Data_Preparation_Meteo_Radiation_Temp_Press.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "17da6281",
   "metadata": {},
   "source": [
    "# Importazione librerie e setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "9d3725ae",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-01-25T09:30:27.352000Z",
     "start_time": "2022-01-25T09:30:27.334967Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>.container { width:90% !important; }</style>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from IPython.core.display import display, HTML\n",
    "\n",
    "display(HTML(\"<style>.container { width:90% !important; }</style>\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "416c0c91",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-01-25T09:30:30.107163Z",
     "start_time": "2022-01-25T09:30:27.843129Z"
    }
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import math as m\n",
    "import seaborn as sns\n",
    "from pandas.api.types import CategoricalDtype"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "af572608",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-01-25T09:30:30.155144Z",
     "start_time": "2022-01-25T09:30:30.141146Z"
    }
   },
   "outputs": [],
   "source": [
    "path = './data/'"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a4193c40",
   "metadata": {
    "tags": []
   },
   "source": [
    "# Conversione files e Importazione datasets"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e63d95f6",
   "metadata": {},
   "source": [
    "## Convesione da `.csv` a `.parquet`"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f1631d44",
   "metadata": {},
   "source": [
    "Data la grande dimensione di alcuni dei dataset utilizzati, questi verranno convertiti da `.csv` a `.parquet` (Apache Parquet Format)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "3ee688d7",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-01-25T09:30:32.300831Z",
     "start_time": "2022-01-25T09:30:32.287834Z"
    }
   },
   "outputs": [],
   "source": [
    "#df = pd.read_csv('./Datasets/Dati_sensori_meteo_2021.csv', low_memory=False)\n",
    "#df.to_parquet('./Datasets/Dati_sensori_meteo_2021.parquet')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "35f53d80",
   "metadata": {},
   "source": [
    "## Dataset Meteo - group"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2362e611",
   "metadata": {},
   "source": [
    "### Attributi"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ecdfd91b",
   "metadata": {},
   "source": [
    "- IdSensore: \n",
    "    - Tipologia: Testo normale\n",
    "- Data: \n",
    "    - Data e ora, Marcatura oraria flessibile\n",
    "- Valore: \n",
    "    - Tipologia: numero\n",
    "    - Legenda: 9999 = dato mancante 888, 8888 = direzione vento variabile 777, 7777 = calma (solo per direzione di vento)\n",
    "- idOperatore\t\n",
    "    - *Molto utile per capire la dimensione del dato*\n",
    "    - LEGENDA: 1: Valore medio 3: Valore massimo 4: Valore cumulato (per la pioggia)\n",
    "    - Testo normale\n",
    "- Stato\t\n",
    "    - LEGENDA: VA, VV = dato valido NA, NV, NC = dato invalido NI = dato incerto ND = dato non disponibile\n",
    "    - Testo normale"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "16d41c19",
   "metadata": {},
   "source": [
    "### Read_csv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "ccd89aa5",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-01-21T14:42:22.826285Z",
     "start_time": "2022-01-21T14:42:22.812285Z"
    },
    "hidden": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\ProgramData\\Anaconda3\\lib\\site-packages\\numpy\\lib\\arraysetops.py:583: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison\n",
      "  mask |= (ar1 == a)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "IdSensore                int64\n",
       "Data            datetime64[ns]\n",
       "Valore_mean            float64\n",
       "Valore_std             float64\n",
       "Valore_max             float64\n",
       "Valore_count             int64\n",
       "dtype: object"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "meteo__id_day = pd.read_csv(f'{path}data_meteo/meteo_group_17_21.csv', parse_dates = ['Data'], index_col = 0)\n",
    "meteo__id_day.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "385a899c",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>IdSensore</th>\n",
       "      <th>Data</th>\n",
       "      <th>Valore_mean</th>\n",
       "      <th>Valore_std</th>\n",
       "      <th>Valore_max</th>\n",
       "      <th>Valore_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3</td>\n",
       "      <td>2017-01-01</td>\n",
       "      <td>37.054861</td>\n",
       "      <td>0.934560</td>\n",
       "      <td>38.3</td>\n",
       "      <td>144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3</td>\n",
       "      <td>2017-01-02</td>\n",
       "      <td>37.584028</td>\n",
       "      <td>0.618894</td>\n",
       "      <td>38.3</td>\n",
       "      <td>144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>2017-01-03</td>\n",
       "      <td>37.242361</td>\n",
       "      <td>0.567238</td>\n",
       "      <td>38.2</td>\n",
       "      <td>144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>2017-01-04</td>\n",
       "      <td>37.350694</td>\n",
       "      <td>0.591075</td>\n",
       "      <td>38.3</td>\n",
       "      <td>144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3</td>\n",
       "      <td>2017-01-05</td>\n",
       "      <td>37.583333</td>\n",
       "      <td>0.470084</td>\n",
       "      <td>38.3</td>\n",
       "      <td>144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1507592</th>\n",
       "      <td>32413</td>\n",
       "      <td>2021-12-27</td>\n",
       "      <td>34.013889</td>\n",
       "      <td>62.178514</td>\n",
       "      <td>214.0</td>\n",
       "      <td>144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1507593</th>\n",
       "      <td>32413</td>\n",
       "      <td>2021-12-28</td>\n",
       "      <td>93.618056</td>\n",
       "      <td>171.915575</td>\n",
       "      <td>531.0</td>\n",
       "      <td>144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1507594</th>\n",
       "      <td>32413</td>\n",
       "      <td>2021-12-29</td>\n",
       "      <td>67.291667</td>\n",
       "      <td>121.751603</td>\n",
       "      <td>410.0</td>\n",
       "      <td>144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1507595</th>\n",
       "      <td>32413</td>\n",
       "      <td>2021-12-30</td>\n",
       "      <td>69.659722</td>\n",
       "      <td>128.552521</td>\n",
       "      <td>440.0</td>\n",
       "      <td>144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1507596</th>\n",
       "      <td>32413</td>\n",
       "      <td>2021-12-31</td>\n",
       "      <td>82.708333</td>\n",
       "      <td>152.573764</td>\n",
       "      <td>457.0</td>\n",
       "      <td>144</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1507597 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         IdSensore       Data  Valore_mean  Valore_std  Valore_max  \\\n",
       "0                3 2017-01-01    37.054861    0.934560        38.3   \n",
       "1                3 2017-01-02    37.584028    0.618894        38.3   \n",
       "2                3 2017-01-03    37.242361    0.567238        38.2   \n",
       "3                3 2017-01-04    37.350694    0.591075        38.3   \n",
       "4                3 2017-01-05    37.583333    0.470084        38.3   \n",
       "...            ...        ...          ...         ...         ...   \n",
       "1507592      32413 2021-12-27    34.013889   62.178514       214.0   \n",
       "1507593      32413 2021-12-28    93.618056  171.915575       531.0   \n",
       "1507594      32413 2021-12-29    67.291667  121.751603       410.0   \n",
       "1507595      32413 2021-12-30    69.659722  128.552521       440.0   \n",
       "1507596      32413 2021-12-31    82.708333  152.573764       457.0   \n",
       "\n",
       "         Valore_count  \n",
       "0                 144  \n",
       "1                 144  \n",
       "2                 144  \n",
       "3                 144  \n",
       "4                 144  \n",
       "...               ...  \n",
       "1507592           144  \n",
       "1507593           144  \n",
       "1507594           144  \n",
       "1507595           144  \n",
       "1507596           144  \n",
       "\n",
       "[1507597 rows x 6 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "meteo__id_day"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f8bfa39c",
   "metadata": {
    "heading_collapsed": true
   },
   "source": [
    "## Dataset Meteo - sensori"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f624b390",
   "metadata": {
    "hidden": true
   },
   "source": [
    "### Attributi"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ac4dca40",
   "metadata": {
    "hidden": true
   },
   "source": [
    "- **IdSensore**\n",
    "    - Foreign Key con vincolo di integrità referenziale a `IdSensore` di meteo_21\n",
    "    - Testo normale\n",
    "- **Tipologia**\n",
    "    - Grandezza misurata\n",
    "    - Testo normale\n",
    "- **Unità DiMisura**\n",
    "    - Unità di misura della grandezza\n",
    "    - Testo normale\n",
    "- IdStazione\t\n",
    "    - Numero identificativo della stazione (penso perchè ogni stazione può avere più sensori)\n",
    "    - Testo normale\n",
    "- NomeStazione\t\n",
    "    - Località della stazione (Spesso è 'Comune via' o 'Comune località)'\n",
    "    - Testo normale\n",
    "- Quota\t\n",
    "    - Altitudine\n",
    "    - Numero\n",
    "- Provincia\n",
    "    - Sigla della provincia\n",
    "    - Testo normale\n",
    "- DataStart\t\n",
    "    - Data e ora\n",
    "- DataStop\t\n",
    "    - Data e ora\n",
    "- Storico\t\n",
    "    - Noto che assume valori N e S ma non capisco cosa sia\n",
    "    - Testo normale\n",
    "- UTM_Nord\t\n",
    "    - Coordinata UTM nord (le cordinate utm permettono di individuare univocamente un punto sulla cartina terrestre)\n",
    "    - Testo normale\n",
    "- UTM_Est\t\n",
    "    - Coordinata UTM est\n",
    "    - Testo normale\n",
    "- lng\t\n",
    "    - Longitudine (senza simbolo gradi)\n",
    "    - Numero\n",
    "- lat\t\n",
    "    - Latitudine (senza simbolo gradi)\n",
    "    - Numero\n",
    "- location\t\n",
    "    - (latitudine°, longitudine°)\n",
    "    - Posizione"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e5c434f2",
   "metadata": {
    "hidden": true
   },
   "source": [
    "### Caratteristiche"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a2cebcc0",
   "metadata": {
    "hidden": true
   },
   "source": [
    "Sono disponibili i dati delle grandezze:\n",
    "- Livello Idrometrico (cm)\n",
    "- Altezza neve (cm)\n",
    "- Precipitazione (mm)\n",
    "- Temperatura (°C)\n",
    "- Umidità Relativa (%)\n",
    "- Radiazione Globale (W/m2)\n",
    "- Velocità e Direzione Vento (m/s e gradi).\n",
    "- Velocità e direzione del vento (m/s e gradi N) raffica\n",
    "NB: l’orario del dato è \"ora solare\" e si riferisce alle osservazioni ottenute fino all’orario indicato."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e80d8a70",
   "metadata": {
    "hidden": true
   },
   "source": [
    "### Read_csv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "9c1aee03",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-01-21T14:42:22.826285Z",
     "start_time": "2022-01-21T14:42:22.812285Z"
    },
    "hidden": true
   },
   "outputs": [
    {
     "data": {
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>IdSensore</th>\n",
       "      <th>Tipologia</th>\n",
       "      <th>Unità DiMisura</th>\n",
       "      <th>IdStazione</th>\n",
