WeatherAVGData_FINAL.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "view-in-github"
   },
   "source": [
    "<a href=\"https://colab.research.google.com/github/Soumi7/PG-StockManagement/blob/master/WeatherAVGData_FINAL.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 127
    },
    "colab_type": "code",
    "id": "V0wpmuHuENDj",
    "outputId": "7462efba-0b98-4740-9a36-4afdd2ae6867"
   },
   "outputs": [
    {
     "ename": "ModuleNotFoundError",
     "evalue": "No module named 'google.colab'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mModuleNotFoundError\u001b[0m                       Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-108-d5df0069828e>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0;32mfrom\u001b[0m \u001b[0mgoogle\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolab\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mdrive\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0mdrive\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmount\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'/content/drive'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'google.colab'"
     ]
    }
   ],
   "source": [
    "from google.colab import drive\n",
    "drive.mount('/content/drive')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 179
    },
    "colab_type": "code",
    "id": "XBDCBwDrEeF9",
    "outputId": "1c465f42-01c1-4b60-c1cf-234d8945b374"
   },
   "outputs": [],
   "source": [
    "pip install wwo-hist"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 629
    },
    "colab_type": "code",
    "id": "jMqqdKhQGed1",
    "outputId": "01cde179-01de-4454-e555-08b888c3f2e0"
   },
   "outputs": [],
   "source": [
    "import requests\n",
    "from wwo_hist import retrieve_hist_data\n",
    "frequency = 24\n",
    "start_date = '1-JAN-2018'\n",
    "end_date = '1-JAN-2019'\n",
    "api_key = '12b2c18a34194a8ca93113127200405'\n",
    "location_list = ['Mlawa']\n",
    "hist_weather_data = retrieve_hist_data(api_key,\n",
    "                                location_list,\n",
    "                                start_date,\n",
    "                                end_date,\n",
    "                                frequency,\n",
    "                                location_label = False,\n",
    "                                export_csv = True,\n",
    "                                store_df = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 467,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 309
    },
    "colab_type": "code",
    "id": "2Il01xJYH2ln",
    "outputId": "66cabd76-72f8-4c19-99b3-240124780c57",
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "df=pd.read_csv(\"Mlawa.csv\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 468,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_copy=pd.read_csv(\"Mlawa.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 469,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-12, -11, -10,  -8,  -7,  -6,  -5,  -4,  -3,  -2,  -1,   0,   1,\n",
       "         2,   3,   4,   5,   6,   7,   8,   9,  10,  11,  12,  13,  14,\n",
       "        15,  16,  17,  18,  19,  20,  21,  22,  23,  24,  25,  26,  27])"
      ]
     },
     "execution_count": 469,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "heatindex=df_copy[\"HeatIndexC\"].unique()\n",
    "heatindex.sort()\n",
    "heatindex"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 470,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.drop(df.tail(1).index,inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 471,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(365, 25)"
      ]
     },
     "execution_count": 471,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 472,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 593
    },
    "colab_type": "code",
    "id": "2WIuXcbwIKT1",
    "outputId": "23ad93e1-aa2a-46b6-902d-83b7bd0ccdc1"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 365 entries, 0 to 364\n",
      "Data columns (total 25 columns):\n",
      " #   Column             Non-Null Count  Dtype  \n",
      "---  ------             --------------  -----  \n",
      " 0   date_time          365 non-null    object \n",
      " 1   maxtempC           365 non-null    int64  \n",
      " 2   mintempC           365 non-null    int64  \n",
      " 3   totalSnow_cm       365 non-null    float64\n",
      " 4   sunHour            365 non-null    float64\n",
      " 5   uvIndex            365 non-null    int64  \n",
      " 6   uvIndex.1          365 non-null    int64  \n",
      " 7   moon_illumination  365 non-null    int64  \n",
      " 8   moonrise           365 non-null    object \n",
      " 9   moonset            365 non-null    object \n",
      " 10  sunrise            365 non-null    object \n",
      " 11  sunset             365 non-null    object \n",
      " 12  DewPointC          365 non-null    int64  \n",
      " 13  FeelsLikeC         365 non-null    int64  \n",
      " 14  HeatIndexC         365 non-null    int64  \n",
      " 15  WindChillC         365 non-null    int64  \n",
      " 16  WindGustKmph       365 non-null    int64  \n",
      " 17  cloudcover         365 non-null    int64  \n",
      " 18  humidity           365 non-null    int64  \n",
      " 19  precipMM           365 non-null    float64\n",
      " 20  pressure           365 non-null    int64  \n",
      " 21  tempC              365 non-null    int64  \n",
      " 22  visibility         365 non-null    int64  \n",
      " 23  winddirDegree      365 non-null    int64  \n",
      " 24  windspeedKmph      365 non-null    int64  \n",
      "dtypes: float64(3), int64(17), object(5)\n",
      "memory usage: 74.1+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 473,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "U4K-kU9PIUbz"
   },
   "outputs": [],
   "source": [
    "df=df.drop(['uvIndex','uvIndex.1','moon_illumination','moonrise','moonset','sunrise','sunset','DewPointC','pressure','winddirDegree','sunHour'],axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 474,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 395
    },
    "colab_type": "code",
    "id": "kF9BssIfI_bJ",
    "outputId": "7a3888d1-c38c-4454-e75b-85e142c9c817"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 365 entries, 0 to 364\n",
      "Data columns (total 14 columns):\n",
      " #   Column         Non-Null Count  Dtype  \n",
      "---  ------         --------------  -----  \n",
      " 0   date_time      365 non-null    object \n",
      " 1   maxtempC       365 non-null    int64  \n",
      " 2   mintempC       365 non-null    int64  \n",
      " 3   totalSnow_cm   365 non-null    float64\n",
      " 4   FeelsLikeC     365 non-null    int64  \n",
      " 5   HeatIndexC     365 non-null    int64  \n",
      " 6   WindChillC     365 non-null    int64  \n",
      " 7   WindGustKmph   365 non-null    int64  \n",
      " 8   cloudcover     365 non-null    int64  \n",
      " 9   humidity       365 non-null    int64  \n",
      " 10  precipMM       365 non-null    float64\n",
      " 11  tempC          365 non-null    int64  \n",
      " 12  visibility     365 non-null    int64  \n",
      " 13  windspeedKmph  365 non-null    int64  \n",
      "dtypes: float64(2), int64(11), object(1)\n",
      "memory usage: 42.8+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 475,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 204
    },
    "colab_type": "code",
    "id": "4Xz9UJK2JlVC",
    "outputId": "70502fdf-abc9-40ee-b505-b647219750cf"
   },
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date_time</th>\n",
       "      <th>maxtempC</th>\n",
       "      <th>mintempC</th>\n",
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       "      <th>FeelsLikeC</th>\n",
       "      <th>HeatIndexC</th>\n",
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       "      <th>0</th>\n",
       "      <td>2018-01-01</td>\n",
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       "      <td>2018-01-03</td>\n",
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       "      <td>2018-01-04</td>\n",
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       "      <td>2018-01-05</td>\n",
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       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
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       "      <td>89</td>\n",
       "      <td>82</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7</td>\n",
       "      <td>10</td>\n",
       "      <td>24</td>\n",
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      ],
      "text/plain": [
       "    date_time  maxtempC  mintempC  totalSnow_cm  FeelsLikeC  HeatIndexC  \\\n",
       "0  2018-01-01         8         3           0.0           3           6   \n",
       "1  2018-01-02         3         1           0.0          -1           2   \n",
       "2  2018-01-03         3         0           0.1          -3           2   \n",
       "3  2018-01-04         6         3           0.0           0           4   \n",
       "4  2018-01-05         7         3           0.0           1           5   \n",
       "\n",
       "   WindChillC  WindGustKmph  cloudcover  humidity  precipMM  tempC  \\\n",
       "0           3            32          79        89       0.0      8   \n",
       "1          -1            18          62        89       0.6      3   \n",
       "2          -3            28          81        88       0.9      3   \n",
       "3           0            35          84        84       0.0      6   \n",
       "4           1            35          89        82       0.0      7   \n",
       "\n",
       "   visibility  windspeedKmph  \n",
       "0          10             19  \n",
       "1          10             11  \n",
       "2           6             19  \n",
       "3          10             23  \n",
       "4          10             24  "
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     "execution_count": 475,
     "metadata": {},
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   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 476,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "XXZCwVzDJtwt"
   },
   "outputs": [],
   "source": [
    "def avg(l):\n",
    "  return(sum(l)/len(l))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 477,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 204
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    "colab_type": "code",
    "id": "N4gPB2KmJ28y",
    "outputId": "254bb020-96f0-47d9-ba50-f0f763439653"
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       "      <th>FeelsLikeC</th>\n",
       "      <th>HeatIndexC</th>\n",
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      ],
      "text/plain": [
       "   maxtempC  mintempC  totalSnow_cm  FeelsLikeC  HeatIndexC  WindChillC  \\\n",
       "0         8         3           0.0           3           6           3   \n",
       "1         3         1           0.0          -1           2          -1   \n",
       "2         3         0           0.1          -3           2          -3   \n",
       "3         6         3           0.0           0           4           0   \n",
       "4         7         3           0.0           1           5           1   \n",
       "\n",
       "   WindGustKmph  cloudcover  humidity  precipMM  tempC  visibility  \\\n",
       "0            32          79        89       0.0      8          10   \n",
       "1            18          62        89       0.6      3          10   \n",
       "2            28          81        88       0.9      3           6   \n",
       "3            35          84        84       0.0      6          10   \n",
       "4            35          89        82       0.0      7          10   \n",
       "\n",
       "   windspeedKmph       date  \n",
       "0             19 2018-01-01  \n",
       "1             11 2018-01-02  \n",
       "2             19 2018-01-03  \n",
       "3             23 2018-01-04  \n",
       "4             24 2018-01-05  "
      ]
     },
     "execution_count": 477,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['date'] = pd.to_datetime(df['date_time'],format=\"%Y.%m.%d\")\n",
    "df= df.drop(columns=[\"date_time\"],axis=1)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 478,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "0cptkJx-KmN3"
   },
   "outputs": [],
   "source": [
    "df.set_index('date',inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 479,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "vjzyu4vCMNYU"
   },
   "outputs": [],
   "source": [
    "months=df.index.month"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 480,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "jzKnarxsMUow"
   },
   "outputs": [],
   "source": [
    "monthly_avg_maxtemp=df.groupby(months).maxtempC.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 481,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 269
    },
    "colab_type": "code",
    "id": "n-C2H1NxMgCw",
    "outputId": "afcb9a2f-e52f-4932-888c-d8a828f395bd"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "date\n",
      "1      1.290323\n",
      "2     -1.535714\n",
      "3      3.225806\n",
      "4     17.433333\n",
      "5     21.483871\n",
      "6     22.233333\n",
      "7     24.483871\n",
      "8     24.677419\n",
      "9     20.200000\n",
      "10    14.451613\n",
      "11     6.266667\n",
      "12     1.838710\n",
      "Name: maxtempC, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "print(monthly_avg_maxtemp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 482,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(12,)"
      ]
     },
     "execution_count": 482,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "monthly_avg_maxtemp.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 483,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 269
    },
    "colab_type": "code",
    "id": "yg2KSr5XMkVv",
    "outputId": "43926a2b-5a56-4245-d99b-a99375c373da"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "date\n",
      "1     -2.129032\n",
      "2     -5.035714\n",
      "3     -2.903226\n",
      "4      6.733333\n",
      "5     10.451613\n",
      "6     11.900000\n",
      "7     14.967742\n",
      "8     15.161290\n",
      "9     11.466667\n",
      "10     6.967742\n",
      "11     1.666667\n",
      "12    -1.096774\n",
      "Name: mintempC, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "monthly_avg_mintemp=df.groupby(months).mintempC.mean()\n",
    "print(monthly_avg_mintemp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 484,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 269
    },
    "colab_type": "code",
    "id": "Liy5rZRiM0_L",
    "outputId": "5ab0a478-0183-4617-fc26-a2d1455f9496"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "date\n",
      "1     0.061290\n",
      "2     0.035714\n",
      "3     0.070968\n",
      "4     0.000000\n",
      "5     0.000000\n",
      "6     0.000000\n",
      "7     0.000000\n",
      "8     0.000000\n",
      "9     0.000000\n",
      "10    0.000000\n",
      "11    0.010000\n",
      "12    0.170968\n",
      "Name: totalSnow_cm, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "monthly_avg_totalSnow_cm=df.groupby(months).totalSnow_cm.mean()\n",
    "print(monthly_avg_totalSnow_cm)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 485,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 269
    },
    "colab_type": "code",
    "id": "fF_SOpGuM_ks",
    "outputId": "7dfd7451-d612-48e2-8d6b-70966541df38"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "date\n",
      "1     -4.838710\n",
      "2     -7.607143\n",
      "3     -4.032258\n",
