weather_forecast.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "from sklearn.linear_model import Ridge\n",
    "from sklearn.metrics import mean_absolute_error\n",
    "import requests\n",
    "from bs4 import BeautifulSoup\n",
    "import re\n",
    "import dateutil\n",
    "import sys\n",
    "import logging\n",
    "from typing import List\n",
    "from google.cloud import bigquery\n",
    "from google.cloud import bigquery\n",
    "from google.oauth2 import service_account"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "#---------------------Data Cleaning/Transformation-----------------------------------------\n",
    "#read csv to dataframe\n",
    "weather_df = pd.read_csv('./data/noaa_weather_data.csv', index_col='DATE')\n",
    "#rename and filter columns which can be useful\n",
    "core_weather_df = weather_df[['NAME','PRCP', 'SNOW','SNWD', 'TMAX','TMIN']].copy()\n",
    "core_weather_df.columns = ['name','precip', 'snow', 'snow_depth', 'temp_max','temp_min']\n",
    "#fill missing data points\n",
    "core_weather_df['precip'] = core_weather_df['precip'].fillna(0)\n",
    "core_weather_df['snow'] = core_weather_df['snow'].fillna(0)\n",
    "core_weather_df['snow_depth'] = core_weather_df['snow_depth'].fillna(0)\n",
    "#map the name to a number variable to be used as a predictor\n",
    "core_weather_df['name_num'] = pd.factorize(core_weather_df['name'])[0]\n",
    "#'ffill' ('forward fill') fills the value in with the value from the previous date this will apply to the temp_min/max columns since the others have already been filled in\n",
    "core_weather_df = core_weather_df.fillna(method='ffill')\n",
    "#change date index to a datetime data type\n",
    "core_weather_df.index = pd.to_datetime(core_weather_df.index)\n",
    "#make a visual representation of the data and remove cities that have large chunks of missing data\n",
    "core_weather_df = core_weather_df[core_weather_df.name.isin(['BEMIDJI, MN US', 'SHARJAH INTER. AIRP, AE']) == False]\n",
    "# core_weather_df.groupby(by='name').plot()\n",
    "#create a column 'target_temp_max' by shifting all values in the temp_max column back a day...creates a column based on temperatures from tomorrows temps\n",
    "core_weather_df['target_temp_max_day_1'] = core_weather_df.groupby('name')['temp_max'].shift(-1)\n",
    "core_weather_df['target_temp_max_day_2'] = core_weather_df.groupby('name')['target_temp_max_day_1'].shift(-1)\n",
    "core_weather_df['target_temp_max_day_3'] = core_weather_df.groupby('name')['target_temp_max_day_2'].shift(-1)\n",
    "core_weather_df['target_temp_max_day_4'] = core_weather_df.groupby('name')['target_temp_max_day_3'].shift(-1)\n",
    "core_weather_df['target_temp_max_day_5'] = core_weather_df.groupby('name')['target_temp_max_day_4'].shift(-1)\n",
    "core_weather_df['target_temp_max_day_6'] = core_weather_df.groupby('name')['target_temp_max_day_5'].shift(-1)\n",
    "core_weather_df['target_temp_max_day_7'] = core_weather_df.groupby('name')['target_temp_max_day_6'].shift(-1)\n",
    "core_weather_df['target_temp_max_day_8'] = core_weather_df.groupby('name')['target_temp_max_day_7'].shift(-1)\n",
    "core_weather_df['target_temp_max_day_9'] = core_weather_df.groupby('name')['target_temp_max_day_8'].shift(-1)\n",
    "core_weather_df['target_temp_max_day_10'] = core_weather_df.groupby('name')['target_temp_max_day_9'].shift(-1)\n",
    "#remove the last row since its a NaN value cuz that value would be in the future\n",
    "core_weather_df = core_weather_df.dropna()\n",
    "#map each citiy to a numerical values to be used in the regression analysis\n",
    "core_weather_df['name'] = core_weather_df['name'].astype('category')\n",
    "core_weather_df['city_number'] = core_weather_df['name'].cat.codes\n",
    "#training set includes all data before and including dec 12th 2021, this is teh set that is used to train the model to predict future data\n",
    "training_set = core_weather_df.loc[:'2021-12-31']\n",
    "#test set includes all data after and including jan 1st 2022\n",
    "test_set = core_weather_df.loc['2022-01-01':]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>actual</th>\n",
       "      <th>Predicted_temp_next_day</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DATE</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2023-02-10</th>\n",
       "      <td>ORLANDO EXECUTIVE AIRPORT, FL US</td>\n",
       "      <td>84.0</td>\n",
       "      <td>83.125554</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-02-11</th>\n",
       "      <td>ORLANDO EXECUTIVE AIRPORT, FL US</td>\n",
       "      <td>72.0</td>\n",
       "      <td>83.602435</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-02-12</th>\n",
       "      <td>ORLANDO EXECUTIVE AIRPORT, FL US</td>\n",
       "      <td>71.0</td>\n",
       "      <td>71.718667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-02-13</th>\n",
       "      <td>ORLANDO EXECUTIVE AIRPORT, FL US</td>\n",
       "      <td>77.0</td>\n",
       "      <td>70.124692</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-02-14</th>\n",
       "      <td>ORLANDO EXECUTIVE AIRPORT, FL US</td>\n",
       "      <td>82.0</td>\n",
       "      <td>74.840060</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                        name  actual  Predicted_temp_next_day\n",
       "DATE                                                                         \n",
       "2023-02-10  ORLANDO EXECUTIVE AIRPORT, FL US    84.0                83.125554\n",
       "2023-02-11  ORLANDO EXECUTIVE AIRPORT, FL US    72.0                83.602435\n",
       "2023-02-12  ORLANDO EXECUTIVE AIRPORT, FL US    71.0                71.718667\n",
       "2023-02-13  ORLANDO EXECUTIVE AIRPORT, FL US    77.0                70.124692\n",
       "2023-02-14  ORLANDO EXECUTIVE AIRPORT, FL US    82.0                74.840060"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#-----------------create/test data model--------------------------------\n",
    "#using Ridge regression to minimize overfitting\n",
    "regression = Ridge(alpha=.1)\n",
    "predictors = ['precip','temp_max','temp_min','city_number']\n",
    "#training set includes all data before and including dec 12th 2021, this is teh set that is used to train the model to predict future data\n",
    "training_set = core_weather_df.loc[:'2021-12-31']\n",
    "# #test set includes all data after and including jan 1st 2022\n",
    "test_set = test_set.loc['2022-01-01':]\n",
    "\n",
    "# test_set_shifted = test_set.shift(365, freq='D')\n",
    "# test_set2= test_set_shifted.loc['2023-01-01':'2023-12-31']\n",
    "\n",
    "#train the model based on the predictors\n",
    "regression.fit(training_set[predictors], training_set['target_temp_max_day_1'])\n",
    "predictions = regression.predict(test_set[predictors])\n",
    "\n",
    "combined_df = pd.concat([test_set[['name','target_temp_max_day_1']], pd.Series(predictions, index = test_set.index)], axis=1)\n",
    "combined_df.columns = ['name','actual','Predicted_temp_next_day']\n",
    "\n",
    "display(combined_df.tail())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>temp</th>\n",
       "      <th>tempmin</th>\n",
       "      <th>tempmax</th>\n",
       "      <th>Barometer</th>\n",
       "      <th>Dewpoint</th>\n",
       "      <th>Humidity</th>\n",
       "      <th>Last update</th>\n",
       "      <th>Visibility</th>\n",
       "      <th>Wind Chill</th>\n",
       "      <th>Wind Speed</th>\n",
       "      <th>elevation_ft</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>weather_station</th>\n",
       "      <th>Heat Index</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>48°F</td>\n",
       "      <td>Low: 30 °F</td>\n",
       "      <td>High: 51 °F</td>\n",
       "      <td>30.17 in (1021.7 mb)</td>\n",
       "      <td>24°F (-4°C)</td>\n",
       "      <td>39%</td>\n",
       "      <td>8 Mar 4:54 pm EST</td>\n",
       "      <td>10.00 mi</td>\n",
       "      <td>42°F (6°C)</td>\n",
       "      <td>N 16 mph</td>\n",
       "      <td>7</td>\n",
       "      <td>39.87</td>\n",
       "      <td>75.23</td>\n",
       "      <td>Philadelphia, Philadelphia International Airpo...</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>77°F</td>\n",
       "      <td>Low: 60 °F</td>\n",
       "      <td>High: 80 °F</td>\n",
       "      <td>30.07 in (1018.0 mb)</td>\n",
       "      <td>61°F (16°C)</td>\n",
       "      <td>58%</td>\n",
       "      <td>8 Mar 4:53 pm EST</td>\n",
       "      <td>10.00 mi</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NE 20 mph</td>\n",
       "      <td>89</td>\n",
       "      <td>28.42</td>\n",
       "      <td>81.32</td>\n",
       "      <td>Orlando International Airport (KMCO)</td>\n",
       "      <td>79°F (26°C)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>40°F</td>\n",
       "      <td>Low: 32 °F</td>\n",
       "      <td>High: 37 °F</td>\n",
       "      <td>30.50 in (1033.5 mb)</td>\n",
       "      <td>23°F (-5°C)</td>\n",
       "      <td>51%</td>\n",
       "      <td>8 Mar 3:52 pm CST</td>\n",
       "      <td>10.00 mi</td>\n",
       "      <td>33°F (1°C)</td>\n",
       "      <td>NE 12 mph</td>\n",
       "      <td>722</td>\n",
       "      <td>42.96</td>\n",
       "      <td>87.9</td>\n",
       "      <td>Milwaukee, General Mitchell International Airp...</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>60°F</td>\n",
       "      <td>Low: 30 °F</td>\n",
       "      <td>High: 60 °F</td>\n",
       "      <td>30.19 in (1022.3 mb)</td>\n",
       "      <td>21°F (-6°C)</td>\n",
       "      <td>22%</td>\n",
       "      <td>8 Mar 4:54 pm EST</td>\n",
       "      <td>10.00 mi</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NW 5 mph</td>\n",
       "      <td>935</td>\n",
       "      <td>37.32</td>\n",
       "      <td>79.21</td>\n",
       "      <td>Lynchburg, Lynchburg Regional Airport (KLYH)</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>34°F</td>\n",
       "      <td>Low: 9 °F</td>\n",
       "      <td>High: 32 °F</td>\n",
       "      <td>29.97 in (1014.9 mb)</td>\n",
       "      <td>16°F (-9°C)</td>\n",
       "      <td>47%</td>\n",
       "      <td>08 Mar 03:35 PM MST</td>\n",
       "      <td>10.00 mi</td>\n",
       "      <td>23°F (-5°C)</td>\n",
       "      <td>NNE 18 MPH</td>\n",
       "      <td>2972</td>\n",
       "      <td>48.30417</td>\n",
       "      <td>114.26361</td>\n",
       "      <td>Kalispell, Glacier Park International Airport ...</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>70°F</td>\n",
       "      <td>Low: 66 °F</td>\n",
       "      <td>High: 80 °F</td>\n",
       "      <td>29.80 in</td>\n",
       "      <td>66°F (19°C)</td>\n",
       "      <td>88%</td>\n",
       "      <td>8 Mar 12:31 pm HST</td>\n",
       "      <td>8.00 mi</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S 20 G 31 mph</td>\n",
       "      <td>52</td>\n",
       "      <td>20.89</td>\n",
       "      <td>156.44</td>\n",
       "      <td>Kahului, Kahului Airport (PHOG)</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>24°F</td>\n",
       "      <td>Low: 20 °F</td>\n",
       "      <td>High: 31 °F</td>\n",
       "      <td>30.21 in (1024.2 mb)</td>\n",
       "      <td>18°F (-8°C)</td>\n",
       "      <td>77%</td>\n",
       "      <td>8 Mar 12:53 pm AKST</td>\n",
       "      <td>10.00 mi</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Calm</td>\n",
       "      <td>433</td>\n",
       "      <td>64.8</td>\n",
       "      <td>147.88</td>\n",
       "      <td>Fairbanks, Fairbanks International Airport (PAFA)</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>43°F</td>\n",
       "      <td>Low: 31 °F</td>\n",
       "      <td>High: 41 °F</td>\n",
       "      <td>29.99 in (1015.6 mb)</td>\n",
       "      <td>28°F (-2°C)</td>\n",
       "      <td>56%</td>\n",
       "      <td>8 Mar 4:53 pm EST</td>\n",
       "      <td>10.00 mi</td>\n",
       "      <td>35°F (2°C)</td>\n",
       "      <td>N 18 G 24 mph</td>\n",
       "      <td>190</td>\n",
       "      <td>44.8</td>\n",
       "      <td>68.82</td>\n",