       "      <th>NomeStazione</th>\n",
       "      <th>Quota</th>\n",
       "      <th>Provincia</th>\n",
       "      <th>DataStart</th>\n",
       "      <th>DataStop</th>\n",
       "      <th>Storico</th>\n",
       "      <th>UTM_Nord</th>\n",
       "      <th>UTM_Est</th>\n",
       "      <th>lng</th>\n",
       "      <th>lat</th>\n",
       "      <th>location</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>22006</td>\n",
       "      <td>Umidità Relativa</td>\n",
       "      <td>%</td>\n",
       "      <td>1890</td>\n",
       "      <td>Tavernole sul Mella Monte Guglielmo</td>\n",
       "      <td>1790</td>\n",
       "      <td>BS</td>\n",
       "      <td>14/10/2019</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N</td>\n",
       "      <td>5067376</td>\n",
       "      <td>591417</td>\n",
       "      <td>10.175407</td>\n",
       "      <td>45.753896</td>\n",
       "      <td>(45.75389593743312, 10.175407094582125)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>22007</td>\n",
       "      <td>Direzione Vento</td>\n",
       "      <td>°</td>\n",
       "      <td>1890</td>\n",
       "      <td>Tavernole sul Mella Monte Guglielmo</td>\n",
       "      <td>1790</td>\n",
       "      <td>BS</td>\n",
       "      <td>14/10/2019</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N</td>\n",
       "      <td>5067376</td>\n",
       "      <td>591417</td>\n",
       "      <td>10.175407</td>\n",
       "      <td>45.753896</td>\n",
       "      <td>(45.75389593743312, 10.175407094582125)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>22003</td>\n",
       "      <td>Temperatura</td>\n",
       "      <td>°C</td>\n",
       "      <td>1890</td>\n",
       "      <td>Tavernole sul Mella Monte Guglielmo</td>\n",
       "      <td>1790</td>\n",
       "      <td>BS</td>\n",
       "      <td>14/10/2019</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N</td>\n",
       "      <td>5067376</td>\n",
       "      <td>591417</td>\n",
       "      <td>10.175407</td>\n",
       "      <td>45.753896</td>\n",
       "      <td>(45.75389593743312, 10.175407094582125)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>22009</td>\n",
       "      <td>Velocità Vento</td>\n",
       "      <td>m/s</td>\n",
       "      <td>1890</td>\n",
       "      <td>Tavernole sul Mella Monte Guglielmo</td>\n",
       "      <td>1790</td>\n",
       "      <td>BS</td>\n",
       "      <td>14/10/2019</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N</td>\n",
       "      <td>5067376</td>\n",
       "      <td>591417</td>\n",
       "      <td>10.175407</td>\n",
       "      <td>45.753896</td>\n",
       "      <td>(45.75389593743312, 10.175407094582125)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>17612</td>\n",
       "      <td>Altezza Neve</td>\n",
       "      <td>cm</td>\n",
       "      <td>1545</td>\n",
       "      <td>San Siro Alpe Rescascìa</td>\n",
       "      <td>1285</td>\n",
       "      <td>CO</td>\n",
       "      <td>07/11/2019</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N</td>\n",
       "      <td>5102069</td>\n",
       "      <td>518430</td>\n",
       "      <td>9.238323</td>\n",
       "      <td>46.071947</td>\n",
       "      <td>(46.071947417956004, 9.238323435918229)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   IdSensore         Tipologia Unità DiMisura  IdStazione  \\\n",
       "0      22006  Umidità Relativa              %        1890   \n",
       "1      22007   Direzione Vento              °        1890   \n",
       "2      22003       Temperatura             °C        1890   \n",
       "3      22009    Velocità Vento            m/s        1890   \n",
       "4      17612      Altezza Neve             cm        1545   \n",
       "\n",
       "                          NomeStazione  Quota Provincia   DataStart DataStop  \\\n",
       "0  Tavernole sul Mella Monte Guglielmo   1790        BS  14/10/2019      NaN   \n",
       "1  Tavernole sul Mella Monte Guglielmo   1790        BS  14/10/2019      NaN   \n",
       "2  Tavernole sul Mella Monte Guglielmo   1790        BS  14/10/2019      NaN   \n",
       "3  Tavernole sul Mella Monte Guglielmo   1790        BS  14/10/2019      NaN   \n",
       "4              San Siro Alpe Rescascìa   1285        CO  07/11/2019      NaN   \n",
       "\n",
       "  Storico  UTM_Nord  UTM_Est        lng        lat  \\\n",
       "0       N   5067376   591417  10.175407  45.753896   \n",
       "1       N   5067376   591417  10.175407  45.753896   \n",
       "2       N   5067376   591417  10.175407  45.753896   \n",
       "3       N   5067376   591417  10.175407  45.753896   \n",
       "4       N   5102069   518430   9.238323  46.071947   \n",
       "\n",
       "                                  location  \n",
       "0  (45.75389593743312, 10.175407094582125)  \n",
       "1  (45.75389593743312, 10.175407094582125)  \n",
       "2  (45.75389593743312, 10.175407094582125)  \n",
       "3  (45.75389593743312, 10.175407094582125)  \n",
       "4  (46.071947417956004, 9.238323435918229)  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sensori_meteo = pd.read_csv(f'{path}Stazioni_Meteorologiche.csv')\n",
    "sensori_meteo.head()\n",
    "#stazioni_meteo['Tipologia'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5e7e09a7",
   "metadata": {},
   "source": [
    "## Dataset Zonizzazione"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "e2b3ff11",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-01-21T14:44:26.253288Z",
     "start_time": "2022-01-21T14:44:26.224286Z"
    }
   },
   "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>Provincia</th>\n",
       "      <th>Codice Istat</th>\n",
       "      <th>Comune</th>\n",
       "      <th>Zona</th>\n",
       "      <th>Residenti 2008</th>\n",
       "      <th>Superficie (ha)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>BG</td>\n",
       "      <td>16009</td>\n",
       "      <td>AMBIVERE</td>\n",
       "      <td>A</td>\n",
       "      <td>2341</td>\n",
       "      <td>327</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>BG</td>\n",
       "      <td>16013</td>\n",
       "      <td>ARZAGO D'ADDA</td>\n",
       "      <td>A</td>\n",
       "      <td>2836</td>\n",
       "      <td>944</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>BG</td>\n",
       "      <td>16018</td>\n",
       "      <td>BAGNATICA</td>\n",
       "      <td>A</td>\n",
       "      <td>4119</td>\n",
       "      <td>639</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>BG</td>\n",
       "      <td>16020</td>\n",
       "      <td>BARIANO</td>\n",
       "      <td>A</td>\n",
       "      <td>4396</td>\n",
       "      <td>714</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>BG</td>\n",
       "      <td>16021</td>\n",
       "      <td>BARZANO'</td>\n",
       "      <td>A</td>\n",
       "      <td>5178</td>\n",
       "      <td>356</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Provincia  Codice Istat         Comune Zona  Residenti 2008  Superficie (ha)\n",
       "0        BG         16009       AMBIVERE    A            2341              327\n",
       "1        BG         16013  ARZAGO D'ADDA    A            2836              944\n",
       "2        BG         16018      BAGNATICA    A            4119              639\n",
       "3        BG         16020        BARIANO    A            4396              714\n",
       "4        BG         16021       BARZANO'    A            5178              356"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "zonizzazione = pd.read_csv(f'{path}zonizzazione/zonizzazione_ABCD.csv')\n",
    "zonizzazione.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "531ada5d",
   "metadata": {},
   "source": [
    "## Dataset pressione atmosferica"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "d1b5e2d3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Data_ora</th>\n",
       "      <th>Valore</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>01/01/2016 23.59.00</td>\n",
       "      <td>1017.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>02/01/2016 23.59.00</td>\n",
       "      <td>1011.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>03/01/2016 23.59.00</td>\n",
       "      <td>1002.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>04/01/2016 23.59.00</td>\n",
       "      <td>993.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>05/01/2016 23.59.00</td>\n",
       "      <td>993.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Data_ora  Valore\n",
       "0  01/01/2016 23.59.00  1017.4\n",
       "1  02/01/2016 23.59.00  1011.6\n",
       "2  03/01/2016 23.59.00  1002.6\n",
       "3  04/01/2016 23.59.00   993.0\n",
       "4  05/01/2016 23.59.00   993.0"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "press_zama = pd.read_csv(f'{path}data_meteo/press/press_zama.csv', na_values = -9999)\n",
    "press_zama.dtypes\n",
    "press_zama.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d83924c3",
   "metadata": {},
   "source": [
    "# Data Exploration e Data Cleansing (*superset*)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "340aaf00",
   "metadata": {},
   "source": [
    "## Data Exploration"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "07b67b84",
   "metadata": {},
   "source": [
    "- verificare quali siano tutte le quantità uniche rilevate dai sensori qualità dell'aria\n",
    "- quali siano i gruppi di inquinanti principali\n",
    "- quali siano i limiti di assunzione umana (gionralieri e annuali)\n",
    "    - Vedi [qui](https://www.arpalombardia.it/Pages/Aria/Inquinanti.aspx) per limiti e piccola descrizione\n",
    "    - Vedi [qui](https://www.regione.lombardia.it/wps/portal/istituzionale/HP/DettaglioRedazionale/servizi-e-informazioni/cittadini/salute-e-prevenzione/Sicurezza-negli-ambienti-di-vita-e-di-lavoro/inquinamento-atmosferico/inquinamento-atmosferico/) per approfondimento"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "94655e3c",
   "metadata": {},
   "source": [
    "Determino il numero di sensori per ogni tipologia\n",
    "\n",
    "- Si potrebbero considerare solo gli inquinanti **più importanti e con più stazioni**\n",
    "- Ovvero **Biossido di Azoto | PM10 (SM2005) e PM2,5 e/o Particolato totale | Ozono troposferico | Bisossido di Zolfo**\n",
    "- Facoltativi perchè non presenti nella valutazione della qualità dell'aria [qui](https://www.arpalombardia.it/Pages/Aria/Modellistica/Indice-qualit%C3%A0-aria.aspx): Monossido di carbonio e benzene"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "cbca3194",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-01-21T14:44:26.269287Z",
     "start_time": "2022-01-21T14:44:26.255285Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Precipitazione         281\n",
       "Temperatura            258\n",
       "Umidità Relativa       199\n",
       "Direzione Vento        144\n",
       "Velocità Vento         144\n",
       "Radiazione Globale     110\n",
       "Livello Idrometrico     85\n",
       "Altezza Neve            41\n",
       "Name: Tipologia, dtype: int64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sensori_meteo['Tipologia'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "619a353b",
   "metadata": {},
   "source": [
    "Determino il numero di zone in cui é suddiviso il territorio Lombardo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "ab0e8872",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-01-21T14:44:26.285283Z",
     "start_time": "2022-01-21T14:44:26.271289Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "B         448\n",
       "C         423\n",
       "A         406\n",
       "AGG MI    107\n",
       "C D       102\n",
       "AGG BG     37\n",
       "AGG BS     20\n",
       "D           2\n",