      "4     10.366667\n",
      "5     15.419355\n",
      "6     17.100000\n",
      "7     19.903226\n",
      "8     20.064516\n",
      "9     14.733333\n",
      "10     8.193548\n",
      "11     0.766667\n",
      "12    -3.612903\n",
      "Name: FeelsLikeC, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "monthly_avg_FeelsLikeC=df.groupby(months).FeelsLikeC.mean()\n",
    "print(monthly_avg_FeelsLikeC)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 486,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 269
    },
    "colab_type": "code",
    "id": "M1S5bWbENerg",
    "outputId": "b36ba804-be6a-4592-af4b-6d6657203895"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "date\n",
      "1     82.806452\n",
      "2     76.035714\n",
      "3     73.225806\n",
      "4     72.466667\n",
      "5     73.225806\n",
      "6     72.300000\n",
      "7     75.967742\n",
      "8     69.967742\n",
      "9     69.233333\n",
      "10    71.645161\n",
      "11    80.600000\n",
      "12    88.580645\n",
      "Name: humidity, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "monthly_avg_humidity=df.groupby(months).humidity.mean()\n",
    "print(monthly_avg_humidity)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 487,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 269
    },
    "colab_type": "code",
    "id": "JhPqq6PmNmzp",
    "outputId": "1755303c-33ed-49f3-a997-f1d9c4829e39"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "date\n",
      "1     0.290323\n",
      "2     0.067857\n",
      "3     0.222581\n",
      "4     0.506667\n",
      "5     0.919355\n",
      "6     0.396667\n",
      "7     1.583871\n",
      "8     0.941935\n",
      "9     0.460000\n",
      "10    0.270968\n",
      "11    0.083333\n",
      "12    0.458065\n",
      "Name: precipMM, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "monthly_avg_precipMM=df.groupby(months).precipMM.mean()\n",
    "print(monthly_avg_precipMM)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 488,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 269
    },
    "colab_type": "code",
    "id": "3MpXCh8FOYUE",
    "outputId": "8d144e14-896d-4f8f-9d24-375af6f4d4d7"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "date\n",
      "1     8.322581\n",
      "2     9.750000\n",
      "3     9.096774\n",
      "4     9.700000\n",
      "5     9.645161\n",
      "6     9.466667\n",
      "7     9.354839\n",
      "8     9.806452\n",
      "9     9.533333\n",
      "10    9.903226\n",
      "11    9.400000\n",
      "12    8.419355\n",
      "Name: visibility, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "monthly_avg_visibility=df.groupby(months).visibility.mean()\n",
    "print(monthly_avg_visibility)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 489,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 269
    },
    "colab_type": "code",
    "id": "pp5TRehTOqLi",
    "outputId": "8901681e-a524-42ae-c9c0-38cfe579c9b3"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "date\n",
      "1     -0.322581\n",
      "2     -3.428571\n",
      "3     -0.096774\n",
      "4     11.900000\n",
      "5     16.322581\n",
      "6     17.866667\n",
      "7     20.419355\n",
      "8     20.419355\n",
      "9     15.766667\n",
      "10    10.064516\n",
      "11     3.700000\n",
      "12     0.451613\n",
      "Name: HeatIndexC, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "monthly_avg_HeatIndexC=df.groupby(months).HeatIndexC.mean()\n",
    "print(monthly_avg_HeatIndexC)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 490,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 269
    },
    "colab_type": "code",
    "id": "iPE9FkiTOfvh",
    "outputId": "c5c384e4-be8e-400a-ccd6-3b883586f8d6"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "date\n",
      "1     16.612903\n",
      "2     11.642857\n",
      "3     14.032258\n",
      "4     15.733333\n",
      "5     13.129032\n",
      "6     11.900000\n",
      "7     12.225806\n",
      "8     10.677419\n",
      "9     13.233333\n",
      "10    15.290323\n",
      "11    12.800000\n",
      "12    15.258065\n",
      "Name: windspeedKmph, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "monthly_avg_windspeedKmph=df.groupby(months).windspeedKmph.mean()\n",
    "print(monthly_avg_windspeedKmph)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 491,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 269
    },
    "colab_type": "code",
    "id": "ThDa815QO2Iu",
    "outputId": "f1a5ea31-d08c-4674-a708-96169b4f9237"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "date\n",
      "1     -4.838710\n",
      "2     -7.607143\n",
      "3     -4.032258\n",
      "4     10.366667\n",
      "5     15.419355\n",
      "6     17.100000\n",
      "7     19.612903\n",
      "8     19.806452\n",
      "9     14.733333\n",
      "10     8.193548\n",
      "11     0.766667\n",
      "12    -3.612903\n",
      "Name: WindChillC, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "monthly_avg_WindChillC=df.groupby(months).WindChillC.mean()\n",
    "print(monthly_avg_WindChillC)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 492,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 269
    },
    "colab_type": "code",
    "id": "arThEkkpPCsk",
    "outputId": "fea65e2c-19c1-45b3-a1d0-9845d5dcf98c"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "date\n",
      "1     26.161290\n",
      "2     17.071429\n",
      "3     21.000000\n",
      "4     24.200000\n",
      "5     20.935484\n",
      "6     18.133333\n",
      "7     19.096774\n",
      "8     16.806452\n",
      "9     21.033333\n",
      "10    24.612903\n",
      "11    21.133333\n",
      "12    24.096774\n",
      "Name: WindGustKmph, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "monthly_avg_WindGustKmph=df.groupby(months).WindGustKmph.mean()\n",
    "print(monthly_avg_WindGustKmph)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 493,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 269
    },
    "colab_type": "code",
    "id": "AwkuM0OoPSNg",
    "outputId": "c0bf55de-bef8-4b52-cfb4-2ca86996bf72"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "date\n",
      "1     67.161290\n",
      "2     64.000000\n",
      "3     61.322581\n",
      "4     31.866667\n",
      "5     23.354839\n",
      "6     29.866667\n",
      "7     33.354839\n",
      "8     24.032258\n",
      "9     32.600000\n",
      "10    34.580645\n",
      "11    40.566667\n",
      "12    81.903226\n",
      "Name: cloudcover, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "monthly_avg_cloudcover=df.groupby(months).cloudcover.mean()\n",
    "print(monthly_avg_cloudcover)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 494,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 269
    },
    "colab_type": "code",
    "id": "hq4N8KWTRVUV",
    "outputId": "80334617-7010-472f-c7a7-2c23eb82e691"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "date\n",
      "1      1.290323\n",
      "2     -1.535714\n",
      "3      3.225806\n",
      "4     17.433333\n",
      "5     21.483871\n",
      "6     22.233333\n",
      "7     24.483871\n",
      "8     24.677419\n",
      "9     20.200000\n",
      "10    14.451613\n",
      "11     6.266667\n",
      "12     1.838710\n",
      "Name: tempC, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "monthly_avg_tempC=df.groupby(months).tempC.mean()\n",
    "print(monthly_avg_tempC)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 495,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 235
    },
    "colab_type": "code",
    "id": "lK2JKhKbQmTr",
    "outputId": "230f500a-0804-4b5b-ad71-d31149e1dfe3"
   },
   "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>maxtempC</th>\n",
       "      <th>mintempC</th>\n",
       "      <th>totalSnow_cm</th>\n",
       "      <th>FeelsLikeC</th>\n",
       "      <th>HeatIndexC</th>\n",
       "      <th>WindChillC</th>\n",
       "      <th>WindGustKmph</th>\n",
       "      <th>cloudcover</th>\n",
       "      <th>humidity</th>\n",
       "      <th>precipMM</th>\n",
       "      <th>tempC</th>\n",
       "      <th>visibility</th>\n",
       "      <th>windspeedKmph</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>2018-01-01</th>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>32</td>\n",
       "      <td>79</td>\n",
       "      <td>89</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8</td>\n",
       "      <td>10</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-02</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1</td>\n",
       "      <td>2</td>\n",
       "      <td>-1</td>\n",
       "      <td>18</td>\n",
       "      <td>62</td>\n",
       "      <td>89</td>\n",
       "      <td>0.6</td>\n",
       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-03</th>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>-3</td>\n",
       "      <td>2</td>\n",
       "      <td>-3</td>\n",
       "      <td>28</td>\n",
       "      <td>81</td>\n",
       "      <td>88</td>\n",
       "      <td>0.9</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-04</th>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>84</td>\n",
       "      <td>84</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6</td>\n",
       "      <td>10</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-05</th>\n",
       "      <td>7</td>\n",
       "      <td>3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>35</td>\n",
       "      <td>89</td>\n",
       "      <td>82</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7</td>\n",
       "      <td>10</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            maxtempC  mintempC  totalSnow_cm  FeelsLikeC  HeatIndexC  \\\n",
       "date                                                                   \n",
       "2018-01-01         8         3           0.0           3           6   \n",
       "2018-01-02         3         1           0.0          -1           2   \n",
       "2018-01-03         3         0           0.1          -3           2   \n",
       "2018-01-04         6         3           0.0           0           4   \n",
       "2018-01-05         7         3           0.0           1           5   \n",
       "\n",
       "            WindChillC  WindGustKmph  cloudcover  humidity  precipMM  tempC  \\\n",
       "date                                                                          \n",
       "2018-01-01           3            32          79        89       0.0      8   \n",
       "2018-01-02          -1            18          62        89       0.6      3   \n",
       "2018-01-03          -3            28          81        88       0.9      3   \n",
       "2018-01-04           0            35          84        84       0.0      6   \n",
       "2018-01-05           1            35          89        82       0.0      7   \n",
       "\n",
       "            visibility  windspeedKmph  \n",
       "date                                   \n",
       "2018-01-01          10             19  \n",
       "2018-01-02          10             11  \n",
       "2018-01-03           6             19  \n",
       "2018-01-04          10             23  \n",
       "2018-01-05          10             24  "
      ]
     },
     "execution_count": 495,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 496,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "rj8RUQDbPcsj"
   },
   "outputs": [],
   "source": [
    "l={'monthly_avg_maxtemp':monthly_avg_maxtemp,\n",
    "   'monthly_avg_mintemp': monthly_avg_mintemp,\n",
    "   'monthly_avg_totalSnow_cm':monthly_avg_totalSnow_cm,\n",
    "   'monthly_avg_FeelsLikeC':monthly_avg_FeelsLikeC,\n",
    "   'monthly_avg_HeatIndexC':monthly_avg_HeatIndexC,\n",
    "   'monthly_avg_WindChillC':monthly_avg_WindChillC,\n",
    "   'monthly_avg_WindGustKmph':monthly_avg_WindGustKmph,\n",
    "   'monthly_avg_cloudcover':monthly_avg_cloudcover,\n",
    "   'monthly_avg_humidity':monthly_avg_humidity,\n",
    "   'monthly_avg_precipMM':monthly_avg_precipMM,\n",
    "   'monthly_avg_tempC':monthly_avg_tempC,\n",
    "   'monthly_avg_visibility':monthly_avg_visibility,\n",
    "   'monthly_avg_windspeedKmph':monthly_avg_windspeedKmph}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 497,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 35
    },
    "colab_type": "code",
    "id": "BbFfU-F6QWTZ",
    "outputId": "c9bc61b9-f92c-4680-b3ae-91c3708a7d75"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "13\n"
     ]
    }
   ],
   "source": [
    "print(len(l))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 498,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "kr5rurLdTA-3"
   },
   "outputs": [],
   "source": [
    "weather_data=pd.DataFrame(l) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 499,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 472
    },
    "colab_type": "code",
    "id": "-S9OOmkcTJsS",
    "outputId": "951ac6e2-3b89-4e64-d4e6-0bf304c2aa88"
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>monthly_avg_maxtemp</th>\n",
       "      <th>monthly_avg_mintemp</th>\n",
       "      <th>monthly_avg_totalSnow_cm</th>\n",
       "      <th>monthly_avg_FeelsLikeC</th>\n",
       "      <th>monthly_avg_HeatIndexC</th>\n",
       "      <th>monthly_avg_WindChillC</th>\n",
       "      <th>monthly_avg_WindGustKmph</th>\n",
       "      <th>monthly_avg_cloudcover</th>\n",
       "      <th>monthly_avg_humidity</th>\n",
       "      <th>monthly_avg_precipMM</th>\n",
       "      <th>monthly_avg_tempC</th>\n",
       "      <th>monthly_avg_visibility</th>\n",
       "      <th>monthly_avg_windspeedKmph</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",
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       "      <th>1</th>\n",
       "      <td>1.290323</td>\n",
       "      <td>-2.129032</td>\n",
       "      <td>0.061290</td>\n",
       "      <td>-4.838710</td>\n",
       "      <td>-0.322581</td>\n",
       "      <td>-4.838710</td>\n",
       "      <td>26.161290</td>\n",
       "      <td>67.161290</td>\n",
       "      <td>82.806452</td>\n",
       "      <td>0.290323</td>\n",
       "      <td>1.290323</td>\n",
       "      <td>8.322581</td>\n",
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       "    </tr>\n",
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       "      <th>2</th>\n",
       "      <td>-1.535714</td>\n",
       "      <td>-5.035714</td>\n",
       "      <td>0.035714</td>\n",
       "      <td>-7.607143</td>\n",
       "      <td>-3.428571</td>\n",
       "      <td>-7.607143</td>\n",
       "      <td>17.071429</td>\n",
       "      <td>64.000000</td>\n",
       "      <td>76.035714</td>\n",
       "      <td>0.067857</td>\n",
       "      <td>-1.535714</td>\n",
       "      <td>9.750000</td>\n",
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       "      <th>3</th>\n",
       "      <td>3.225806</td>\n",
       "      <td>-2.903226</td>\n",
       "      <td>0.070968</td>\n",
       "      <td>-4.032258</td>\n",
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       "      <td>-4.032258</td>\n",
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       "      <td>0.222581</td>\n",
       "      <td>3.225806</td>\n",
       "      <td>9.096774</td>\n",
       "      <td>14.032258</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>17.433333</td>\n",
       "      <td>6.733333</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>10.366667</td>\n",
       "      <td>11.900000</td>\n",
       "      <td>10.366667</td>\n",
       "      <td>24.200000</td>\n",
       "      <td>31.866667</td>\n",
       "      <td>72.466667</td>\n",
