td>\n",
       "      <td>-18.088</td>\n",
       "      <td>288.21</td>\n",
       "      <td>3.5705</td>\n",
       "      <td>...</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>3.591898</td>\n",
       "      <td>-11.175023</td>\n",
       "      <td>-0.000016</td>\n",
       "      <td>2.557376</td>\n",
       "      <td>-10.726027</td>\n",
       "      <td>-0.000013</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>56</td>\n",
       "      <td>WF1</td>\n",
       "      <td>03/05/2018 08:00</td>\n",
       "      <td>6.0120</td>\n",
       "      <td>-18.630</td>\n",
       "      <td>288.69</td>\n",
       "      <td>7.4550</td>\n",
       "      <td>-18.299</td>\n",
       "      <td>288.74</td>\n",
       "      <td>3.4870</td>\n",
       "      <td>...</td>\n",
       "      <td>1.275681</td>\n",
       "      <td>3.244605</td>\n",
       "      <td>-11.843853</td>\n",
       "      <td>-0.000016</td>\n",
       "      <td>1.746500</td>\n",
       "      <td>-11.037889</td>\n",
       "      <td>11.263017</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>57</td>\n",
       "      <td>WF1</td>\n",
       "      <td>03/05/2018 09:00</td>\n",
       "      <td>5.7299</td>\n",
       "      <td>-18.485</td>\n",
       "      <td>289.62</td>\n",
       "      <td>7.6540</td>\n",
       "      <td>-18.614</td>\n",
       "      <td>289.39</td>\n",
       "      <td>3.3818</td>\n",
       "      <td>...</td>\n",
       "      <td>16.074334</td>\n",
       "      <td>2.809036</td>\n",
       "      <td>-12.053718</td>\n",
       "      <td>-0.000016</td>\n",
       "      <td>1.454366</td>\n",
       "      <td>-10.960683</td>\n",
       "      <td>5.195844</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>58</td>\n",
       "      <td>WF1</td>\n",
       "      <td>03/05/2018 10:00</td>\n",
       "      <td>5.3751</td>\n",
       "      <td>-18.239</td>\n",
       "      <td>290.64</td>\n",
       "      <td>6.9948</td>\n",
       "      <td>-18.827</td>\n",
       "      <td>290.28</td>\n",
       "      <td>3.1364</td>\n",
       "      <td>...</td>\n",
       "      <td>13.553467</td>\n",
       "      <td>2.787548</td>\n",
       "      <td>-11.955325</td>\n",
       "      <td>-0.000016</td>\n",
       "      <td>1.244139</td>\n",
       "      <td>-11.059166</td>\n",
       "      <td>0.207517</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>59</td>\n",
       "      <td>WF1</td>\n",
       "      <td>03/05/2018 11:00</td>\n",
       "      <td>5.5955</td>\n",
       "      <td>-17.480</td>\n",
       "      <td>291.36</td>\n",
       "      <td>6.7829</td>\n",
       "      <td>-18.651</td>\n",
       "      <td>290.95</td>\n",
       "      <td>3.4461</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.000012</td>\n",
       "      <td>2.561633</td>\n",
       "      <td>-12.437953</td>\n",
       "      <td>-0.000016</td>\n",
       "      <td>1.417235</td>\n",
       "      <td>-10.858553</td>\n",
       "      <td>-0.000013</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>60</td>\n",
       "      <td>WF1</td>\n",
       "      <td>03/05/2018 12:00</td>\n",
       "      <td>5.5660</td>\n",
       "      <td>-16.395</td>\n",
       "      <td>292.00</td>\n",
       "      <td>6.9793</td>\n",
       "      <td>-18.224</td>\n",
       "      <td>291.60</td>\n",
       "      <td>3.8957</td>\n",
       "      <td>...</td>\n",
       "      <td>0.419624</td>\n",
       "      <td>2.952484</td>\n",
       "      <td>-12.382529</td>\n",
       "      <td>24.822596</td>\n",
       "      <td>1.671692</td>\n",
       "      <td>-11.575896</td>\n",
       "      <td>6.166347</td>\n",
       "      <td>1.514590</td>\n",
       "      <td>-11.544158</td>\n",
       "      <td>53.060285</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>60 rows × 105 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    ID   WF              Time  NWP1_00h_D-2_U  NWP1_00h_D-2_V  NWP1_00h_D-2_T  \\\n",
       "0    1  WF1  01/05/2018 01:00             NaN             NaN             NaN   \n",
       "1    2  WF1  01/05/2018 02:00             NaN             NaN             NaN   \n",
       "2    3  WF1  01/05/2018 03:00             NaN             NaN             NaN   \n",
       "3    4  WF1  01/05/2018 04:00             NaN             NaN             NaN   \n",
       "4    5  WF1  01/05/2018 05:00             NaN             NaN             NaN   \n",
       "5    6  WF1  01/05/2018 06:00             NaN             NaN             NaN   \n",
       "6    7  WF1  01/05/2018 07:00             NaN             NaN             NaN   \n",
       "7    8  WF1  01/05/2018 08:00             NaN             NaN             NaN   \n",
       "8    9  WF1  01/05/2018 09:00             NaN             NaN             NaN   \n",
       "9   10  WF1  01/05/2018 10:00             NaN             NaN             NaN   \n",
       "10  11  WF1  01/05/2018 11:00             NaN             NaN             NaN   \n",
       "11  12  WF1  01/05/2018 12:00             NaN             NaN             NaN   \n",
       "12  13  WF1  01/05/2018 13:00             NaN             NaN             NaN   \n",
       "13  14  WF1  01/05/2018 14:00             NaN             NaN             NaN   \n",
       "14  15  WF1  01/05/2018 15:00             NaN             NaN             NaN   \n",
       "15  16  WF1  01/05/2018 16:00             NaN             NaN             NaN   \n",
       "16  17  WF1  01/05/2018 17:00             NaN             NaN             NaN   \n",
       "17  18  WF1  01/05/2018 18:00             NaN             NaN             NaN   \n",
       "18  19  WF1  01/05/2018 19:00             NaN             NaN             NaN   \n",
       "19  20  WF1  01/05/2018 20:00             NaN             NaN             NaN   \n",
       "20  21  WF1  01/05/2018 21:00             NaN             NaN             NaN   \n",
       "21  22  WF1  01/05/2018 22:00             NaN             NaN             NaN   \n",
       "22  23  WF1  01/05/2018 23:00             NaN             NaN             NaN   \n",
       "23  24  WF1  02/05/2018 00:00             NaN             NaN             NaN   \n",
       "24  25  WF1  02/05/2018 01:00             NaN             NaN             NaN   \n",
       "25  26  WF1  02/05/2018 02:00             NaN             NaN             NaN   \n",
       "26  27  WF1  02/05/2018 03:00             NaN             NaN             NaN   \n",
       "27  28  WF1  02/05/2018 04:00             NaN             NaN             NaN   \n",
       "28  29  WF1  02/05/2018 05:00             NaN             NaN             NaN   \n",
       "29  30  WF1  02/05/2018 06:00             NaN             NaN             NaN   \n",
       "30  31  WF1  02/05/2018 07:00             NaN             NaN             NaN   \n",
       "31  32  WF1  02/05/2018 08:00             NaN             NaN             NaN   \n",
       "32  33  WF1  02/05/2018 09:00             NaN             NaN             NaN   \n",
       "33  34  WF1  02/05/2018 10:00             NaN             NaN             NaN   \n",
       "34  35  WF1  02/05/2018 11:00             NaN             NaN             NaN   \n",
       "35  36  WF1  02/05/2018 12:00             NaN             NaN             NaN   \n",
       "36  37  WF1  02/05/2018 13:00             NaN             NaN             NaN   \n",
       "37  38  WF1  02/05/2018 14:00             NaN             NaN             NaN   \n",
       "38  39  WF1  02/05/2018 15:00             NaN             NaN             NaN   \n",
       "39  40  WF1  02/05/2018 16:00             NaN             NaN             NaN   \n",
       "40  41  WF1  02/05/2018 17:00             NaN             NaN             NaN   \n",