       "      <td>Bangor, Bangor International Airport (KBGR)</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>70°F</td>\n",
       "      <td>Low: 36 °F</td>\n",
       "      <td>High: 71 °F</td>\n",
       "      <td>29.95 in (1009.5 mb)</td>\n",
       "      <td>26°F (-3°C)</td>\n",
       "      <td>19%</td>\n",
       "      <td>8 Mar 2:52 pm MST</td>\n",
       "      <td>10.00 mi</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SW 24 G 36 mph</td>\n",
       "      <td>5351</td>\n",
       "      <td>35.04</td>\n",
       "      <td>106.61</td>\n",
       "      <td>Albuquerque, Albuquerque International Airport...</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>43°F</td>\n",
       "      <td>Low: 36 °F</td>\n",
       "      <td>High: 48 °F</td>\n",
       "      <td>30.0 in (1015.92 mb)</td>\n",
       "      <td>36°F (2°C)</td>\n",
       "      <td>75%</td>\n",
       "      <td>08 Mar 02:20 PM PST</td>\n",
       "      <td>10.00 mi</td>\n",
       "      <td>38°F (3°C)</td>\n",
       "      <td>ESE 8 MPH</td>\n",
       "      <td>20</td>\n",
       "      <td>45.59578</td>\n",
       "      <td>122.60917</td>\n",
       "      <td>Portland, Portland International Airport (KPDX)</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>35°F</td>\n",
       "      <td>Low: 17 °F</td>\n",
       "      <td>High: 29 °F</td>\n",
       "      <td>30.21 in (1023.1 mb)</td>\n",
       "      <td>9°F (-13°C)</td>\n",
       "      <td>34%</td>\n",
       "      <td>8 Mar 12:53 pm AKST</td>\n",
       "      <td>10.00 mi</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Calm</td>\n",
       "      <td>13</td>\n",
       "      <td>57.05</td>\n",
       "      <td>135.36</td>\n",
       "      <td>Sitka - Sitka Airport (PASI)</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    temp     tempmin      tempmax             Barometer     Dewpoint Humidity  \\\n",
       "0   48°F  Low: 30 °F  High: 51 °F  30.17 in (1021.7 mb)  24°F (-4°C)      39%   \n",
       "1   77°F  Low: 60 °F  High: 80 °F  30.07 in (1018.0 mb)  61°F (16°C)      58%   \n",
       "2   40°F  Low: 32 °F  High: 37 °F  30.50 in (1033.5 mb)  23°F (-5°C)      51%   \n",
       "3   60°F  Low: 30 °F  High: 60 °F  30.19 in (1022.3 mb)  21°F (-6°C)      22%   \n",
       "4   34°F   Low: 9 °F  High: 32 °F  29.97 in (1014.9 mb)  16°F (-9°C)      47%   \n",
       "5   70°F  Low: 66 °F  High: 80 °F              29.80 in  66°F (19°C)      88%   \n",
       "6   24°F  Low: 20 °F  High: 31 °F  30.21 in (1024.2 mb)  18°F (-8°C)      77%   \n",
       "7   43°F  Low: 31 °F  High: 41 °F  29.99 in (1015.6 mb)  28°F (-2°C)      56%   \n",
       "8   70°F  Low: 36 °F  High: 71 °F  29.95 in (1009.5 mb)  26°F (-3°C)      19%   \n",
       "9   43°F  Low: 36 °F  High: 48 °F  30.0 in (1015.92 mb)   36°F (2°C)      75%   \n",
       "10  35°F  Low: 17 °F  High: 29 °F  30.21 in (1023.1 mb)  9°F (-13°C)      34%   \n",
       "\n",
       "            Last update Visibility   Wind Chill      Wind Speed elevation_ft  \\\n",
       "0     8 Mar 4:54 pm EST   10.00 mi   42°F (6°C)        N 16 mph            7   \n",
       "1     8 Mar 4:53 pm EST   10.00 mi          NaN       NE 20 mph           89   \n",
       "2     8 Mar 3:52 pm CST   10.00 mi   33°F (1°C)       NE 12 mph          722   \n",
       "3     8 Mar 4:54 pm EST   10.00 mi          NaN        NW 5 mph          935   \n",
       "4   08 Mar 03:35 PM MST   10.00 mi  23°F (-5°C)      NNE 18 MPH         2972   \n",
       "5    8 Mar 12:31 pm HST    8.00 mi          NaN   S 20 G 31 mph           52   \n",
       "6   8 Mar 12:53 pm AKST   10.00 mi          NaN            Calm          433   \n",
       "7     8 Mar 4:53 pm EST   10.00 mi   35°F (2°C)   N 18 G 24 mph          190   \n",
       "8     8 Mar 2:52 pm MST   10.00 mi          NaN  SW 24 G 36 mph         5351   \n",
       "9   08 Mar 02:20 PM PST   10.00 mi   38°F (3°C)       ESE 8 MPH           20   \n",
       "10  8 Mar 12:53 pm AKST   10.00 mi          NaN            Calm           13   \n",
       "\n",
       "    latitude  longitude                                    weather_station  \\\n",
       "0      39.87      75.23  Philadelphia, Philadelphia International Airpo...   \n",
       "1      28.42      81.32               Orlando International Airport (KMCO)   \n",
       "2      42.96       87.9  Milwaukee, General Mitchell International Airp...   \n",
       "3      37.32      79.21       Lynchburg, Lynchburg Regional Airport (KLYH)   \n",
       "4   48.30417  114.26361  Kalispell, Glacier Park International Airport ...   \n",
       "5      20.89     156.44                    Kahului, Kahului Airport (PHOG)   \n",
       "6       64.8     147.88  Fairbanks, Fairbanks International Airport (PAFA)   \n",
       "7       44.8      68.82        Bangor, Bangor International Airport (KBGR)   \n",
       "8      35.04     106.61  Albuquerque, Albuquerque International Airport...   \n",
       "9   45.59578  122.60917    Portland, Portland International Airport (KPDX)   \n",
       "10     57.05     135.36                       Sitka - Sitka Airport (PASI)   \n",
       "\n",
       "     Heat Index  \n",
       "0           NaN  \n",
       "1   79°F (26°C)  \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  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#------------scrape current data an append to historical dataset---------------------------------\n",
    "#-------------------Extract-------------------------\n",
    "urls = [\"https://forecast.weather.gov/MapClick.php?lat=57.0826&lon=-135.2692#.Y-vs_9LMJkg\",\n",
    "        'https://forecast.weather.gov/MapClick.php?lat=45.5118&lon=-122.6756#.Y-vtHNLMJkg',\n",
    "        'https://forecast.weather.gov/MapClick.php?lat=35.0842&lon=-106.649#.ZAKIR9LMJhE',\n",
    "        'https://forecast.weather.gov/MapClick.php?lat=44.8017&lon=-68.7708#.ZAKIY9LMJhE',\n",
    "        'https://forecast.weather.gov/MapClick.php?lat=64.8453&lon=-147.7221#.ZAKId9LMJhE',\n",
    "        'https://forecast.weather.gov/MapClick.php?lat=20.8986&lon=-156.4305#.ZAKIjtLMJhE',\n",
    "        'https://forecast.weather.gov/MapClick.php?lat=48.1786&lon=-114.3037#.ZAKIqNLMJhE',\n",
    "        'https://forecast.weather.gov/MapClick.php?lat=37.4142&lon=-79.143#.ZAKIwtLMJhE',\n",
    "        'https://forecast.weather.gov/MapClick.php?lat=42.9467&lon=-87.8967#.ZAKI0tLMJhE',\n",
    "        'https://forecast.weather.gov/MapClick.php?lat=28.4272&lon=-81.308#.ZAKI5NLMJhE',\n",
    "        'https://forecast.weather.gov/MapClick.php?lat=39.8784&lon=-75.2402#.ZAKJAdLMJhE'\n",
    "        ]\n",
    "        \n",
    "combined_df = pd.DataFrame()\n",
    "\n",
    "for url in urls:\n",
    "    r = requests.get(url)\n",
    "    soup = BeautifulSoup(r.content,\"html.parser\")\n",
    "\n",
    "    #various containers\n",
    "    item1 = soup.find_all(id='current_conditions-summary')\n",
    "    item2 = soup.find_all(id='current_conditions_detail')\n",
    "    item4 = soup.find_all(id='tombstone-container')\n",
    "\n",
    "    #raw data\n",
    "    temp_f = [item.find(class_=\"myforecast-current-lrg\").get_text() for item in item1]\n",
    "    temp_min = soup.find('p', {'class': 'temp temp-low'}).text.strip()\n",
    "    temp_max = soup.find('p', {'class': 'temp temp-high'}).text.strip()\n",
    "\n",
    "\n",
    "    #df of temperatures\n",
    "    df_temperature = pd.DataFrame({\"temp\" : temp_f,'tempmin': temp_min,'tempmax': temp_max})\n",
    "\n",
    "    #df_2 is a df of current conditions in detail (Humidity, Wind Speed, Barometer, Dewpoint, Visibility, Last update)\n",
    "    table = soup.find_all('table')\n",
    "    df_2 = pd.read_html(str(table))[0]\n",
    "    df_2 = df_2.rename(columns={'1':'metrics'})\n",
    "    # df_2['1'] = df_2['1'].fillna(0)\n",
    "    df_2 = df_2.pivot(columns=0, values=1).ffill().dropna().reset_index().drop(columns=['index'])\n",
    "\n",
    "    #merge both dataframes\n",
    "    temp_df=pd.concat([df_temperature,df_2],axis=1)\n",
    "\n",
    "    #scrape lattitude, longitude, and elevation \n",
    "    lat_lon_elev = soup.find('span', {'class': 'smallTxt'}).text.strip()\n",
    "    lat, lon, elev = re.findall(r'[-+]?\\d*\\.\\d+|\\d+', lat_lon_elev)\n",
    "\n",
    "    #scrape name\n",
    "    station = soup.find('h2', {'class': 'panel-title'}).text.strip()\n",
    "\n",
    "    #add location, lat, long, and elev to source_df\n",
    "    temp_df['elevation_ft'] = elev\n",
    "    temp_df['latitude'] = lat\n",
    "    temp_df['longitude'] = lon\n",
    "    temp_df['weather_station'] = station\n",
    "\n",
    "    combined_df = pd.concat([temp_df, combined_df], ignore_index=True, sort=False)\n",
    "\n",
    "display(combined_df)"
   ]
  },
  {
   "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>temp</th>\n",
       "      <th>tempmin</th>\n",
       "      <th>tempmax</th>\n",
       "      <th>Barometer</th>\n",
       "      <th>Dewpoint</th>\n",
       "      <th>Humidity</th>\n",
       "      <th>Last update</th>\n",
       "      <th>Visibility</th>\n",
       "      <th>Wind Chill</th>\n",
       "      <th>Wind Speed</th>\n",
       "      <th>elevation_ft</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>weather_station</th>\n",
       "      <th>Heat Index</th>\n",
       "      <th>precip</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>48°F</td>\n",
       "      <td>Low: 30 °F</td>\n",
       "      <td>High: 51 °F</td>\n",
       "      <td>30.17 in (1021.7 mb)</td>\n",
       "      <td>24°F (-4°C)</td>\n",
       "      <td>39%</td>\n",
       "      <td>8 Mar 4:54 pm EST</td>\n",
       "      <td>10.00 mi</td>\n",
       "      <td>42°F (6°C)</td>\n",
       "      <td>N 16 mph</td>\n",
       "      <td>7</td>\n",
       "      <td>39.87</td>\n",
       "      <td>75.23</td>\n",
       "      <td>Philadelphia, Philadelphia International Airpo...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>77°F</td>\n",
       "      <td>Low: 60 °F</td>\n",
       "      <td>High: 80 °F</td>\n",
       "      <td>30.07 in (1018.0 mb)</td>\n",
       "      <td>61°F (16°C)</td>\n",
       "      <td>58%</td>\n",
       "      <td>8 Mar 4:53 pm EST</td>\n",
       "      <td>10.00 mi</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NE 20 mph</td>\n",
       "      <td>89</td>\n",
       "      <td>28.42</td>\n",
       "      <td>81.32</td>\n",
       "      <td>Orlando International Airport (KMCO)</td>\n",
       "      <td>79°F (26°C)</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>40°F</td>\n",
       "      <td>Low: 32 °F</td>\n",
       "      <td>High: 37 °F</td>\n",
       "      <td>30.50 in (1033.5 mb)</td>\n",
       "      <td>23°F (-5°C)</td>\n",
       "      <td>51%</td>\n",
       "      <td>8 Mar 3:52 pm CST</td>\n",
       "      <td>10.00 mi</td>\n",
       "      <td>33°F (1°C)</td>\n",
       "      <td>NE 12 mph</td>\n",
       "      <td>722</td>\n",
       "      <td>42.96</td>\n",
       "      <td>87.9</td>\n",
       "      <td>Milwaukee, General Mitchell International Airp...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>60°F</td>\n",
       "      <td>Low: 30 °F</td>\n",
       "      <td>High: 60 °F</td>\n",
       "      <td>30.19 in (1022.3 mb)</td>\n",
       "      <td>21°F (-6°C)</td>\n",
       "      <td>22%</td>\n",
       "      <td>8 Mar 4:54 pm EST</td>\n",
       "      <td>10.00 mi</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NW 5 mph</td>\n",
       "      <td>935</td>\n",
       "      <td>37.32</td>\n",
       "      <td>79.21</td>\n",
       "      <td>Lynchburg, Lynchburg Regional Airport (KLYH)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>34°F</td>\n",
       "      <td>Low: 9 °F</td>\n",
       "      <td>High: 32 °F</td>\n",
       "      <td>29.97 in (1014.9 mb)</td>\n",
       "      <td>16°F (-9°C)</td>\n",
       "      <td>47%</td>\n",
       "      <td>08 Mar 03:35 PM MST</td>\n",
       "      <td>10.00 mi</td>\n",
       "      <td>23°F (-5°C)</td>\n",
       "      <td>NNE 18 MPH</td>\n",
       "      <td>2972</td>\n",
       "      <td>48.30417</td>\n",
       "      <td>114.26361</td>\n",