       "      <td>0.506667</td>\n",
       "      <td>17.433333</td>\n",
       "      <td>9.700000</td>\n",
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       "      <th>5</th>\n",
       "      <td>21.483871</td>\n",
       "      <td>10.451613</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>15.419355</td>\n",
       "      <td>16.322581</td>\n",
       "      <td>15.419355</td>\n",
       "      <td>20.935484</td>\n",
       "      <td>23.354839</td>\n",
       "      <td>73.225806</td>\n",
       "      <td>0.919355</td>\n",
       "      <td>21.483871</td>\n",
       "      <td>9.645161</td>\n",
       "      <td>13.129032</td>\n",
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       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>22.233333</td>\n",
       "      <td>11.900000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>17.100000</td>\n",
       "      <td>17.866667</td>\n",
       "      <td>17.100000</td>\n",
       "      <td>18.133333</td>\n",
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       "      <td>72.300000</td>\n",
       "      <td>0.396667</td>\n",
       "      <td>22.233333</td>\n",
       "      <td>9.466667</td>\n",
       "      <td>11.900000</td>\n",
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       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>24.483871</td>\n",
       "      <td>14.967742</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>19.903226</td>\n",
       "      <td>20.419355</td>\n",
       "      <td>19.612903</td>\n",
       "      <td>19.096774</td>\n",
       "      <td>33.354839</td>\n",
       "      <td>75.967742</td>\n",
       "      <td>1.583871</td>\n",
       "      <td>24.483871</td>\n",
       "      <td>9.354839</td>\n",
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       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>24.677419</td>\n",
       "      <td>15.161290</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>20.064516</td>\n",
       "      <td>20.419355</td>\n",
       "      <td>19.806452</td>\n",
       "      <td>16.806452</td>\n",
       "      <td>24.032258</td>\n",
       "      <td>69.967742</td>\n",
       "      <td>0.941935</td>\n",
       "      <td>24.677419</td>\n",
       "      <td>9.806452</td>\n",
       "      <td>10.677419</td>\n",
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       "    <tr>\n",
       "      <th>9</th>\n",
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       "      <td>69.233333</td>\n",
       "      <td>0.460000</td>\n",
       "      <td>20.200000</td>\n",
       "      <td>9.533333</td>\n",
       "      <td>13.233333</td>\n",
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       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>14.451613</td>\n",
       "      <td>6.967742</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>8.193548</td>\n",
       "      <td>10.064516</td>\n",
       "      <td>8.193548</td>\n",
       "      <td>24.612903</td>\n",
       "      <td>34.580645</td>\n",
       "      <td>71.645161</td>\n",
       "      <td>0.270968</td>\n",
       "      <td>14.451613</td>\n",
       "      <td>9.903226</td>\n",
       "      <td>15.290323</td>\n",
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       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>6.266667</td>\n",
       "      <td>1.666667</td>\n",
       "      <td>0.010000</td>\n",
       "      <td>0.766667</td>\n",
       "      <td>3.700000</td>\n",
       "      <td>0.766667</td>\n",
       "      <td>21.133333</td>\n",
       "      <td>40.566667</td>\n",
       "      <td>80.600000</td>\n",
       "      <td>0.083333</td>\n",
       "      <td>6.266667</td>\n",
       "      <td>9.400000</td>\n",
       "      <td>12.800000</td>\n",
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       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>1.838710</td>\n",
       "      <td>-1.096774</td>\n",
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       "      <td>-3.612903</td>\n",
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       "      <td>0.458065</td>\n",
       "      <td>1.838710</td>\n",
       "      <td>8.419355</td>\n",
       "      <td>15.258065</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      monthly_avg_maxtemp  monthly_avg_mintemp  monthly_avg_totalSnow_cm  \\\n",
       "date                                                                       \n",
       "1                1.290323            -2.129032                  0.061290   \n",
       "2               -1.535714            -5.035714                  0.035714   \n",
       "3                3.225806            -2.903226                  0.070968   \n",
       "4               17.433333             6.733333                  0.000000   \n",
       "5               21.483871            10.451613                  0.000000   \n",
       "6               22.233333            11.900000                  0.000000   \n",
       "7               24.483871            14.967742                  0.000000   \n",
       "8               24.677419            15.161290                  0.000000   \n",
       "9               20.200000            11.466667                  0.000000   \n",
       "10              14.451613             6.967742                  0.000000   \n",
       "11               6.266667             1.666667                  0.010000   \n",
       "12               1.838710            -1.096774                  0.170968   \n",
       "\n",
       "      monthly_avg_FeelsLikeC  monthly_avg_HeatIndexC  monthly_avg_WindChillC  \\\n",
       "date                                                                           \n",
       "1                  -4.838710               -0.322581               -4.838710   \n",
       "2                  -7.607143               -3.428571               -7.607143   \n",
       "3                  -4.032258               -0.096774               -4.032258   \n",
       "4                  10.366667               11.900000               10.366667   \n",
       "5                  15.419355               16.322581               15.419355   \n",
       "6                  17.100000               17.866667               17.100000   \n",
       "7                  19.903226               20.419355               19.612903   \n",
       "8                  20.064516               20.419355               19.806452   \n",
       "9                  14.733333               15.766667               14.733333   \n",
       "10                  8.193548               10.064516                8.193548   \n",
       "11                  0.766667                3.700000                0.766667   \n",
       "12                 -3.612903                0.451613               -3.612903   \n",
       "\n",
       "      monthly_avg_WindGustKmph  monthly_avg_cloudcover  monthly_avg_humidity  \\\n",
       "date                                                                           \n",
       "1                    26.161290               67.161290             82.806452   \n",
       "2                    17.071429               64.000000             76.035714   \n",
       "3                    21.000000               61.322581             73.225806   \n",
       "4                    24.200000               31.866667             72.466667   \n",
       "5                    20.935484               23.354839             73.225806   \n",
       "6                    18.133333               29.866667             72.300000   \n",
       "7                    19.096774               33.354839             75.967742   \n",
       "8                    16.806452               24.032258             69.967742   \n",
       "9                    21.033333               32.600000             69.233333   \n",
       "10                   24.612903               34.580645             71.645161   \n",
       "11                   21.133333               40.566667             80.600000   \n",
       "12                   24.096774               81.903226             88.580645   \n",
       "\n",
       "      monthly_avg_precipMM  monthly_avg_tempC  monthly_avg_visibility  \\\n",
       "date                                                                    \n",
       "1                 0.290323           1.290323                8.322581   \n",
       "2                 0.067857          -1.535714                9.750000   \n",
       "3                 0.222581           3.225806                9.096774   \n",
       "4                 0.506667          17.433333                9.700000   \n",
       "5                 0.919355          21.483871                9.645161   \n",
       "6                 0.396667          22.233333                9.466667   \n",
       "7                 1.583871          24.483871                9.354839   \n",
       "8                 0.941935          24.677419                9.806452   \n",
       "9                 0.460000          20.200000                9.533333   \n",
       "10                0.270968          14.451613                9.903226   \n",
       "11                0.083333           6.266667                9.400000   \n",
       "12                0.458065           1.838710                8.419355   \n",
       "\n",
       "      monthly_avg_windspeedKmph  \n",
       "date                             \n",
       "1                     16.612903  \n",
       "2                     11.642857  \n",
       "3                     14.032258  \n",
       "4                     15.733333  \n",
       "5                     13.129032  \n",
       "6                     11.900000  \n",
       "7                     12.225806  \n",
       "8                     10.677419  \n",
       "9                     13.233333  \n",
       "10                    15.290323  \n",
       "11                    12.800000  \n",
       "12                    15.258065  "
      ]
     },
     "execution_count": 499,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "weather_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 500,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "DtSkSlatTVGn"
   },
   "outputs": [],
   "source": [
    "weather_data.to_csv('MonthlyWeatherData.csv') "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 501,
   "metadata": {},
   "outputs": [],
   "source": [
    "weather_data=weather_data.round(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 502,
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>monthly_avg_maxtemp</th>\n",
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       "      <th>monthly_avg_precipMM</th>\n",
       "      <th>monthly_avg_tempC</th>\n",
       "      <th>monthly_avg_visibility</th>\n",
       "      <th>monthly_avg_windspeedKmph</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>8</th>\n",
       "      <td>24.68</td>\n",
       "      <td>15.16</td>\n",
       "      <td>0.00</td>\n",
       "      <td>20.06</td>\n",
       "      <td>20.42</td>\n",
       "      <td>19.81</td>\n",
       "      <td>16.81</td>\n",
       "      <td>24.03</td>\n",
       "      <td>69.97</td>\n",
       "      <td>0.94</td>\n",
       "      <td>24.68</td>\n",
       "      <td>9.81</td>\n",
       "      <td>10.68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>20.20</td>\n",
       "      <td>11.47</td>\n",
       "      <td>0.00</td>\n",
       "      <td>14.73</td>\n",
       "      <td>15.77</td>\n",
       "      <td>14.73</td>\n",
       "      <td>21.03</td>\n",
       "      <td>32.60</td>\n",
       "      <td>69.23</td>\n",
       "      <td>0.46</td>\n",
       "      <td>20.20</td>\n",
       "      <td>9.53</td>\n",
       "      <td>13.23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>14.45</td>\n",
       "      <td>6.97</td>\n",
       "      <td>0.00</td>\n",
       "      <td>8.19</td>\n",
       "      <td>10.06</td>\n",
       "      <td>8.19</td>\n",
       "      <td>24.61</td>\n",
       "      <td>34.58</td>\n",
       "      <td>71.65</td>\n",
       "      <td>0.27</td>\n",
       "      <td>14.45</td>\n",
       "      <td>9.90</td>\n",
       "      <td>15.29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>6.27</td>\n",
       "      <td>1.67</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.77</td>\n",
       "      <td>3.70</td>\n",
       "      <td>0.77</td>\n",
       "      <td>21.13</td>\n",
       "      <td>40.57</td>\n",
       "      <td>80.60</td>\n",
       "      <td>0.08</td>\n",
       "      <td>6.27</td>\n",
       "      <td>9.40</td>\n",
       "      <td>12.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>1.84</td>\n",
       "      <td>-1.10</td>\n",
       "      <td>0.17</td>\n",
       "      <td>-3.61</td>\n",
       "      <td>0.45</td>\n",
       "      <td>-3.61</td>\n",
       "      <td>24.10</td>\n",
       "      <td>81.90</td>\n",
       "      <td>88.58</td>\n",
       "      <td>0.46</td>\n",
       "      <td>1.84</td>\n",
       "      <td>8.42</td>\n",
       "      <td>15.26</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      monthly_avg_maxtemp  monthly_avg_mintemp  monthly_avg_totalSnow_cm  \\\n",
       "date                                                                       \n",
       "8                   24.68                15.16                      0.00   \n",
       "9                   20.20                11.47                      0.00   \n",
       "10                  14.45                 6.97                      0.00   \n",
       "11                   6.27                 1.67                      0.01   \n",
       "12                   1.84                -1.10                      0.17   \n",
       "\n",
       "      monthly_avg_FeelsLikeC  monthly_avg_HeatIndexC  monthly_avg_WindChillC  \\\n",
       "date                                                                           \n",
       "8                      20.06                   20.42                   19.81   \n",
       "9                      14.73                   15.77                   14.73   \n",
       "10                      8.19                   10.06                    8.19   \n",
       "11                      0.77                    3.70                    0.77   \n",
       "12                     -3.61                    0.45                   -3.61   \n",
       "\n",
       "      monthly_avg_WindGustKmph  monthly_avg_cloudcover  monthly_avg_humidity  \\\n",
       "date                                                                           \n",
       "8                        16.81                   24.03                 69.97   \n",
       "9                        21.03                   32.60                 69.23   \n",
       "10                       24.61                   34.58                 71.65   \n",
       "11                       21.13                   40.57                 80.60   \n",
       "12                       24.10                   81.90                 88.58   \n",
       "\n",
       "      monthly_avg_precipMM  monthly_avg_tempC  monthly_avg_visibility  \\\n",
       "date                                                                    \n",
       "8                     0.94              24.68                    9.81   \n",
       "9                     0.46              20.20                    9.53   \n",
       "10                    0.27              14.45                    9.90   \n",
       "11                    0.08               6.27                    9.40   \n",
       "12                    0.46               1.84                    8.42   \n",
       "\n",
       "      monthly_avg_windspeedKmph  \n",
       "date                             \n",