       "Name: Zona, dtype: int64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "zonizzazione['Zona'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f18dcb79",
   "metadata": {},
   "source": [
    "## Data Cleansing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "205823f0",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-01-21T14:44:56.560284Z",
     "start_time": "2022-01-21T14:44:56.503286Z"
    }
   },
   "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>IdSensore</th>\n",
       "      <th>Tipologia</th>\n",
       "      <th>Unità DiMisura</th>\n",
       "      <th>IdStazione</th>\n",
       "      <th>NomeStazione</th>\n",
       "      <th>Quota</th>\n",
       "      <th>Provincia</th>\n",
       "      <th>DataStart</th>\n",
       "      <th>DataStop</th>\n",
       "      <th>Storico</th>\n",
       "      <th>UTM_Nord</th>\n",
       "      <th>UTM_Est</th>\n",
       "      <th>lng</th>\n",
       "      <th>lat</th>\n",
       "      <th>location</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>22003</td>\n",
       "      <td>Temperatura</td>\n",
       "      <td>°C</td>\n",
       "      <td>1890</td>\n",
       "      <td>Tavernole sul Mella Monte Guglielmo</td>\n",
       "      <td>1790</td>\n",
       "      <td>BS</td>\n",
       "      <td>14/10/2019</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N</td>\n",
       "      <td>5067376</td>\n",
       "      <td>591417</td>\n",
       "      <td>10.175407</td>\n",
       "      <td>45.753896</td>\n",
       "      <td>(45.75389593743312, 10.175407094582125)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>22017</td>\n",
       "      <td>Radiazione Globale</td>\n",
       "      <td>W/m²</td>\n",
       "      <td>1890</td>\n",
       "      <td>Tavernole sul Mella Monte Guglielmo</td>\n",
       "      <td>1790</td>\n",
       "      <td>BS</td>\n",
       "      <td>14/10/2019</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N</td>\n",
       "      <td>5067376</td>\n",
       "      <td>591417</td>\n",
       "      <td>10.175407</td>\n",
       "      <td>45.753896</td>\n",
       "      <td>(45.75389593743312, 10.175407094582125)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>5865</td>\n",
       "      <td>Temperatura</td>\n",
       "      <td>°C</td>\n",
       "      <td>596</td>\n",
       "      <td>Osio Sotto v.per Levate</td>\n",
       "      <td>182</td>\n",
       "      <td>BG</td>\n",
       "      <td>04/04/2000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N</td>\n",
       "      <td>5052072</td>\n",
       "      <td>547691</td>\n",
       "      <td>9.611738</td>\n",
       "      <td>45.620556</td>\n",
       "      <td>(45.62055567939559, 9.611737821812373)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>19293</td>\n",
       "      <td>Temperatura</td>\n",
       "      <td>°C</td>\n",
       "      <td>1514</td>\n",
       "      <td>Carenno centro sportivo</td>\n",
       "      <td>633</td>\n",
       "      <td>LC</td>\n",
       "      <td>08/05/2018</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N</td>\n",
       "      <td>5072042</td>\n",
       "      <td>536210</td>\n",
       "      <td>9.465967</td>\n",
       "      <td>45.800989</td>\n",
       "      <td>(45.80098941456421, 9.46596663838796)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2190</td>\n",
       "      <td>Radiazione Globale</td>\n",
       "      <td>W/m²</td>\n",
       "      <td>114</td>\n",
       "      <td>Landriano Cascina Marianna</td>\n",
       "      <td>88</td>\n",
       "      <td>PV</td>\n",
       "      <td>29/09/2005</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N</td>\n",
       "      <td>5018600</td>\n",
       "      <td>520938</td>\n",
       "      <td>9.267153</td>\n",
       "      <td>45.320594</td>\n",
       "      <td>(45.32059361110084, 9.26715311477454)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>363</th>\n",
       "      <td>9827</td>\n",
       "      <td>Radiazione Globale</td>\n",
       "      <td>W/m²</td>\n",
       "      <td>835</td>\n",
       "      <td>Valdisotto Oga S. Colombano</td>\n",
       "      <td>2300</td>\n",
       "      <td>SO</td>\n",
       "      <td>01/10/1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N</td>\n",
       "      <td>5145272</td>\n",
       "      <td>600293</td>\n",
       "      <td>10.305952</td>\n",
       "      <td>46.453563</td>\n",
       "      <td>(46.45356305894081, 10.305951823970043)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>364</th>\n",
       "      <td>8008</td>\n",
       "      <td>Temperatura</td>\n",
       "      <td>°C</td>\n",
       "      <td>835</td>\n",
       "      <td>Valdisotto Oga S. Colombano</td>\n",
       "      <td>2300</td>\n",
       "      <td>SO</td>\n",
       "      <td>01/01/1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N</td>\n",
       "      <td>5145272</td>\n",
       "      <td>600293</td>\n",
       "      <td>10.305952</td>\n",
       "      <td>46.453563</td>\n",
       "      <td>(46.45356305894081, 10.305951823970043)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>365</th>\n",
       "      <td>12759</td>\n",
       "      <td>Temperatura</td>\n",
       "      <td>°C</td>\n",
       "      <td>1512</td>\n",
       "      <td>Pogliano Milanese</td>\n",
       "      <td>160</td>\n",
       "      <td>MI</td>\n",
       "      <td>25/11/2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N</td>\n",
       "      <td>5042449</td>\n",
       "      <td>500406</td>\n",
       "      <td>9.005200</td>\n",
       "      <td>45.535577</td>\n",
       "      <td>(45.535576719250145, 9.005199956067523)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>366</th>\n",
       "      <td>12755</td>\n",
       "      <td>Temperatura</td>\n",
       "      <td>°C</td>\n",
       "      <td>1510</td>\n",
       "      <td>Monza v.Monte Generoso</td>\n",
       "      <td>173</td>\n",
       "      <td>MB</td>\n",
       "      <td>25/11/2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N</td>\n",
       "      <td>5048372</td>\n",
       "      <td>519174</td>\n",
       "      <td>9.245807</td>\n",
       "      <td>45.588626</td>\n",
       "      <td>(45.58862552802921, 9.245807488805221)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>367</th>\n",
       "      <td>12757</td>\n",
       "      <td>Temperatura</td>\n",
       "      <td>°C</td>\n",
       "      <td>1511</td>\n",
       "      <td>Rescaldina</td>\n",
       "      <td>215</td>\n",
       "      <td>MI</td>\n",
       "      <td>25/11/2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N</td>\n",
       "      <td>5050479</td>\n",
       "      <td>496327</td>\n",
       "      <td>8.952897</td>\n",
       "      <td>45.607845</td>\n",
       "      <td>(45.60784533497315, 8.95289667553321)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>368 rows × 15 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     IdSensore           Tipologia Unità DiMisura  IdStazione  \\\n",
       "0        22003         Temperatura             °C        1890   \n",
       "1        22017  Radiazione Globale           W/m²        1890   \n",
       "2         5865         Temperatura             °C         596   \n",
       "3        19293         Temperatura             °C        1514   \n",
       "4         2190  Radiazione Globale           W/m²         114   \n",
       "..         ...                 ...            ...         ...   \n",
       "363       9827  Radiazione Globale           W/m²         835   \n",
       "364       8008         Temperatura             °C         835   \n",
       "365      12759         Temperatura             °C        1512   \n",
       "366      12755         Temperatura             °C        1510   \n",
       "367      12757         Temperatura             °C        1511   \n",
       "\n",
       "                            NomeStazione  Quota Provincia   DataStart  \\\n",
       "0    Tavernole sul Mella Monte Guglielmo   1790        BS  14/10/2019   \n",
       "1    Tavernole sul Mella Monte Guglielmo   1790        BS  14/10/2019   \n",
       "2                Osio Sotto v.per Levate    182        BG  04/04/2000   \n",
       "3                Carenno centro sportivo    633        LC  08/05/2018   \n",
       "4             Landriano Cascina Marianna     88        PV  29/09/2005   \n",
       "..                                   ...    ...       ...         ...   \n",
       "363          Valdisotto Oga S. Colombano   2300        SO  01/10/1992   \n",
       "364          Valdisotto Oga S. Colombano   2300        SO  01/01/1992   \n",
       "365                    Pogliano Milanese    160        MI  25/11/2020   \n",
       "366               Monza v.Monte Generoso    173        MB  25/11/2020   \n",
       "367                           Rescaldina    215        MI  25/11/2020   \n",
       "\n",
       "    DataStop Storico  UTM_Nord  UTM_Est        lng        lat  \\\n",
       "0        NaN       N   5067376   591417  10.175407  45.753896   \n",
       "1        NaN       N   5067376   591417  10.175407  45.753896   \n",
       "2        NaN       N   5052072   547691   9.611738  45.620556   \n",
       "3        NaN       N   5072042   536210   9.465967  45.800989   \n",
       "4        NaN       N   5018600   520938   9.267153  45.320594   \n",
       "..       ...     ...       ...      ...        ...        ...   \n",
       "363      NaN       N   5145272   600293  10.305952  46.453563   \n",
       "364      NaN       N   5145272   600293  10.305952  46.453563   \n",
       "365      NaN       N   5042449   500406   9.005200  45.535577   \n",
       "366      NaN       N   5048372   519174   9.245807  45.588626   \n",
       "367      NaN       N   5050479   496327   8.952897  45.607845   \n",
       "\n",
       "                                    location  \n",
       "0    (45.75389593743312, 10.175407094582125)  \n",
       "1    (45.75389593743312, 10.175407094582125)  \n",
       "2     (45.62055567939559, 9.611737821812373)  \n",
       "3      (45.80098941456421, 9.46596663838796)  \n",
       "4      (45.32059361110084, 9.26715311477454)  \n",
       "..                                       ...  \n",
       "363  (46.45356305894081, 10.305951823970043)  \n",
       "364  (46.45356305894081, 10.305951823970043)  \n",
       "365  (45.535576719250145, 9.005199956067523)  \n",
       "366   (45.58862552802921, 9.245807488805221)  \n",
       "367    (45.60784533497315, 8.95289667553321)  \n",
       "\n",
       "[368 rows x 15 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sensori_meteo.drop(sensori_meteo[~sensori_meteo['Tipologia'].isin(['Temperatura', 'Radiazione Globale'])].index, inplace = True)\n",
    "sensori_meteo.reset_index(drop=True, inplace=True)\n",
    "sensori_meteo"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c367220f",
   "metadata": {},
   "source": [
    "# Data preparation (group by e join su *superset*)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "532a1406",
   "metadata": {},
   "source": [
    "## JOIN meteo e sensori"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "c524de53",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-01-21T14:46:00.891285Z",
     "start_time": "2022-01-21T14:45:59.321286Z"
    }
   },
   "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>IdSensore</th>\n",
       "      <th>Data</th>\n",
       "      <th>Valore_mean</th>\n",
       "      <th>Valore_std</th>\n",
       "      <th>Valore_max</th>\n",
       "      <th>Valore_count</th>\n",
       "      <th>Tipologia</th>\n",
       "      <th>Unità DiMisura</th>\n",
       "      <th>IdStazione</th>\n",
       "      <th>NomeStazione</th>\n",
       "      <th>Quota</th>\n",
       "      <th>Provincia</th>\n",
       "      <th>DataStart</th>\n",
       "      <th>DataStop</th>\n",
       "      <th>Storico</th>\n",