       "      <td>Kalispell, Glacier Park International Airport ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.004</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>70°F</td>\n",
       "      <td>Low: 66 °F</td>\n",
       "      <td>High: 80 °F</td>\n",
       "      <td>29.80 in</td>\n",
       "      <td>66°F (19°C)</td>\n",
       "      <td>88%</td>\n",
       "      <td>8 Mar 12:31 pm HST</td>\n",
       "      <td>8.00 mi</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S 20 G 31 mph</td>\n",
       "      <td>52</td>\n",
       "      <td>20.89</td>\n",
       "      <td>156.44</td>\n",
       "      <td>Kahului, Kahului Airport (PHOG)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.272</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>24°F</td>\n",
       "      <td>Low: 20 °F</td>\n",
       "      <td>High: 31 °F</td>\n",
       "      <td>30.21 in (1024.2 mb)</td>\n",
       "      <td>18°F (-8°C)</td>\n",
       "      <td>77%</td>\n",
       "      <td>8 Mar 12:53 pm AKST</td>\n",
       "      <td>10.00 mi</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Calm</td>\n",
       "      <td>433</td>\n",
       "      <td>64.8</td>\n",
       "      <td>147.88</td>\n",
       "      <td>Fairbanks, Fairbanks International Airport (PAFA)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>43°F</td>\n",
       "      <td>Low: 31 °F</td>\n",
       "      <td>High: 41 °F</td>\n",
       "      <td>29.99 in (1015.6 mb)</td>\n",
       "      <td>28°F (-2°C)</td>\n",
       "      <td>56%</td>\n",
       "      <td>8 Mar 4:53 pm EST</td>\n",
       "      <td>10.00 mi</td>\n",
       "      <td>35°F (2°C)</td>\n",
       "      <td>N 18 G 24 mph</td>\n",
       "      <td>190</td>\n",
       "      <td>44.8</td>\n",
       "      <td>68.82</td>\n",
       "      <td>Bangor, Bangor International Airport (KBGR)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>70°F</td>\n",
       "      <td>Low: 36 °F</td>\n",
       "      <td>High: 71 °F</td>\n",
       "      <td>29.95 in (1009.5 mb)</td>\n",
       "      <td>26°F (-3°C)</td>\n",
       "      <td>19%</td>\n",
       "      <td>8 Mar 2:52 pm MST</td>\n",
       "      <td>10.00 mi</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SW 24 G 36 mph</td>\n",
       "      <td>5351</td>\n",
       "      <td>35.04</td>\n",
       "      <td>106.61</td>\n",
       "      <td>Albuquerque, Albuquerque International Airport...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>43°F</td>\n",
       "      <td>Low: 36 °F</td>\n",
       "      <td>High: 48 °F</td>\n",
       "      <td>30.0 in (1015.92 mb)</td>\n",
       "      <td>36°F (2°C)</td>\n",
       "      <td>75%</td>\n",
       "      <td>08 Mar 02:20 PM PST</td>\n",
       "      <td>10.00 mi</td>\n",
       "      <td>38°F (3°C)</td>\n",
       "      <td>ESE 8 MPH</td>\n",
       "      <td>20</td>\n",
       "      <td>45.59578</td>\n",
       "      <td>122.60917</td>\n",
       "      <td>Portland, Portland International Airport (KPDX)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.251</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>35°F</td>\n",
       "      <td>Low: 17 °F</td>\n",
       "      <td>High: 29 °F</td>\n",
       "      <td>30.21 in (1023.1 mb)</td>\n",
       "      <td>9°F (-13°C)</td>\n",
       "      <td>34%</td>\n",
       "      <td>8 Mar 12:53 pm AKST</td>\n",
       "      <td>10.00 mi</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Calm</td>\n",
       "      <td>13</td>\n",
       "      <td>57.05</td>\n",
       "      <td>135.36</td>\n",
       "      <td>Sitka - Sitka Airport (PASI)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    temp     tempmin      tempmax             Barometer     Dewpoint Humidity  \\\n",
       "0   48°F  Low: 30 °F  High: 51 °F  30.17 in (1021.7 mb)  24°F (-4°C)      39%   \n",
       "1   77°F  Low: 60 °F  High: 80 °F  30.07 in (1018.0 mb)  61°F (16°C)      58%   \n",
       "2   40°F  Low: 32 °F  High: 37 °F  30.50 in (1033.5 mb)  23°F (-5°C)      51%   \n",
       "3   60°F  Low: 30 °F  High: 60 °F  30.19 in (1022.3 mb)  21°F (-6°C)      22%   \n",
       "4   34°F   Low: 9 °F  High: 32 °F  29.97 in (1014.9 mb)  16°F (-9°C)      47%   \n",
       "5   70°F  Low: 66 °F  High: 80 °F              29.80 in  66°F (19°C)      88%   \n",
       "6   24°F  Low: 20 °F  High: 31 °F  30.21 in (1024.2 mb)  18°F (-8°C)      77%   \n",
       "7   43°F  Low: 31 °F  High: 41 °F  29.99 in (1015.6 mb)  28°F (-2°C)      56%   \n",
       "8   70°F  Low: 36 °F  High: 71 °F  29.95 in (1009.5 mb)  26°F (-3°C)      19%   \n",
       "9   43°F  Low: 36 °F  High: 48 °F  30.0 in (1015.92 mb)   36°F (2°C)      75%   \n",
       "10  35°F  Low: 17 °F  High: 29 °F  30.21 in (1023.1 mb)  9°F (-13°C)      34%   \n",
       "\n",
       "            Last update Visibility   Wind Chill      Wind Speed elevation_ft  \\\n",
       "0     8 Mar 4:54 pm EST   10.00 mi   42°F (6°C)        N 16 mph            7   \n",
       "1     8 Mar 4:53 pm EST   10.00 mi          NaN       NE 20 mph           89   \n",
       "2     8 Mar 3:52 pm CST   10.00 mi   33°F (1°C)       NE 12 mph          722   \n",
       "3     8 Mar 4:54 pm EST   10.00 mi          NaN        NW 5 mph          935   \n",
       "4   08 Mar 03:35 PM MST   10.00 mi  23°F (-5°C)      NNE 18 MPH         2972   \n",
       "5    8 Mar 12:31 pm HST    8.00 mi          NaN   S 20 G 31 mph           52   \n",
       "6   8 Mar 12:53 pm AKST   10.00 mi          NaN            Calm          433   \n",
       "7     8 Mar 4:53 pm EST   10.00 mi   35°F (2°C)   N 18 G 24 mph          190   \n",
       "8     8 Mar 2:52 pm MST   10.00 mi          NaN  SW 24 G 36 mph         5351   \n",
       "9   08 Mar 02:20 PM PST   10.00 mi   38°F (3°C)       ESE 8 MPH           20   \n",
       "10  8 Mar 12:53 pm AKST   10.00 mi          NaN            Calm           13   \n",
       "\n",
       "    latitude  longitude                                    weather_station  \\\n",
       "0      39.87      75.23  Philadelphia, Philadelphia International Airpo...   \n",
       "1      28.42      81.32               Orlando International Airport (KMCO)   \n",
       "2      42.96       87.9  Milwaukee, General Mitchell International Airp...   \n",
       "3      37.32      79.21       Lynchburg, Lynchburg Regional Airport (KLYH)   \n",
       "4   48.30417  114.26361  Kalispell, Glacier Park International Airport ...   \n",
       "5      20.89     156.44                    Kahului, Kahului Airport (PHOG)   \n",
       "6       64.8     147.88  Fairbanks, Fairbanks International Airport (PAFA)   \n",
       "7       44.8      68.82        Bangor, Bangor International Airport (KBGR)   \n",
       "8      35.04     106.61  Albuquerque, Albuquerque International Airport...   \n",
       "9   45.59578  122.60917    Portland, Portland International Airport (KPDX)   \n",
       "10     57.05     135.36                       Sitka - Sitka Airport (PASI)   \n",
       "\n",
       "     Heat Index  precip  \n",
       "0           NaN   0.011  \n",
       "1   79°F (26°C)   0.000  \n",
       "2           NaN   0.002  \n",
       "3           NaN   0.000  \n",
       "4           NaN   0.004  \n",
       "5           NaN   0.272  \n",
       "6           NaN   0.000  \n",
       "7           NaN   0.006  \n",
       "8           NaN   0.000  \n",
       "9           NaN   0.251  \n",
       "10          NaN   0.000  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "urls = [\n",
    "        'https://www.localconditions.com/weather-philadelphia-pennsylvania/19019/past.php',\n",
    "        'https://www.localconditions.com/weather-orlando-florida/32801/past.php',\n",
    "        'https://www.localconditions.com/weather-milwaukee-wisconsin/53201/past.php',\n",
    "        'https://www.localconditions.com/weather-lynchburg-virginia/24501/past.php',\n",
    "        'https://www.localconditions.com/weather-kalispell-montana/59901/past.php',\n",
    "        'https://www.localconditions.com/weather-kahului-hawaii/96732/past.php',\n",
    "        'https://www.localconditions.com/weather-fairbanks-alaska/99701/past.php',\n",
    "        'https://www.localconditions.com/weather-bangor-maine/04401/past.php',\n",
    "        'https://www.localconditions.com/weather-albuquerque-new-mexico/87101/past.php',\n",
    "        'https://www.localconditions.com/weather-portland-oregon/97201/past.php',\n",
    "        \"https://www.localconditions.com/weather-sitka-alaska/99835/past.php\"\n",
    "        ]\n",
    "\n",
    "precip_df = pd.DataFrame()\n",
    "\n",
    "for url in urls:\n",
    "        r = requests.get(url)\n",
    "        soup = BeautifulSoup(r.content,\"html.parser\")\n",
    "        details = soup.select_one(\".past_weather_express\")\n",
    "        # Find all div elements with class=\"panel\"\n",
    "        panel_divs = soup.find_all('div', {'class': 'panel'})\n",
    "        # Extract the text content of each div element and store it in a list\n",
    "        panel_texts = [panel_div.text.strip() for panel_div in panel_divs]\n",
    "        # Print the list of extracted text content\n",
    "        data = panel_texts[1]\n",
    "        data = [item.strip() for item in data]\n",
    "        data = [item for item in data if item]\n",
    "        data = data[77:90]\n",
    "        data=\"\".join(data)\n",
    "        df = pd.DataFrame([data], columns=['precip'])\n",
    "        precip_df = pd.concat([precip_df, df], ignore_index=True, sort=False)\n",
    "        \n",
    "precip_df['precip'] = precip_df['precip'].str.extract(pat='(\\d+\\.?\\d*)').astype(float)\n",
    "precip_df = precip_df.fillna(0)\n",
    "\n",
    "source_df =pd.concat([combined_df,precip_df],axis=1)\n",
    "display(source_df.head(11))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "DatetimeIndex: 11 entries, 2023-03-08 to 2023-03-08\n",
      "Data columns (total 10 columns):\n",
      " #   Column      Non-Null Count  Dtype  \n",
      "---  ------      --------------  -----  \n",
      " 0   name        11 non-null     object \n",
      " 1   precip      11 non-null     float64\n",
      " 2   temp_max    11 non-null     float64\n",
      " 3   temp_min    11 non-null     float64\n",
      " 4   temp        11 non-null     float64\n",
      " 5   windchill   11 non-null     float64\n",
      " 6   dewpoint    11 non-null     float64\n",
      " 7   humidity    11 non-null     float64\n",
      " 8   windspeed   11 non-null     float64\n",
      " 9   visibility  11 non-null     float64\n",
      "dtypes: float64(9), object(1)\n",
      "memory usage: 968.0+ bytes\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "None"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#-----------Data Transformations-----------------\n",
    "\n",
    "# Convert 'lat' and 'lon' columns to float type\n",
    "source_df['latitude'] = source_df['latitude'].astype(float)\n",
    "source_df['longitude'] = source_df['longitude'].astype(float)\n",
    "\n",
    "# Convert 'elev' column to int type\n",
    "source_df['elevation_ft'] = source_df['elevation_ft'].astype(int)\n",
    "\n",
    "# Extract the numeric part of the temperature string and convert it to int\n",
    "source_df['temp'] = source_df['temp'].str.extract('(\\d+)').astype(float)\n",
    "\n",
    "# Extract the numeric part of the tempmin string and convert it to int\n",
    "source_df['tempmin'] = source_df['tempmin'].str.extract('(\\d+)').astype(float)\n",
    "\n",
    "# Extract the numeric part of the temperature string and convert it to int\n",
    "source_df['tempmax'] = source_df['tempmax'].str.extract('(\\d+)').astype(float)\n",
    "\n",
    "# Split wind speed values into components and convert speed to int type\n",
    "source_df['Wind Speed'] = source_df['Wind Speed'].str.extract('(\\d+)', expand=False).fillna(0).astype(float)\n",
    "\n",
    "# Convert 'humidity' column to int type\n",
    "source_df['Humidity'] = source_df['Humidity'].str.extract('(\\d+)', expand=False).astype(float)\n",
    "\n",
    "# Convert 'barometer' column to float type, and convert inches to millibars\n",
    "source_df['Barometer'] = round(source_df['Barometer'].apply(lambda x: float(x.split()[0]) * 33.8639 if 'in' in x and x != 'NA' else None), 2)\n",