       "41  42  WF1  02/05/2018 18:00             NaN             NaN             NaN   \n",
       "42  43  WF1  02/05/2018 19:00             NaN             NaN             NaN   \n",
       "43  44  WF1  02/05/2018 20:00             NaN             NaN             NaN   \n",
       "44  45  WF1  02/05/2018 21:00             NaN             NaN             NaN   \n",
       "45  46  WF1  02/05/2018 22:00             NaN             NaN             NaN   \n",
       "46  47  WF1  02/05/2018 23:00             NaN             NaN             NaN   \n",
       "47  48  WF1  03/05/2018 00:00          5.4041         -14.749          289.73   \n",
       "48  49  WF1  03/05/2018 01:00          4.8424         -15.405          289.38   \n",
       "49  50  WF1  03/05/2018 02:00          4.4050         -16.085          289.05   \n",
       "50  51  WF1  03/05/2018 03:00          4.4229         -16.527          288.68   \n",
       "51  52  WF1  03/05/2018 04:00          5.0740         -16.985          288.40   \n",
       "52  53  WF1  03/05/2018 05:00          5.8899         -17.983          288.21   \n",
       "53  54  WF1  03/05/2018 06:00          6.1131         -18.897          287.97   \n",
       "54  55  WF1  03/05/2018 07:00          5.8758         -18.879          288.07   \n",
       "55  56  WF1  03/05/2018 08:00          6.0120         -18.630          288.69   \n",
       "56  57  WF1  03/05/2018 09:00          5.7299         -18.485          289.62   \n",
       "57  58  WF1  03/05/2018 10:00          5.3751         -18.239          290.64   \n",
       "58  59  WF1  03/05/2018 11:00          5.5955         -17.480          291.36   \n",
       "59  60  WF1  03/05/2018 12:00          5.5660         -16.395          292.00   \n",
       "\n",
       "    NWP1_06h_D-2_U  NWP1_06h_D-2_V  NWP1_06h_D-2_T  NWP1_12h_D-2_U  ...  \\\n",
       "0              NaN             NaN             NaN             NaN  ...   \n",
       "1              NaN             NaN             NaN             NaN  ...   \n",
       "2              NaN             NaN             NaN             NaN  ...   \n",
       "3              NaN             NaN             NaN             NaN  ...   \n",
       "4              NaN             NaN             NaN             NaN  ...   \n",
       "5              NaN             NaN             NaN             NaN  ...   \n",
       "6              NaN             NaN             NaN             NaN  ...   \n",
       "7              NaN             NaN             NaN             NaN  ...   \n",
       "8              NaN             NaN             NaN             NaN  ...   \n",
       "9              NaN             NaN             NaN             NaN  ...   \n",
       "10             NaN             NaN             NaN             NaN  ...   \n",
       "11             NaN             NaN             NaN             NaN  ...   \n",
       "12             NaN             NaN             NaN             NaN  ...   \n",
       "13             NaN             NaN             NaN             NaN  ...   \n",
       "14             NaN             NaN             NaN             NaN  ...   \n",
       "15             NaN             NaN             NaN             NaN  ...   \n",
       "16             NaN             NaN             NaN             NaN  ...   \n",
       "17             NaN             NaN             NaN             NaN  ...   \n",
       "18             NaN             NaN             NaN             NaN  ...   \n",
       "19             NaN             NaN             NaN             NaN  ...   \n",
       "20             NaN             NaN             NaN             NaN  ...   \n",
       "21             NaN             NaN             NaN             NaN  ...   \n",
       "22             NaN             NaN             NaN             NaN  ...   \n",
       "23             NaN             NaN             NaN             NaN  ...   \n",
       "24             NaN             NaN             NaN             NaN  ...   \n",
       "25             NaN             NaN             NaN             NaN  ...   \n",
       "26             NaN             NaN             NaN             NaN  ...   \n",
       "27             NaN             NaN             NaN             NaN  ...   \n",
       "28             NaN             NaN             NaN             NaN  ...   \n",
       "29             NaN             NaN             NaN             NaN  ...   \n",
       "30             NaN             NaN             NaN             NaN  ...   \n",
       "31             NaN             NaN             NaN             NaN  ...   \n",
       "32             NaN             NaN             NaN             NaN  ...   \n",
       "33             NaN             NaN             NaN             NaN  ...   \n",
       "34             NaN             NaN             NaN             NaN  ...   \n",
       "35             NaN             NaN             NaN             NaN  ...   \n",
       "36             NaN             NaN             NaN             NaN  ...   \n",
       "37             NaN             NaN             NaN             NaN  ...   \n",
       "38             NaN             NaN             NaN             NaN  ...   \n",
       "39             NaN             NaN             NaN             NaN  ...   \n",
       "40             NaN             NaN             NaN             NaN  ...   \n",
       "41             NaN             NaN             NaN             NaN  ...   \n",
       "42             NaN             NaN             NaN             NaN  ...   \n",
       "43             NaN             NaN             NaN             NaN  ...   \n",
       "44             NaN             NaN             NaN             NaN  ...   \n",
       "45             NaN             NaN             NaN             NaN  ...   \n",
       "46             NaN             NaN             NaN             NaN  ...   \n",
       "47          5.9457         -14.636          289.52          3.6308  ...   \n",
       "48          5.8611         -15.396          289.17          3.3366  ...   \n",
       "49          5.8946         -15.977          288.92          3.0016  ...   \n",
       "50          6.3428         -16.317          288.57          2.8521  ...   \n",
       "51          6.7567         -16.895          288.23          2.7426  ...   \n",
       "52          6.8435         -17.223          287.99          3.0243  ...   \n",
       "53          7.1638         -17.580          287.95          3.4257  ...   \n",
       "54          7.2675         -18.088          288.21          3.5705  ...   \n",
       "55          7.4550         -18.299          288.74          3.4870  ...   \n",
       "56          7.6540         -18.614          289.39          3.3818  ...   \n",
       "57          6.9948         -18.827          290.28          3.1364  ...   \n",
       "58          6.7829         -18.651          290.95          3.4461  ...   \n",
       "59          6.9793         -18.224          291.60          3.8957  ...   \n",
       "\n",
       "    NWP4_00h_D-1_CLCT  NWP4_12h_D-1_U  NWP4_12h_D-1_V  NWP4_12h_D-1_CLCT  \\\n",
       "0                 NaN             NaN             NaN                NaN   \n",
       "1                 NaN             NaN             NaN                NaN   \n",
       "2                 NaN             NaN             NaN                NaN   \n",
       "3                 NaN             NaN             NaN                NaN   \n",
       "4                 NaN             NaN             NaN                NaN   \n",
       "5                 NaN             NaN             NaN                NaN   \n",
       "6                 NaN             NaN             NaN                NaN   \n",
       "7                 NaN             NaN             NaN                NaN   \n",