       "      <th>UTM_Nord</th>\n",
       "      <th>UTM_Est</th>\n",
       "      <th>lng</th>\n",
       "      <th>lat</th>\n",
       "      <th>location</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>13</td>\n",
       "      <td>2017-01-01</td>\n",
       "      <td>-0.491667</td>\n",
       "      <td>2.179983</td>\n",
       "      <td>4.0</td>\n",
       "      <td>72</td>\n",
       "      <td>Temperatura</td>\n",
       "      <td>°C</td>\n",
       "      <td>6</td>\n",
       "      <td>Bormio Ponte sul  Frodolfo</td>\n",
       "      <td>1250</td>\n",
       "      <td>SO</td>\n",
       "      <td>25/11/1987</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N</td>\n",
       "      <td>5146642</td>\n",
       "      <td>605400</td>\n",
       "      <td>10.372743</td>\n",
       "      <td>46.465110</td>\n",
       "      <td>(46.46511042549073, 10.372742774828684)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>13</td>\n",
       "      <td>2017-01-02</td>\n",
       "      <td>-1.538889</td>\n",
       "      <td>2.608035</td>\n",
       "      <td>4.1</td>\n",
       "      <td>72</td>\n",
       "      <td>Temperatura</td>\n",
       "      <td>°C</td>\n",
       "      <td>6</td>\n",
       "      <td>Bormio Ponte sul  Frodolfo</td>\n",
       "      <td>1250</td>\n",
       "      <td>SO</td>\n",
       "      <td>25/11/1987</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N</td>\n",
       "      <td>5146642</td>\n",
       "      <td>605400</td>\n",
       "      <td>10.372743</td>\n",
       "      <td>46.465110</td>\n",
       "      <td>(46.46511042549073, 10.372742774828684)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>13</td>\n",
       "      <td>2017-01-03</td>\n",
       "      <td>-0.752778</td>\n",
       "      <td>1.479339</td>\n",
       "      <td>2.2</td>\n",
       "      <td>72</td>\n",
       "      <td>Temperatura</td>\n",
       "      <td>°C</td>\n",
       "      <td>6</td>\n",
       "      <td>Bormio Ponte sul  Frodolfo</td>\n",
       "      <td>1250</td>\n",
       "      <td>SO</td>\n",
       "      <td>25/11/1987</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N</td>\n",
       "      <td>5146642</td>\n",
       "      <td>605400</td>\n",
       "      <td>10.372743</td>\n",
       "      <td>46.465110</td>\n",
       "      <td>(46.46511042549073, 10.372742774828684)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>13</td>\n",
       "      <td>2017-01-04</td>\n",
       "      <td>2.743056</td>\n",
       "      <td>2.741380</td>\n",
       "      <td>8.2</td>\n",
       "      <td>72</td>\n",
       "      <td>Temperatura</td>\n",
       "      <td>°C</td>\n",
       "      <td>6</td>\n",
       "      <td>Bormio Ponte sul  Frodolfo</td>\n",
       "      <td>1250</td>\n",
       "      <td>SO</td>\n",
       "      <td>25/11/1987</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N</td>\n",
       "      <td>5146642</td>\n",
       "      <td>605400</td>\n",
       "      <td>10.372743</td>\n",
       "      <td>46.465110</td>\n",
       "      <td>(46.46511042549073, 10.372742774828684)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>13</td>\n",
       "      <td>2017-01-05</td>\n",
       "      <td>-3.972222</td>\n",
       "      <td>1.392760</td>\n",
       "      <td>-1.3</td>\n",
       "      <td>72</td>\n",
       "      <td>Temperatura</td>\n",
       "      <td>°C</td>\n",
       "      <td>6</td>\n",
       "      <td>Bormio Ponte sul  Frodolfo</td>\n",
       "      <td>1250</td>\n",
       "      <td>SO</td>\n",
       "      <td>25/11/1987</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N</td>\n",
       "      <td>5146642</td>\n",
       "      <td>605400</td>\n",
       "      <td>10.372743</td>\n",
       "      <td>46.465110</td>\n",
       "      <td>(46.46511042549073, 10.372742774828684)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>527961</th>\n",
       "      <td>12759</td>\n",
       "      <td>2021-12-27</td>\n",
       "      <td>4.034965</td>\n",
       "      <td>1.388091</td>\n",
       "      <td>5.6</td>\n",
       "      <td>143</td>\n",
       "      <td>Temperatura</td>\n",
       "      <td>°C</td>\n",
       "      <td>1512</td>\n",
       "      <td>Pogliano Milanese</td>\n",
       "      <td>160</td>\n",
       "      <td>MI</td>\n",
       "      <td>25/11/2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N</td>\n",
       "      <td>5042449</td>\n",
       "      <td>500406</td>\n",
       "      <td>9.005200</td>\n",
       "      <td>45.535577</td>\n",
       "      <td>(45.535576719250145, 9.005199956067523)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>527962</th>\n",
       "      <td>12759</td>\n",
       "      <td>2021-12-28</td>\n",
       "      <td>5.043750</td>\n",
       "      <td>1.134501</td>\n",
       "      <td>7.1</td>\n",
       "      <td>144</td>\n",
       "      <td>Temperatura</td>\n",
       "      <td>°C</td>\n",
       "      <td>1512</td>\n",
       "      <td>Pogliano Milanese</td>\n",
       "      <td>160</td>\n",
       "      <td>MI</td>\n",
       "      <td>25/11/2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N</td>\n",
       "      <td>5042449</td>\n",
       "      <td>500406</td>\n",
       "      <td>9.005200</td>\n",
       "      <td>45.535577</td>\n",
       "      <td>(45.535576719250145, 9.005199956067523)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>527963</th>\n",
       "      <td>12759</td>\n",
       "      <td>2021-12-29</td>\n",
       "      <td>4.531250</td>\n",
       "      <td>2.949706</td>\n",
       "      <td>10.8</td>\n",
       "      <td>144</td>\n",
       "      <td>Temperatura</td>\n",
       "      <td>°C</td>\n",
       "      <td>1512</td>\n",
       "      <td>Pogliano Milanese</td>\n",
       "      <td>160</td>\n",
       "      <td>MI</td>\n",
       "      <td>25/11/2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N</td>\n",
       "      <td>5042449</td>\n",
       "      <td>500406</td>\n",
       "      <td>9.005200</td>\n",
       "      <td>45.535577</td>\n",
       "      <td>(45.535576719250145, 9.005199956067523)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>527964</th>\n",
       "      <td>12759</td>\n",
       "      <td>2021-12-30</td>\n",
       "      <td>2.679167</td>\n",
       "      <td>0.754091</td>\n",
       "      <td>4.0</td>\n",
       "      <td>144</td>\n",
       "      <td>Temperatura</td>\n",
       "      <td>°C</td>\n",
       "      <td>1512</td>\n",
       "      <td>Pogliano Milanese</td>\n",
       "      <td>160</td>\n",
       "      <td>MI</td>\n",
       "      <td>25/11/2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N</td>\n",
       "      <td>5042449</td>\n",
       "      <td>500406</td>\n",
       "      <td>9.005200</td>\n",
       "      <td>45.535577</td>\n",
       "      <td>(45.535576719250145, 9.005199956067523)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>527965</th>\n",
       "      <td>12759</td>\n",
       "      <td>2021-12-31</td>\n",
       "      <td>1.528472</td>\n",
       "      <td>2.392315</td>\n",
       "      <td>8.0</td>\n",
       "      <td>144</td>\n",
       "      <td>Temperatura</td>\n",
       "      <td>°C</td>\n",
       "      <td>1512</td>\n",
       "      <td>Pogliano Milanese</td>\n",
       "      <td>160</td>\n",
       "      <td>MI</td>\n",
       "      <td>25/11/2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N</td>\n",
       "      <td>5042449</td>\n",
       "      <td>500406</td>\n",
       "      <td>9.005200</td>\n",
       "      <td>45.535577</td>\n",
       "      <td>(45.535576719250145, 9.005199956067523)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>527966 rows × 20 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        IdSensore       Data  Valore_mean  Valore_std  Valore_max  \\\n",
       "0              13 2017-01-01    -0.491667    2.179983         4.0   \n",
       "1              13 2017-01-02    -1.538889    2.608035         4.1   \n",
       "2              13 2017-01-03    -0.752778    1.479339         2.2   \n",
       "3              13 2017-01-04     2.743056    2.741380         8.2   \n",
       "4              13 2017-01-05    -3.972222    1.392760        -1.3   \n",
       "...           ...        ...          ...         ...         ...   \n",
       "527961      12759 2021-12-27     4.034965    1.388091         5.6   \n",
       "527962      12759 2021-12-28     5.043750    1.134501         7.1   \n",
       "527963      12759 2021-12-29     4.531250    2.949706        10.8   \n",
       "527964      12759 2021-12-30     2.679167    0.754091         4.0   \n",
       "527965      12759 2021-12-31     1.528472    2.392315         8.0   \n",
       "\n",
       "        Valore_count    Tipologia Unità DiMisura  IdStazione  \\\n",
       "0                 72  Temperatura             °C           6   \n",
       "1                 72  Temperatura             °C           6   \n",
       "2                 72  Temperatura             °C           6   \n",
       "3                 72  Temperatura             °C           6   \n",
       "4                 72  Temperatura             °C           6   \n",
       "...              ...          ...            ...         ...   \n",
       "527961           143  Temperatura             °C        1512   \n",
       "527962           144  Temperatura             °C        1512   \n",
       "527963           144  Temperatura             °C        1512   \n",
       "527964           144  Temperatura             °C        1512   \n",
       "527965           144  Temperatura             °C        1512   \n",
       "\n",
       "                      NomeStazione  Quota Provincia   DataStart DataStop  \\\n",
       "0       Bormio Ponte sul  Frodolfo   1250        SO  25/11/1987      NaN   \n",
       "1       Bormio Ponte sul  Frodolfo   1250        SO  25/11/1987      NaN   \n",
       "2       Bormio Ponte sul  Frodolfo   1250        SO  25/11/1987      NaN   \n",
       "3       Bormio Ponte sul  Frodolfo   1250        SO  25/11/1987      NaN   \n",
       "4       Bormio Ponte sul  Frodolfo   1250        SO  25/11/1987      NaN   \n",
       "...                            ...    ...       ...         ...      ...   \n",
       "527961           Pogliano Milanese    160        MI  25/11/2020      NaN   \n",
       "527962           Pogliano Milanese    160        MI  25/11/2020      NaN   \n",
       "527963           Pogliano Milanese    160        MI  25/11/2020      NaN   \n",
       "527964           Pogliano Milanese    160        MI  25/11/2020      NaN   \n",
       "527965           Pogliano Milanese    160        MI  25/11/2020      NaN   \n",
       "\n",
       "       Storico  UTM_Nord  UTM_Est        lng        lat  \\\n",
       "0            N   5146642   605400  10.372743  46.465110   \n",
       "1            N   5146642   605400  10.372743  46.465110   \n",
       "2            N   5146642   605400  10.372743  46.465110   \n",
       "3            N   5146642   605400  10.372743  46.465110   \n",
       "4            N   5146642   605400  10.372743  46.465110   \n",
       "...        ...       ...      ...        ...        ...   \n",
       "527961       N   5042449   500406   9.005200  45.535577   \n",
       "527962       N   5042449   500406   9.005200  45.535577   \n",
       "527963       N   5042449   500406   9.005200  45.535577   \n",
       "527964       N   5042449   500406   9.005200  45.535577   \n",
       "527965       N   5042449   500406   9.005200  45.535577   \n",
       "\n",
       "                                       location  \n",
       "0       (46.46511042549073, 10.372742774828684)  \n",
       "1       (46.46511042549073, 10.372742774828684)  \n",
       "2       (46.46511042549073, 10.372742774828684)  \n",