    "\n",
    "# Convert 'Visibility' column to float type\n",
    "source_df['Visibility'] = source_df['Visibility'].str.extract('(\\d+\\.\\d+|\\d+)', expand=False).astype(float).round(2)\n",
    "\n",
    "#Convert 'last_update' column to UTC\n",
    "source_df['Last update'] = source_df['Last update'].apply(lambda x: dateutil.parser.parse(x, tzinfos={\"EST\": -5 * 3600, \"CST\": -6 * 3600, \"MST\": -7 * 3600,\"PST\": -8 * 3600,\"AKST\": -9 * 3600,\"HST\": -10 * 3600}))\n",
    "source_df['Last update'] = source_df['Last update'].apply(lambda x: x.astimezone(dateutil.tz.tzutc()))\n",
    "source_df['datetime'] = source_df['Last update'].dt.strftime('%Y-%m-%d')\n",
    "source_df['datetime'] = pd.to_datetime(source_df['datetime'])\n",
    "\n",
    "# make wind chill a float if exists and only display degree F\n",
    "try:\n",
    "    source_df[['Wind Chill']] = source_df['Wind Chill'].str.extract('(\\d+)', expand=True).astype(float)\n",
    "except:\n",
    "    None\n",
    "\n",
    "# extract the numeric value of dewpoint and only display the degree n farenheit\n",
    "source_df[['Dewpoint']] = source_df['Dewpoint'].str.extract('(\\d+)', expand=True).astype(float)\n",
    "\n",
    "#change precip data type to float\n",
    "source_df['precip'] = source_df['precip'].astype(float)\n",
    "\n",
    "#rename weather station column to the city\n",
    "def rename_station(value):\n",
    "    if value == 'Portland, Portland International Airport (KPDX)':\n",
    "        return 'PORTLAND INTERNATIONAL AIRPORT, OR US'\n",
    "    elif value == 'Sitka - Sitka Airport (PASI)':\n",
    "        return 'SITKA AIRPORT, AK US'\n",
    "    elif value == 'Philadelphia, Philadelphia International Airport (KPHL)':\n",
    "        return 'PHILADELPHIA INTERNATIONAL AIRPORT, PA US'\n",
    "    elif value == 'Orlando International Airport (KMCO)':\n",
    "        return 'ORLANDO EXECUTIVE AIRPORT, FL US'\n",
    "    elif value == 'Milwaukee, General Mitchell International Airport (KMKE)':\n",
    "        return 'MILWAUKEE MITCHELL AIRPORT, WI US'\n",
    "    elif value == 'Lynchburg, Lynchburg Regional Airport (KLYH)':\n",
    "        return 'LYNCHBURG REGIONAL AIRPORT, VA US'\n",
    "    elif value == 'Kalispell, Glacier Park International Airport (KGPI)':\n",
    "        return 'KALISPELL GLACIER AIRPORT, MT US'\n",
    "    elif value == 'Kahului, Kahului Airport (PHOG)':\n",
    "        return 'KAHULUI AIRPORT, HI US'\n",
    "    elif value == 'Fairbanks, Fairbanks International Airport (PAFA)':\n",
    "        return 'FAIRBANKS INTERNATIONAL AIRPORT, AK US'\n",
    "    elif value == 'Albuquerque, Albuquerque International Airport (KABQ)':\n",
    "        return 'ALBUQUERQUE INTERNATIONAL AIRPORT, NM US'\n",
    "    elif value == 'Bangor, Bangor International Airport (KBGR)':\n",
    "        return 'BANGOR INTERNATIONAL AIRPORT, ME US'\n",
    "source_df['name'] = source_df['weather_station'].map(rename_station)\n",
    "\n",
    "#change the names and order of columns to better fit the historical data\n",
    "source_df = source_df.rename({'Humidity': 'humidity', 'Wind Speed': 'windspeed', 'Visibility': 'visibility','Wind Chill': 'windchill','Dewpoint':'dewpoint','tempmax':'temp_max','tempmin':'temp_min'}, axis=1) \n",
    "#this line only includes necesarry columns\n",
    "source_df = source_df[['name','datetime','precip','temp_max','temp_min','temp','windchill','dewpoint','humidity','windspeed','visibility']]\n",
    "source_df = source_df.fillna(0)\n",
    "source_df = source_df.set_index(['datetime'])\n",
    "source_df.index.names = ['DATE']\n",
    "\n",
    "#combine source df and test set so the test set had the most current info\n",
    "test_set_forecast = pd.concat([test_set, source_df])\n",
    "#map each citiy to a numerical values to be used in the regression analysis\n",
    "test_set_forecast['name'] = test_set_forecast['name'].astype('category')\n",
    "test_set_forecast['city_number'] = test_set_forecast['name'].cat.codes\n",
    "test_set_forecast = test_set_forecast[['name','precip','temp_max','temp_min','city_number']]\n",
    "display(source_df.info())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>precip</th>\n",
       "      <th>temp_max</th>\n",
       "      <th>temp_min</th>\n",
       "      <th>temp</th>\n",
       "      <th>windchill</th>\n",
       "      <th>dewpoint</th>\n",
       "      <th>humidity</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>visibility</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DATE</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2023-03-08</th>\n",
       "      <td>PHILADELPHIA INTERNATIONAL AIRPORT, PA US</td>\n",
       "      <td>0.011</td>\n",
       "      <td>51.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>39.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-08</th>\n",
       "      <td>ORLANDO EXECUTIVE AIRPORT, FL US</td>\n",
       "      <td>0.000</td>\n",
       "      <td>80.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>61.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-08</th>\n",
       "      <td>MILWAUKEE MITCHELL AIRPORT, WI US</td>\n",
       "      <td>0.002</td>\n",
       "      <td>37.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-08</th>\n",
       "      <td>LYNCHBURG REGIONAL AIRPORT, VA US</td>\n",
       "      <td>0.000</td>\n",
       "      <td>60.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-08</th>\n",
       "      <td>KALISPELL GLACIER AIRPORT, MT US</td>\n",
       "      <td>0.004</td>\n",
       "      <td>32.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>47.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-08</th>\n",
       "      <td>KAHULUI AIRPORT, HI US</td>\n",
       "      <td>0.272</td>\n",
       "      <td>80.0</td>\n",
       "      <td>66.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>66.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-08</th>\n",
       "      <td>FAIRBANKS INTERNATIONAL AIRPORT, AK US</td>\n",
       "      <td>0.000</td>\n",
       "      <td>31.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-08</th>\n",
       "      <td>BANGOR INTERNATIONAL AIRPORT, ME US</td>\n",
       "      <td>0.006</td>\n",
       "      <td>41.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>43.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>56.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-08</th>\n",
       "      <td>ALBUQUERQUE INTERNATIONAL AIRPORT, NM US</td>\n",
       "      <td>0.000</td>\n",
       "      <td>71.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-08</th>\n",
       "      <td>PORTLAND INTERNATIONAL AIRPORT, OR US</td>\n",
       "      <td>0.251</td>\n",
       "      <td>48.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>43.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-08</th>\n",
       "      <td>SITKA AIRPORT, AK US</td>\n",
       "      <td>0.000</td>\n",
       "      <td>29.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                 name  precip  temp_max  \\\n",
       "DATE                                                                      \n",
       "2023-03-08  PHILADELPHIA INTERNATIONAL AIRPORT, PA US   0.011      51.0   \n",
       "2023-03-08           ORLANDO EXECUTIVE AIRPORT, FL US   0.000      80.0   \n",
       "2023-03-08          MILWAUKEE MITCHELL AIRPORT, WI US   0.002      37.0   \n",
       "2023-03-08          LYNCHBURG REGIONAL AIRPORT, VA US   0.000      60.0   \n",
       "2023-03-08           KALISPELL GLACIER AIRPORT, MT US   0.004      32.0   \n",
       "2023-03-08                     KAHULUI AIRPORT, HI US   0.272      80.0   \n",
       "2023-03-08     FAIRBANKS INTERNATIONAL AIRPORT, AK US   0.000      31.0   \n",
       "2023-03-08        BANGOR INTERNATIONAL AIRPORT, ME US   0.006      41.0   \n",
       "2023-03-08   ALBUQUERQUE INTERNATIONAL AIRPORT, NM US   0.000      71.0   \n",
       "2023-03-08      PORTLAND INTERNATIONAL AIRPORT, OR US   0.251      48.0   \n",
       "2023-03-08                       SITKA AIRPORT, AK US   0.000      29.0   \n",
       "\n",
       "            temp_min  temp  windchill  dewpoint  humidity  windspeed  \\\n",
       "DATE                                                                   \n",
       "2023-03-08      30.0  48.0       42.0      24.0      39.0       16.0   \n",
       "2023-03-08      60.0  77.0        0.0      61.0      58.0       20.0   \n",
       "2023-03-08      32.0  40.0       33.0      23.0      51.0       12.0   \n",
       "2023-03-08      30.0  60.0        0.0      21.0      22.0        5.0   \n",
       "2023-03-08       9.0  34.0       23.0      16.0      47.0       18.0   \n",
       "2023-03-08      66.0  70.0        0.0      66.0      88.0       20.0   \n",
       "2023-03-08      20.0  24.0        0.0      18.0      77.0        0.0   \n",
       "2023-03-08      31.0  43.0       35.0      28.0      56.0       18.0   \n",
       "2023-03-08      36.0  70.0        0.0      26.0      19.0       24.0   \n",
       "2023-03-08      36.0  43.0       38.0      36.0      75.0        8.0   \n",
       "2023-03-08      17.0  35.0        0.0       9.0      34.0        0.0   \n",
       "\n",
       "            visibility  \n",
       "DATE                    \n",
       "2023-03-08        10.0  \n",
       "2023-03-08        10.0  \n",
       "2023-03-08        10.0  \n",
       "2023-03-08        10.0  \n",
       "2023-03-08        10.0  \n",
       "2023-03-08         8.0  \n",
       "2023-03-08        10.0  \n",
       "2023-03-08        10.0  \n",
       "2023-03-08        10.0  \n",
       "2023-03-08        10.0  \n",
       "2023-03-08        10.0  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(source_df.head(11))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "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>name</th>\n",
       "      <th>current_day_max_temp</th>\n",
       "      <th>Predicted_high_temp_1_day</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DATE</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2023-02-11</th>\n",
       "      <td>ORLANDO EXECUTIVE AIRPORT, FL US</td>\n",
       "      <td>84</td>\n",
       "      <td>83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-02-12</th>\n",
       "      <td>ORLANDO EXECUTIVE AIRPORT, FL US</td>\n",
       "      <td>72</td>\n",
       "      <td>71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-02-13</th>\n",
       "      <td>ORLANDO EXECUTIVE AIRPORT, FL US</td>\n",
       "      <td>71</td>\n",
       "      <td>70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-02-14</th>\n",
       "      <td>ORLANDO EXECUTIVE AIRPORT, FL US</td>\n",
       "      <td>77</td>\n",
       "      <td>75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-08</th>\n",
       "      <td>PHILADELPHIA INTERNATIONAL AIRPORT, PA US</td>\n",
       "      <td>51</td>\n",
       "      <td>51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-08</th>\n",
       "      <td>ORLANDO EXECUTIVE AIRPORT, FL US</td>\n",
       "      <td>80</td>\n",
       "      <td>79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-08</th>\n",
       "      <td>MILWAUKEE MITCHELL AIRPORT, WI US</td>\n",
       "      <td>37</td>\n",
       "      <td>39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-08</th>\n",
       "      <td>LYNCHBURG REGIONAL AIRPORT, VA US</td>\n",
       "      <td>60</td>\n",
       "      <td>58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-08</th>\n",
       "      <td>KALISPELL GLACIER AIRPORT, MT US</td>\n",
       "      <td>32</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-08</th>\n",
       "      <td>KAHULUI AIRPORT, HI US</td>\n",
       "      <td>80</td>\n",
       "      <td>79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-08</th>\n",
       "      <td>FAIRBANKS INTERNATIONAL AIRPORT, AK US</td>\n",
       "      <td>31</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-08</th>\n",
       "      <td>BANGOR INTERNATIONAL AIRPORT, ME US</td>\n",
       "      <td>41</td>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-08</th>\n",
       "      <td>ALBUQUERQUE INTERNATIONAL AIRPORT, NM US</td>\n",