       "8                 NaN             NaN             NaN                NaN   \n",
       "9                 NaN             NaN             NaN                NaN   \n",
       "10                NaN             NaN             NaN                NaN   \n",
       "11                NaN             NaN             NaN                NaN   \n",
       "12                NaN             NaN             NaN                NaN   \n",
       "13                NaN             NaN             NaN                NaN   \n",
       "14                NaN             NaN             NaN                NaN   \n",
       "15                NaN             NaN             NaN                NaN   \n",
       "16                NaN             NaN             NaN                NaN   \n",
       "17                NaN             NaN             NaN                NaN   \n",
       "18                NaN             NaN             NaN                NaN   \n",
       "19                NaN             NaN             NaN                NaN   \n",
       "20                NaN             NaN             NaN                NaN   \n",
       "21                NaN             NaN             NaN                NaN   \n",
       "22                NaN             NaN             NaN                NaN   \n",
       "23           2.201930        2.039775       -3.862883          99.879450   \n",
       "24          59.734784        2.271200       -4.077832          32.372993   \n",
       "25           8.687213        2.702943       -3.887500          63.816698   \n",
       "26         100.000000        2.526264       -3.587892          82.242532   \n",
       "27          70.034940        2.952409       -3.812448          75.546667   \n",
       "28          88.111332        2.854116       -4.123464          43.298787   \n",
       "29         100.000000        2.752712       -4.614003           0.315856   \n",
       "30          12.969026        2.773242       -6.454279           5.618529   \n",
       "31         100.000000        1.897312       -7.835836          99.594098   \n",
       "32           8.176020        1.642870       -7.874863          10.370334   \n",
       "33           3.363177        1.787821       -7.937907         100.000000   \n",
       "34          94.544732        2.619581       -7.957120          50.835450   \n",
       "35          56.742398        2.837941       -7.988342          94.334151   \n",
       "36          99.195825        3.102959       -8.042980          82.836126   \n",
       "37          99.542215        2.964851       -8.483085           1.017793   \n",
       "38          75.247582        3.226759       -8.752671         100.000000   \n",
       "39         100.000000        3.296435       -8.546128         100.000000   \n",
       "40         100.000000        2.884599       -8.501697          61.158494   \n",
       "41         100.000000        2.762044       -7.773993          74.521230   \n",
       "42         100.000000        3.478091       -7.007262          70.001369   \n",
       "43         100.000000        3.758040       -7.524220          52.939733   \n",
       "44          99.992370        5.116103       -7.429955          45.595341   \n",
       "45          98.805182        5.531672       -8.150454          20.746787   \n",
       "46          97.823997        5.762474       -8.417639          65.351802   \n",
       "47          68.173283        5.231959       -6.665716         100.000000   \n",
       "48          68.757721        4.953195       -7.086070          68.599021   \n",
       "49          97.662246        4.284162       -7.198787           0.224298   \n",
       "50         100.000000        4.295196       -7.850803          -0.000016   \n",
       "51         100.000000        4.295196       -8.693379          -0.000016   \n",
       "52         100.000000        4.292873       -8.995411          -0.000016   \n",
       "53          98.792974        4.220859       -9.930776          -0.000016   \n",
       "54         100.000000        3.591898      -11.175023          -0.000016   \n",
       "55           1.275681        3.244605      -11.843853          -0.000016   \n",
       "56          16.074334        2.809036      -12.053718          -0.000016   \n",
       "57          13.553467        2.787548      -11.955325          -0.000016   \n",
       "58          -0.000012        2.561633      -12.437953          -0.000016   \n",
       "59           0.419624        2.952484      -12.382529          24.822596   \n",
       "\n",
       "    NWP4_00h_D_U  NWP4_00h_D_V  NWP4_00h_D_CLCT  NWP4_12h_D_U  NWP4_12h_D_V  \\\n",
       "0       1.254603     -0.289687        82.543144           NaN           NaN   \n",
       "1       2.490908     -0.413370        99.990844           NaN           NaN   \n",
       "2       0.997093     -1.415138        98.367235           NaN           NaN   \n",
       "3       0.689598     -0.961441        94.860604           NaN           NaN   \n",
       "4       0.290994     -0.294963        95.905879           NaN           NaN   \n",
       "5       0.265054     -0.170694        65.376218           NaN           NaN   \n",
       "6       1.230561     -0.128490        75.218589           NaN           NaN   \n",
       "7       2.703497     -0.072804        90.929759           NaN           NaN   \n",
       "8       3.204599     -0.791451       100.000000           NaN           NaN   \n",
       "9       3.257113     -2.163680        96.865701           NaN           NaN   \n",
       "10      2.243520     -2.020068        96.589504           NaN           NaN   \n",
       "11      1.908820     -2.987252        99.896235      0.882653     -3.794436   \n",
       "12      2.051178     -2.661340       100.000000      1.235389     -3.403565   \n",
       "13      1.326099     -3.894060        86.255778      1.632916     -4.047811   \n",
       "14      0.977479     -4.057602        93.855003      1.240988     -4.487316   \n",
       "15      0.924332     -3.855959        85.776630      0.268632     -4.810940   \n",
       "16      1.396329     -3.966746        71.360990      0.483881     -4.692058   \n",
       "17      1.505154     -3.777412        59.133560      0.811733     -4.503527   \n",
       "18      2.013216     -3.626180        78.133151      2.167308     -3.744001   \n",
       "19      2.128368     -3.977883        10.271148      1.976320     -3.728390   \n",
       "20      2.097366     -3.503083        68.653956      1.580659     -3.299092   \n",
       "21      2.230866     -3.783860        20.345463      1.855009     -2.956855   \n",
       "22      2.002460     -3.733449         2.839777      1.978187     -3.643731   \n",
       "23      1.484437     -4.114376        92.121526           NaN           NaN   \n",
       "24      2.142778     -4.139025       100.000000           NaN           NaN   \n",
       "25      2.501176     -4.206309       100.000000           NaN           NaN   \n",
       "26      2.523022     -3.656705       100.000000           NaN           NaN   \n",
       "27      2.401982     -3.419543       100.000000           NaN           NaN   \n",
       "28      2.482282     -3.476169        40.587178           NaN           NaN   \n",
       "29      2.777502     -3.531462        91.384492           NaN           NaN   \n",
       "30      2.425599     -5.259551       100.000000           NaN           NaN   \n",
       "31      1.409451     -7.608527        53.861408           NaN           NaN   \n",
       "32      2.089048     -8.139478        99.586468           NaN           NaN   \n",
       "33      2.166396     -8.527865        99.751270           NaN           NaN   \n",