       "8                         10.68  \n",
       "9                         13.23  \n",
       "10                        15.29  \n",
       "11                        12.80  \n",
       "12                        15.26  "
      ]
     },
     "execution_count": 502,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "weather_data.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 503,
   "metadata": {},
   "outputs": [],
   "source": [
    "dates=['2018-01-01', '2018-01-02', '2018-01-03', '2018-01-04',\n",
    "       '2018-01-05', '2018-01-06', '2018-01-07', '2018-01-08',\n",
    "       '2018-01-09', '2018-01-10', '2018-01-11', '2018-01-12']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 504,
   "metadata": {},
   "outputs": [],
   "source": [
    "weather_data[\"date\"]=dates"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 505,
   "metadata": {},
   "outputs": [],
   "source": [
    "weather_data[\"date\"]=pd.to_datetime(weather_data[\"date\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 506,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>monthly_avg_maxtemp</th>\n",
       "      <th>monthly_avg_mintemp</th>\n",
       "      <th>monthly_avg_totalSnow_cm</th>\n",
       "      <th>monthly_avg_FeelsLikeC</th>\n",
       "      <th>monthly_avg_HeatIndexC</th>\n",
       "      <th>monthly_avg_WindChillC</th>\n",
       "      <th>monthly_avg_WindGustKmph</th>\n",
       "      <th>monthly_avg_cloudcover</th>\n",
       "      <th>monthly_avg_humidity</th>\n",
       "      <th>monthly_avg_precipMM</th>\n",
       "      <th>monthly_avg_tempC</th>\n",
       "      <th>monthly_avg_visibility</th>\n",
       "      <th>monthly_avg_windspeedKmph</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",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.29</td>\n",
       "      <td>-2.13</td>\n",
       "      <td>0.06</td>\n",
       "      <td>-4.84</td>\n",
       "      <td>-0.32</td>\n",
       "      <td>-4.84</td>\n",
       "      <td>26.16</td>\n",
       "      <td>67.16</td>\n",
       "      <td>82.81</td>\n",
       "      <td>0.29</td>\n",
       "      <td>1.29</td>\n",
       "      <td>8.32</td>\n",
       "      <td>16.61</td>\n",
       "      <td>2018-01-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-1.54</td>\n",
       "      <td>-5.04</td>\n",
       "      <td>0.04</td>\n",
       "      <td>-7.61</td>\n",
       "      <td>-3.43</td>\n",
       "      <td>-7.61</td>\n",
       "      <td>17.07</td>\n",
       "      <td>64.00</td>\n",
       "      <td>76.04</td>\n",
       "      <td>0.07</td>\n",
       "      <td>-1.54</td>\n",
       "      <td>9.75</td>\n",
       "      <td>11.64</td>\n",
       "      <td>2018-01-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3.23</td>\n",
       "      <td>-2.90</td>\n",
       "      <td>0.07</td>\n",
       "      <td>-4.03</td>\n",
       "      <td>-0.10</td>\n",
       "      <td>-4.03</td>\n",
       "      <td>21.00</td>\n",
       "      <td>61.32</td>\n",
       "      <td>73.23</td>\n",
       "      <td>0.22</td>\n",
       "      <td>3.23</td>\n",
       "      <td>9.10</td>\n",
       "      <td>14.03</td>\n",
       "      <td>2018-01-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>17.43</td>\n",
       "      <td>6.73</td>\n",
       "      <td>0.00</td>\n",
       "      <td>10.37</td>\n",
       "      <td>11.90</td>\n",
       "      <td>10.37</td>\n",
       "      <td>24.20</td>\n",
       "      <td>31.87</td>\n",
       "      <td>72.47</td>\n",
       "      <td>0.51</td>\n",
       "      <td>17.43</td>\n",
       "      <td>9.70</td>\n",
       "      <td>15.73</td>\n",
       "      <td>2018-01-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>21.48</td>\n",
       "      <td>10.45</td>\n",
       "      <td>0.00</td>\n",
       "      <td>15.42</td>\n",
       "      <td>16.32</td>\n",
       "      <td>15.42</td>\n",
       "      <td>20.94</td>\n",
       "      <td>23.35</td>\n",
       "      <td>73.23</td>\n",
       "      <td>0.92</td>\n",
       "      <td>21.48</td>\n",
       "      <td>9.65</td>\n",
       "      <td>13.13</td>\n",
       "      <td>2018-01-05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>22.23</td>\n",
       "      <td>11.90</td>\n",
       "      <td>0.00</td>\n",
       "      <td>17.10</td>\n",
       "      <td>17.87</td>\n",
       "      <td>17.10</td>\n",
       "      <td>18.13</td>\n",
       "      <td>29.87</td>\n",
       "      <td>72.30</td>\n",
       "      <td>0.40</td>\n",
       "      <td>22.23</td>\n",
       "      <td>9.47</td>\n",
       "      <td>11.90</td>\n",
       "      <td>2018-01-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>24.48</td>\n",
       "      <td>14.97</td>\n",
       "      <td>0.00</td>\n",
       "      <td>19.90</td>\n",
       "      <td>20.42</td>\n",
       "      <td>19.61</td>\n",
       "      <td>19.10</td>\n",
       "      <td>33.35</td>\n",
       "      <td>75.97</td>\n",
       "      <td>1.58</td>\n",
       "      <td>24.48</td>\n",
       "      <td>9.35</td>\n",
       "      <td>12.23</td>\n",
       "      <td>2018-01-07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>24.68</td>\n",
       "      <td>15.16</td>\n",
       "      <td>0.00</td>\n",
       "      <td>20.06</td>\n",
       "      <td>20.42</td>\n",
       "      <td>19.81</td>\n",
       "      <td>16.81</td>\n",
       "      <td>24.03</td>\n",
       "      <td>69.97</td>\n",
       "      <td>0.94</td>\n",
       "      <td>24.68</td>\n",
       "      <td>9.81</td>\n",
       "      <td>10.68</td>\n",
       "      <td>2018-01-08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>20.20</td>\n",
       "      <td>11.47</td>\n",
       "      <td>0.00</td>\n",
       "      <td>14.73</td>\n",
       "      <td>15.77</td>\n",
       "      <td>14.73</td>\n",
       "      <td>21.03</td>\n",
       "      <td>32.60</td>\n",
       "      <td>69.23</td>\n",
       "      <td>0.46</td>\n",
       "      <td>20.20</td>\n",
       "      <td>9.53</td>\n",
       "      <td>13.23</td>\n",
       "      <td>2018-01-09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>14.45</td>\n",
       "      <td>6.97</td>\n",
       "      <td>0.00</td>\n",
       "      <td>8.19</td>\n",
       "      <td>10.06</td>\n",
       "      <td>8.19</td>\n",
       "      <td>24.61</td>\n",
       "      <td>34.58</td>\n",
       "      <td>71.65</td>\n",
       "      <td>0.27</td>\n",
       "      <td>14.45</td>\n",
       "      <td>9.90</td>\n",
       "      <td>15.29</td>\n",
       "      <td>2018-01-10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>6.27</td>\n",
       "      <td>1.67</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.77</td>\n",
       "      <td>3.70</td>\n",
       "      <td>0.77</td>\n",
       "      <td>21.13</td>\n",
       "      <td>40.57</td>\n",
       "      <td>80.60</td>\n",
       "      <td>0.08</td>\n",
       "      <td>6.27</td>\n",
       "      <td>9.40</td>\n",
       "      <td>12.80</td>\n",
       "      <td>2018-01-11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>1.84</td>\n",
       "      <td>-1.10</td>\n",
       "      <td>0.17</td>\n",
       "      <td>-3.61</td>\n",
       "      <td>0.45</td>\n",
       "      <td>-3.61</td>\n",
       "      <td>24.10</td>\n",
       "      <td>81.90</td>\n",
       "      <td>88.58</td>\n",
       "      <td>0.46</td>\n",
       "      <td>1.84</td>\n",
       "      <td>8.42</td>\n",
       "      <td>15.26</td>\n",
       "      <td>2018-01-12</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      monthly_avg_maxtemp  monthly_avg_mintemp  monthly_avg_totalSnow_cm  \\\n",
       "date                                                                       \n",
       "1                    1.29                -2.13                      0.06   \n",
       "2                   -1.54                -5.04                      0.04   \n",
       "3                    3.23                -2.90                      0.07   \n",
       "4                   17.43                 6.73                      0.00   \n",
       "5                   21.48                10.45                      0.00   \n",
       "6                   22.23                11.90                      0.00   \n",
       "7                   24.48                14.97                      0.00   \n",
       "8                   24.68                15.16                      0.00   \n",
       "9                   20.20                11.47                      0.00   \n",
       "10                  14.45                 6.97                      0.00   \n",
       "11                   6.27                 1.67                      0.01   \n",
       "12                   1.84                -1.10                      0.17   \n",
       "\n",
       "      monthly_avg_FeelsLikeC  monthly_avg_HeatIndexC  monthly_avg_WindChillC  \\\n",
       "date                                                                           \n",
       "1                      -4.84                   -0.32                   -4.84   \n",
       "2                      -7.61                   -3.43                   -7.61   \n",
       "3                      -4.03                   -0.10                   -4.03   \n",
       "4                      10.37                   11.90                   10.37   \n",
       "5                      15.42                   16.32                   15.42   \n",
       "6                      17.10                   17.87                   17.10   \n",
       "7                      19.90                   20.42                   19.61   \n",
       "8                      20.06                   20.42                   19.81   \n",
       "9                      14.73                   15.77                   14.73   \n",
       "10                      8.19                   10.06                    8.19   \n",
       "11                      0.77                    3.70                    0.77   \n",
       "12                     -3.61                    0.45                   -3.61   \n",
       "\n",
       "      monthly_avg_WindGustKmph  monthly_avg_cloudcover  monthly_avg_humidity  \\\n",
       "date                                                                           \n",
       "1                        26.16                   67.16                 82.81   \n",
       "2                        17.07                   64.00                 76.04   \n",
       "3                        21.00                   61.32                 73.23   \n",
       "4                        24.20                   31.87                 72.47   \n",
       "5                        20.94                   23.35                 73.23   \n",
       "6                        18.13                   29.87                 72.30   \n",
       "7                        19.10                   33.35                 75.97   \n",
       "8                        16.81                   24.03                 69.97   \n",
       "9                        21.03                   32.60                 69.23   \n",
       "10                       24.61                   34.58                 71.65   \n",
       "11                       21.13                   40.57                 80.60   \n",
       "12                       24.10                   81.90                 88.58   \n",
       "\n",
       "      monthly_avg_precipMM  monthly_avg_tempC  monthly_avg_visibility  \\\n",
       "date                                                                    \n",
       "1                     0.29               1.29                    8.32   \n",
       "2                     0.07              -1.54                    9.75   \n",
       "3                     0.22               3.23                    9.10   \n",
       "4                     0.51              17.43                    9.70   \n",
       "5                     0.92              21.48                    9.65   \n",
       "6                     0.40              22.23                    9.47   \n",
       "7                     1.58              24.48                    9.35   \n",
       "8                     0.94              24.68                    9.81   \n",
       "9                     0.46              20.20                    9.53   \n",
       "10                    0.27              14.45                    9.90   \n",
       "11                    0.08               6.27                    9.40   \n",
       "12                    0.46               1.84                    8.42   \n",
       "\n",
       "      monthly_avg_windspeedKmph       date  \n",
       "date                                        \n",
       "1                         16.61 2018-01-01  \n",
       "2                         11.64 2018-01-02  \n",
       "3                         14.03 2018-01-03  \n",
       "4                         15.73 2018-01-04  \n",
       "5                         13.13 2018-01-05  \n",
       "6                         11.90 2018-01-06  \n",
       "7                         12.23 2018-01-07  \n",
       "8                         10.68 2018-01-08  \n",
       "9                         13.23 2018-01-09  \n",
       "10                        15.29 2018-01-10  \n",
       "11                        12.80 2018-01-11  \n",
       "12                        15.26 2018-01-12  "
      ]
     },
     "execution_count": 506,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "weather_data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## manually checking if the months has a sunday or saturday , along with a holiday and entering it "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 507,
   "metadata": {},
   "outputs": [],
   "source": [
    "weather_data[\"ishol/week\"]=[9,8,9,10,11,9,9,9,10,8,9,12]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 508,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>monthly_avg_maxtemp</th>\n",
       "      <th>monthly_avg_mintemp</th>\n",
       "      <th>monthly_avg_totalSnow_cm</th>\n",
       "      <th>monthly_avg_FeelsLikeC</th>\n",
       "      <th>monthly_avg_HeatIndexC</th>\n",
       "      <th>monthly_avg_WindChillC</th>\n",
       "      <th>monthly_avg_WindGustKmph</th>\n",
       "      <th>monthly_avg_cloudcover</th>\n",
       "      <th>monthly_avg_humidity</th>\n",
       "      <th>monthly_avg_precipMM</th>\n",
       "      <th>monthly_avg_tempC</th>\n",
       "      <th>monthly_avg_visibility</th>\n",
       "      <th>monthly_avg_windspeedKmph</th>\n",
       "      <th>date</th>\n",
       "      <th>ishol/week</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",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.29</td>\n",
       "      <td>-2.13</td>\n",
       "      <td>0.06</td>\n",
       "      <td>-4.84</td>\n",
       "      <td>-0.32</td>\n",
       "      <td>-4.84</td>\n",
       "      <td>26.16</td>\n",
       "      <td>67.16</td>\n",
       "      <td>82.81</td>\n",
       "      <td>0.29</td>\n",
       "      <td>1.29</td>\n",
       "      <td>8.32</td>\n",
       "      <td>16.61</td>\n",
       "      <td>2018-01-01</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-1.54</td>\n",
       "      <td>-5.04</td>\n",
       "      <td>0.04</td>\n",
       "      <td>-7.61</td>\n",
       "      <td>-3.43</td>\n",
       "      <td>-7.61</td>\n",
       "      <td>17.07</td>\n",
       "      <td>64.00</td>\n",
       "      <td>76.04</td>\n",
       "      <td>0.07</td>\n",
       "      <td>-1.54</td>\n",
       "      <td>9.75</td>\n",
       "      <td>11.64</td>\n",
       "      <td>2018-01-02</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3.23</td>\n",