       "      <td>71</td>\n",
       "      <td>68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-08</th>\n",
       "      <td>PORTLAND INTERNATIONAL AIRPORT, OR US</td>\n",
       "      <td>48</td>\n",
       "      <td>49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-08</th>\n",
       "      <td>SITKA AIRPORT, AK US</td>\n",
       "      <td>29</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                 name  current_day_max_temp  \\\n",
       "DATE                                                                          \n",
       "2023-02-11           ORLANDO EXECUTIVE AIRPORT, FL US                    84   \n",
       "2023-02-12           ORLANDO EXECUTIVE AIRPORT, FL US                    72   \n",
       "2023-02-13           ORLANDO EXECUTIVE AIRPORT, FL US                    71   \n",
       "2023-02-14           ORLANDO EXECUTIVE AIRPORT, FL US                    77   \n",
       "2023-03-08  PHILADELPHIA INTERNATIONAL AIRPORT, PA US                    51   \n",
       "2023-03-08           ORLANDO EXECUTIVE AIRPORT, FL US                    80   \n",
       "2023-03-08          MILWAUKEE MITCHELL AIRPORT, WI US                    37   \n",
       "2023-03-08          LYNCHBURG REGIONAL AIRPORT, VA US                    60   \n",
       "2023-03-08           KALISPELL GLACIER AIRPORT, MT US                    32   \n",
       "2023-03-08                     KAHULUI AIRPORT, HI US                    80   \n",
       "2023-03-08     FAIRBANKS INTERNATIONAL AIRPORT, AK US                    31   \n",
       "2023-03-08        BANGOR INTERNATIONAL AIRPORT, ME US                    41   \n",
       "2023-03-08   ALBUQUERQUE INTERNATIONAL AIRPORT, NM US                    71   \n",
       "2023-03-08      PORTLAND INTERNATIONAL AIRPORT, OR US                    48   \n",
       "2023-03-08                       SITKA AIRPORT, AK US                    29   \n",
       "\n",
       "            Predicted_high_temp_1_day  \n",
       "DATE                                   \n",
       "2023-02-11                         83  \n",
       "2023-02-12                         71  \n",
       "2023-02-13                         70  \n",
       "2023-02-14                         75  \n",
       "2023-03-08                         51  \n",
       "2023-03-08                         79  \n",
       "2023-03-08                         39  \n",
       "2023-03-08                         58  \n",
       "2023-03-08                         32  \n",
       "2023-03-08                         79  \n",
       "2023-03-08                         33  \n",
       "2023-03-08                         42  \n",
       "2023-03-08                         68  \n",
       "2023-03-08                         49  \n",
       "2023-03-08                         31  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#-----------------create/test data model--------------------------------\n",
    "#using Ridge regression to minimize overfitting\n",
    "regression = Ridge(alpha=.1)\n",
    "predictors = ['precip','temp_max','temp_min']\n",
    "#training set includes all data before and including dec 12th 2021, this is teh set that is used to train the model to predict future data\n",
    "training_set = core_weather_df.loc[:'2021-12-31']\n",
    "# #test set includes all data after and including jan 1st 2022\n",
    "#test_set = test_set.loc['2022-01-01':]\n",
    "\n",
    "# test_set_shifted = test_set.shift(365, freq='D')\n",
    "# test_set2= test_set_shifted.loc['2023-01-01':'2023-12-31']\n",
    "\n",
    "#train the model based on the predictors\n",
    "regression.fit(training_set[predictors], training_set['target_temp_max_day_1'])\n",
    "predictions = regression.predict(test_set_forecast[predictors])\n",
    "\n",
    "combined_df = pd.concat([test_set_forecast[['name','temp_max']], pd.Series(predictions, index = test_set_forecast.index)], axis=1)\n",
    "combined_df.columns = ['name','current_day_max_temp','Predicted_high_temp_1_day']\n",
    "combined_df = combined_df.astype({\"Predicted_high_temp_1_day\": int, \"current_day_max_temp\": int})\n",
    "\n",
    "core_weather_df.name.unique()\n",
    "display(combined_df.tail(15))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2022-01-01</th>\n",
       "      <td>FAIRBANKS INTERNATIONAL AIRPORT, AK US</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-7.0</td>\n",
       "      <td>-17.0</td>\n",
       "      <td>2</td>\n",
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       "    <tr>\n",
       "      <th>2022-01-02</th>\n",
       "      <td>FAIRBANKS INTERNATIONAL AIRPORT, AK US</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>2</td>\n",
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       "    <tr>\n",
       "      <th>2022-01-03</th>\n",
       "      <td>FAIRBANKS INTERNATIONAL AIRPORT, AK US</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-14.0</td>\n",
       "      <td>-45.0</td>\n",
       "      <td>2</td>\n",
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       "    <tr>\n",
       "      <th>2022-01-04</th>\n",
       "      <td>FAIRBANKS INTERNATIONAL AIRPORT, AK US</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-19.0</td>\n",
       "      <td>-37.0</td>\n",
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       "    <tr>\n",
       "      <th>2022-01-05</th>\n",
       "      <td>FAIRBANKS INTERNATIONAL AIRPORT, AK US</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-26.0</td>\n",
       "      <td>-38.0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                              name  precip  temp_max  \\\n",
       "DATE                                                                   \n",
       "2022-01-01  FAIRBANKS INTERNATIONAL AIRPORT, AK US     0.0      -7.0   \n",
       "2022-01-02  FAIRBANKS INTERNATIONAL AIRPORT, AK US     0.0     -16.0   \n",
       "2022-01-03  FAIRBANKS INTERNATIONAL AIRPORT, AK US     0.0     -14.0   \n",
       "2022-01-04  FAIRBANKS INTERNATIONAL AIRPORT, AK US     0.0     -19.0   \n",
       "2022-01-05  FAIRBANKS INTERNATIONAL AIRPORT, AK US     0.0     -26.0   \n",
       "\n",
       "            temp_min  city_number  \n",
       "DATE                               \n",
       "2022-01-01     -17.0            2  \n",
       "2022-01-02     -47.0            2  \n",
       "2022-01-03     -45.0            2  \n",
       "2022-01-04     -37.0            2  \n",
       "2022-01-05     -38.0            2  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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       "      <th></th>\n",
       "      <th>name</th>\n",
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       "      <th>temp_max</th>\n",
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       "      <th>target_temp_max_day_4</th>\n",
       "      <th>target_temp_max_day_5</th>\n",
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       "      <th>2022-01-01</th>\n",
       "      <td>FAIRBANKS INTERNATIONAL AIRPORT, AK US</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.1</td>\n",
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       "      <th>2022-01-02</th>\n",
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       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>12.0</td>\n",
       "      <td>2</td>\n",
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       "    <tr>\n",
       "      <th>2022-01-03</th>\n",
       "      <td>FAIRBANKS INTERNATIONAL AIRPORT, AK US</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>33.1</td>\n",
       "      <td>-14.0</td>\n",
       "      <td>-45.0</td>\n",
       "      <td>0</td>\n",
       "      <td>-19.0</td>\n",
       "      <td>-26.0</td>\n",
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       "      <td>-26.0</td>\n",
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       "      <td>7.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>2</td>\n",
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       "    <tr>\n",
       "      <th>2022-01-04</th>\n",
       "      <td>FAIRBANKS INTERNATIONAL AIRPORT, AK US</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>33.1</td>\n",
       "      <td>-19.0</td>\n",
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       "      <td>20.0</td>\n",
       "      <td>2</td>\n",
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       "    <tr>\n",
       "      <th>2022-01-05</th>\n",
       "      <td>FAIRBANKS INTERNATIONAL AIRPORT, AK US</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>33.1</td>\n",
       "      <td>-26.0</td>\n",
       "      <td>-38.0</td>\n",
       "      <td>0</td>\n",
       "      <td>-6.0</td>\n",
       "      <td>-26.0</td>\n",
       "      <td>-30.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2</td>\n",
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       "    <tr>\n",
       "      <th>2023-02-10</th>\n",
       "      <td>ORLANDO EXECUTIVE AIRPORT, FL US</td>\n",
       "      <td>0.21</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>84.0</td>\n",
       "      <td>66.0</td>\n",
       "      <td>12</td>\n",
       "      <td>84.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>71.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>71.0</td>\n",
       "      <td>84.0</td>\n",
       "      <td>84.0</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-02-11</th>\n",
       "      <td>ORLANDO EXECUTIVE AIRPORT, FL US</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>84.0</td>\n",
       "      <td>67.0</td>\n",
       "      <td>12</td>\n",
       "      <td>72.0</td>\n",
       "      <td>71.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>71.0</td>\n",
       "      <td>84.0</td>\n",
       "      <td>84.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-02-12</th>\n",
       "      <td>ORLANDO EXECUTIVE AIRPORT, FL US</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>12</td>\n",
       "      <td>71.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>71.0</td>\n",
       "      <td>84.0</td>\n",
       "      <td>84.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-02-13</th>\n",
       "      <td>ORLANDO EXECUTIVE AIRPORT, FL US</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>71.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>12</td>\n",
       "      <td>77.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>71.0</td>\n",
       "      <td>84.0</td>\n",
       "      <td>84.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-02-14</th>\n",
       "      <td>ORLANDO EXECUTIVE AIRPORT, FL US</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>12</td>\n",
       "      <td>82.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>71.0</td>\n",
       "      <td>84.0</td>\n",
       "      <td>84.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
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       "</table>\n",
       "<p>4508 rows × 18 columns</p>\n",
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      ],
      "text/plain": [
       "                                              name  precip  snow  snow_depth  \\\n",
       "DATE                                                                           \n",
       "2022-01-01  FAIRBANKS INTERNATIONAL AIRPORT, AK US    0.00   0.1        33.9   \n",
       "2022-01-02  FAIRBANKS INTERNATIONAL AIRPORT, AK US    0.00   0.0        33.1   \n",
       "2022-01-03  FAIRBANKS INTERNATIONAL AIRPORT, AK US    0.00   0.0        33.1   \n",
       "2022-01-04  FAIRBANKS INTERNATIONAL AIRPORT, AK US    0.00   0.0        33.1   \n",
       "2022-01-05  FAIRBANKS INTERNATIONAL AIRPORT, AK US    0.00   0.0        33.1   \n",
       "...                                            ...     ...   ...         ...   \n",
       "2023-02-10        ORLANDO EXECUTIVE AIRPORT, FL US    0.21   0.0         0.0   \n",
       "2023-02-11        ORLANDO EXECUTIVE AIRPORT, FL US    0.01   0.0         0.0   \n",
       "2023-02-12        ORLANDO EXECUTIVE AIRPORT, FL US    0.02   0.0         0.0   \n",
       "2023-02-13        ORLANDO EXECUTIVE AIRPORT, FL US    0.00   0.0         0.0   \n",