       "34      2.525384     -8.445258        97.560008           NaN           NaN   \n",
       "35      3.499611     -8.483230        51.734235      2.356626     -7.909963   \n",
       "36      3.731654     -8.613803       100.000000      2.353141     -8.055063   \n",
       "37      4.167399     -9.000191        71.287745      2.595898     -8.174631   \n",
       "38      3.712760     -8.788344        99.580364      2.112127     -7.955424   \n",
       "39      3.091616     -8.906259        67.582741      2.152199     -7.808456   \n",
       "40      2.720229     -8.597814        90.236979      1.497104     -7.827761   \n",
       "41      2.528926     -8.401289        75.358976      1.288031     -7.055555   \n",
       "42      3.006003     -8.693079        99.450658      2.400183     -6.676926   \n",
       "43      3.687371     -8.522535       100.000000      3.007075     -6.238512   \n",
       "44      4.584251     -8.120158        99.708544      4.097158     -5.714159   \n",
       "45      4.792086     -8.270050       100.000000      4.944484     -5.801967   \n",
       "46      4.663370     -8.625794        84.641324      5.194790     -6.508161   \n",
       "47      5.251561     -6.225002         0.581374           NaN           NaN   \n",
       "48      5.045156     -6.093691        -0.000013           NaN           NaN   \n",
       "49      4.799436     -5.973324        -0.000013           NaN           NaN   \n",
       "50      4.450514     -6.487014        -0.000013           NaN           NaN   \n",
       "51      4.369153     -7.600720        -0.000013           NaN           NaN   \n",
       "52      3.888633     -8.621414        -0.000013           NaN           NaN   \n",
       "53      3.100145     -9.882844         0.035084           NaN           NaN   \n",
       "54      2.557376    -10.726027        -0.000013           NaN           NaN   \n",
       "55      1.746500    -11.037889        11.263017           NaN           NaN   \n",
       "56      1.454366    -10.960683         5.195844           NaN           NaN   \n",
       "57      1.244139    -11.059166         0.207517           NaN           NaN   \n",
       "58      1.417235    -10.858553        -0.000013           NaN           NaN   \n",
       "59      1.671692    -11.575896         6.166347      1.514590    -11.544158   \n",
       "\n",
       "    NWP4_12h_D_CLCT  \n",
       "0               NaN  \n",
       "1               NaN  \n",
       "2               NaN  \n",
       "3               NaN  \n",
       "4               NaN  \n",
       "5               NaN  \n",
       "6               NaN  \n",
       "7               NaN  \n",
       "8               NaN  \n",
       "9               NaN  \n",
       "10              NaN  \n",
       "11        97.579845  \n",
       "12       100.000000  \n",
       "13        98.750248  \n",
       "14        89.463322  \n",
       "15        78.000393  \n",
       "16        58.352274  \n",
       "17        72.673306  \n",
       "18        97.230403  \n",
       "19        71.301477  \n",
       "20        85.144887  \n",
       "21        84.595545  \n",
       "22        82.483632  \n",
       "23              NaN  \n",
       "24              NaN  \n",
       "25              NaN  \n",
       "26              NaN  \n",
       "27              NaN  \n",
       "28              NaN  \n",
       "29              NaN  \n",
       "30              NaN  \n",
       "31              NaN  \n",
       "32              NaN  \n",
       "33              NaN  \n",
       "34              NaN  \n",
       "35        10.477150  \n",
       "36        73.851338  \n",
       "37        97.775166  \n",
       "38        93.520821  \n",
       "39        99.876398  \n",
       "40       100.000000  \n",
       "41       100.000000  \n",
       "42        70.297403  \n",
       "43        83.835622  \n",
       "44       100.000000  \n",
       "45       100.000000  \n",
       "46        98.661743  \n",
       "47              NaN  \n",
       "48              NaN  \n",
       "49              NaN  \n",
       "50              NaN  \n",
       "51              NaN  \n",
       "52              NaN  \n",
       "53              NaN  \n",
       "54              NaN  \n",
       "55              NaN  \n",
       "56              NaN  \n",
       "57              NaN  \n",
       "58              NaN  \n",
       "59        53.060285  \n",
       "\n",
       "[60 rows x 105 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "raw_df.head(60)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "wip_df = raw_df.query(\"WF == 'WF1'\").copy()\n",
    "wip_df['dt'] = pd.to_datetime(wip_df['Time'],format='%d/%m/%Y %H:%M') - pd.DateOffset(hours=1)\n",
    "wip_df['date'] = wip_df['dt'].dt.date\n",
    "wip_df['hour'] = wip_df['dt'].dt.hour\n",
    "final_df = wip_df[['ID','dt','date','hour']].merge(raw_df_y,how='left',on='ID',validate='one_to_one')\n",
    "\n",
    "wip_df_test = raw_df_test.query(\"WF == 'WF1'\").copy()\n",
    "wip_df_test['dt'] = pd.to_datetime(wip_df_test['Time'],format='%d/%m/%Y %H:%M') - pd.DateOffset(hours=1)\n",
    "wip_df_test['date'] = wip_df_test['dt'].dt.date\n",
    "wip_df_test['hour'] = wip_df_test['dt'].dt.hour\n",
    "final_df_test = wip_df_test[['ID','dt','date','hour']].copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "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>ID</th>\n",
       "      <th>WF</th>\n",
       "      <th>Time</th>\n",
       "      <th>NWP1_00h_D-2_U</th>\n",
       "      <th>NWP1_00h_D-2_V</th>\n",
       "      <th>NWP1_00h_D-2_T</th>\n",
       "      <th>NWP1_06h_D-2_U</th>\n",
       "      <th>NWP1_06h_D-2_V</th>\n",
       "      <th>NWP1_06h_D-2_T</th>\n",
       "      <th>NWP1_12h_D-2_U</th>\n",
       "      <th>...</th>\n",
       "      <th>NWP4_12h_D-1_CLCT</th>\n",
       "      <th>NWP4_00h_D_U</th>\n",
       "      <th>NWP4_00h_D_V</th>\n",
       "      <th>NWP4_00h_D_CLCT</th>\n",
       "      <th>NWP4_12h_D_U</th>\n",
       "      <th>NWP4_12h_D_V</th>\n",
       "      <th>NWP4_12h_D_CLCT</th>\n",
       "      <th>dt</th>\n",
       "      <th>date</th>\n",
       "      <th>hour</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>WF1</td>\n",
       "      <td>01/05/2018 01:00</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>1.254603</td>\n",
       "      <td>-0.289687</td>\n",
       "      <td>82.543144</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2018-05-01 00:00:00</td>\n",
       "      <td>2018-05-01</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>WF1</td>\n",
       "      <td>01/05/2018 02:00</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>2.490908</td>\n",
       "      <td>-0.413370</td>\n",
       "      <td>99.990844</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2018-05-01 01:00:00</td>\n",
       "      <td>2018-05-01</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>WF1</td>\n",
       "      <td>01/05/2018 03:00</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>0.997093</td>\n",
       "      <td>-1.415138</td>\n",
       "      <td>98.367235</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2018-05-01 02:00:00</td>\n",
       "      <td>2018-05-01</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>WF1</td>\n",
       "      <td>01/05/2018 04:00</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>0.689598</td>\n",
       "      <td>-0.961441</td>\n",
       "      <td>94.860604</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2018-05-01 03:00:00</td>\n",
       "      <td>2018-05-01</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>WF1</td>\n",
       "      <td>01/05/2018 05:00</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>0.290994</td>\n",
       "      <td>-0.294963</td>\n",