       "      <td>-2.90</td>\n",
       "      <td>0.07</td>\n",
       "      <td>-4.03</td>\n",
       "      <td>-0.10</td>\n",
       "      <td>-4.03</td>\n",
       "      <td>21.00</td>\n",
       "      <td>61.32</td>\n",
       "      <td>73.23</td>\n",
       "      <td>0.22</td>\n",
       "      <td>3.23</td>\n",
       "      <td>9.10</td>\n",
       "      <td>14.03</td>\n",
       "      <td>2018-01-03</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>17.43</td>\n",
       "      <td>6.73</td>\n",
       "      <td>0.00</td>\n",
       "      <td>10.37</td>\n",
       "      <td>11.90</td>\n",
       "      <td>10.37</td>\n",
       "      <td>24.20</td>\n",
       "      <td>31.87</td>\n",
       "      <td>72.47</td>\n",
       "      <td>0.51</td>\n",
       "      <td>17.43</td>\n",
       "      <td>9.70</td>\n",
       "      <td>15.73</td>\n",
       "      <td>2018-01-04</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>21.48</td>\n",
       "      <td>10.45</td>\n",
       "      <td>0.00</td>\n",
       "      <td>15.42</td>\n",
       "      <td>16.32</td>\n",
       "      <td>15.42</td>\n",
       "      <td>20.94</td>\n",
       "      <td>23.35</td>\n",
       "      <td>73.23</td>\n",
       "      <td>0.92</td>\n",
       "      <td>21.48</td>\n",
       "      <td>9.65</td>\n",
       "      <td>13.13</td>\n",
       "      <td>2018-01-05</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>22.23</td>\n",
       "      <td>11.90</td>\n",
       "      <td>0.00</td>\n",
       "      <td>17.10</td>\n",
       "      <td>17.87</td>\n",
       "      <td>17.10</td>\n",
       "      <td>18.13</td>\n",
       "      <td>29.87</td>\n",
       "      <td>72.30</td>\n",
       "      <td>0.40</td>\n",
       "      <td>22.23</td>\n",
       "      <td>9.47</td>\n",
       "      <td>11.90</td>\n",
       "      <td>2018-01-06</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>24.48</td>\n",
       "      <td>14.97</td>\n",
       "      <td>0.00</td>\n",
       "      <td>19.90</td>\n",
       "      <td>20.42</td>\n",
       "      <td>19.61</td>\n",
       "      <td>19.10</td>\n",
       "      <td>33.35</td>\n",
       "      <td>75.97</td>\n",
       "      <td>1.58</td>\n",
       "      <td>24.48</td>\n",
       "      <td>9.35</td>\n",
       "      <td>12.23</td>\n",
       "      <td>2018-01-07</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>24.68</td>\n",
       "      <td>15.16</td>\n",
       "      <td>0.00</td>\n",
       "      <td>20.06</td>\n",
       "      <td>20.42</td>\n",
       "      <td>19.81</td>\n",
       "      <td>16.81</td>\n",
       "      <td>24.03</td>\n",
       "      <td>69.97</td>\n",
       "      <td>0.94</td>\n",
       "      <td>24.68</td>\n",
       "      <td>9.81</td>\n",
       "      <td>10.68</td>\n",
       "      <td>2018-01-08</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>20.20</td>\n",
       "      <td>11.47</td>\n",
       "      <td>0.00</td>\n",
       "      <td>14.73</td>\n",
       "      <td>15.77</td>\n",
       "      <td>14.73</td>\n",
       "      <td>21.03</td>\n",
       "      <td>32.60</td>\n",
       "      <td>69.23</td>\n",
       "      <td>0.46</td>\n",
       "      <td>20.20</td>\n",
       "      <td>9.53</td>\n",
       "      <td>13.23</td>\n",
       "      <td>2018-01-09</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>14.45</td>\n",
       "      <td>6.97</td>\n",
       "      <td>0.00</td>\n",
       "      <td>8.19</td>\n",
       "      <td>10.06</td>\n",
       "      <td>8.19</td>\n",
       "      <td>24.61</td>\n",
       "      <td>34.58</td>\n",
       "      <td>71.65</td>\n",
       "      <td>0.27</td>\n",
       "      <td>14.45</td>\n",
       "      <td>9.90</td>\n",
       "      <td>15.29</td>\n",
       "      <td>2018-01-10</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>6.27</td>\n",
       "      <td>1.67</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.77</td>\n",
       "      <td>3.70</td>\n",
       "      <td>0.77</td>\n",
       "      <td>21.13</td>\n",
       "      <td>40.57</td>\n",
       "      <td>80.60</td>\n",
       "      <td>0.08</td>\n",
       "      <td>6.27</td>\n",
       "      <td>9.40</td>\n",
       "      <td>12.80</td>\n",
       "      <td>2018-01-11</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>1.84</td>\n",
       "      <td>-1.10</td>\n",
       "      <td>0.17</td>\n",
       "      <td>-3.61</td>\n",
       "      <td>0.45</td>\n",
       "      <td>-3.61</td>\n",
       "      <td>24.10</td>\n",
       "      <td>81.90</td>\n",
       "      <td>88.58</td>\n",
       "      <td>0.46</td>\n",
       "      <td>1.84</td>\n",
       "      <td>8.42</td>\n",
       "      <td>15.26</td>\n",
       "      <td>2018-01-12</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      monthly_avg_maxtemp  monthly_avg_mintemp  monthly_avg_totalSnow_cm  \\\n",
       "date                                                                       \n",
       "1                    1.29                -2.13                      0.06   \n",
       "2                   -1.54                -5.04                      0.04   \n",
       "3                    3.23                -2.90                      0.07   \n",
       "4                   17.43                 6.73                      0.00   \n",
       "5                   21.48                10.45                      0.00   \n",
       "6                   22.23                11.90                      0.00   \n",
       "7                   24.48                14.97                      0.00   \n",
       "8                   24.68                15.16                      0.00   \n",
       "9                   20.20                11.47                      0.00   \n",
       "10                  14.45                 6.97                      0.00   \n",
       "11                   6.27                 1.67                      0.01   \n",
       "12                   1.84                -1.10                      0.17   \n",
       "\n",
       "      monthly_avg_FeelsLikeC  monthly_avg_HeatIndexC  monthly_avg_WindChillC  \\\n",
       "date                                                                           \n",
       "1                      -4.84                   -0.32                   -4.84   \n",
       "2                      -7.61                   -3.43                   -7.61   \n",
       "3                      -4.03                   -0.10                   -4.03   \n",
       "4                      10.37                   11.90                   10.37   \n",
       "5                      15.42                   16.32                   15.42   \n",
       "6                      17.10                   17.87                   17.10   \n",
       "7                      19.90                   20.42                   19.61   \n",
       "8                      20.06                   20.42                   19.81   \n",
       "9                      14.73                   15.77                   14.73   \n",
       "10                      8.19                   10.06                    8.19   \n",
       "11                      0.77                    3.70                    0.77   \n",
       "12                     -3.61                    0.45                   -3.61   \n",
       "\n",
       "      monthly_avg_WindGustKmph  monthly_avg_cloudcover  monthly_avg_humidity  \\\n",
       "date                                                                           \n",
       "1                        26.16                   67.16                 82.81   \n",
       "2                        17.07                   64.00                 76.04   \n",
       "3                        21.00                   61.32                 73.23   \n",
       "4                        24.20                   31.87                 72.47   \n",
       "5                        20.94                   23.35                 73.23   \n",
       "6                        18.13                   29.87                 72.30   \n",
       "7                        19.10                   33.35                 75.97   \n",
       "8                        16.81                   24.03                 69.97   \n",
       "9                        21.03                   32.60                 69.23   \n",
       "10                       24.61                   34.58                 71.65   \n",
       "11                       21.13                   40.57                 80.60   \n",
       "12                       24.10                   81.90                 88.58   \n",
       "\n",
       "      monthly_avg_precipMM  monthly_avg_tempC  monthly_avg_visibility  \\\n",
       "date                                                                    \n",
       "1                     0.29               1.29                    8.32   \n",
       "2                     0.07              -1.54                    9.75   \n",
       "3                     0.22               3.23                    9.10   \n",
       "4                     0.51              17.43                    9.70   \n",
       "5                     0.92              21.48                    9.65   \n",
       "6                     0.40              22.23                    9.47   \n",
       "7                     1.58              24.48                    9.35   \n",
       "8                     0.94              24.68                    9.81   \n",
       "9                     0.46              20.20                    9.53   \n",
       "10                    0.27              14.45                    9.90   \n",
       "11                    0.08               6.27                    9.40   \n",
       "12                    0.46               1.84                    8.42   \n",
       "\n",
       "      monthly_avg_windspeedKmph       date  ishol/week  \n",
       "date                                                    \n",
       "1                         16.61 2018-01-01           9  \n",
       "2                         11.64 2018-01-02           8  \n",
       "3                         14.03 2018-01-03           9  \n",
       "4                         15.73 2018-01-04          10  \n",
       "5                         13.13 2018-01-05          11  \n",
       "6                         11.90 2018-01-06           9  \n",
       "7                         12.23 2018-01-07           9  \n",
       "8                         10.68 2018-01-08           9  \n",
       "9                         13.23 2018-01-09          10  \n",
       "10                        15.29 2018-01-10           8  \n",
       "11                        12.80 2018-01-11           9  \n",
       "12                        15.26 2018-01-12          12  "
      ]
     },
     "execution_count": 508,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "weather_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 509,
   "metadata": {},
   "outputs": [],
   "source": [
    "def avgtemp(max,min):\n",
    "  return (max+min)/2\n",
    "\n",
    "weather_data[\"monthly_Avgtemp\"] =avgtemp(weather_data['monthly_avg_maxtemp'],weather_data['monthly_avg_mintemp']) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 510,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>monthly_avg_maxtemp</th>\n",
       "      <th>monthly_avg_mintemp</th>\n",
       "      <th>monthly_avg_totalSnow_cm</th>\n",
       "      <th>monthly_avg_FeelsLikeC</th>\n",
       "      <th>monthly_avg_HeatIndexC</th>\n",
       "      <th>monthly_avg_WindChillC</th>\n",
       "      <th>monthly_avg_WindGustKmph</th>\n",
       "      <th>monthly_avg_cloudcover</th>\n",
       "      <th>monthly_avg_humidity</th>\n",
       "      <th>monthly_avg_precipMM</th>\n",
       "      <th>monthly_avg_tempC</th>\n",
       "      <th>monthly_avg_visibility</th>\n",
       "      <th>monthly_avg_windspeedKmph</th>\n",
       "      <th>date</th>\n",
       "      <th>ishol/week</th>\n",
       "      <th>monthly_Avgtemp</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",
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       "      <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>1</th>\n",
       "      <td>1.29</td>\n",
       "      <td>-2.13</td>\n",
       "      <td>0.06</td>\n",
       "      <td>-4.84</td>\n",
       "      <td>-0.32</td>\n",
       "      <td>-4.84</td>\n",
       "      <td>26.16</td>\n",
       "      <td>67.16</td>\n",
       "      <td>82.81</td>\n",
       "      <td>0.29</td>\n",
       "      <td>1.29</td>\n",
       "      <td>8.32</td>\n",
       "      <td>16.61</td>\n",
       "      <td>2018-01-01</td>\n",
       "      <td>9</td>\n",
       "      <td>-0.420</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-1.54</td>\n",
       "      <td>-5.04</td>\n",
       "      <td>0.04</td>\n",
       "      <td>-7.61</td>\n",
       "      <td>-3.43</td>\n",
       "      <td>-7.61</td>\n",
       "      <td>17.07</td>\n",
       "      <td>64.00</td>\n",
       "      <td>76.04</td>\n",
       "      <td>0.07</td>\n",
       "      <td>-1.54</td>\n",
       "      <td>9.75</td>\n",
       "      <td>11.64</td>\n",
       "      <td>2018-01-02</td>\n",
       "      <td>8</td>\n",
       "      <td>-3.290</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3.23</td>\n",
       "      <td>-2.90</td>\n",
       "      <td>0.07</td>\n",
       "      <td>-4.03</td>\n",
       "      <td>-0.10</td>\n",
       "      <td>-4.03</td>\n",
       "      <td>21.00</td>\n",
       "      <td>61.32</td>\n",
       "      <td>73.23</td>\n",
       "      <td>0.22</td>\n",
       "      <td>3.23</td>\n",
       "      <td>9.10</td>\n",
       "      <td>14.03</td>\n",
       "      <td>2018-01-03</td>\n",
       "      <td>9</td>\n",
       "      <td>0.165</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>17.43</td>\n",
       "      <td>6.73</td>\n",
       "      <td>0.00</td>\n",
       "      <td>10.37</td>\n",
       "      <td>11.90</td>\n",
       "      <td>10.37</td>\n",
       "      <td>24.20</td>\n",
       "      <td>31.87</td>\n",
       "      <td>72.47</td>\n",
       "      <td>0.51</td>\n",
       "      <td>17.43</td>\n",
       "      <td>9.70</td>\n",
       "      <td>15.73</td>\n",
       "      <td>2018-01-04</td>\n",
       "      <td>10</td>\n",
       "      <td>12.080</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>21.48</td>\n",
       "      <td>10.45</td>\n",
       "      <td>0.00</td>\n",
       "      <td>15.42</td>\n",
       "      <td>16.32</td>\n",
       "      <td>15.42</td>\n",
       "      <td>20.94</td>\n",
       "      <td>23.35</td>\n",
       "      <td>73.23</td>\n",
       "      <td>0.92</td>\n",
       "      <td>21.48</td>\n",
       "      <td>9.65</td>\n",
       "      <td>13.13</td>\n",
       "      <td>2018-01-05</td>\n",
       "      <td>11</td>\n",
       "      <td>15.965</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>22.23</td>\n",
       "      <td>11.90</td>\n",
       "      <td>0.00</td>\n",
       "      <td>17.10</td>\n",
       "      <td>17.87</td>\n",
       "      <td>17.10</td>\n",
       "      <td>18.13</td>\n",
       "      <td>29.87</td>\n",
       "      <td>72.30</td>\n",
       "      <td>0.40</td>\n",
       "      <td>22.23</td>\n",
       "      <td>9.47</td>\n",
       "      <td>11.90</td>\n",
       "      <td>2018-01-06</td>\n",
       "      <td>9</td>\n",
       "      <td>17.065</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>24.48</td>\n",
       "      <td>14.97</td>\n",
       "      <td>0.00</td>\n",
       "      <td>19.90</td>\n",