       "2023-02-14        ORLANDO EXECUTIVE AIRPORT, FL US    0.00   0.0         0.0   \n",
       "\n",
       "            temp_max  temp_min  name_num  target_temp_max_day_1  \\\n",
       "DATE                                                              \n",
       "2022-01-01      -7.0     -17.0         0                  -16.0   \n",
       "2022-01-02     -16.0     -47.0         0                  -14.0   \n",
       "2022-01-03     -14.0     -45.0         0                  -19.0   \n",
       "2022-01-04     -19.0     -37.0         0                  -26.0   \n",
       "2022-01-05     -26.0     -38.0         0                   -6.0   \n",
       "...              ...       ...       ...                    ...   \n",
       "2023-02-10      84.0      66.0        12                   84.0   \n",
       "2023-02-11      84.0      67.0        12                   72.0   \n",
       "2023-02-12      72.0      54.0        12                   71.0   \n",
       "2023-02-13      71.0      49.0        12                   77.0   \n",
       "2023-02-14      77.0      48.0        12                   82.0   \n",
       "\n",
       "            target_temp_max_day_2  target_temp_max_day_3  \\\n",
       "DATE                                                       \n",
       "2022-01-01                  -14.0                  -19.0   \n",
       "2022-01-02                  -19.0                  -26.0   \n",
       "2022-01-03                  -26.0                   -6.0   \n",
       "2022-01-04                   -6.0                  -26.0   \n",
       "2022-01-05                  -26.0                  -30.0   \n",
       "...                           ...                    ...   \n",
       "2023-02-10                   72.0                   71.0   \n",
       "2023-02-11                   71.0                   77.0   \n",
       "2023-02-12                   77.0                   82.0   \n",
       "2023-02-13                   82.0                   85.0   \n",
       "2023-02-14                   85.0                   87.0   \n",
       "\n",
       "            target_temp_max_day_4  target_temp_max_day_5  \\\n",
       "DATE                                                       \n",
       "2022-01-01                  -26.0                   -6.0   \n",
       "2022-01-02                   -6.0                  -26.0   \n",
       "2022-01-03                  -26.0                  -30.0   \n",
       "2022-01-04                  -30.0                    2.0   \n",
       "2022-01-05                    2.0                    3.0   \n",
       "...                           ...                    ...   \n",
       "2023-02-10                   77.0                   82.0   \n",
       "2023-02-11                   82.0                   85.0   \n",
       "2023-02-12                   85.0                   87.0   \n",
       "2023-02-13                   87.0                   71.0   \n",
       "2023-02-14                   71.0                   84.0   \n",
       "\n",
       "            target_temp_max_day_6  target_temp_max_day_7  \\\n",
       "DATE                                                       \n",
       "2022-01-01                  -26.0                  -30.0   \n",
       "2022-01-02                  -30.0                    2.0   \n",
       "2022-01-03                    2.0                    3.0   \n",
       "2022-01-04                    3.0                    7.0   \n",
       "2022-01-05                    7.0                   12.0   \n",
       "...                           ...                    ...   \n",
       "2023-02-10                   85.0                   87.0   \n",
       "2023-02-11                   87.0                   71.0   \n",
       "2023-02-12                   71.0                   84.0   \n",
       "2023-02-13                   84.0                   84.0   \n",
       "2023-02-14                   84.0                   85.0   \n",
       "\n",
       "            target_temp_max_day_8  target_temp_max_day_9  \\\n",
       "DATE                                                       \n",
       "2022-01-01                    2.0                    3.0   \n",
       "2022-01-02                    3.0                    7.0   \n",
       "2022-01-03                    7.0                   12.0   \n",
       "2022-01-04                   12.0                   21.0   \n",
       "2022-01-05                   21.0                   20.0   \n",
       "...                           ...                    ...   \n",
       "2023-02-10                   71.0                   84.0   \n",
       "2023-02-11                   84.0                   84.0   \n",
       "2023-02-12                   84.0                   85.0   \n",
       "2023-02-13                   85.0                   87.0   \n",
       "2023-02-14                   87.0                   88.0   \n",
       "\n",
       "            target_temp_max_day_10  city_number  \n",
       "DATE                                             \n",
       "2022-01-01                     7.0            2  \n",
       "2022-01-02                    12.0            2  \n",
       "2022-01-03                    21.0            2  \n",
       "2022-01-04                    20.0            2  \n",
       "2022-01-05                     7.0            2  \n",
       "...                            ...          ...  \n",
       "2023-02-10                    84.0            7  \n",
       "2023-02-11                    85.0            7  \n",
       "2023-02-12                    87.0            7  \n",
       "2023-02-13                    88.0            7  \n",
       "2023-02-14                    88.0            7  \n",
       "\n",
       "[4508 rows x 18 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(test_set_forecast.head())\n",
    "display(test_set)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "def max_temp_10_day_forecast(predictors, core_weather_df,test_set_forecast, regression):\n",
    "    \n",
    "    training_set = core_weather_df.loc[:'2021-12-31']\n",
    "    test_set_forecast = test_set_forecast[['name','precip','temp_max','temp_min','city_number']]\n",
    "    \n",
    "    regression.fit(training_set[predictors], training_set['target_temp_max_day_1'])\n",
    "    predictions = regression.predict(test_set_forecast[predictors])\n",
    "    combined_df = pd.concat([test_set_forecast[['name','temp_max']], pd.Series(predictions, index = test_set_forecast.index)], axis=1)\n",
    "    combined_df.columns = ['name','current_day_max_temp','Predicted_high_temp_day_1']\n",
    "\n",
    "    regression.fit(training_set[predictors], training_set['target_temp_max_day_2'])\n",
    "    predictions = regression.predict(test_set_forecast[predictors])\n",
    "    combined_df = pd.concat([combined_df[['name','current_day_max_temp','Predicted_high_temp_day_1']], pd.Series(predictions, index = test_set_forecast.index)], axis=1)\n",
    "    combined_df.columns = ['name','current_day_max_temp','Predicted_high_temp_day_1','Predicted_high_temp_day_2']\n",
    "\n",
    "    regression.fit(training_set[predictors], training_set['target_temp_max_day_3'])\n",
    "    predictions = regression.predict(test_set_forecast[predictors])\n",
    "    combined_df = pd.concat([combined_df[['name','current_day_max_temp','Predicted_high_temp_day_1','Predicted_high_temp_day_2']], pd.Series(predictions, index = test_set_forecast.index)], axis=1)\n",
    "    combined_df.columns = ['name','current_day_max_temp','Predicted_high_temp_day_1','Predicted_high_temp_day_2','Predicted_high_temp_day_3']\n",
    "\n",
    "    regression.fit(training_set[predictors], training_set['target_temp_max_day_4'])\n",
    "    predictions = regression.predict(test_set_forecast[predictors])\n",
    "    combined_df = pd.concat([combined_df[['name','current_day_max_temp','Predicted_high_temp_day_1','Predicted_high_temp_day_2','Predicted_high_temp_day_3']], pd.Series(predictions, index = test_set_forecast.index)], axis=1)\n",
    "    combined_df.columns = ['name','current_day_max_temp','Predicted_high_temp_day_1','Predicted_high_temp_day_2','Predicted_high_temp_day_3','Predicted_high_temp_day_4']\n",
    "    \n",
    "    regression.fit(training_set[predictors], training_set['target_temp_max_day_5'])\n",
    "    predictions = regression.predict(test_set_forecast[predictors])\n",
    "    combined_df = pd.concat([combined_df[['name','current_day_max_temp','Predicted_high_temp_day_1','Predicted_high_temp_day_2','Predicted_high_temp_day_3','Predicted_high_temp_day_4']], pd.Series(predictions, index = test_set_forecast.index)], axis=1)\n",
    "    combined_df.columns = ['name','current_day_max_temp','Predicted_high_temp_day_1','Predicted_high_temp_day_2','Predicted_high_temp_day_3','Predicted_high_temp_day_4','Predicted_high_temp_day_5']\n",
    "    \n",
    "    regression.fit(training_set[predictors], training_set['target_temp_max_day_6'])\n",
    "    predictions = regression.predict(test_set_forecast[predictors])\n",
    "    combined_df = pd.concat([combined_df[['name','current_day_max_temp','Predicted_high_temp_day_1','Predicted_high_temp_day_2','Predicted_high_temp_day_3','Predicted_high_temp_day_4','Predicted_high_temp_day_5']], pd.Series(predictions, index = test_set_forecast.index)], axis=1)\n",
    "    combined_df.columns = ['name','current_day_max_temp','Predicted_high_temp_day_1','Predicted_high_temp_day_2','Predicted_high_temp_day_3','Predicted_high_temp_day_4','Predicted_high_temp_day_5','Predicted_high_temp_day_6']\n",
    "    \n",
    "    regression.fit(training_set[predictors], training_set['target_temp_max_day_7'])\n",
    "    predictions = regression.predict(test_set_forecast[predictors])\n",
    "    combined_df = pd.concat([combined_df[['name','current_day_max_temp','Predicted_high_temp_day_1','Predicted_high_temp_day_2','Predicted_high_temp_day_3','Predicted_high_temp_day_4','Predicted_high_temp_day_5','Predicted_high_temp_day_6']], pd.Series(predictions, index = test_set_forecast.index)], axis=1)\n",
    "    combined_df.columns = ['name','current_day_max_temp','Predicted_high_temp_day_1','Predicted_high_temp_day_2','Predicted_high_temp_day_3','Predicted_high_temp_day_4','Predicted_high_temp_day_5','Predicted_high_temp_day_6','Predicted_high_temp_day_7']\n",
    "    \n",
    "    regression.fit(training_set[predictors], training_set['target_temp_max_day_8'])\n",
    "    predictions = regression.predict(test_set_forecast[predictors])\n",
    "    combined_df = pd.concat([combined_df[['name','current_day_max_temp','Predicted_high_temp_day_1','Predicted_high_temp_day_2','Predicted_high_temp_day_3','Predicted_high_temp_day_4','Predicted_high_temp_day_5','Predicted_high_temp_day_6','Predicted_high_temp_day_7']], pd.Series(predictions, index = test_set_forecast.index)], axis=1)\n",
    "    combined_df.columns = ['name','current_day_max_temp','Predicted_high_temp_day_1','Predicted_high_temp_day_2','Predicted_high_temp_day_3','Predicted_high_temp_day_4','Predicted_high_temp_day_5','Predicted_high_temp_day_6','Predicted_high_temp_day_7','Predicted_high_temp_day_8']\n",
    "    \n",
    "    regression.fit(training_set[predictors], training_set['target_temp_max_day_9'])\n",
    "    predictions = regression.predict(test_set_forecast[predictors])\n",
    "    combined_df = pd.concat([combined_df[['name','current_day_max_temp','Predicted_high_temp_day_1','Predicted_high_temp_day_2','Predicted_high_temp_day_3','Predicted_high_temp_day_4','Predicted_high_temp_day_5','Predicted_high_temp_day_6','Predicted_high_temp_day_7','Predicted_high_temp_day_8']], pd.Series(predictions, index = test_set_forecast.index)], axis=1)\n",
    "    combined_df.columns = ['name','current_day_max_temp','Predicted_high_temp_day_1','Predicted_high_temp_day_2','Predicted_high_temp_day_3','Predicted_high_temp_day_4','Predicted_high_temp_day_5','Predicted_high_temp_day_6','Predicted_high_temp_day_7','Predicted_high_temp_day_8','Predicted_high_temp_day_9']\n",
    "    \n",
    "    regression.fit(training_set[predictors], training_set['target_temp_max_day_10'])\n",
    "    predictions = regression.predict(test_set_forecast[predictors])\n",