       "3       (46.46511042549073, 10.372742774828684)  \n",
       "4       (46.46511042549073, 10.372742774828684)  \n",
       "...                                         ...  \n",
       "527961  (45.535576719250145, 9.005199956067523)  \n",
       "527962  (45.535576719250145, 9.005199956067523)  \n",
       "527963  (45.535576719250145, 9.005199956067523)  \n",
       "527964  (45.535576719250145, 9.005199956067523)  \n",
       "527965  (45.535576719250145, 9.005199956067523)  \n",
       "\n",
       "[527966 rows x 20 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "meteo_sensori__id_day = pd.merge(meteo__id_day, sensori_meteo, how = 'inner', on = 'IdSensore')\n",
    "meteo_sensori__id_day"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d2e191f7",
   "metadata": {},
   "source": [
    "## Controllo significativitá medie e unitá di misura"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5ce26265",
   "metadata": {},
   "source": [
    "### Medie ottenute da piú di un'osservazione"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "c2423535",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "527966"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "meteo_sensori__id_day.shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "6a9e3243",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-01-21T14:46:09.530287Z",
     "start_time": "2022-01-21T14:46:08.733288Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "441723"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "meteo_sensori__id_day[meteo_sensori__id_day.Valore_count == 144].shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "c2b42de9",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-01-21T14:46:09.748322Z",
     "start_time": "2022-01-21T14:46:09.674285Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "40407"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "meteo_sensori__id_day[meteo_sensori__id_day.Valore_count < 130].shape[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b65aab0f",
   "metadata": {},
   "source": [
    "#### Rimozione medie ottenute da meno di 130 osservazioni"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "93645e4b",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-01-21T14:46:10.464341Z",
     "start_time": "2022-01-21T14:46:09.813284Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>IdSensore</th>\n",
       "      <th>Data</th>\n",
       "      <th>Valore_mean</th>\n",
       "      <th>Valore_std</th>\n",
       "      <th>Valore_max</th>\n",
       "      <th>Valore_count</th>\n",
       "      <th>Tipologia</th>\n",
       "      <th>Unità DiMisura</th>\n",
       "      <th>IdStazione</th>\n",
       "      <th>NomeStazione</th>\n",
       "      <th>Quota</th>\n",
       "      <th>Provincia</th>\n",
       "      <th>DataStart</th>\n",
       "      <th>DataStop</th>\n",
       "      <th>Storico</th>\n",
       "      <th>UTM_Nord</th>\n",
       "      <th>UTM_Est</th>\n",
       "      <th>lng</th>\n",
       "      <th>lat</th>\n",
       "      <th>location</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>13</td>\n",
       "      <td>2020-01-01</td>\n",
       "      <td>2.045390</td>\n",
       "      <td>1.888404</td>\n",
       "      <td>6.2</td>\n",
       "      <td>141</td>\n",
       "      <td>Temperatura</td>\n",
       "      <td>°C</td>\n",
       "      <td>6</td>\n",
       "      <td>Bormio Ponte sul  Frodolfo</td>\n",
       "      <td>1250</td>\n",
       "      <td>SO</td>\n",
       "      <td>25/11/1987</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N</td>\n",
       "      <td>5146642</td>\n",
       "      <td>605400</td>\n",
       "      <td>10.372743</td>\n",
       "      <td>46.46511</td>\n",
       "      <td>(46.46511042549073, 10.372742774828684)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>13</td>\n",
       "      <td>2020-01-02</td>\n",
       "      <td>-0.215972</td>\n",
       "      <td>2.324773</td>\n",
       "      <td>5.1</td>\n",
       "      <td>144</td>\n",
       "      <td>Temperatura</td>\n",
       "      <td>°C</td>\n",
       "      <td>6</td>\n",
       "      <td>Bormio Ponte sul  Frodolfo</td>\n",
       "      <td>1250</td>\n",
       "      <td>SO</td>\n",
       "      <td>25/11/1987</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N</td>\n",
       "      <td>5146642</td>\n",
       "      <td>605400</td>\n",
       "      <td>10.372743</td>\n",
       "      <td>46.46511</td>\n",
       "      <td>(46.46511042549073, 10.372742774828684)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>13</td>\n",
       "      <td>2020-01-03</td>\n",
       "      <td>1.945833</td>\n",
       "      <td>2.679131</td>\n",
       "      <td>7.1</td>\n",
       "      <td>144</td>\n",
       "      <td>Temperatura</td>\n",
       "      <td>°C</td>\n",
       "      <td>6</td>\n",
       "      <td>Bormio Ponte sul  Frodolfo</td>\n",
       "      <td>1250</td>\n",
       "      <td>SO</td>\n",
       "      <td>25/11/1987</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N</td>\n",
       "      <td>5146642</td>\n",
       "      <td>605400</td>\n",
       "      <td>10.372743</td>\n",
       "      <td>46.46511</td>\n",
       "      <td>(46.46511042549073, 10.372742774828684)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>13</td>\n",
       "      <td>2020-01-04</td>\n",
       "      <td>5.172222</td>\n",
       "      <td>2.549796</td>\n",
       "      <td>9.7</td>\n",
       "      <td>144</td>\n",
       "      <td>Temperatura</td>\n",
       "      <td>°C</td>\n",
       "      <td>6</td>\n",
       "      <td>Bormio Ponte sul  Frodolfo</td>\n",
       "      <td>1250</td>\n",
       "      <td>SO</td>\n",
       "      <td>25/11/1987</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N</td>\n",
       "      <td>5146642</td>\n",
       "      <td>605400</td>\n",
       "      <td>10.372743</td>\n",
       "      <td>46.46511</td>\n",
       "      <td>(46.46511042549073, 10.372742774828684)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>13</td>\n",
       "      <td>2020-01-05</td>\n",
       "      <td>4.391667</td>\n",
       "      <td>2.540126</td>\n",
       "      <td>8.9</td>\n",
       "      <td>144</td>\n",
       "      <td>Temperatura</td>\n",
       "      <td>°C</td>\n",
       "      <td>6</td>\n",
       "      <td>Bormio Ponte sul  Frodolfo</td>\n",
       "      <td>1250</td>\n",
       "      <td>SO</td>\n",
       "      <td>25/11/1987</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N</td>\n",
       "      <td>5146642</td>\n",
       "      <td>605400</td>\n",
       "      <td>10.372743</td>\n",
       "      <td>46.46511</td>\n",
       "      <td>(46.46511042549073, 10.372742774828684)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   IdSensore       Data  Valore_mean  Valore_std  Valore_max  Valore_count  \\\n",
       "0         13 2020-01-01     2.045390    1.888404         6.2           141   \n",
       "1         13 2020-01-02    -0.215972    2.324773         5.1           144   \n",
       "2         13 2020-01-03     1.945833    2.679131         7.1           144   \n",
       "3         13 2020-01-04     5.172222    2.549796         9.7           144   \n",
       "4         13 2020-01-05     4.391667    2.540126         8.9           144   \n",
       "\n",
       "     Tipologia Unità DiMisura  IdStazione                NomeStazione  Quota  \\\n",
       "0  Temperatura             °C           6  Bormio Ponte sul  Frodolfo   1250   \n",
       "1  Temperatura             °C           6  Bormio Ponte sul  Frodolfo   1250   \n",
       "2  Temperatura             °C           6  Bormio Ponte sul  Frodolfo   1250   \n",
       "3  Temperatura             °C           6  Bormio Ponte sul  Frodolfo   1250   \n",
       "4  Temperatura             °C           6  Bormio Ponte sul  Frodolfo   1250   \n",
       "\n",
       "  Provincia   DataStart DataStop Storico  UTM_Nord  UTM_Est        lng  \\\n",
       "0        SO  25/11/1987      NaN       N   5146642   605400  10.372743   \n",
       "1        SO  25/11/1987      NaN       N   5146642   605400  10.372743   \n",
       "2        SO  25/11/1987      NaN       N   5146642   605400  10.372743   \n",
       "3        SO  25/11/1987      NaN       N   5146642   605400  10.372743   \n",
       "4        SO  25/11/1987      NaN       N   5146642   605400  10.372743   \n",
       "\n",
       "        lat                                 location  \n",
       "0  46.46511  (46.46511042549073, 10.372742774828684)  \n",
       "1  46.46511  (46.46511042549073, 10.372742774828684)  \n",
       "2  46.46511  (46.46511042549073, 10.372742774828684)  \n",
       "3  46.46511  (46.46511042549073, 10.372742774828684)  \n",
       "4  46.46511  (46.46511042549073, 10.372742774828684)  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "meteo_sensori__id_day.drop(meteo_sensori__id_day[meteo_sensori__id_day.Valore_count < 130].index, inplace=True)\n",
    "meteo_sensori__id_day.reset_index(drop=True, inplace=True)\n",
    "meteo_sensori__id_day.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "35c20862",
   "metadata": {},
   "source": [
    "## Tengo solo MI"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2ea3a415",
   "metadata": {},
   "source": [
    "- Inner joint tra `meteo_sensori__id_day` e `zonizzazione` a dare `meteo_sensori_zone__id_day`\n",
    "- Non perdo nessuna riga con l'inner joint perché sono presenti tutti i comuni nel dataset `zonizzazione`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "07bf353e",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-01-21T14:46:22.610286Z",
     "start_time": "2022-01-21T14:46:19.773287Z"
    }
   },
   "outputs": [],
   "source": [
    "#meteo_sensori_zone__id_day = pd.merge(meteo_sensori__id_day, zonizzazione['Zona'], left_on = meteo_sensori__id_day['Comune'].str.lower(), right_on = zonizzazione['Comune'].str.lower())\n",
    "#meteo_sensori_zone__id_day.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "1c584788",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-01-21T14:46:22.626291Z",
     "start_time": "2022-01-21T14:46:22.612291Z"
    }
   },
   "outputs": [],
   "source": [
    "#meteo_sensori_zone__id_day.drop(meteo_sensori_zone__id_day[meteo_sensori_zone__id_day['Zona'] != 'AGG MI'].index, inplace = True)\n",
    "#meteo_sensori_zone__id_day.reset_index(drop = True, inplace = True)\n",
    "#meteo_sensori_zone__id_day"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "9a44a207",
   "metadata": {
    "scrolled": false
   },
   "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>IdSensore</th>\n",
       "      <th>Data</th>\n",
       "      <th>Valore_mean</th>\n",
       "      <th>Valore_std</th>\n",
       "      <th>Valore_max</th>\n",
       "      <th>Valore_count</th>\n",
       "      <th>Tipologia</th>\n",
       "      <th>Unità DiMisura</th>\n",
       "      <th>IdStazione</th>\n",
       "      <th>NomeStazione</th>\n",
       "      <th>Quota</th>\n",
       "      <th>Provincia</th>\n",
       "      <th>DataStart</th>\n",
       "      <th>DataStop</th>\n",
       "      <th>Storico</th>\n",
       "      <th>UTM_Nord</th>\n",
       "      <th>UTM_Est</th>\n",
       "      <th>lng</th>\n",
       "      <th>lat</th>\n",
       "      <th>location</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2001</td>\n",
       "      <td>2017-01-01</td>\n",
       "      <td>0.818881</td>\n",
       "      <td>4.269808</td>\n",
       "      <td>9.6</td>\n",
       "      <td>143</td>\n",
       "      <td>Temperatura</td>\n",
       "      <td>°C</td>\n",
       "      <td>100</td>\n",
       "      <td>Milano Lambrate</td>\n",
       "      <td>120</td>\n",
       "      <td>MI</td>\n",
       "      <td>29/06/2001</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N</td>\n",
       "      <td>5038171</td>\n",