       "      <td>20.42</td>\n",
       "      <td>19.61</td>\n",
       "      <td>19.10</td>\n",
       "      <td>33.35</td>\n",
       "      <td>75.97</td>\n",
       "      <td>1.58</td>\n",
       "      <td>24.48</td>\n",
       "      <td>9.35</td>\n",
       "      <td>12.23</td>\n",
       "      <td>2018-01-07</td>\n",
       "      <td>9</td>\n",
       "      <td>19.725</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>24.68</td>\n",
       "      <td>15.16</td>\n",
       "      <td>0.00</td>\n",
       "      <td>20.06</td>\n",
       "      <td>20.42</td>\n",
       "      <td>19.81</td>\n",
       "      <td>16.81</td>\n",
       "      <td>24.03</td>\n",
       "      <td>69.97</td>\n",
       "      <td>0.94</td>\n",
       "      <td>24.68</td>\n",
       "      <td>9.81</td>\n",
       "      <td>10.68</td>\n",
       "      <td>2018-01-08</td>\n",
       "      <td>9</td>\n",
       "      <td>19.920</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>20.20</td>\n",
       "      <td>11.47</td>\n",
       "      <td>0.00</td>\n",
       "      <td>14.73</td>\n",
       "      <td>15.77</td>\n",
       "      <td>14.73</td>\n",
       "      <td>21.03</td>\n",
       "      <td>32.60</td>\n",
       "      <td>69.23</td>\n",
       "      <td>0.46</td>\n",
       "      <td>20.20</td>\n",
       "      <td>9.53</td>\n",
       "      <td>13.23</td>\n",
       "      <td>2018-01-09</td>\n",
       "      <td>10</td>\n",
       "      <td>15.835</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>14.45</td>\n",
       "      <td>6.97</td>\n",
       "      <td>0.00</td>\n",
       "      <td>8.19</td>\n",
       "      <td>10.06</td>\n",
       "      <td>8.19</td>\n",
       "      <td>24.61</td>\n",
       "      <td>34.58</td>\n",
       "      <td>71.65</td>\n",
       "      <td>0.27</td>\n",
       "      <td>14.45</td>\n",
       "      <td>9.90</td>\n",
       "      <td>15.29</td>\n",
       "      <td>2018-01-10</td>\n",
       "      <td>8</td>\n",
       "      <td>10.710</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>6.27</td>\n",
       "      <td>1.67</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.77</td>\n",
       "      <td>3.70</td>\n",
       "      <td>0.77</td>\n",
       "      <td>21.13</td>\n",
       "      <td>40.57</td>\n",
       "      <td>80.60</td>\n",
       "      <td>0.08</td>\n",
       "      <td>6.27</td>\n",
       "      <td>9.40</td>\n",
       "      <td>12.80</td>\n",
       "      <td>2018-01-11</td>\n",
       "      <td>9</td>\n",
       "      <td>3.970</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>1.84</td>\n",
       "      <td>-1.10</td>\n",
       "      <td>0.17</td>\n",
       "      <td>-3.61</td>\n",
       "      <td>0.45</td>\n",
       "      <td>-3.61</td>\n",
       "      <td>24.10</td>\n",
       "      <td>81.90</td>\n",
       "      <td>88.58</td>\n",
       "      <td>0.46</td>\n",
       "      <td>1.84</td>\n",
       "      <td>8.42</td>\n",
       "      <td>15.26</td>\n",
       "      <td>2018-01-12</td>\n",
       "      <td>12</td>\n",
       "      <td>0.370</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      monthly_avg_maxtemp  monthly_avg_mintemp  monthly_avg_totalSnow_cm  \\\n",
       "date                                                                       \n",
       "1                    1.29                -2.13                      0.06   \n",
       "2                   -1.54                -5.04                      0.04   \n",
       "3                    3.23                -2.90                      0.07   \n",
       "4                   17.43                 6.73                      0.00   \n",
       "5                   21.48                10.45                      0.00   \n",
       "6                   22.23                11.90                      0.00   \n",
       "7                   24.48                14.97                      0.00   \n",
       "8                   24.68                15.16                      0.00   \n",
       "9                   20.20                11.47                      0.00   \n",
       "10                  14.45                 6.97                      0.00   \n",
       "11                   6.27                 1.67                      0.01   \n",
       "12                   1.84                -1.10                      0.17   \n",
       "\n",
       "      monthly_avg_FeelsLikeC  monthly_avg_HeatIndexC  monthly_avg_WindChillC  \\\n",
       "date                                                                           \n",
       "1                      -4.84                   -0.32                   -4.84   \n",
       "2                      -7.61                   -3.43                   -7.61   \n",
       "3                      -4.03                   -0.10                   -4.03   \n",
       "4                      10.37                   11.90                   10.37   \n",
       "5                      15.42                   16.32                   15.42   \n",
       "6                      17.10                   17.87                   17.10   \n",
       "7                      19.90                   20.42                   19.61   \n",
       "8                      20.06                   20.42                   19.81   \n",
       "9                      14.73                   15.77                   14.73   \n",
       "10                      8.19                   10.06                    8.19   \n",
       "11                      0.77                    3.70                    0.77   \n",
       "12                     -3.61                    0.45                   -3.61   \n",
       "\n",
       "      monthly_avg_WindGustKmph  monthly_avg_cloudcover  monthly_avg_humidity  \\\n",
       "date                                                                           \n",
       "1                        26.16                   67.16                 82.81   \n",
       "2                        17.07                   64.00                 76.04   \n",
       "3                        21.00                   61.32                 73.23   \n",
       "4                        24.20                   31.87                 72.47   \n",
       "5                        20.94                   23.35                 73.23   \n",
       "6                        18.13                   29.87                 72.30   \n",
       "7                        19.10                   33.35                 75.97   \n",
       "8                        16.81                   24.03                 69.97   \n",
       "9                        21.03                   32.60                 69.23   \n",
       "10                       24.61                   34.58                 71.65   \n",
       "11                       21.13                   40.57                 80.60   \n",
       "12                       24.10                   81.90                 88.58   \n",
       "\n",
       "      monthly_avg_precipMM  monthly_avg_tempC  monthly_avg_visibility  \\\n",
       "date                                                                    \n",
       "1                     0.29               1.29                    8.32   \n",
       "2                     0.07              -1.54                    9.75   \n",
       "3                     0.22               3.23                    9.10   \n",
       "4                     0.51              17.43                    9.70   \n",
       "5                     0.92              21.48                    9.65   \n",
       "6                     0.40              22.23                    9.47   \n",
       "7                     1.58              24.48                    9.35   \n",
       "8                     0.94              24.68                    9.81   \n",
       "9                     0.46              20.20                    9.53   \n",
       "10                    0.27              14.45                    9.90   \n",
       "11                    0.08               6.27                    9.40   \n",
       "12                    0.46               1.84                    8.42   \n",
       "\n",
       "      monthly_avg_windspeedKmph       date  ishol/week  monthly_Avgtemp  \n",
       "date                                                                     \n",
       "1                         16.61 2018-01-01           9           -0.420  \n",
       "2                         11.64 2018-01-02           8           -3.290  \n",
       "3                         14.03 2018-01-03           9            0.165  \n",
       "4                         15.73 2018-01-04          10           12.080  \n",
       "5                         13.13 2018-01-05          11           15.965  \n",
       "6                         11.90 2018-01-06           9           17.065  \n",
       "7                         12.23 2018-01-07           9           19.725  \n",
       "8                         10.68 2018-01-08           9           19.920  \n",
       "9                         13.23 2018-01-09          10           15.835  \n",
       "10                        15.29 2018-01-10           8           10.710  \n",
       "11                        12.80 2018-01-11           9            3.970  \n",
       "12                        15.26 2018-01-12          12            0.370  "
      ]
     },
     "execution_count": 510,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "weather_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 511,
   "metadata": {},
   "outputs": [],
   "source": [
    "weather_data.drop([\"monthly_avg_mintemp\",\"monthly_avg_totalSnow_cm\",\"monthly_avg_maxtemp\",\"monthly_avg_WindChillC\",\"monthly_avg_WindGustKmph\",\"monthly_avg_visibility\",\"monthly_avg_windspeedKmph\",],axis=1,inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 512,
   "metadata": {},
   "outputs": [],
   "source": [
    "weather_data.drop([\"monthly_avg_precipMM\"],axis=1,inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 513,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>monthly_avg_FeelsLikeC</th>\n",
       "      <th>monthly_avg_HeatIndexC</th>\n",
       "      <th>monthly_avg_cloudcover</th>\n",
       "      <th>monthly_avg_humidity</th>\n",
       "      <th>monthly_avg_tempC</th>\n",
       "      <th>date</th>\n",
       "      <th>ishol/week</th>\n",
       "      <th>monthly_Avgtemp</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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-4.84</td>\n",
       "      <td>-0.32</td>\n",
       "      <td>67.16</td>\n",
       "      <td>82.81</td>\n",
       "      <td>1.29</td>\n",
       "      <td>2018-01-01</td>\n",
       "      <td>9</td>\n",
       "      <td>-0.420</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-7.61</td>\n",
       "      <td>-3.43</td>\n",
       "      <td>64.00</td>\n",
       "      <td>76.04</td>\n",
       "      <td>-1.54</td>\n",
       "      <td>2018-01-02</td>\n",
       "      <td>8</td>\n",
       "      <td>-3.290</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-4.03</td>\n",
       "      <td>-0.10</td>\n",
       "      <td>61.32</td>\n",
       "      <td>73.23</td>\n",
       "      <td>3.23</td>\n",
       "      <td>2018-01-03</td>\n",
       "      <td>9</td>\n",
       "      <td>0.165</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10.37</td>\n",
       "      <td>11.90</td>\n",
       "      <td>31.87</td>\n",
       "      <td>72.47</td>\n",
       "      <td>17.43</td>\n",
       "      <td>2018-01-04</td>\n",
       "      <td>10</td>\n",
       "      <td>12.080</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>15.42</td>\n",
       "      <td>16.32</td>\n",
       "      <td>23.35</td>\n",
       "      <td>73.23</td>\n",
       "      <td>21.48</td>\n",
       "      <td>2018-01-05</td>\n",
       "      <td>11</td>\n",
       "      <td>15.965</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>17.10</td>\n",
       "      <td>17.87</td>\n",
       "      <td>29.87</td>\n",
       "      <td>72.30</td>\n",
       "      <td>22.23</td>\n",
       "      <td>2018-01-06</td>\n",
       "      <td>9</td>\n",
       "      <td>17.065</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>19.90</td>\n",
       "      <td>20.42</td>\n",
       "      <td>33.35</td>\n",
       "      <td>75.97</td>\n",
       "      <td>24.48</td>\n",
       "      <td>2018-01-07</td>\n",
       "      <td>9</td>\n",
       "      <td>19.725</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>20.06</td>\n",
       "      <td>20.42</td>\n",
       "      <td>24.03</td>\n",
       "      <td>69.97</td>\n",
       "      <td>24.68</td>\n",
       "      <td>2018-01-08</td>\n",
       "      <td>9</td>\n",
       "      <td>19.920</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>14.73</td>\n",
       "      <td>15.77</td>\n",
       "      <td>32.60</td>\n",
       "      <td>69.23</td>\n",
       "      <td>20.20</td>\n",
       "      <td>2018-01-09</td>\n",
       "      <td>10</td>\n",
       "      <td>15.835</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>8.19</td>\n",
       "      <td>10.06</td>\n",
       "      <td>34.58</td>\n",
       "      <td>71.65</td>\n",
       "      <td>14.45</td>\n",
       "      <td>2018-01-10</td>\n",
       "      <td>8</td>\n",
       "      <td>10.710</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0.77</td>\n",
       "      <td>3.70</td>\n",
       "      <td>40.57</td>\n",
       "      <td>80.60</td>\n",
       "      <td>6.27</td>\n",
       "      <td>2018-01-11</td>\n",
       "      <td>9</td>\n",
       "      <td>3.970</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>-3.61</td>\n",
       "      <td>0.45</td>\n",
       "      <td>81.90</td>\n",
       "      <td>88.58</td>\n",
       "      <td>1.84</td>\n",
       "      <td>2018-01-12</td>\n",
       "      <td>12</td>\n",
       "      <td>0.370</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      monthly_avg_FeelsLikeC  monthly_avg_HeatIndexC  monthly_avg_cloudcover  \\\n",
       "date                                                                           \n",
       "1                      -4.84                   -0.32                   67.16   \n",
       "2                      -7.61                   -3.43                   64.00   \n",
       "3                      -4.03                   -0.10                   61.32   \n",
       "4                      10.37                   11.90                   31.87   \n",
       "5                      15.42                   16.32                   23.35   \n",
       "6                      17.10                   17.87                   29.87   \n",
       "7                      19.90                   20.42                   33.35   \n",
       "8                      20.06                   20.42                   24.03   \n",
       "9                      14.73                   15.77                   32.60   \n",
       "10                      8.19                   10.06                   34.58   \n",
       "11                      0.77                    3.70                   40.57   \n",
       "12                     -3.61                    0.45                   81.90   \n",
       "\n",
       "      monthly_avg_humidity  monthly_avg_tempC       date  ishol/week  \\\n",
       "date                                                                   \n",
       "1                    82.81               1.29 2018-01-01           9   \n",
       "2                    76.04              -1.54 2018-01-02           8   \n",
       "3                    73.23               3.23 2018-01-03           9   \n",