    "    combined_df = pd.concat([combined_df[['name','current_day_max_temp','Predicted_high_temp_day_1','Predicted_high_temp_day_2','Predicted_high_temp_day_3','Predicted_high_temp_day_4','Predicted_high_temp_day_5','Predicted_high_temp_day_6','Predicted_high_temp_day_7','Predicted_high_temp_day_8','Predicted_high_temp_day_9']], pd.Series(predictions, index = test_set_forecast.index)], axis=1)\n",
    "    combined_df.columns = ['name','current_day_max_temp','Predicted_high_temp_day_1','Predicted_high_temp_day_2','Predicted_high_temp_day_3','Predicted_high_temp_day_4','Predicted_high_temp_day_5','Predicted_high_temp_day_6','Predicted_high_temp_day_7','Predicted_high_temp_day_8','Predicted_high_temp_day_9','Predicted_high_temp_day_10']\n",
    "    \n",
    "    combined_df['date'] = combined_df.index\n",
    "\n",
    "    combined_df = combined_df.astype({'current_day_max_temp':int,'Predicted_high_temp_day_1':int,'Predicted_high_temp_day_2':int,'Predicted_high_temp_day_3':int,'Predicted_high_temp_day_4':int,'Predicted_high_temp_day_5':int,'Predicted_high_temp_day_6':int,'Predicted_high_temp_day_7':int,'Predicted_high_temp_day_8':int,'Predicted_high_temp_day_9':int,'Predicted_high_temp_day_10':int})\n",
    "\n",
    "    combined_df = combined_df.iloc[-11:]\n",
    "\n",
    "    return combined_df\n",
    "\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "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>name</th>\n",
       "      <th>current_day_max_temp</th>\n",
       "      <th>Predicted_high_temp_day_1</th>\n",
       "      <th>Predicted_high_temp_day_2</th>\n",
       "      <th>Predicted_high_temp_day_3</th>\n",
       "      <th>Predicted_high_temp_day_4</th>\n",
       "      <th>Predicted_high_temp_day_5</th>\n",
       "      <th>Predicted_high_temp_day_6</th>\n",
       "      <th>Predicted_high_temp_day_7</th>\n",
       "      <th>Predicted_high_temp_day_8</th>\n",
       "      <th>Predicted_high_temp_day_9</th>\n",
       "      <th>Predicted_high_temp_day_10</th>\n",
       "      <th>date</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DATE</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2023-03-08</th>\n",
       "      <td>PHILADELPHIA INTERNATIONAL AIRPORT, PA US</td>\n",
       "      <td>51</td>\n",
       "      <td>51</td>\n",
       "      <td>51</td>\n",
       "      <td>51</td>\n",
       "      <td>51</td>\n",
       "      <td>51</td>\n",
       "      <td>51</td>\n",
       "      <td>51</td>\n",
       "      <td>51</td>\n",
       "      <td>51</td>\n",
       "      <td>51</td>\n",
       "      <td>2023-03-08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-08</th>\n",
       "      <td>ORLANDO EXECUTIVE AIRPORT, FL US</td>\n",
       "      <td>80</td>\n",
       "      <td>79</td>\n",
       "      <td>78</td>\n",
       "      <td>78</td>\n",
       "      <td>78</td>\n",
       "      <td>78</td>\n",
       "      <td>78</td>\n",
       "      <td>78</td>\n",
       "      <td>78</td>\n",
       "      <td>77</td>\n",
       "      <td>77</td>\n",
       "      <td>2023-03-08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-08</th>\n",
       "      <td>MILWAUKEE MITCHELL AIRPORT, WI US</td>\n",
       "      <td>37</td>\n",
       "      <td>39</td>\n",
       "      <td>41</td>\n",
       "      <td>42</td>\n",
       "      <td>42</td>\n",
       "      <td>42</td>\n",
       "      <td>42</td>\n",
       "      <td>43</td>\n",
       "      <td>43</td>\n",
       "      <td>43</td>\n",
       "      <td>43</td>\n",
       "      <td>2023-03-08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-08</th>\n",
       "      <td>LYNCHBURG REGIONAL AIRPORT, VA US</td>\n",
       "      <td>60</td>\n",
       "      <td>58</td>\n",
       "      <td>57</td>\n",
       "      <td>57</td>\n",
       "      <td>57</td>\n",
       "      <td>57</td>\n",
       "      <td>57</td>\n",
       "      <td>57</td>\n",
       "      <td>57</td>\n",
       "      <td>57</td>\n",
       "      <td>57</td>\n",
       "      <td>2023-03-08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-08</th>\n",
       "      <td>KALISPELL GLACIER AIRPORT, MT US</td>\n",
       "      <td>32</td>\n",
       "      <td>32</td>\n",
       "      <td>32</td>\n",
       "      <td>33</td>\n",
       "      <td>33</td>\n",
       "      <td>33</td>\n",
       "      <td>33</td>\n",
       "      <td>33</td>\n",
       "      <td>33</td>\n",
       "      <td>33</td>\n",
       "      <td>34</td>\n",
       "      <td>2023-03-08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-08</th>\n",
       "      <td>KAHULUI AIRPORT, HI US</td>\n",
       "      <td>80</td>\n",
       "      <td>79</td>\n",
       "      <td>79</td>\n",
       "      <td>79</td>\n",
       "      <td>79</td>\n",
       "      <td>79</td>\n",
       "      <td>79</td>\n",
       "      <td>79</td>\n",
       "      <td>79</td>\n",
       "      <td>79</td>\n",
       "      <td>79</td>\n",
       "      <td>2023-03-08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-08</th>\n",
       "      <td>FAIRBANKS INTERNATIONAL AIRPORT, AK US</td>\n",
       "      <td>31</td>\n",
       "      <td>33</td>\n",
       "      <td>34</td>\n",
       "      <td>35</td>\n",
       "      <td>35</td>\n",
       "      <td>35</td>\n",
       "      <td>35</td>\n",
       "      <td>35</td>\n",
       "      <td>36</td>\n",
       "      <td>36</td>\n",
       "      <td>36</td>\n",
       "      <td>2023-03-08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-08</th>\n",
       "      <td>BANGOR INTERNATIONAL AIRPORT, ME US</td>\n",
       "      <td>41</td>\n",
       "      <td>42</td>\n",
       "      <td>44</td>\n",
       "      <td>44</td>\n",
       "      <td>44</td>\n",
       "      <td>45</td>\n",
       "      <td>45</td>\n",
       "      <td>45</td>\n",
       "      <td>45</td>\n",
       "      <td>45</td>\n",
       "      <td>45</td>\n",
       "      <td>2023-03-08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-08</th>\n",
       "      <td>ALBUQUERQUE INTERNATIONAL AIRPORT, NM US</td>\n",
       "      <td>71</td>\n",
       "      <td>68</td>\n",
       "      <td>67</td>\n",
       "      <td>66</td>\n",
       "      <td>66</td>\n",
       "      <td>66</td>\n",
       "      <td>66</td>\n",
       "      <td>65</td>\n",
       "      <td>65</td>\n",
       "      <td>65</td>\n",
       "      <td>65</td>\n",
       "      <td>2023-03-08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-08</th>\n",
       "      <td>PORTLAND INTERNATIONAL AIRPORT, OR US</td>\n",
       "      <td>48</td>\n",
       "      <td>49</td>\n",
       "      <td>49</td>\n",
       "      <td>50</td>\n",
       "      <td>50</td>\n",
       "      <td>50</td>\n",
       "      <td>50</td>\n",
       "      <td>50</td>\n",
       "      <td>50</td>\n",
       "      <td>50</td>\n",
       "      <td>50</td>\n",
       "      <td>2023-03-08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-08</th>\n",
       "      <td>SITKA AIRPORT, AK US</td>\n",
       "      <td>29</td>\n",
       "      <td>31</td>\n",
       "      <td>32</td>\n",
       "      <td>33</td>\n",
       "      <td>33</td>\n",
       "      <td>33</td>\n",
       "      <td>33</td>\n",
       "      <td>33</td>\n",
       "      <td>34</td>\n",
       "      <td>34</td>\n",
       "      <td>34</td>\n",
       "      <td>2023-03-08</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                 name  current_day_max_temp  \\\n",
       "DATE                                                                          \n",
       "2023-03-08  PHILADELPHIA INTERNATIONAL AIRPORT, PA US                    51   \n",
       "2023-03-08           ORLANDO EXECUTIVE AIRPORT, FL US                    80   \n",
       "2023-03-08          MILWAUKEE MITCHELL AIRPORT, WI US                    37   \n",
       "2023-03-08          LYNCHBURG REGIONAL AIRPORT, VA US                    60   \n",
       "2023-03-08           KALISPELL GLACIER AIRPORT, MT US                    32   \n",
       "2023-03-08                     KAHULUI AIRPORT, HI US                    80   \n",
       "2023-03-08     FAIRBANKS INTERNATIONAL AIRPORT, AK US                    31   \n",
       "2023-03-08        BANGOR INTERNATIONAL AIRPORT, ME US                    41   \n",
       "2023-03-08   ALBUQUERQUE INTERNATIONAL AIRPORT, NM US                    71   \n",
       "2023-03-08      PORTLAND INTERNATIONAL AIRPORT, OR US                    48   \n",
       "2023-03-08                       SITKA AIRPORT, AK US                    29   \n",
       "\n",
       "            Predicted_high_temp_day_1  Predicted_high_temp_day_2  \\\n",
       "DATE                                                               \n",
       "2023-03-08                         51                         51   \n",
       "2023-03-08                         79                         78   \n",
       "2023-03-08                         39                         41   \n",
       "2023-03-08                         58                         57   \n",
       "2023-03-08                         32                         32   \n",
       "2023-03-08                         79                         79   \n",
       "2023-03-08                         33                         34   \n",
       "2023-03-08                         42                         44   \n",
       "2023-03-08                         68                         67   \n",
       "2023-03-08                         49                         49   \n",
       "2023-03-08                         31                         32   \n",
       "\n",
       "            Predicted_high_temp_day_3  Predicted_high_temp_day_4  \\\n",
       "DATE                                                               \n",
       "2023-03-08                         51                         51   \n",
       "2023-03-08                         78                         78   \n",
       "2023-03-08                         42                         42   \n",
       "2023-03-08                         57                         57   \n",
       "2023-03-08                         33                         33   \n",
       "2023-03-08                         79                         79   \n",
       "2023-03-08                         35                         35   \n",
       "2023-03-08                         44                         44   \n",
       "2023-03-08                         66                         66   \n",
       "2023-03-08                         50                         50   \n",
       "2023-03-08                         33                         33   \n",
       "\n",
       "            Predicted_high_temp_day_5  Predicted_high_temp_day_6  \\\n",
       "DATE                                                               \n",
       "2023-03-08                         51                         51   \n",
       "2023-03-08                         78                         78   \n",
       "2023-03-08                         42                         42   \n",
       "2023-03-08                         57                         57   \n",
       "2023-03-08                         33                         33   \n",
       "2023-03-08                         79                         79   \n",
       "2023-03-08                         35                         35   \n",
       "2023-03-08                         45                         45   \n",
       "2023-03-08                         66                         66   \n",
       "2023-03-08                         50                         50   \n",
       "2023-03-08                         33                         33   \n",
       "\n",
       "            Predicted_high_temp_day_7  Predicted_high_temp_day_8  \\\n",
       "DATE                                                               \n",
       "2023-03-08                         51                         51   \n",
       "2023-03-08                         78                         78   \n",
       "2023-03-08                         43                         43   \n",
       "2023-03-08                         57                         57   \n",