       "      <td>520120</td>\n",
       "      <td>9.257515</td>\n",
       "      <td>45.496780</td>\n",
       "      <td>(45.49677982403948, 9.257515399681068)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2001</td>\n",
       "      <td>2017-01-02</td>\n",
       "      <td>2.469444</td>\n",
       "      <td>2.840375</td>\n",
       "      <td>7.9</td>\n",
       "      <td>144</td>\n",
       "      <td>Temperatura</td>\n",
       "      <td>°C</td>\n",
       "      <td>100</td>\n",
       "      <td>Milano Lambrate</td>\n",
       "      <td>120</td>\n",
       "      <td>MI</td>\n",
       "      <td>29/06/2001</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N</td>\n",
       "      <td>5038171</td>\n",
       "      <td>520120</td>\n",
       "      <td>9.257515</td>\n",
       "      <td>45.496780</td>\n",
       "      <td>(45.49677982403948, 9.257515399681068)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2001</td>\n",
       "      <td>2017-01-03</td>\n",
       "      <td>2.319444</td>\n",
       "      <td>3.701696</td>\n",
       "      <td>9.0</td>\n",
       "      <td>144</td>\n",
       "      <td>Temperatura</td>\n",
       "      <td>°C</td>\n",
       "      <td>100</td>\n",
       "      <td>Milano Lambrate</td>\n",
       "      <td>120</td>\n",
       "      <td>MI</td>\n",
       "      <td>29/06/2001</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N</td>\n",
       "      <td>5038171</td>\n",
       "      <td>520120</td>\n",
       "      <td>9.257515</td>\n",
       "      <td>45.496780</td>\n",
       "      <td>(45.49677982403948, 9.257515399681068)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2001</td>\n",
       "      <td>2017-01-04</td>\n",
       "      <td>4.503472</td>\n",
       "      <td>4.753937</td>\n",
       "      <td>10.8</td>\n",
       "      <td>144</td>\n",
       "      <td>Temperatura</td>\n",
       "      <td>°C</td>\n",
       "      <td>100</td>\n",
       "      <td>Milano Lambrate</td>\n",
       "      <td>120</td>\n",
       "      <td>MI</td>\n",
       "      <td>29/06/2001</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N</td>\n",
       "      <td>5038171</td>\n",
       "      <td>520120</td>\n",
       "      <td>9.257515</td>\n",
       "      <td>45.496780</td>\n",
       "      <td>(45.49677982403948, 9.257515399681068)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2001</td>\n",
       "      <td>2017-01-05</td>\n",
       "      <td>6.384722</td>\n",
       "      <td>1.438498</td>\n",
       "      <td>9.3</td>\n",
       "      <td>144</td>\n",
       "      <td>Temperatura</td>\n",
       "      <td>°C</td>\n",
       "      <td>100</td>\n",
       "      <td>Milano Lambrate</td>\n",
       "      <td>120</td>\n",
       "      <td>MI</td>\n",
       "      <td>29/06/2001</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N</td>\n",
       "      <td>5038171</td>\n",
       "      <td>520120</td>\n",
       "      <td>9.257515</td>\n",
       "      <td>45.496780</td>\n",
       "      <td>(45.49677982403948, 9.257515399681068)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39689</th>\n",
       "      <td>12759</td>\n",
       "      <td>2021-12-27</td>\n",
       "      <td>4.034965</td>\n",
       "      <td>1.388091</td>\n",
       "      <td>5.6</td>\n",
       "      <td>143</td>\n",
       "      <td>Temperatura</td>\n",
       "      <td>°C</td>\n",
       "      <td>1512</td>\n",
       "      <td>Pogliano Milanese</td>\n",
       "      <td>160</td>\n",
       "      <td>MI</td>\n",
       "      <td>25/11/2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N</td>\n",
       "      <td>5042449</td>\n",
       "      <td>500406</td>\n",
       "      <td>9.005200</td>\n",
       "      <td>45.535577</td>\n",
       "      <td>(45.535576719250145, 9.005199956067523)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39690</th>\n",
       "      <td>12759</td>\n",
       "      <td>2021-12-28</td>\n",
       "      <td>5.043750</td>\n",
       "      <td>1.134501</td>\n",
       "      <td>7.1</td>\n",
       "      <td>144</td>\n",
       "      <td>Temperatura</td>\n",
       "      <td>°C</td>\n",
       "      <td>1512</td>\n",
       "      <td>Pogliano Milanese</td>\n",
       "      <td>160</td>\n",
       "      <td>MI</td>\n",
       "      <td>25/11/2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N</td>\n",
       "      <td>5042449</td>\n",
       "      <td>500406</td>\n",
       "      <td>9.005200</td>\n",
       "      <td>45.535577</td>\n",
       "      <td>(45.535576719250145, 9.005199956067523)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39691</th>\n",
       "      <td>12759</td>\n",
       "      <td>2021-12-29</td>\n",
       "      <td>4.531250</td>\n",
       "      <td>2.949706</td>\n",
       "      <td>10.8</td>\n",
       "      <td>144</td>\n",
       "      <td>Temperatura</td>\n",
       "      <td>°C</td>\n",
       "      <td>1512</td>\n",
       "      <td>Pogliano Milanese</td>\n",
       "      <td>160</td>\n",
       "      <td>MI</td>\n",
       "      <td>25/11/2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N</td>\n",
       "      <td>5042449</td>\n",
       "      <td>500406</td>\n",
       "      <td>9.005200</td>\n",
       "      <td>45.535577</td>\n",
       "      <td>(45.535576719250145, 9.005199956067523)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39692</th>\n",
       "      <td>12759</td>\n",
       "      <td>2021-12-30</td>\n",
       "      <td>2.679167</td>\n",
       "      <td>0.754091</td>\n",
       "      <td>4.0</td>\n",
       "      <td>144</td>\n",
       "      <td>Temperatura</td>\n",
       "      <td>°C</td>\n",
       "      <td>1512</td>\n",
       "      <td>Pogliano Milanese</td>\n",
       "      <td>160</td>\n",
       "      <td>MI</td>\n",
       "      <td>25/11/2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N</td>\n",
       "      <td>5042449</td>\n",
       "      <td>500406</td>\n",
       "      <td>9.005200</td>\n",
       "      <td>45.535577</td>\n",
       "      <td>(45.535576719250145, 9.005199956067523)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39693</th>\n",
       "      <td>12759</td>\n",
       "      <td>2021-12-31</td>\n",
       "      <td>1.528472</td>\n",
       "      <td>2.392315</td>\n",
       "      <td>8.0</td>\n",
       "      <td>144</td>\n",
       "      <td>Temperatura</td>\n",
       "      <td>°C</td>\n",
       "      <td>1512</td>\n",
       "      <td>Pogliano Milanese</td>\n",
       "      <td>160</td>\n",
       "      <td>MI</td>\n",
       "      <td>25/11/2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N</td>\n",
       "      <td>5042449</td>\n",
       "      <td>500406</td>\n",
       "      <td>9.005200</td>\n",
       "      <td>45.535577</td>\n",
       "      <td>(45.535576719250145, 9.005199956067523)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>39694 rows × 20 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       IdSensore       Data  Valore_mean  Valore_std  Valore_max  \\\n",
       "0           2001 2017-01-01     0.818881    4.269808         9.6   \n",
       "1           2001 2017-01-02     2.469444    2.840375         7.9   \n",
       "2           2001 2017-01-03     2.319444    3.701696         9.0   \n",
       "3           2001 2017-01-04     4.503472    4.753937        10.8   \n",
       "4           2001 2017-01-05     6.384722    1.438498         9.3   \n",
       "...          ...        ...          ...         ...         ...   \n",
       "39689      12759 2021-12-27     4.034965    1.388091         5.6   \n",
       "39690      12759 2021-12-28     5.043750    1.134501         7.1   \n",
       "39691      12759 2021-12-29     4.531250    2.949706        10.8   \n",
       "39692      12759 2021-12-30     2.679167    0.754091         4.0   \n",
       "39693      12759 2021-12-31     1.528472    2.392315         8.0   \n",
       "\n",
       "       Valore_count    Tipologia Unità DiMisura  IdStazione  \\\n",
       "0               143  Temperatura             °C         100   \n",
       "1               144  Temperatura             °C         100   \n",
       "2               144  Temperatura             °C         100   \n",
       "3               144  Temperatura             °C         100   \n",
       "4               144  Temperatura             °C         100   \n",
       "...             ...          ...            ...         ...   \n",
       "39689           143  Temperatura             °C        1512   \n",
       "39690           144  Temperatura             °C        1512   \n",
       "39691           144  Temperatura             °C        1512   \n",
       "39692           144  Temperatura             °C        1512   \n",
       "39693           144  Temperatura             °C        1512   \n",
       "\n",
       "            NomeStazione  Quota Provincia   DataStart DataStop Storico  \\\n",
       "0        Milano Lambrate    120        MI  29/06/2001      NaN       N   \n",
       "1        Milano Lambrate    120        MI  29/06/2001      NaN       N   \n",
       "2        Milano Lambrate    120        MI  29/06/2001      NaN       N   \n",
       "3        Milano Lambrate    120        MI  29/06/2001      NaN       N   \n",
       "4        Milano Lambrate    120        MI  29/06/2001      NaN       N   \n",
       "...                  ...    ...       ...         ...      ...     ...   \n",
       "39689  Pogliano Milanese    160        MI  25/11/2020      NaN       N   \n",
       "39690  Pogliano Milanese    160        MI  25/11/2020      NaN       N   \n",
       "39691  Pogliano Milanese    160        MI  25/11/2020      NaN       N   \n",
       "39692  Pogliano Milanese    160        MI  25/11/2020      NaN       N   \n",
       "39693  Pogliano Milanese    160        MI  25/11/2020      NaN       N   \n",
       "\n",
       "       UTM_Nord  UTM_Est       lng        lat  \\\n",
       "0       5038171   520120  9.257515  45.496780   \n",
       "1       5038171   520120  9.257515  45.496780   \n",
       "2       5038171   520120  9.257515  45.496780   \n",
       "3       5038171   520120  9.257515  45.496780   \n",
       "4       5038171   520120  9.257515  45.496780   \n",
       "...         ...      ...       ...        ...   \n",
       "39689   5042449   500406  9.005200  45.535577   \n",
       "39690   5042449   500406  9.005200  45.535577   \n",
       "39691   5042449   500406  9.005200  45.535577   \n",
       "39692   5042449   500406  9.005200  45.535577   \n",
       "39693   5042449   500406  9.005200  45.535577   \n",
       "\n",
       "                                      location  \n",
       "0       (45.49677982403948, 9.257515399681068)  \n",
       "1       (45.49677982403948, 9.257515399681068)  \n",
       "2       (45.49677982403948, 9.257515399681068)  \n",
       "3       (45.49677982403948, 9.257515399681068)  \n",
       "4       (45.49677982403948, 9.257515399681068)  \n",
       "...                                        ...  \n",
       "39689  (45.535576719250145, 9.005199956067523)  \n",
       "39690  (45.535576719250145, 9.005199956067523)  \n",
       "39691  (45.535576719250145, 9.005199956067523)  \n",
       "39692  (45.535576719250145, 9.005199956067523)  \n",
       "39693  (45.535576719250145, 9.005199956067523)  \n",
       "\n",
       "[39694 rows x 20 columns]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "meteo_sensori__id_day.drop(meteo_sensori__id_day[meteo_sensori__id_day['Provincia'] != 'MI'].index, inplace = True)\n",
    "meteo_sensori__id_day.reset_index(drop=True, inplace=True)\n",
    "meteo_sensori__id_day"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2e8659e8",
   "metadata": {
    "heading_collapsed": true
   },
   "source": [