       "4                    72.47              17.43 2018-01-04          10   \n",
       "5                    73.23              21.48 2018-01-05          11   \n",
       "6                    72.30              22.23 2018-01-06           9   \n",
       "7                    75.97              24.48 2018-01-07           9   \n",
       "8                    69.97              24.68 2018-01-08           9   \n",
       "9                    69.23              20.20 2018-01-09          10   \n",
       "10                   71.65              14.45 2018-01-10           8   \n",
       "11                   80.60               6.27 2018-01-11           9   \n",
       "12                   88.58               1.84 2018-01-12          12   \n",
       "\n",
       "      monthly_Avgtemp  \n",
       "date                   \n",
       "1              -0.420  \n",
       "2              -3.290  \n",
       "3               0.165  \n",
       "4              12.080  \n",
       "5              15.965  \n",
       "6              17.065  \n",
       "7              19.725  \n",
       "8              19.920  \n",
       "9              15.835  \n",
       "10             10.710  \n",
       "11              3.970  \n",
       "12              0.370  "
      ]
     },
     "execution_count": 513,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "weather_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 514,
   "metadata": {},
   "outputs": [],
   "source": [
    "# function to categorise the heat into 3 different levels ... 0=low( <= -1 ) , 1= normal ( >-1 , <=14 ), 2= high ( >14,<=27 )\n",
    "\n",
    "def cat_heat(data):\n",
    "    monthly_heatindex=[]\n",
    "    for heatindex in data[\"monthly_avg_HeatIndexC\"]:\n",
    "        if heatindex < -2:\n",
    "            monthly_heatindex.append(0)\n",
    "        elif heatindex >=-1 and heatindex<=14:\n",
    "            monthly_heatindex.append(1)\n",
    "        else:\n",
    "            monthly_heatindex.append(2)\n",
    "    return monthly_heatindex\n",
    "            "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 515,
   "metadata": {},
   "outputs": [],
   "source": [
    "heat_index=cat_heat(weather_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 516,
   "metadata": {},
   "outputs": [],
   "source": [
    "weather_data[\"monthly_avg_HeatIndexC\"]=heat_index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 517,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>monthly_avg_FeelsLikeC</th>\n",
       "      <th>monthly_avg_HeatIndexC</th>\n",
       "      <th>monthly_avg_cloudcover</th>\n",
       "      <th>monthly_avg_humidity</th>\n",
       "      <th>monthly_avg_tempC</th>\n",
       "      <th>date</th>\n",
       "      <th>ishol/week</th>\n",
       "      <th>monthly_Avgtemp</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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-4.84</td>\n",
       "      <td>1</td>\n",
       "      <td>67.16</td>\n",
       "      <td>82.81</td>\n",
       "      <td>1.29</td>\n",
       "      <td>2018-01-01</td>\n",
       "      <td>9</td>\n",
       "      <td>-0.420</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-7.61</td>\n",
       "      <td>0</td>\n",
       "      <td>64.00</td>\n",
       "      <td>76.04</td>\n",
       "      <td>-1.54</td>\n",
       "      <td>2018-01-02</td>\n",
       "      <td>8</td>\n",
       "      <td>-3.290</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-4.03</td>\n",
       "      <td>1</td>\n",
       "      <td>61.32</td>\n",
       "      <td>73.23</td>\n",
       "      <td>3.23</td>\n",
       "      <td>2018-01-03</td>\n",
       "      <td>9</td>\n",
       "      <td>0.165</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10.37</td>\n",
       "      <td>1</td>\n",
       "      <td>31.87</td>\n",
       "      <td>72.47</td>\n",
       "      <td>17.43</td>\n",
       "      <td>2018-01-04</td>\n",
       "      <td>10</td>\n",
       "      <td>12.080</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>15.42</td>\n",
       "      <td>2</td>\n",
       "      <td>23.35</td>\n",
       "      <td>73.23</td>\n",
       "      <td>21.48</td>\n",
       "      <td>2018-01-05</td>\n",
       "      <td>11</td>\n",
       "      <td>15.965</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>17.10</td>\n",
       "      <td>2</td>\n",
       "      <td>29.87</td>\n",
       "      <td>72.30</td>\n",
       "      <td>22.23</td>\n",
       "      <td>2018-01-06</td>\n",
       "      <td>9</td>\n",
       "      <td>17.065</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>19.90</td>\n",
       "      <td>2</td>\n",
       "      <td>33.35</td>\n",
       "      <td>75.97</td>\n",
       "      <td>24.48</td>\n",
       "      <td>2018-01-07</td>\n",
       "      <td>9</td>\n",
       "      <td>19.725</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>20.06</td>\n",
       "      <td>2</td>\n",
       "      <td>24.03</td>\n",
       "      <td>69.97</td>\n",
       "      <td>24.68</td>\n",
       "      <td>2018-01-08</td>\n",
       "      <td>9</td>\n",
       "      <td>19.920</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>14.73</td>\n",
       "      <td>2</td>\n",
       "      <td>32.60</td>\n",
       "      <td>69.23</td>\n",
       "      <td>20.20</td>\n",
       "      <td>2018-01-09</td>\n",
       "      <td>10</td>\n",
       "      <td>15.835</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>8.19</td>\n",
       "      <td>1</td>\n",
       "      <td>34.58</td>\n",
       "      <td>71.65</td>\n",
       "      <td>14.45</td>\n",
       "      <td>2018-01-10</td>\n",
       "      <td>8</td>\n",
       "      <td>10.710</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0.77</td>\n",
       "      <td>1</td>\n",
       "      <td>40.57</td>\n",
       "      <td>80.60</td>\n",
       "      <td>6.27</td>\n",
       "      <td>2018-01-11</td>\n",
       "      <td>9</td>\n",
       "      <td>3.970</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>-3.61</td>\n",
       "      <td>1</td>\n",
       "      <td>81.90</td>\n",
       "      <td>88.58</td>\n",
       "      <td>1.84</td>\n",
       "      <td>2018-01-12</td>\n",
       "      <td>12</td>\n",
       "      <td>0.370</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      monthly_avg_FeelsLikeC  monthly_avg_HeatIndexC  monthly_avg_cloudcover  \\\n",
       "date                                                                           \n",
       "1                      -4.84                       1                   67.16   \n",
       "2                      -7.61                       0                   64.00   \n",
       "3                      -4.03                       1                   61.32   \n",
       "4                      10.37                       1                   31.87   \n",
       "5                      15.42                       2                   23.35   \n",
       "6                      17.10                       2                   29.87   \n",
       "7                      19.90                       2                   33.35   \n",
       "8                      20.06                       2                   24.03   \n",
       "9                      14.73                       2                   32.60   \n",
       "10                      8.19                       1                   34.58   \n",
       "11                      0.77                       1                   40.57   \n",
       "12                     -3.61                       1                   81.90   \n",
       "\n",
       "      monthly_avg_humidity  monthly_avg_tempC       date  ishol/week  \\\n",
       "date                                                                   \n",
       "1                    82.81               1.29 2018-01-01           9   \n",
       "2                    76.04              -1.54 2018-01-02           8   \n",
       "3                    73.23               3.23 2018-01-03           9   \n",
       "4                    72.47              17.43 2018-01-04          10   \n",
       "5                    73.23              21.48 2018-01-05          11   \n",
       "6                    72.30              22.23 2018-01-06           9   \n",
       "7                    75.97              24.48 2018-01-07           9   \n",
       "8                    69.97              24.68 2018-01-08           9   \n",
       "9                    69.23              20.20 2018-01-09          10   \n",
       "10                   71.65              14.45 2018-01-10           8   \n",
       "11                   80.60               6.27 2018-01-11           9   \n",
       "12                   88.58               1.84 2018-01-12          12   \n",
       "\n",
       "      monthly_Avgtemp  \n",
       "date                   \n",
       "1              -0.420  \n",
       "2              -3.290  \n",
       "3               0.165  \n",
       "4              12.080  \n",
       "5              15.965  \n",
       "6              17.065  \n",
       "7              19.725  \n",
       "8              19.920  \n",
       "9              15.835  \n",
       "10             10.710  \n",
       "11              3.970  \n",
       "12              0.370  "
      ]
     },
     "execution_count": 517,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "weather_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 518,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "95"
      ]
     },
     "execution_count": 518,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "cloudcover=df_copy[\"cloudcover\"].unique()\n",
    "cloudcover.sort()\n",
    "len(cloudcover)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 519,
   "metadata": {},
   "outputs": [],
   "source": [
    "# function to categorise the heat into 3 different levels ... 0=clear sky( < 250 ) , 1= scattered clouds\n",
    "# ( >25 , <=50 ), 2= broken clouds ( >50,<=75 )  3= overcast/ cloudy (>75)\n",
    "\n",
    "\n",
    "def cat_cloud(data):\n",
    "    monthly_cloudcover=[]\n",
    "    for cloudcover in data[\"monthly_avg_cloudcover\"]:\n",
    "        if cloudcover < 25:\n",
    "            monthly_cloudcover.append(0)\n",
    "        elif cloudcover >=25 and cloudcover<50:\n",
    "            monthly_cloudcover.append(1)\n",
    "        elif cloudcover >=50 and cloudcover<75:\n",
    "            monthly_cloudcover.append(2)    \n",
    "        else:\n",
    "            monthly_cloudcover.append(3)\n",
    "    return monthly_cloudcover\n",
    "            "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 520,
   "metadata": {},
   "outputs": [],
   "source": [
    "weather_data[\"monthly_avg_cloudcover\"]=cat_cloud(weather_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 521,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>monthly_avg_FeelsLikeC</th>\n",
       "      <th>monthly_avg_HeatIndexC</th>\n",
       "      <th>monthly_avg_cloudcover</th>\n",
       "      <th>monthly_avg_humidity</th>\n",
       "      <th>monthly_avg_tempC</th>\n",
       "      <th>date</th>\n",
       "      <th>ishol/week</th>\n",
       "      <th>monthly_Avgtemp</th>\n",
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       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-4.84</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>82.81</td>\n",
       "      <td>1.29</td>\n",
       "      <td>2018-01-01</td>\n",
       "      <td>9</td>\n",
       "      <td>-0.420</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-7.61</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>76.04</td>\n",
       "      <td>-1.54</td>\n",
       "      <td>2018-01-02</td>\n",
       "      <td>8</td>\n",
       "      <td>-3.290</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-4.03</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>73.23</td>\n",
       "      <td>3.23</td>\n",
       "      <td>2018-01-03</td>\n",
       "      <td>9</td>\n",
       "      <td>0.165</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10.37</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>72.47</td>\n",
       "      <td>17.43</td>\n",
       "      <td>2018-01-04</td>\n",
       "      <td>10</td>\n",
       "      <td>12.080</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>15.42</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>73.23</td>\n",
       "      <td>21.48</td>\n",
       "      <td>2018-01-05</td>\n",
       "      <td>11</td>\n",
       "      <td>15.965</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>17.10</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>72.30</td>\n",
       "      <td>22.23</td>\n",
       "      <td>2018-01-06</td>\n",
       "      <td>9</td>\n",
       "      <td>17.065</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>19.90</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>75.97</td>\n",
       "      <td>24.48</td>\n",
       "      <td>2018-01-07</td>\n",
       "      <td>9</td>\n",
       "      <td>19.725</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>20.06</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>69.97</td>\n",
       "      <td>24.68</td>\n",
       "      <td>2018-01-08</td>\n",
       "      <td>9</td>\n",
       "      <td>19.920</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>14.73</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>69.23</td>\n",
       "      <td>20.20</td>\n",
       "      <td>2018-01-09</td>\n",
       "      <td>10</td>\n",
       "      <td>15.835</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>8.19</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>71.65</td>\n",
       "      <td>14.45</td>\n",
       "      <td>2018-01-10</td>\n",
       "      <td>8</td>\n",
       "      <td>10.710</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0.77</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>80.60</td>\n",
       "      <td>6.27</td>\n",
       "      <td>2018-01-11</td>\n",
       "      <td>9</td>\n",
       "      <td>3.970</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>-3.61</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>88.58</td>\n",
       "      <td>1.84</td>\n",
       "      <td>2018-01-12</td>\n",
       "      <td>12</td>\n",
       "      <td>0.370</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      monthly_avg_FeelsLikeC  monthly_avg_HeatIndexC  monthly_avg_cloudcover  \\\n",
       "date                                                                           \n",
       "1                      -4.84                       1                       2   \n",
       "2                      -7.61                       0                       2   \n",
       "3                      -4.03                       1                       2   \n",
       "4                      10.37                       1                       1   \n",
       "5                      15.42                       2                       0   \n",
       "6                      17.10                       2                       1   \n",
       "7                      19.90                       2                       1   \n",
       "8                      20.06                       2                       0   \n",
       "9                      14.73                       2                       1   \n",
       "10                      8.19                       1                       1   \n",
       "11                      0.77                       1                       1   \n",
       "12                     -3.61                       1                       3   \n",
       "\n",