       "2023-03-08                         33                         33   \n",
       "2023-03-08                         79                         79   \n",
       "2023-03-08                         35                         36   \n",
       "2023-03-08                         45                         45   \n",
       "2023-03-08                         65                         65   \n",
       "2023-03-08                         50                         50   \n",
       "2023-03-08                         33                         34   \n",
       "\n",
       "            Predicted_high_temp_day_9  Predicted_high_temp_day_10       date  \n",
       "DATE                                                                          \n",
       "2023-03-08                         51                          51 2023-03-08  \n",
       "2023-03-08                         77                          77 2023-03-08  \n",
       "2023-03-08                         43                          43 2023-03-08  \n",
       "2023-03-08                         57                          57 2023-03-08  \n",
       "2023-03-08                         33                          34 2023-03-08  \n",
       "2023-03-08                         79                          79 2023-03-08  \n",
       "2023-03-08                         36                          36 2023-03-08  \n",
       "2023-03-08                         45                          45 2023-03-08  \n",
       "2023-03-08                         65                          65 2023-03-08  \n",
       "2023-03-08                         50                          50 2023-03-08  \n",
       "2023-03-08                         34                          34 2023-03-08  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(max_temp_10_day_forecast(predictors, core_weather_df,test_set_forecast, regression))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "training_set = core_weather_df.loc[:'2021-12-31']\n",
    "test_set_forecast = test_set_forecast[['name','precip','temp_max','temp_min','city_number']]\n",
    "\n",
    "regression.fit(training_set[predictors], training_set['target_temp_max_day_1'])\n",
    "predictions = regression.predict(test_set_forecast[predictors])\n",
    "combined_df = pd.concat([test_set_forecast[['name','temp_max']], pd.Series(predictions, index = test_set_forecast.index)], axis=1)\n",
    "combined_df.columns = ['name','current_day_max_temp','Predicted_high_temp_day_1']\n",
    "\n",
    "regression.fit(training_set[predictors], training_set['target_temp_max_day_2'])\n",
    "predictions = regression.predict(test_set_forecast[predictors])\n",
    "combined_df = pd.concat([combined_df[['name','current_day_max_temp','Predicted_high_temp_day_1']], pd.Series(predictions, index = test_set_forecast.index)], axis=1)\n",
    "combined_df.columns = ['name','current_day_max_temp','Predicted_high_temp_day_1','Predicted_high_temp_day_2']\n",
    "\n",
    "regression.fit(training_set[predictors], training_set['target_temp_max_day_3'])\n",
    "predictions = regression.predict(test_set_forecast[predictors])\n",
    "combined_df = pd.concat([combined_df[['name','current_day_max_temp','Predicted_high_temp_day_1','Predicted_high_temp_day_2']], pd.Series(predictions, index = test_set_forecast.index)], axis=1)\n",
    "combined_df.columns = ['name','current_day_max_temp','Predicted_high_temp_day_1','Predicted_high_temp_day_2','Predicted_high_temp_day_3']\n",
    "\n",
    "regression.fit(training_set[predictors], training_set['target_temp_max_day_4'])\n",
    "predictions = regression.predict(test_set_forecast[predictors])\n",
    "combined_df = pd.concat([combined_df[['name','current_day_max_temp','Predicted_high_temp_day_1','Predicted_high_temp_day_2','Predicted_high_temp_day_3']], pd.Series(predictions, index = test_set_forecast.index)], axis=1)\n",
    "combined_df.columns = ['name','current_day_max_temp','Predicted_high_temp_day_1','Predicted_high_temp_day_2','Predicted_high_temp_day_3','Predicted_high_temp_day_4']\n",
    "\n",
    "regression.fit(training_set[predictors], training_set['target_temp_max_day_5'])\n",
    "predictions = regression.predict(test_set_forecast[predictors])\n",
    "combined_df = pd.concat([combined_df[['name','current_day_max_temp','Predicted_high_temp_day_1','Predicted_high_temp_day_2','Predicted_high_temp_day_3','Predicted_high_temp_day_4']], pd.Series(predictions, index = test_set_forecast.index)], axis=1)\n",
    "combined_df.columns = ['name','current_day_max_temp','Predicted_high_temp_day_1','Predicted_high_temp_day_2','Predicted_high_temp_day_3','Predicted_high_temp_day_4','Predicted_high_temp_day_5']\n",
    "\n",
    "regression.fit(training_set[predictors], training_set['target_temp_max_day_6'])\n",
    "predictions = regression.predict(test_set_forecast[predictors])\n",
    "combined_df = pd.concat([combined_df[['name','current_day_max_temp','Predicted_high_temp_day_1','Predicted_high_temp_day_2','Predicted_high_temp_day_3','Predicted_high_temp_day_4','Predicted_high_temp_day_5']], pd.Series(predictions, index = test_set_forecast.index)], axis=1)\n",
    "combined_df.columns = ['name','current_day_max_temp','Predicted_high_temp_day_1','Predicted_high_temp_day_2','Predicted_high_temp_day_3','Predicted_high_temp_day_4','Predicted_high_temp_day_5','Predicted_high_temp_day_6']\n",
    "\n",
    "regression.fit(training_set[predictors], training_set['target_temp_max_day_7'])\n",
    "predictions = regression.predict(test_set_forecast[predictors])\n",
    "combined_df = pd.concat([combined_df[['name','current_day_max_temp','Predicted_high_temp_day_1','Predicted_high_temp_day_2','Predicted_high_temp_day_3','Predicted_high_temp_day_4','Predicted_high_temp_day_5','Predicted_high_temp_day_6']], pd.Series(predictions, index = test_set_forecast.index)], axis=1)\n",
    "combined_df.columns = ['name','current_day_max_temp','Predicted_high_temp_day_1','Predicted_high_temp_day_2','Predicted_high_temp_day_3','Predicted_high_temp_day_4','Predicted_high_temp_day_5','Predicted_high_temp_day_6','Predicted_high_temp_day_7']\n",
    "\n",
    "regression.fit(training_set[predictors], training_set['target_temp_max_day_8'])\n",
    "predictions = regression.predict(test_set_forecast[predictors])\n",
    "combined_df = pd.concat([combined_df[['name','current_day_max_temp','Predicted_high_temp_day_1','Predicted_high_temp_day_2','Predicted_high_temp_day_3','Predicted_high_temp_day_4','Predicted_high_temp_day_5','Predicted_high_temp_day_6','Predicted_high_temp_day_7']], pd.Series(predictions, index = test_set_forecast.index)], axis=1)\n",
    "combined_df.columns = ['name','current_day_max_temp','Predicted_high_temp_day_1','Predicted_high_temp_day_2','Predicted_high_temp_day_3','Predicted_high_temp_day_4','Predicted_high_temp_day_5','Predicted_high_temp_day_6','Predicted_high_temp_day_7','Predicted_high_temp_day_8']\n",
    "\n",
    "regression.fit(training_set[predictors], training_set['target_temp_max_day_9'])\n",
    "predictions = regression.predict(test_set_forecast[predictors])\n",
    "combined_df = pd.concat([combined_df[['name','current_day_max_temp','Predicted_high_temp_day_1','Predicted_high_temp_day_2','Predicted_high_temp_day_3','Predicted_high_temp_day_4','Predicted_high_temp_day_5','Predicted_high_temp_day_6','Predicted_high_temp_day_7','Predicted_high_temp_day_8']], pd.Series(predictions, index = test_set_forecast.index)], axis=1)\n",
    "combined_df.columns = ['name','current_day_max_temp','Predicted_high_temp_day_1','Predicted_high_temp_day_2','Predicted_high_temp_day_3','Predicted_high_temp_day_4','Predicted_high_temp_day_5','Predicted_high_temp_day_6','Predicted_high_temp_day_7','Predicted_high_temp_day_8','Predicted_high_temp_day_9']\n",
    "\n",
    "regression.fit(training_set[predictors], training_set['target_temp_max_day_10'])\n",
    "predictions = regression.predict(test_set_forecast[predictors])\n",
    "combined_df = pd.concat([combined_df[['name','current_day_max_temp','Predicted_high_temp_day_1','Predicted_high_temp_day_2','Predicted_high_temp_day_3','Predicted_high_temp_day_4','Predicted_high_temp_day_5','Predicted_high_temp_day_6','Predicted_high_temp_day_7','Predicted_high_temp_day_8','Predicted_high_temp_day_9']], pd.Series(predictions, index = test_set_forecast.index)], axis=1)\n",
    "combined_df.columns = ['name','current_day_max_temp','Predicted_high_temp_day_1','Predicted_high_temp_day_2','Predicted_high_temp_day_3','Predicted_high_temp_day_4','Predicted_high_temp_day_5','Predicted_high_temp_day_6','Predicted_high_temp_day_7','Predicted_high_temp_day_8','Predicted_high_temp_day_9','Predicted_high_temp_day_10']\n",
    "\n",
    "combined_df['date'] = combined_df.index\n",
    "\n",
    "combined_df = combined_df.astype({'current_day_max_temp':int,'Predicted_high_temp_day_1':int,'Predicted_high_temp_day_2':int,'Predicted_high_temp_day_3':int,'Predicted_high_temp_day_4':int,'Predicted_high_temp_day_5':int,'Predicted_high_temp_day_6':int,'Predicted_high_temp_day_7':int,'Predicted_high_temp_day_8':int,'Predicted_high_temp_day_9':int,'Predicted_high_temp_day_10':int})\n",
    "\n",
    "combined_df = combined_df.iloc[-11:]\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/reed/Desktop/epicodus/Weather_Forcaster/venvweather/lib/python3.7/site-packages/google/cloud/bigquery/_pandas_helpers.py:472: UserWarning: Pyarrow could not determine the type of columns: name.\n",
      "  \", \".join(field.name for field in unknown_type_fields)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "LoadJob<project=deb-01-372116, location=US, id=1e14fe42-6af1-4ce8-8b8a-cf386d0e1f0e>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "PROJECT_ID = \"deb-01-372116\"\n",
    "DATASET_ID = \"Weather_Forecaster\"\n",
    "DAILY_TABLE_ID = \"ten_day_forecast\"\n",
    "\n",
    "SCHEMA = [\n",
    "            # indexes are written if only named in the schema\n",
    "            bigquery.SchemaField('name', 'STRING', mode='REQUIRED'),\n",
    "            bigquery.SchemaField('current_day_max_temp', 'INT64', mode='NULLABLE'),\n",
    "            bigquery.SchemaField('Predicted_high_temp_day_1', 'INT64', mode='NULLABLE'),\n",
    "            bigquery.SchemaField('Predicted_high_temp_day_2', 'INT64', mode='NULLABLE'),\n",
    "            bigquery.SchemaField('Predicted_high_temp_day_3', 'INT64', mode='NULLABLE'),\n",
    "            bigquery.SchemaField('Predicted_high_temp_day_4', 'INT64', mode='NULLABLE'),\n",
    "            bigquery.SchemaField('Predicted_high_temp_day_5', 'INT64', mode='NULLABLE'),\n",
    "            bigquery.SchemaField('Predicted_high_temp_day_6', 'INT64', mode='NULLABLE'),\n",
    "            bigquery.SchemaField('Predicted_high_temp_day_7', 'INT64', mode='NULLABLE'),\n",
    "            bigquery.SchemaField('Predicted_high_temp_day_8', 'INT64', mode='NULLABLE'),\n",
    "            bigquery.SchemaField('Predicted_high_temp_day_9', 'INT64', mode='NULLABLE'),\n",
    "            bigquery.SchemaField('Predicted_high_temp_day_10', 'INT64', mode='REQUIRED'),\n",
    "            bigquery.SchemaField('date', 'DATETIME', mode='NULLABLE'),\n",
    "        ]\n",
    "\n",
    "#change the date column back to a datetime dtype\n",
    "# df = pd.DataFrame(data)\n",
    "\n",
    "client = bigquery.Client()\n",
    "\n",
    "try:\n",
    "    dataset_ref = client.dataset(DATASET_ID)\n",
    "    dataset = client.get_dataset(dataset_ref)\n",
    "except:\n",
    "    dataset_ref = client.dataset(DATASET_ID)\n",
    "    dataset = bigquery.Dataset(dataset_ref)\n",
    "    # dataset.location = \"US\"\n",
    "    dataset = client.create_dataset(dataset)\n",
    "\n",
    "table_ref = dataset.table(DAILY_TABLE_ID)\n",
    "\n",
    "try:\n",
    "    client.get_table(table_ref)\n",
    "except:\n",
    "    table = bigquery.Table(table_ref, schema=SCHEMA)\n",
    "    table = client.create_table(table)\n",
    "\n",
    "job_config = bigquery.LoadJobConfig(write_disposition=bigquery.WriteDisposition.WRITE_TRUNCATE)\n",
    "job = client.load_table_from_dataframe(combined_df, table_ref, job_config=job_config)\n",
    "job.result()"
   ]
  }
 ],
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