    "## GROUP BY `meteo_sensori__day`"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d48091be",
   "metadata": {
    "hidden": true
   },
   "source": [
    "- Raggruppo per `Data` (giorno), `Zona`, `NomeTipoSensore`\n",
    "- Calcolo grandezze aggregate\n",
    "    - Calcolo il valore medio e la deviazione standard del `Valore_MEAN_id_day`, cioé il valore mediato di un sensore sull'intera giornata\n",
    "    - Importante sottolineare che le funzioni `mean, count e std` di pandas NON tengono conto dei Na, quindi i valori che vediamo sono esatti\n",
    "- Si perdono le colonne `Valore_count` e `Valore_STD_id_day` ma non sono importanti, sono piú importanti quelle che ricalcoliamo (chiamate `Valore_count_day_zona_tipo` e `Valore_STD_day_zona_tipo`)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "224e2409",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-01-18T15:33:29.841525Z",
     "start_time": "2022-01-18T15:33:19.223491Z"
    },
    "hidden": true
   },
   "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>Data</th>\n",
       "      <th>Tipologia</th>\n",
       "      <th>Valore_mean</th>\n",
       "      <th>Valore_std_mean</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2017-01-01</td>\n",
       "      <td>Radiazione Globale</td>\n",
       "      <td>73.048141</td>\n",
       "      <td>20.409292</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2017-01-02</td>\n",
       "      <td>Radiazione Globale</td>\n",
       "      <td>41.620833</td>\n",
       "      <td>13.619913</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2017-01-03</td>\n",
       "      <td>Radiazione Globale</td>\n",
       "      <td>71.419246</td>\n",
       "      <td>3.751239</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2017-01-04</td>\n",
       "      <td>Radiazione Globale</td>\n",
       "      <td>79.087401</td>\n",
       "      <td>4.263804</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2017-01-05</td>\n",
       "      <td>Radiazione Globale</td>\n",
       "      <td>86.494072</td>\n",
       "      <td>4.794243</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Data           Tipologia  Valore_mean  Valore_std_mean\n",
       "0 2017-01-01  Radiazione Globale    73.048141        20.409292\n",
       "2 2017-01-02  Radiazione Globale    41.620833        13.619913\n",
       "4 2017-01-03  Radiazione Globale    71.419246         3.751239\n",
       "6 2017-01-04  Radiazione Globale    79.087401         4.263804\n",
       "8 2017-01-05  Radiazione Globale    86.494072         4.794243"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "meteo_sensori__day = meteo_sensori__id_day.groupby(['Data', 'Tipologia']).agg({'Valore_mean': ['mean', 'std'], 'Valore_max': ['mean', 'std']}).reset_index()\n",
    "\n",
    "meteo_sensori__day.columns = ['Data', 'Tipologia', 'Valore_mean', 'Valore_std_mean', 'Valore_max','Valore_std_max']\n",
    "meteo_sensori__day\n",
    "\n",
    "temperatura = meteo_sensori__day[meteo_sensori__day['Tipologia'] == 'Temperatura'][['Data', 'Tipologia', 'Valore_max']]\n",
    "radiazione_globale = meteo_sensori__day[meteo_sensori__day['Tipologia'] == 'Radiazione Globale'][['Data', 'Tipologia', 'Valore_mean','Valore_std_mean']]\n",
    "temperatura.head()\n",
    "radiazione_globale.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5c184df7",
   "metadata": {
    "heading_collapsed": true
   },
   "source": [
    "# Controlli (*superset*)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e1564594",
   "metadata": {
    "hidden": true
   },
   "source": [
    "### Valori mancanti per ogni coppia `Zona` - `NomeTipoSensore`"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fe774f61",
   "metadata": {
    "hidden": true
   },
   "source": [
    "#### Numero valori mancanti e valori NaN"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "81ce0bd8",
   "metadata": {
    "hidden": true
   },
   "source": [
    "I valori delle medie mancanti sono dovuti a:\n",
    "\n",
    "- righe effettivamente mancanti\n",
    "- righe con Valore_MEAN uguale a NaN"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "910f3762",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-01-18T15:33:41.522295Z",
     "start_time": "2022-01-18T15:33:41.447562Z"
    },
    "hidden": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2017-01-01', '2017-01-02', '2017-01-03', '2017-01-04',\n",
       "               '2017-01-05', '2017-01-06', '2017-01-07', '2017-01-08',\n",
       "               '2017-01-09', '2017-01-10',\n",
       "               ...\n",
       "               '2021-12-22', '2021-12-23', '2021-12-24', '2021-12-25',\n",
       "               '2021-12-26', '2021-12-27', '2021-12-28', '2021-12-29',\n",
       "               '2021-12-30', '2021-12-31'],\n",
       "              dtype='datetime64[ns]', length=1826, freq='D')"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "indice_date = pd.date_range(meteo_sensori__day.Data.min(), meteo_sensori__day.Data.max())\n",
    "indice_date"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "221a1d90",
   "metadata": {
    "hidden": true
   },
   "source": [
    "#### Aggiunta valori NaN per giorni mancanti"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2c3f4723",
   "metadata": {
    "hidden": true
   },
   "source": [
    "Serve dopo quando si compie la media mobile (per mediare i giorni contigui e non le righe contigue)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "05b22c7d",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-01-18T15:33:48.694553Z",
     "start_time": "2022-01-18T15:33:45.574649Z"
    },
    "hidden": true
   },
   "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>Data</th>\n",
       "      <th>Tipologia</th>\n",
       "      <th>Valore_max</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2017-01-01</td>\n",
       "      <td>Temperatura</td>\n",
       "      <td>7.678571</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2017-01-02</td>\n",
       "      <td>Temperatura</td>\n",
       "      <td>7.378571</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2017-01-03</td>\n",
       "      <td>Temperatura</td>\n",
       "      <td>8.771429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2017-01-04</td>\n",
       "      <td>Temperatura</td>\n",
       "      <td>10.092857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2017-01-05</td>\n",
       "      <td>Temperatura</td>\n",
       "      <td>8.878571</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1821</th>\n",
       "      <td>2021-12-27</td>\n",
       "      <td>Temperatura</td>\n",
       "      <td>6.206250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1822</th>\n",
       "      <td>2021-12-28</td>\n",
       "      <td>Temperatura</td>\n",
       "      <td>8.075000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1823</th>\n",
       "      <td>2021-12-29</td>\n",
       "      <td>Temperatura</td>\n",
       "      <td>9.518750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1824</th>\n",
       "      <td>2021-12-30</td>\n",
       "      <td>Temperatura</td>\n",
       "      <td>6.287500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1825</th>\n",
       "      <td>2021-12-31</td>\n",
       "      <td>Temperatura</td>\n",
       "      <td>8.156250</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1826 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           Data    Tipologia  Valore_max\n",
       "0    2017-01-01  Temperatura    7.678571\n",
       "1    2017-01-02  Temperatura    7.378571\n",
       "2    2017-01-03  Temperatura    8.771429\n",
       "3    2017-01-04  Temperatura   10.092857\n",
       "4    2017-01-05  Temperatura    8.878571\n",
       "...         ...          ...         ...\n",
       "1821 2021-12-27  Temperatura    6.206250\n",
       "1822 2021-12-28  Temperatura    8.075000\n",
       "1823 2021-12-29  Temperatura    9.518750\n",
       "1824 2021-12-30  Temperatura    6.287500\n",
       "1825 2021-12-31  Temperatura    8.156250\n",
       "\n",
       "[1826 rows x 3 columns]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temperatura = temperatura.set_index('Data').reindex(indice_date, fill_value=np.NaN).reset_index()\n",
    "temperatura.columns = ['Data', 'Tipologia', 'Valore_max']\n",
    "temperatura"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "1dd3701d",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-01-18T15:33:48.694553Z",
     "start_time": "2022-01-18T15:33:45.574649Z"
    },
    "hidden": true
   },
   "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>Data</th>\n",
       "      <th>Tipologia</th>\n",
       "      <th>Valore_mean</th>\n",
       "      <th>Valore_std_mean</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2017-01-01</td>\n",
       "      <td>Radiazione Globale</td>\n",
       "      <td>73.048141</td>\n",
       "      <td>20.409292</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2017-01-02</td>\n",
       "      <td>Radiazione Globale</td>\n",
       "      <td>41.620833</td>\n",
       "      <td>13.619913</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2017-01-03</td>\n",
       "      <td>Radiazione Globale</td>\n",
       "      <td>71.419246</td>\n",
       "      <td>3.751239</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2017-01-04</td>\n",
       "      <td>Radiazione Globale</td>\n",
       "      <td>79.087401</td>\n",
       "      <td>4.263804</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2017-01-05</td>\n",
       "      <td>Radiazione Globale</td>\n",
       "      <td>86.494072</td>\n",
       "      <td>4.794243</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1821</th>\n",
       "      <td>2021-12-27</td>\n",
       "      <td>Radiazione Globale</td>\n",
       "      <td>11.376786</td>\n",
       "      <td>1.899456</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1822</th>\n",
       "      <td>2021-12-28</td>\n",
       "      <td>Radiazione Globale</td>\n",
       "      <td>23.749776</td>\n",
       "      <td>2.023651</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1823</th>\n",
       "      <td>2021-12-29</td>\n",
       "      <td>Radiazione Globale</td>\n",
       "      <td>53.417758</td>\n",
       "      <td>11.747264</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1824</th>\n",
       "      <td>2021-12-30</td>\n",
       "      <td>Radiazione Globale</td>\n",
       "      <td>31.981151</td>\n",
       "      <td>11.091993</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1825</th>\n",
       "      <td>2021-12-31</td>\n",
       "      <td>Radiazione Globale</td>\n",
       "      <td>54.105556</td>\n",
       "      <td>15.749424</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1826 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           Data           Tipologia  Valore_mean  Valore_std_mean\n",
       "0    2017-01-01  Radiazione Globale    73.048141        20.409292\n",
       "1    2017-01-02  Radiazione Globale    41.620833        13.619913\n",
       "2    2017-01-03  Radiazione Globale    71.419246         3.751239\n",
       "3    2017-01-04  Radiazione Globale    79.087401         4.263804\n",
       "4    2017-01-05  Radiazione Globale    86.494072         4.794243\n",
       "...         ...                 ...          ...              ...\n",
       "1821 2021-12-27  Radiazione Globale    11.376786         1.899456\n",
       "1822 2021-12-28  Radiazione Globale    23.749776         2.023651\n",
       "1823 2021-12-29  Radiazione Globale    53.417758        11.747264\n",
       "1824 2021-12-30  Radiazione Globale    31.981151        11.091993\n",
       "1825 2021-12-31  Radiazione Globale    54.105556        15.749424\n",
       "\n",
       "[1826 rows x 4 columns]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "radiazione_globale = radiazione_globale.set_index('Data').reindex(indice_date, fill_value=np.NaN).reset_index()\n",