       "      <td>95.905879</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2018-05-01 04:00:00</td>\n",
       "      <td>2018-05-01</td>\n",
       "      <td>4</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>6234</th>\n",
       "      <td>6235</td>\n",
       "      <td>WF1</td>\n",
       "      <td>15/01/2019 20:00</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>0.3473</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.000015</td>\n",
       "      <td>-0.342881</td>\n",
       "      <td>-2.369884</td>\n",
       "      <td>-0.000016</td>\n",
       "      <td>-0.190785</td>\n",
       "      <td>-2.347865</td>\n",
       "      <td>-0.00002</td>\n",
       "      <td>2019-01-15 19:00:00</td>\n",
       "      <td>2019-01-15</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6235</th>\n",
       "      <td>6236</td>\n",
       "      <td>WF1</td>\n",
       "      <td>15/01/2019 21:00</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>0.2612</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.000015</td>\n",
       "      <td>-0.476837</td>\n",
       "      <td>-2.186706</td>\n",
       "      <td>-0.000016</td>\n",
       "      <td>-0.372534</td>\n",
       "      <td>-2.067537</td>\n",
       "      <td>-0.00002</td>\n",
       "      <td>2019-01-15 20:00:00</td>\n",
       "      <td>2019-01-15</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6236</th>\n",
       "      <td>6237</td>\n",
       "      <td>WF1</td>\n",
       "      <td>15/01/2019 22:00</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>0.2305</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.000015</td>\n",
       "      <td>-0.618349</td>\n",
       "      <td>-1.923782</td>\n",
       "      <td>-0.000016</td>\n",
       "      <td>-0.529659</td>\n",
       "      <td>-1.793902</td>\n",
       "      <td>-0.00002</td>\n",
       "      <td>2019-01-15 21:00:00</td>\n",
       "      <td>2019-01-15</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6237</th>\n",
       "      <td>6238</td>\n",
       "      <td>WF1</td>\n",
       "      <td>15/01/2019 23:00</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>-0.0387</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.000015</td>\n",
       "      <td>-0.560645</td>\n",
       "      <td>-1.862986</td>\n",
       "      <td>-0.000016</td>\n",
       "      <td>-0.539040</td>\n",
       "      <td>-1.792415</td>\n",
       "      <td>-0.00002</td>\n",
       "      <td>2019-01-15 22:00:00</td>\n",
       "      <td>2019-01-15</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6238</th>\n",
       "      <td>6239</td>\n",
       "      <td>WF1</td>\n",
       "      <td>16/01/2019 00:00</td>\n",
       "      <td>-4.1665</td>\n",
       "      <td>-3.6297</td>\n",
       "      <td>278.75</td>\n",
       "      <td>-2.8647</td>\n",
       "      <td>-4.8536</td>\n",
       "      <td>278.14</td>\n",
       "      <td>-3.1646</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.000020</td>\n",
       "      <td>-0.490542</td>\n",
       "      <td>-1.902304</td>\n",
       "      <td>-0.000014</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019-01-15 23:00:00</td>\n",
       "      <td>2019-01-15</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6239 rows × 108 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        ID   WF              Time  NWP1_00h_D-2_U  NWP1_00h_D-2_V  \\\n",
       "0        1  WF1  01/05/2018 01:00             NaN             NaN   \n",
       "1        2  WF1  01/05/2018 02:00             NaN             NaN   \n",
       "2        3  WF1  01/05/2018 03:00             NaN             NaN   \n",
       "3        4  WF1  01/05/2018 04:00             NaN             NaN   \n",
       "4        5  WF1  01/05/2018 05:00             NaN             NaN   \n",
       "...    ...  ...               ...             ...             ...   \n",
       "6234  6235  WF1  15/01/2019 20:00             NaN             NaN   \n",
       "6235  6236  WF1  15/01/2019 21:00             NaN             NaN   \n",
       "6236  6237  WF1  15/01/2019 22:00             NaN             NaN   \n",
       "6237  6238  WF1  15/01/2019 23:00             NaN             NaN   \n",
       "6238  6239  WF1  16/01/2019 00:00         -4.1665         -3.6297   \n",
       "\n",
       "      NWP1_00h_D-2_T  NWP1_06h_D-2_U  NWP1_06h_D-2_V  NWP1_06h_D-2_T  \\\n",
       "0                NaN             NaN             NaN             NaN   \n",
       "1                NaN             NaN             NaN             NaN   \n",
       "2                NaN             NaN             NaN             NaN   \n",
       "3                NaN             NaN             NaN             NaN   \n",
       "4                NaN             NaN             NaN             NaN   \n",
       "...              ...             ...             ...             ...   \n",
       "6234             NaN             NaN             NaN             NaN   \n",
       "6235             NaN             NaN             NaN             NaN   \n",
       "6236             NaN             NaN             NaN             NaN   \n",
       "6237             NaN             NaN             NaN             NaN   \n",
       "6238          278.75         -2.8647         -4.8536          278.14   \n",
       "\n",
       "      NWP1_12h_D-2_U  ...  NWP4_12h_D-1_CLCT  NWP4_00h_D_U  NWP4_00h_D_V  \\\n",
       "0                NaN  ...                NaN      1.254603     -0.289687   \n",
       "1                NaN  ...                NaN      2.490908     -0.413370   \n",
       "2                NaN  ...                NaN      0.997093     -1.415138   \n",
       "3                NaN  ...                NaN      0.689598     -0.961441   \n",
       "4                NaN  ...                NaN      0.290994     -0.294963   \n",
       "...              ...  ...                ...           ...           ...   \n",
       "6234          0.3473  ...          -0.000015     -0.342881     -2.369884   \n",
       "6235          0.2612  ...          -0.000015     -0.476837     -2.186706   \n",
       "6236          0.2305  ...          -0.000015     -0.618349     -1.923782   \n",
       "6237         -0.0387  ...          -0.000015     -0.560645     -1.862986   \n",
       "6238         -3.1646  ...          -0.000020     -0.490542     -1.902304   \n",
       "\n",
       "      NWP4_00h_D_CLCT  NWP4_12h_D_U  NWP4_12h_D_V  NWP4_12h_D_CLCT  \\\n",
       "0           82.543144           NaN           NaN              NaN   \n",
       "1           99.990844           NaN           NaN              NaN   \n",
       "2           98.367235           NaN           NaN              NaN   \n",
       "3           94.860604           NaN           NaN              NaN   \n",
       "4           95.905879           NaN           NaN              NaN   \n",
       "...               ...           ...           ...              ...   \n",
       "6234        -0.000016     -0.190785     -2.347865         -0.00002   \n",
       "6235        -0.000016     -0.372534     -2.067537         -0.00002   \n",
       "6236        -0.000016     -0.529659     -1.793902         -0.00002   \n",
       "6237        -0.000016     -0.539040     -1.792415         -0.00002   \n",
       "6238        -0.000014           NaN           NaN              NaN   \n",
       "\n",
       "                      dt        date  hour  \n",
       "0    2018-05-01 00:00:00  2018-05-01     0  \n",
       "1    2018-05-01 01:00:00  2018-05-01     1  \n",
       "2    2018-05-01 02:00:00  2018-05-01     2  \n",
       "3    2018-05-01 03:00:00  2018-05-01     3  \n",
       "4    2018-05-01 04:00:00  2018-05-01     4  \n",
       "...                  ...         ...   ...  \n",