       "      monthly_avg_humidity  monthly_avg_tempC       date  ishol/week  \\\n",
       "date                                                                   \n",
       "1                    82.81               1.29 2018-01-01           9   \n",
       "2                    76.04              -1.54 2018-01-02           8   \n",
       "3                    73.23               3.23 2018-01-03           9   \n",
       "4                    72.47              17.43 2018-01-04          10   \n",
       "5                    73.23              21.48 2018-01-05          11   \n",
       "6                    72.30              22.23 2018-01-06           9   \n",
       "7                    75.97              24.48 2018-01-07           9   \n",
       "8                    69.97              24.68 2018-01-08           9   \n",
       "9                    69.23              20.20 2018-01-09          10   \n",
       "10                   71.65              14.45 2018-01-10           8   \n",
       "11                   80.60               6.27 2018-01-11           9   \n",
       "12                   88.58               1.84 2018-01-12          12   \n",
       "\n",
       "      monthly_Avgtemp  \n",
       "date                   \n",
       "1              -0.420  \n",
       "2              -3.290  \n",
       "3               0.165  \n",
       "4              12.080  \n",
       "5              15.965  \n",
       "6              17.065  \n",
       "7              19.725  \n",
       "8              19.920  \n",
       "9              15.835  \n",
       "10             10.710  \n",
       "11              3.970  \n",
       "12              0.370  "
      ]
     },
     "execution_count": 521,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "weather_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 522,
   "metadata": {},
   "outputs": [],
   "source": [
    "weather_data.drop([\"monthly_avg_tempC\"],axis=1,inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 523,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>monthly_avg_FeelsLikeC</th>\n",
       "      <th>monthly_avg_HeatIndexC</th>\n",
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       "      <th>1</th>\n",
       "      <td>-4.84</td>\n",
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       "      <td>2</td>\n",
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       "      <td>2018-01-01</td>\n",
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       "      <th>3</th>\n",
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       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>73.23</td>\n",
       "      <td>2018-01-03</td>\n",
       "      <td>9</td>\n",
       "      <td>0.165</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10.37</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>72.47</td>\n",
       "      <td>2018-01-04</td>\n",
       "      <td>10</td>\n",
       "      <td>12.080</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>15.42</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>73.23</td>\n",
       "      <td>2018-01-05</td>\n",
       "      <td>11</td>\n",
       "      <td>15.965</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>17.10</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>72.30</td>\n",
       "      <td>2018-01-06</td>\n",
       "      <td>9</td>\n",
       "      <td>17.065</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>19.90</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>75.97</td>\n",
       "      <td>2018-01-07</td>\n",
       "      <td>9</td>\n",
       "      <td>19.725</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>20.06</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>69.97</td>\n",
       "      <td>2018-01-08</td>\n",
       "      <td>9</td>\n",
       "      <td>19.920</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>14.73</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>69.23</td>\n",
       "      <td>2018-01-09</td>\n",
       "      <td>10</td>\n",
       "      <td>15.835</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>8.19</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>71.65</td>\n",
       "      <td>2018-01-10</td>\n",
       "      <td>8</td>\n",
       "      <td>10.710</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0.77</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>80.60</td>\n",
       "      <td>2018-01-11</td>\n",
       "      <td>9</td>\n",
       "      <td>3.970</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>-3.61</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>88.58</td>\n",
       "      <td>2018-01-12</td>\n",
       "      <td>12</td>\n",
       "      <td>0.370</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      monthly_avg_FeelsLikeC  monthly_avg_HeatIndexC  monthly_avg_cloudcover  \\\n",
       "date                                                                           \n",
       "1                      -4.84                       1                       2   \n",
       "2                      -7.61                       0                       2   \n",
       "3                      -4.03                       1                       2   \n",
       "4                      10.37                       1                       1   \n",
       "5                      15.42                       2                       0   \n",
       "6                      17.10                       2                       1   \n",
       "7                      19.90                       2                       1   \n",
       "8                      20.06                       2                       0   \n",
       "9                      14.73                       2                       1   \n",
       "10                      8.19                       1                       1   \n",
       "11                      0.77                       1                       1   \n",
       "12                     -3.61                       1                       3   \n",
       "\n",
       "      monthly_avg_humidity       date  ishol/week  monthly_Avgtemp  \n",
       "date                                                                \n",
       "1                    82.81 2018-01-01           9           -0.420  \n",
       "2                    76.04 2018-01-02           8           -3.290  \n",
       "3                    73.23 2018-01-03           9            0.165  \n",
       "4                    72.47 2018-01-04          10           12.080  \n",
       "5                    73.23 2018-01-05          11           15.965  \n",
       "6                    72.30 2018-01-06           9           17.065  \n",
       "7                    75.97 2018-01-07           9           19.725  \n",
       "8                    69.97 2018-01-08           9           19.920  \n",
       "9                    69.23 2018-01-09          10           15.835  \n",
       "10                   71.65 2018-01-10           8           10.710  \n",
       "11                   80.60 2018-01-11           9            3.970  \n",
       "12                   88.58 2018-01-12          12            0.370  "
      ]
     },
     "execution_count": 523,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "weather_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 524,
   "metadata": {},
   "outputs": [],
   "source": [
    "# reindexing the data so that it becomes normal. We can use pd.reindex too but this works so why complicate it"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 525,
   "metadata": {},
   "outputs": [],
   "source": [
    "weather_data=weather_data[[\"date\",\"monthly_Avgtemp\",\"monthly_avg_FeelsLikeC\",\"monthly_avg_HeatIndexC\",\"monthly_avg_cloudcover\",\"monthly_avg_humidity\",\"ishol/week\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 526,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>9</td>\n",
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       "    <tr>\n",
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       "      <td>10.37</td>\n",
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       "      <td>72.47</td>\n",
       "      <td>10</td>\n",
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       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2018-01-05</td>\n",
       "      <td>15.965</td>\n",
       "      <td>15.42</td>\n",
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       "      <td>19.920</td>\n",
       "      <td>20.06</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>69.97</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2018-01-09</td>\n",
       "      <td>15.835</td>\n",
       "      <td>14.73</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>69.23</td>\n",
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       "      <td>-3.61</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>88.58</td>\n",
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       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           date  monthly_Avgtemp  monthly_avg_FeelsLikeC  \\\n",
       "date                                                       \n",
       "1    2018-01-01           -0.420                   -4.84   \n",
       "2    2018-01-02           -3.290                   -7.61   \n",
       "3    2018-01-03            0.165                   -4.03   \n",
       "4    2018-01-04           12.080                   10.37   \n",
       "5    2018-01-05           15.965                   15.42   \n",
       "6    2018-01-06           17.065                   17.10   \n",
       "7    2018-01-07           19.725                   19.90   \n",
       "8    2018-01-08           19.920                   20.06   \n",
       "9    2018-01-09           15.835                   14.73   \n",
       "10   2018-01-10           10.710                    8.19   \n",
       "11   2018-01-11            3.970                    0.77   \n",
       "12   2018-01-12            0.370                   -3.61   \n",
       "\n",
       "      monthly_avg_HeatIndexC  monthly_avg_cloudcover  monthly_avg_humidity  \\\n",
       "date                                                                         \n",
       "1                          1                       2                 82.81   \n",
       "2                          0                       2                 76.04   \n",
       "3                          1                       2                 73.23   \n",
       "4                          1                       1                 72.47   \n",
       "5                          2                       0                 73.23   \n",
       "6                          2                       1                 72.30   \n",
       "7                          2                       1                 75.97   \n",
       "8                          2                       0                 69.97   \n",
       "9                          2                       1                 69.23   \n",
       "10                         1                       1                 71.65   \n",
       "11                         1                       1                 80.60   \n",
       "12                         1                       3                 88.58   \n",
       "\n",
       "      ishol/week  \n",
       "date              \n",
       "1              9  \n",
       "2              8  \n",
       "3              9  \n",
       "4             10  \n",
       "5             11  \n",
       "6              9  \n",
       "7              9  \n",
       "8              9  \n",
       "9             10  \n",
       "10             8  \n",
       "11             9  \n",
       "12            12  "
      ]
     },
     "execution_count": 526,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "weather_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 527,
   "metadata": {},
   "outputs": [],
   "source": [
    "weather_data=weather_data.set_index(\"date\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 528,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>69.97</td>\n",
       "      <td>9</td>\n",
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       "      <th>2018-01-09</th>\n",
       "      <td>15.835</td>\n",
       "      <td>14.73</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>69.23</td>\n",
       "      <td>10</td>\n",
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       "      <td>10.710</td>\n",
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       "      <td>1</td>\n",
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       "      <th>2018-01-11</th>\n",
       "      <td>3.970</td>\n",
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       "      <td>1</td>\n",
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       "      <td>1</td>\n",
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      ],
      "text/plain": [
       "            monthly_Avgtemp  monthly_avg_FeelsLikeC  monthly_avg_HeatIndexC  \\\n",
       "date                                                                          \n",
       "2018-01-01           -0.420                   -4.84                       1   \n",
       "2018-01-02           -3.290                   -7.61                       0   \n",
       "2018-01-03            0.165                   -4.03                       1   \n",
       "2018-01-04           12.080                   10.37                       1   \n",
       "2018-01-05           15.965                   15.42                       2   \n",
       "2018-01-06           17.065                   17.10                       2   \n",
       "2018-01-07           19.725                   19.90                       2   \n",
       "2018-01-08           19.920                   20.06                       2   \n",
       "2018-01-09           15.835                   14.73                       2   \n",
       "2018-01-10           10.710                    8.19                       1   \n",
       "2018-01-11            3.970                    0.77                       1   \n",
       "2018-01-12            0.370                   -3.61                       1   \n",
       "\n",
       "            monthly_avg_cloudcover  monthly_avg_humidity  ishol/week  \n",
       "date                                                                  \n",
       "2018-01-01                       2                 82.81           9  \n",
       "2018-01-02                       2                 76.04           8  \n",
       "2018-01-03                       2                 73.23           9  \n",
       "2018-01-04                       1                 72.47          10  \n",
       "2018-01-05                       0                 73.23          11  \n",
       "2018-01-06                       1                 72.30           9  \n",
       "2018-01-07                       1                 75.97           9  \n",
       "2018-01-08                       0                 69.97           9  \n",
       "2018-01-09                       1                 69.23          10  \n",
       "2018-01-10                       1                 71.65           8  \n",
       "2018-01-11                       1                 80.60           9  \n",
       "2018-01-12                       3                 88.58          12  "
      ]
     },
     "execution_count": 528,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "weather_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 529,
   "metadata": {},
   "outputs": [],
   "source": [
    "weather_data.to_csv(\"Final_Weather_Data.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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