    "radiazione_globale.columns = ['Data', 'Tipologia', 'Valore_mean', 'Valore_std_mean']\n",
    "radiazione_globale"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3817c50f",
   "metadata": {
    "hidden": true
   },
   "source": [
    "Abbiamo ottenuto un numero di righe uguale a quelle teoriche con presenti dei NaN"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "19e3c5ca",
   "metadata": {},
   "source": [
    "# Medio/massimo negli anni"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "ae9c9087",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>Valore_max_mean</th>\n",
       "      <th>Valore_max_std</th>\n",
       "      <th>Data</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>6.347744</td>\n",
       "      <td>3.055694</td>\n",
       "      <td>2020-01-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>9.534527</td>\n",
       "      <td>3.591281</td>\n",
       "      <td>2020-01-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>8.255363</td>\n",
       "      <td>0.623810</td>\n",
       "      <td>2020-01-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>9.407524</td>\n",
       "      <td>3.296207</td>\n",
       "      <td>2020-01-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>9.018952</td>\n",
       "      <td>2.798265</td>\n",
       "      <td>2020-01-05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>361</th>\n",
       "      <td>361</td>\n",
       "      <td>6.514774</td>\n",
       "      <td>2.057278</td>\n",
       "      <td>2020-12-27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>362</th>\n",
       "      <td>362</td>\n",
       "      <td>7.929286</td>\n",
       "      <td>3.650608</td>\n",
       "      <td>2020-12-28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>363</th>\n",
       "      <td>363</td>\n",
       "      <td>7.588798</td>\n",
       "      <td>3.516738</td>\n",
       "      <td>2020-12-29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>364</th>\n",
       "      <td>364</td>\n",
       "      <td>9.021690</td>\n",
       "      <td>4.668642</td>\n",
       "      <td>2020-12-30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>365</th>\n",
       "      <td>365</td>\n",
       "      <td>8.140298</td>\n",
       "      <td>2.734184</td>\n",
       "      <td>2020-12-31</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>366 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     index  Valore_max_mean  Valore_max_std       Data\n",
       "0        0         6.347744        3.055694 2020-01-01\n",
       "1        1         9.534527        3.591281 2020-01-02\n",
       "2        2         8.255363        0.623810 2020-01-03\n",
       "3        3         9.407524        3.296207 2020-01-04\n",
       "4        4         9.018952        2.798265 2020-01-05\n",
       "..     ...              ...             ...        ...\n",
       "361    361         6.514774        2.057278 2020-12-27\n",
       "362    362         7.929286        3.650608 2020-12-28\n",
       "363    363         7.588798        3.516738 2020-12-29\n",
       "364    364         9.021690        4.668642 2020-12-30\n",
       "365    365         8.140298        2.734184 2020-12-31\n",
       "\n",
       "[366 rows x 4 columns]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temperatura['month'] = temperatura.Data.dt.month\n",
    "temperatura['day'] = temperatura.Data.dt.day\n",
    "temperatura_year = temperatura.groupby(['month', 'day'], as_index = False).agg(Valore_max_mean =('Valore_max', 'mean'), Valore_max_std = ('Valore_max', 'std')).reset_index()\n",
    "temperatura_year['year'] = 2020\n",
    "\n",
    "temperatura_year['Data'] = pd.to_datetime(temperatura_year[['year', 'month', 'day']])\n",
    "\n",
    "temperatura.drop(['month', 'day'], axis = 1, inplace = True)\n",
    "temperatura_year.drop(['month', 'day', 'year'], axis = 1, inplace = True)\n",
    "temperatura_year"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "7a1af2e0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>Valore_mean_max</th>\n",
       "      <th>Valore_mean_mean</th>\n",
       "      <th>Valore_mean_std</th>\n",
       "      <th>Data</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>75.617088</td>\n",
       "      <td>45.452980</td>\n",
       "      <td>30.360625</td>\n",
       "      <td>2020-01-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>86.009375</td>\n",
       "      <td>57.931202</td>\n",
       "      <td>32.406506</td>\n",
       "      <td>2020-01-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>71.419246</td>\n",
       "      <td>52.181673</td>\n",
       "      <td>15.663368</td>\n",
       "      <td>2020-01-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>79.087401</td>\n",
       "      <td>62.985493</td>\n",
       "      <td>25.733121</td>\n",
       "      <td>2020-01-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>86.494072</td>\n",
       "      <td>53.750202</td>\n",
       "      <td>35.743162</td>\n",
       "      <td>2020-01-05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>361</th>\n",
       "      <td>361</td>\n",
       "      <td>60.957484</td>\n",
       "      <td>37.417460</td>\n",
       "      <td>27.707753</td>\n",
       "      <td>2020-12-27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>362</th>\n",
       "      <td>362</td>\n",
       "      <td>72.034821</td>\n",
       "      <td>43.399349</td>\n",
       "      <td>22.198376</td>\n",
       "      <td>2020-12-28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>363</th>\n",
       "      <td>363</td>\n",
       "      <td>74.004960</td>\n",
       "      <td>52.726936</td>\n",
       "      <td>22.426863</td>\n",
       "      <td>2020-12-29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>364</th>\n",
       "      <td>364</td>\n",
       "      <td>68.918750</td>\n",
       "      <td>53.281244</td>\n",
       "      <td>14.121205</td>\n",
       "      <td>2020-12-30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>365</th>\n",
       "      <td>365</td>\n",
       "      <td>71.831250</td>\n",
       "      <td>56.879675</td>\n",
       "      <td>21.806467</td>\n",
       "      <td>2020-12-31</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>366 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     index  Valore_mean_max  Valore_mean_mean  Valore_mean_std       Data\n",
       "0        0        75.617088         45.452980        30.360625 2020-01-01\n",
       "1        1        86.009375         57.931202        32.406506 2020-01-02\n",
       "2        2        71.419246         52.181673        15.663368 2020-01-03\n",
       "3        3        79.087401         62.985493        25.733121 2020-01-04\n",
       "4        4        86.494072         53.750202        35.743162 2020-01-05\n",
       "..     ...              ...               ...              ...        ...\n",
       "361    361        60.957484         37.417460        27.707753 2020-12-27\n",
       "362    362        72.034821         43.399349        22.198376 2020-12-28\n",
       "363    363        74.004960         52.726936        22.426863 2020-12-29\n",
       "364    364        68.918750         53.281244        14.121205 2020-12-30\n",
       "365    365        71.831250         56.879675        21.806467 2020-12-31\n",
       "\n",
       "[366 rows x 5 columns]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "radiazione_globale['month'] = radiazione_globale.Data.dt.month\n",
    "radiazione_globale['day'] = radiazione_globale.Data.dt.day\n",
    "radiazione_globale_year = radiazione_globale.groupby(['month', 'day'], as_index = False).agg(Valore_mean_max =('Valore_mean', 'max'), Valore_mean_mean =('Valore_mean', 'mean'), Valore_mean_std =('Valore_mean', 'std')).reset_index()\n",
    "radiazione_globale_year['year'] = 2020\n",
    "\n",
    "radiazione_globale_year['Data'] = pd.to_datetime(radiazione_globale_year[['year', 'month', 'day']])\n",
    "\n",
    "radiazione_globale.drop(['month', 'day'], axis = 1, inplace = True)\n",
    "radiazione_globale_year.drop(['month', 'day', 'year'], axis = 1, inplace = True)\n",
    "radiazione_globale_year"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "b4cdc659",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "valore   2020-06-21\n",
       "dtype: datetime64[ns]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "anno = pd.date_range('2020-01-01', '2020-12-31')\n",
    "valori = list(range(0, 366))\n",
    "sin = [round(((m.sin(m.pi/366*(x + 11)))**2)*275 + 70, 4) for x in valori]\n",
    "\n",
    "sinusoide = pd.DataFrame(sin, columns =['valore'], index = anno)\n",
    "sinusoide.idxmax()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "074de369",
   "metadata": {},
   "source": [
    "## Pressione stazione Zama"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "7c56a2ce",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<div>\n",
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       "    .dataframe tbody tr th {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Data_ora</th>\n",
       "      <th>Valore</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>01/01/2016 23.59.00</td>\n",
       "      <td>1017.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>02/01/2016 23.59.00</td>\n",
       "      <td>1011.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>03/01/2016 23.59.00</td>\n",
       "      <td>1002.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>04/01/2016 23.59.00</td>\n",
       "      <td>993.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>05/01/2016 23.59.00</td>\n",
       "      <td>993.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      "text/plain": [
       "              Data_ora  Valore\n",
       "0  01/01/2016 23.59.00  1017.4\n",
       "1  02/01/2016 23.59.00  1011.6\n",
       "2  03/01/2016 23.59.00  1002.6\n",
       "3  04/01/2016 23.59.00   993.0\n",
       "4  05/01/2016 23.59.00   993.0"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "press_zama.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "98430c6c",
   "metadata": {},
   "outputs": [],
   "source": [
    "press_zama['Data'] = pd.to_datetime(press_zama['Data_ora'], format = '%d/%m/%Y %H.%M.%S')\n",
    "press_zama['month'] = press_zama['Data'].dt.month\n",
    "press_zama['day'] = press_zama['Data'].dt.day\n",
    "press_zama_year = press_zama.groupby([press_zama['month'], press_zama['day']]).agg(press_mean =('Valore', 'mean'), press_std = ('Valore', 'std')).reset_index()\n",
    "press_zama_year['year'] = 2020\n",
    "press_zama_year['Data'] = pd.to_datetime(press_zama_year[['year', 'month', 'day']])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "44238c59",
   "metadata": {},
   "source": [
    "### calcolo percentili"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "981609d3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "993.3\n",
      "1021.115\n"
     ]
    }
   ],
   "source": [
    "print(np.nanpercentile(press_zama['Valore'], 5))\n",
    "print(np.nanpercentile(press_zama['Valore'], 95))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dec3d317",
   "metadata": {
    "hidden": true
   },
   "source": [
    "## Esportazione"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "dcb05c1c",
   "metadata": {},
   "outputs": [],
   "source": [
    "sinusoide.to_csv(f'{path}/sinusoide.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "20aaadaf",
   "metadata": {},
   "outputs": [],
   "source": [
    "press_zama_year.to_csv(f'{path}/press_zama.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "8f51fa8c",
   "metadata": {},
   "outputs": [],
   "source": [
    "temperatura_year.to_csv(f'{path}/temperatura.csv')\n",
    "radiazione_globale_year.to_csv(f'{path}/radiazione_globale.csv')"
   ]
  }
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