       "6234 2019-01-15 19:00:00  2019-01-15    19  \n",
       "6235 2019-01-15 20:00:00  2019-01-15    20  \n",
       "6236 2019-01-15 21:00:00  2019-01-15    21  \n",
       "6237 2019-01-15 22:00:00  2019-01-15    22  \n",
       "6238 2019-01-15 23:00:00  2019-01-15    23  \n",
       "\n",
       "[6239 rows x 108 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wip_df\n",
    "#wip_df_test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def combine_forecasts(wip_df,final_df):\n",
    "    for nwp_ix in range(1,5):\n",
    "        nwp_df = wip_df.filter(like='NWP' + str(nwp_ix)).copy()\n",
    "\n",
    "        print(\"######\")\n",
    "        print(\"NWP: \" + str(nwp_ix))\n",
    "\n",
    "        for fcst_item in ['U','V','T','CLCT']:\n",
    "            #nwp_df.filter(regex= \"_\" + fcst_item + \"$\")\n",
    "            print(\"------\")\n",
    "            print(\"Item: \" + str(fcst_item))\n",
    "            fcst_item_df = nwp_df.filter(regex= \"_\" + fcst_item + \"$\")\n",
    "            print(\"Ncol: \" + str(len(list(fcst_item_df.columns))))\n",
    "            if len(list(fcst_item_df.columns)) == 0:\n",
    "                continue\n",
    "\n",
    "            the_col_name = 'NWP'+ str(nwp_ix) +'_' + fcst_item \n",
    "            final_df[the_col_name + '_train'] = np.NaN\n",
    "            final_df[the_col_name + '_test'] = np.NaN\n",
    "\n",
    "            ## 00h_D-1\n",
    "            allowed_for_test = True\n",
    "            for col in fcst_item_df.columns:\n",
    "                print(\"Column: \" + col)\n",
    "                final_df[the_col_name + '_train'] = nwp_df[col].fillna(final_df[the_col_name + '_train'])\n",
    "                if allowed_for_test:\n",
    "                    final_df[the_col_name + '_test'] = final_df[the_col_name + '_train']\n",
    "               # print(re.search(\"00h_D-1_\",col)\n",
    "                if re.search(\"00h_D-1_\",col) is not None:\n",
    "                    print(\"End of test\")\n",
    "                    allowed_for_test = False\n",
    "\n",
    "        print(\"######\")\n",
    "    return final_df\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "######\n",
      "NWP: 1\n",
      "------\n",
      "Item: U\n",
      "Ncol: 12\n",
      "Column: NWP1_00h_D-2_U\n",
      "Column: NWP1_06h_D-2_U\n",
      "Column: NWP1_12h_D-2_U\n",
      "Column: NWP1_18h_D-2_U\n",
      "Column: NWP1_00h_D-1_U\n",
      "End of test\n",
      "Column: NWP1_06h_D-1_U\n",
      "Column: NWP1_12h_D-1_U\n",
      "Column: NWP1_18h_D-1_U\n",
      "Column: NWP1_00h_D_U\n",
      "Column: NWP1_06h_D_U\n",
      "Column: NWP1_12h_D_U\n",
      "Column: NWP1_18h_D_U\n",
      "------\n",
      "Item: V\n",
      "Ncol: 12\n",
      "Column: NWP1_00h_D-2_V\n",
      "Column: NWP1_06h_D-2_V\n",
      "Column: NWP1_12h_D-2_V\n",
      "Column: NWP1_18h_D-2_V\n",
      "Column: NWP1_00h_D-1_V\n",
      "End of test\n",
      "Column: NWP1_06h_D-1_V\n",
      "Column: NWP1_12h_D-1_V\n",
      "Column: NWP1_18h_D-1_V\n",
      "Column: NWP1_00h_D_V\n",
      "Column: NWP1_06h_D_V\n",
      "Column: NWP1_12h_D_V\n",
      "Column: NWP1_18h_D_V\n",
      "------\n",
      "Item: T\n",
      "Ncol: 12\n",
      "Column: NWP1_00h_D-2_T\n",
      "Column: NWP1_06h_D-2_T\n",
      "Column: NWP1_12h_D-2_T\n",
      "Column: NWP1_18h_D-2_T\n",
      "Column: NWP1_00h_D-1_T\n",
      "End of test\n",
      "Column: NWP1_06h_D-1_T\n",
      "Column: NWP1_12h_D-1_T\n",
      "Column: NWP1_18h_D-1_T\n",
      "Column: NWP1_00h_D_T\n",
      "Column: NWP1_06h_D_T\n",
      "Column: NWP1_12h_D_T\n",
      "Column: NWP1_18h_D_T\n",
      "------\n",
      "Item: CLCT\n",
      "Ncol: 0\n",
      "######\n",
      "######\n",
      "NWP: 2\n",
      "------\n",
      "Item: U\n",
      "Ncol: 6\n",
      "Column: NWP2_00h_D-2_U\n",
      "Column: NWP2_12h_D-2_U\n",
      "Column: NWP2_00h_D-1_U\n",
      "End of test\n",
      "Column: NWP2_12h_D-1_U\n",
      "Column: NWP2_00h_D_U\n",
      "Column: NWP2_12h_D_U\n",
      "------\n",
      "Item: V\n",
      "Ncol: 6\n",
      "Column: NWP2_00h_D-2_V\n",
      "Column: NWP2_12h_D-2_V\n",
      "Column: NWP2_00h_D-1_V\n",
      "End of test\n",
      "Column: NWP2_12h_D-1_V\n",
      "Column: NWP2_00h_D_V\n",
      "Column: NWP2_12h_D_V\n",
      "------\n",
      "Item: T\n",
      "Ncol: 0\n",
      "------\n",
      "Item: CLCT\n",
      "Ncol: 0\n",
      "######\n",
      "######\n",
      "NWP: 3\n",
      "------\n",
      "Item: U\n",
      "Ncol: 12\n",
      "Column: NWP3_00h_D-2_U\n",
      "Column: NWP3_06h_D-2_U\n",
      "Column: NWP3_12h_D-2_U\n",
      "Column: NWP3_18h_D-2_U\n",
      "Column: NWP3_00h_D-1_U\n",
      "End of test\n",
      "Column: NWP3_06h_D-1_U\n",
      "Column: NWP3_12h_D-1_U\n",
      "Column: NWP3_18h_D-1_U\n",
      "Column: NWP3_00h_D_U\n",
      "Column: NWP3_06h_D_U\n",
      "Column: NWP3_12h_D_U\n",
      "Column: NWP3_18h_D_U\n",
      "------\n",
      "Item: V\n",
      "Ncol: 12\n",
      "Column: NWP3_00h_D-2_V\n",
      "Column: NWP3_06h_D-2_V\n",
      "Column: NWP3_12h_D-2_V\n",
      "Column: NWP3_18h_D-2_V\n",
      "Column: NWP3_00h_D-1_V\n",
      "End of test\n",
      "Column: NWP3_06h_D-1_V\n",
      "Column: NWP3_12h_D-1_V\n",
      "Column: NWP3_18h_D-1_V\n",
      "Column: NWP3_00h_D_V\n",
      "Column: NWP3_06h_D_V\n",
      "Column: NWP3_12h_D_V\n",
      "Column: NWP3_18h_D_V\n",
      "------\n",
      "Item: T\n",
      "Ncol: 12\n",
      "Column: NWP3_00h_D-2_T\n",
      "Column: NWP3_06h_D-2_T\n",
      "Column: NWP3_12h_D-2_T\n",
      "Column: NWP3_18h_D-2_T\n",
      "Column: NWP3_00h_D-1_T\n",
      "End of test\n",
      "Column: NWP3_06h_D-1_T\n",
      "Column: NWP3_12h_D-1_T\n",
      "Column: NWP3_18h_D-1_T\n",
      "Column: NWP3_00h_D_T\n",
      "Column: NWP3_06h_D_T\n",
      "Column: NWP3_12h_D_T\n",
      "Column: NWP3_18h_D_T\n",
      "------\n",
      "Item: CLCT\n",
      "Ncol: 0\n",
      "######\n",
      "######\n",
      "NWP: 4\n",
      "------\n",
      "Item: U\n",
      "Ncol: 6\n",
      "Column: NWP4_00h_D-2_U\n",
      "Column: NWP4_12h_D-2_U\n",
      "Column: NWP4_00h_D-1_U\n",
      "End of test\n",
      "Column: NWP4_12h_D-1_U\n",
      "Column: NWP4_00h_D_U\n",
      "Column: NWP4_12h_D_U\n",
      "------\n",
      "Item: V\n",
      "Ncol: 6\n",
      "Column: NWP4_00h_D-2_V\n",
      "Column: NWP4_12h_D-2_V\n",
      "Column: NWP4_00h_D-1_V\n",
      "End of test\n",
      "Column: NWP4_12h_D-1_V\n",
      "Column: NWP4_00h_D_V\n",
      "Column: NWP4_12h_D_V\n",
      "------\n",
      "Item: T\n",
      "Ncol: 0\n",
      "------\n",
      "Item: CLCT\n",
      "Ncol: 6\n",
      "Column: NWP4_00h_D-2_CLCT\n",
      "Column: NWP4_12h_D-2_CLCT\n",
      "Column: NWP4_00h_D-1_CLCT\n",
      "End of test\n",
      "Column: NWP4_12h_D-1_CLCT\n",
      "Column: NWP4_00h_D_CLCT\n",
      "Column: NWP4_12h_D_CLCT\n",
      "######\n",
      "######\n",
      "NWP: 1\n",
      "------\n",
      "Item: U\n",
      "Ncol: 12\n",
      "Column: NWP1_00h_D-2_U\n",
      "Column: NWP1_06h_D-2_U\n",
      "Column: NWP1_12h_D-2_U\n",
      "Column: NWP1_18h_D-2_U\n",
      "Column: NWP1_00h_D-1_U\n",
      "End of test\n",
      "Column: NWP1_06h_D-1_U\n",
      "Column: NWP1_12h_D-1_U\n",
      "Column: NWP1_18h_D-1_U\n",
      "Column: NWP1_00h_D_U\n",
      "Column: NWP1_06h_D_U\n",
      "Column: NWP1_12h_D_U\n",
      "Column: NWP1_18h_D_U\n",
      "------\n",
      "Item: V\n",
      "Ncol: 12\n",
      "Column: NWP1_00h_D-2_V\n",
      "Column: NWP1_06h_D-2_V\n",
      "Column: NWP1_12h_D-2_V\n",
      "Column: NWP1_18h_D-2_V\n",
      "Column: NWP1_00h_D-1_V\n",
      "End of test\n",
      "Column: NWP1_06h_D-1_V\n",
      "Column: NWP1_12h_D-1_V\n",
      "Column: NWP1_18h_D-1_V\n",
      "Column: NWP1_00h_D_V\n",
      "Column: NWP1_06h_D_V\n",
      "Column: NWP1_12h_D_V\n",
      "Column: NWP1_18h_D_V\n",
      "------\n",
      "Item: T\n",
      "Ncol: 12\n",
      "Column: NWP1_00h_D-2_T\n",
      "Column: NWP1_06h_D-2_T\n",
      "Column: NWP1_12h_D-2_T\n",
      "Column: NWP1_18h_D-2_T\n",
      "Column: NWP1_00h_D-1_T\n",
      "End of test\n",
      "Column: NWP1_06h_D-1_T\n",
      "Column: NWP1_12h_D-1_T\n",
      "Column: NWP1_18h_D-1_T\n",
      "Column: NWP1_00h_D_T\n",
      "Column: NWP1_06h_D_T\n",
      "Column: NWP1_12h_D_T\n",
      "Column: NWP1_18h_D_T\n",
      "------\n",
      "Item: CLCT\n",
      "Ncol: 0\n",
      "######\n",
      "######\n",
      "NWP: 2\n",
      "------\n",
      "Item: U\n",
      "Ncol: 6\n",
      "Column: NWP2_00h_D-2_U\n",
      "Column: NWP2_12h_D-2_U\n",
      "Column: NWP2_00h_D-1_U\n",
      "End of test\n",
      "Column: NWP2_12h_D-1_U\n",
      "Column: NWP2_00h_D_U\n",
      "Column: NWP2_12h_D_U\n",
      "------\n",
      "Item: V\n",
      "Ncol: 6\n",
      "Column: NWP2_00h_D-2_V\n",
      "Column: NWP2_12h_D-2_V\n",
      "Column: NWP2_00h_D-1_V\n",
      "End of test\n",
      "Column: NWP2_12h_D-1_V\n",
      "Column: NWP2_00h_D_V\n",
      "Column: NWP2_12h_D_V\n",
      "------\n",
      "Item: T\n",
      "Ncol: 0\n",
      "------\n",
      "Item: CLCT\n",
      "Ncol: 0\n",
      "######\n",
      "######\n",
      "NWP: 3\n",
      "------\n",
      "Item: U\n",
      "Ncol: 12\n",
      "Column: NWP3_00h_D-2_U\n",
      "Column: NWP3_06h_D-2_U\n",
      "Column: NWP3_12h_D-2_U\n",
      "Column: NWP3_18h_D-2_U\n",
      "Column: NWP3_00h_D-1_U\n",
      "End of test\n",
      "Column: NWP3_06h_D-1_U\n",
      "Column: NWP3_12h_D-1_U\n",
      "Column: NWP3_18h_D-1_U\n",
      "Column: NWP3_00h_D_U\n",
      "Column: NWP3_06h_D_U\n",
      "Column: NWP3_12h_D_U\n",
      "Column: NWP3_18h_D_U\n",
      "------\n",
      "Item: V\n",
      "Ncol: 12\n",
      "Column: NWP3_00h_D-2_V\n",
      "Column: NWP3_06h_D-2_V\n",
      "Column: NWP3_12h_D-2_V\n",
      "Column: NWP3_18h_D-2_V\n",
      "Column: NWP3_00h_D-1_V\n",
      "End of test\n",
      "Column: NWP3_06h_D-1_V\n",
      "Column: NWP3_12h_D-1_V\n",
      "Column: NWP3_18h_D-1_V\n",
      "Column: NWP3_00h_D_V\n",
      "Column: NWP3_06h_D_V\n",
      "Column: NWP3_12h_D_V\n",
      "Column: NWP3_18h_D_V\n",
      "------\n",
      "Item: T\n",
      "Ncol: 12\n",
      "Column: NWP3_00h_D-2_T\n",
      "Column: NWP3_06h_D-2_T\n",
      "Column: NWP3_12h_D-2_T\n",
      "Column: NWP3_18h_D-2_T\n",
      "Column: NWP3_00h_D-1_T\n",
      "End of test\n",
      "Column: NWP3_06h_D-1_T\n",
      "Column: NWP3_12h_D-1_T\n",
      "Column: NWP3_18h_D-1_T\n",
      "Column: NWP3_00h_D_T\n",
      "Column: NWP3_06h_D_T\n",
      "Column: NWP3_12h_D_T\n",
      "Column: NWP3_18h_D_T\n",
      "------\n",
      "Item: CLCT\n",
      "Ncol: 0\n",
      "######\n",
      "######\n",
      "NWP: 4\n",
      "------\n",
      "Item: U\n",
      "Ncol: 6\n",
      "Column: NWP4_00h_D-2_U\n",
      "Column: NWP4_12h_D-2_U\n",
      "Column: NWP4_00h_D-1_U\n",
      "End of test\n",
      "Column: NWP4_12h_D-1_U\n",
      "Column: NWP4_00h_D_U\n",
      "Column: NWP4_12h_D_U\n",
      "------\n",
      "Item: V\n",
      "Ncol: 6\n",
      "Column: NWP4_00h_D-2_V\n",
      "Column: NWP4_12h_D-2_V\n",
      "Column: NWP4_00h_D-1_V\n",
      "End of test\n",
      "Column: NWP4_12h_D-1_V\n",
      "Column: NWP4_00h_D_V\n",
      "Column: NWP4_12h_D_V\n",
      "------\n",
      "Item: T\n",
      "Ncol: 0\n",
      "------\n",
      "Item: CLCT\n",
      "Ncol: 6\n",
      "Column: NWP4_00h_D-2_CLCT\n",
      "Column: NWP4_12h_D-2_CLCT\n",
      "Column: NWP4_00h_D-1_CLCT\n",
      "End of test\n",
      "Column: NWP4_12h_D-1_CLCT\n",
      "Column: NWP4_00h_D_CLCT\n",
      "Column: NWP4_12h_D_CLCT\n",
      "######\n"
     ]
    }
   ],
   "source": [
    "train_df = combine_forecasts(wip_df,final_df)\n",
    "test_df = combine_forecasts(wip_df_test,final_df_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_df.to_excel(\"data/cnr_train_data.xlsx\",index=False)\n",
    "test_df.to_excel(\"data/cnr_test_data.xlsx\",index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['ID',\n",
       " 'dt',\n",
       " 'date',\n",
       " 'hour',\n",
       " 'Production',\n",
       " 'NWP1_U_train',\n",
       " 'NWP1_U_test',\n",
       " 'NWP1_V_train',\n",
       " 'NWP1_V_test',\n",
       " 'NWP1_T_train',\n",
       " 'NWP1_T_test',\n",
       " 'NWP2_U_train',\n",
       " 'NWP2_U_test',\n",
       " 'NWP2_V_train',\n",
       " 'NWP2_V_test',\n",
       " 'NWP3_U_train',\n",
       " 'NWP3_U_test',\n",
       " 'NWP3_V_train',\n",
       " 'NWP3_V_test',\n",
       " 'NWP3_T_train',\n",
       " 'NWP3_T_test',\n",
       " 'NWP4_U_train',\n",
       " 'NWP4_U_test',\n",
       " 'NWP4_V_train',\n",
       " 'NWP4_V_test',\n",
       " 'NWP4_CLCT_train',\n",
       " 'NWP4_CLCT_test']"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(train_df.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_raw_data = train_df.copy()\n",
    "train_wip_data = train_raw_data.set_index('dt').copy()\n",
    "nwp_col = [col for col in train_wip_data if col.startswith('NWP')]\n",
    "train_wip_data[nwp_col] = train_wip_data[nwp_col].interpolate(method='time')\n",
    "train_cols = ['ID','date','hour','Production'] + [col for col in train_wip_data if col.endswith('_train')] \n",
    "train_cols_proper = [col.replace(\"_train\",\"\") for col in train_cols]\n",
    "train_cols_proper = map(lambda x:x.lower(),train_cols_proper)\n",
    "train_final_df = train_wip_data[train_cols].copy()\n",
    "train_final_df.columns = train_cols_proper\n",
    "\n",
    "train_final_df.to_excel(\"data/preprocessed_train_data.xlsx\",index=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "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>id</th>\n",
       "      <th>date</th>\n",
       "      <th>hour</th>\n",
       "      <th>production</th>\n",
       "      <th>nwp1_u</th>\n",
       "      <th>nwp1_v</th>\n",
       "      <th>nwp1_t</th>\n",
       "      <th>nwp2_u</th>\n",
       "      <th>nwp2_v</th>\n",
       "      <th>nwp3_u</th>\n",
       "      <th>nwp3_v</th>\n",
       "      <th>nwp3_t</th>\n",
       "      <th>nwp4_u</th>\n",
       "      <th>nwp4_v</th>\n",
       "      <th>nwp4_clct</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>dt</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>2018-05-01 00:00:00</th>\n",
       "      <td>1</td>\n",
       "      <td>2018-05-01</td>\n",
       "      <td>0</td>\n",
       "      <td>0.02</td>\n",
       "      <td>-2.2485</td>\n",
       "      <td>-3.2578</td>\n",
       "      <td>286.44</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.254603</td>\n",
       "      <td>-0.289687</td>\n",
       "      <td>82.543144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-01 01:00:00</th>\n",
       "      <td>2</td>\n",
       "      <td>2018-05-01</td>\n",
       "      <td>1</td>\n",
       "      <td>0.07</td>\n",
       "      <td>-2.4345</td>\n",
       "      <td>-1.4461</td>\n",
       "      <td>286.26</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.490908</td>\n",
       "      <td>-0.413370</td>\n",
       "      <td>99.990844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-01 02:00:00</th>\n",
       "      <td>3</td>\n",
       "      <td>2018-05-01</td>\n",
       "      <td>2</td>\n",
       "      <td>0.22</td>\n",
       "      <td>3.3659</td>\n",
       "      <td>-3.0605</td>\n",
       "      <td>285.75</td>\n",
       "      <td>2.6117</td>\n",
       "      <td>-2.342700</td>\n",
       "      <td>-1.148957</td>\n",
       "      <td>-2.274751</td>\n",
       "      <td>286.000000</td>\n",
       "      <td>0.997093</td>\n",
       "      <td>-1.415138</td>\n",
       "      <td>98.367235</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-01 03:00:00</th>\n",
       "      <td>4</td>\n",
       "      <td>2018-05-01</td>\n",
       "      <td>3</td>\n",
       "      <td>0.39</td>\n",
       "      <td>3.7065</td>\n",
       "      <td>-6.2174</td>\n",
       "      <td>284.78</td>\n",
       "      <td>3.1783</td>\n",
       "      <td>-2.783800</td>\n",
       "      <td>-0.518961</td>\n",
       "      <td>-2.721086</td>\n",
       "      <td>285.666667</td>\n",
       "      <td>0.689598</td>\n",
       "      <td>-0.961441</td>\n",
       "      <td>94.860604</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-01 04:00:00</th>\n",
       "      <td>5</td>\n",
       "      <td>2018-05-01</td>\n",
       "      <td>4</td>\n",
       "      <td>0.41</td>\n",
       "      <td>3.8134</td>\n",
       "      <td>-5.4446</td>\n",
       "      <td>284.46</td>\n",
       "      <td>3.7449</td>\n",
       "      <td>-3.224900</td>\n",
       "      <td>0.111036</td>\n",
       "      <td>-3.167422</td>\n",
       "      <td>285.333333</td>\n",
       "      <td>0.290994</td>\n",
       "      <td>-0.294963</td>\n",
       "      <td>95.905879</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-01-15 19:00:00</th>\n",
       "      <td>6235</td>\n",
       "      <td>2019-01-15</td>\n",
       "      <td>19</td>\n",
       "      <td>0.45</td>\n",
       "      <td>-2.5467</td>\n",
       "      <td>-7.6859</td>\n",
       "      <td>280.14</td>\n",
       "      <td>0.3670</td>\n",
       "      <td>-7.042467</td>\n",
       "      <td>-1.072121</td>\n",
       "      <td>-4.298934</td>\n",
       "      <td>281.999746</td>\n",
       "      <td>-0.190785</td>\n",
       "      <td>-2.347865</td>\n",
       "      <td>-0.000020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-01-15 20:00:00</th>\n",
       "      <td>6236</td>\n",
       "      <td>2019-01-15</td>\n",
       "      <td>20</td>\n",
       "      <td>0.54</td>\n",
       "      <td>-3.0983</td>\n",
       "      <td>-6.7763</td>\n",
       "      <td>279.73</td>\n",
       "      <td>0.3789</td>\n",
       "      <td>-6.624100</td>\n",
       "      <td>-1.304119</td>\n",
       "      <td>-3.577566</td>\n",
       "      <td>281.837891</td>\n",
       "      <td>-0.372534</td>\n",
       "      <td>-2.067537</td>\n",
       "      <td>-0.000020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-01-15 21:00:00</th>\n",
       "      <td>6237</td>\n",
       "      <td>2019-01-15</td>\n",
       "      <td>21</td>\n",
       "      <td>0.05</td>\n",
       "      <td>-3.2611</td>\n",
       "      <td>-5.2765</td>\n",
       "      <td>279.39</td>\n",
       "      <td>-0.3486</td>\n",
       "      <td>-4.886033</td>\n",
       "      <td>-1.655604</td>\n",
       "      <td>-2.932216</td>\n",
       "      <td>281.601522</td>\n",
       "      <td>-0.529659</td>\n",
       "      <td>-1.793902</td>\n",
       "      <td>-0.000020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-01-15 22:00:00</th>\n",
       "      <td>6238</td>\n",
       "      <td>2019-01-15</td>\n",
       "      <td>22</td>\n",
       "      <td>0.04</td>\n",
       "      <td>-3.3457</td>\n",
       "      <td>-3.0868</td>\n",
       "      <td>279.20</td>\n",
       "      <td>-1.0761</td>\n",
       "      <td>-3.147967</td>\n",
       "      <td>-2.007089</td>\n",
       "      <td>-2.286866</td>\n",
       "      <td>281.365153</td>\n",
       "      <td>-0.539040</td>\n",
       "      <td>-1.792415</td>\n",
       "      <td>-0.000020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-01-15 23:00:00</th>\n",
       "      <td>6239</td>\n",
       "      <td>2019-01-15</td>\n",
       "      <td>23</td>\n",
       "      <td>0.05</td>\n",
       "      <td>-3.9338</td>\n",
       "      <td>-1.2971</td>\n",
       "      <td>278.90</td>\n",
       "      <td>-1.8036</td>\n",
       "      <td>-1.409900</td>\n",
       "      <td>-2.358574</td>\n",
       "      <td>-1.641516</td>\n",
       "      <td>281.128784</td>\n",
       "      <td>-0.490542</td>\n",
       "      <td>-1.902304</td>\n",
       "      <td>-0.000014</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6239 rows × 15 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                       id        date  hour  production  nwp1_u  nwp1_v  \\\n",
       "dt                                                                        \n",
       "2018-05-01 00:00:00     1  2018-05-01     0        0.02 -2.2485 -3.2578   \n",
       "2018-05-01 01:00:00     2  2018-05-01     1        0.07 -2.4345 -1.4461   \n",
       "2018-05-01 02:00:00     3  2018-05-01     2        0.22  3.3659 -3.0605   \n",
       "2018-05-01 03:00:00     4  2018-05-01     3        0.39  3.7065 -6.2174   \n",
       "2018-05-01 04:00:00     5  2018-05-01     4        0.41  3.8134 -5.4446   \n",
       "...                   ...         ...   ...         ...     ...     ...   \n",
       "2019-01-15 19:00:00  6235  2019-01-15    19        0.45 -2.5467 -7.6859   \n",
       "2019-01-15 20:00:00  6236  2019-01-15    20        0.54 -3.0983 -6.7763   \n",
       "2019-01-15 21:00:00  6237  2019-01-15    21        0.05 -3.2611 -5.2765   \n",
       "2019-01-15 22:00:00  6238  2019-01-15    22        0.04 -3.3457 -3.0868   \n",
       "2019-01-15 23:00:00  6239  2019-01-15    23        0.05 -3.9338 -1.2971   \n",
       "\n",
       "                     nwp1_t  nwp2_u    nwp2_v    nwp3_u    nwp3_v      nwp3_t  \\\n",
       "dt                                                                              \n",
       "2018-05-01 00:00:00  286.44     NaN       NaN       NaN       NaN         NaN   \n",
       "2018-05-01 01:00:00  286.26     NaN       NaN       NaN       NaN         NaN   \n",
       "2018-05-01 02:00:00  285.75  2.6117 -2.342700 -1.148957 -2.274751  286.000000   \n",
       "2018-05-01 03:00:00  284.78  3.1783 -2.783800 -0.518961 -2.721086  285.666667   \n",
       "2018-05-01 04:00:00  284.46  3.7449 -3.224900  0.111036 -3.167422  285.333333   \n",
       "...                     ...     ...       ...       ...       ...         ...   \n",
       "2019-01-15 19:00:00  280.14  0.3670 -7.042467 -1.072121 -4.298934  281.999746   \n",
       "2019-01-15 20:00:00  279.73  0.3789 -6.624100 -1.304119 -3.577566  281.837891   \n",
       "2019-01-15 21:00:00  279.39 -0.3486 -4.886033 -1.655604 -2.932216  281.601522   \n",
       "2019-01-15 22:00:00  279.20 -1.0761 -3.147967 -2.007089 -2.286866  281.365153   \n",
       "2019-01-15 23:00:00  278.90 -1.8036 -1.409900 -2.358574 -1.641516  281.128784   \n",
       "\n",
       "                       nwp4_u    nwp4_v  nwp4_clct  \n",
       "dt                                                  \n",
       "2018-05-01 00:00:00  1.254603 -0.289687  82.543144  \n",
       "2018-05-01 01:00:00  2.490908 -0.413370  99.990844  \n",
       "2018-05-01 02:00:00  0.997093 -1.415138  98.367235  \n",
       "2018-05-01 03:00:00  0.689598 -0.961441  94.860604  \n",
       "2018-05-01 04:00:00  0.290994 -0.294963  95.905879  \n",
       "...                       ...       ...        ...  \n",
       "2019-01-15 19:00:00 -0.190785 -2.347865  -0.000020  \n",
       "2019-01-15 20:00:00 -0.372534 -2.067537  -0.000020  \n",
       "2019-01-15 21:00:00 -0.529659 -1.793902  -0.000020  \n",
       "2019-01-15 22:00:00 -0.539040 -1.792415  -0.000020  \n",
       "2019-01-15 23:00:00 -0.490542 -1.902304  -0.000014  \n",
       "\n",
       "[6239 rows x 15 columns]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_final_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}